WATER & SOIL - These are not the droids you are looking for.

WATER & SOIL 

TECHNICAL PUBLICATION 

No. 20 

Regional Flood Estimation 

IN 

New Zealand 

Water & soil technical publication no. 20 (1982) 

,?,.t' :'; ISSN 0110-4144

WATER & SOIL TECHNICAL PUBLICATION NO. 20 

iï 

Regional Flood Estimation 

in New Zealand 

"$' 

M.E. BEABLE & A.l. McKERCHAR 

Head Office 

Water and Soil Science Centre 

wãiãtã"d Soil Division Water and Soil Division 

MWD 

MWD 

Christchurch 

Wellington 

WELLINGTON 1982 

Water & soil technical publication no. 20 (1982)

Regional flood est¡mat¡on in New Zealand 

M.E. BEABLE & A.l. McKERCHAR 

Head Office 

Water and Soil Science Centre 

Water and Soil Division Water and Soil Division 

MWD 

MWD 

Ìùr'ellington 

Christchurch 

Water & Soil Technical publication No. 20. t9g2. t32p. ISSN Olt}_4lu 

AbsÉract 

eastern and western parts of the British Isles. 

National Llbrary of New Zealed 

Cataloguing-in-E ublication data 

BEÀBLE, M. E. (Mlchael Eduard), I94Z- 

RegionêL flood estj-nation / M.E. 

Beabl€ r À-I. McKerchâr. - útellington, 

N.Z. : úùater ðd Soll Dlvision Ministry 

of Works ed DevoloE[ent for the 

Nåtlonal Watêr md SoiI Conservâti,on 

oEganisatLon. f992. - I v. - (gtater E 

soil technical publícatlon, ISSN OIIO- 

4144 ; no. 20) 

5s1.4890993I 

1. Flæd forecaating. I. McK€lchar, À. I. 

Allstalr lan), 1945- . Ir. Tltlê. 

III. Series. 

O Crown copyrighf 19t2 

Published for the National water and Soil conservation organisation 

by the vy'ater and soil Division, Ministry of works and Devãlop¡nent, 

P.O. Box lz-0/l, tr)Vellington, New Zealand 


I 

1.1 

1.2 

1.3 

Contents 

¡ntroduct¡on 

PageT 

Introduction 7 

Return period, risk and design life 7 

Methods for estimating design floods 7 

1.3.1 Empirical methods 8 

1.3.2 Unit hydrograph methods 8 

1.3.3 Simulation methods 8 

1.3.4 Regional flood frequency methods 9 

2 Gollection of data 

2.1 Climate of New Zealand 

2.2 Selection of catchments 

' 2.3 Sources of data 

2.4 Qualityofdata 

2.5 Historicalinformation 

poge ll ll 

ll 

ll 

ll 

ll 

3 Regionalflood frequency analysis page 13 

3.1 Flood frequency method 13 

3.1.1 General 13 

3.1.2 Terminology 13 

3.1.3 General extreme value distribution 15 

3.1.4 Sampling proPerties 16 

3.1.5 Types of samPle 17 

3.1.6 Plotting 17 

3.1.7 Computer Programs 

18 

3.2 Flood frequencY data l8 

3.2.1 Data collection 18 

3.2.2 Minimum record length and outliers 19 

3.2.3 Lake outflows 19 

3.3 Flood frequency regions 19 

3.3.1 Regional boundaries 19 

3.3.2 Development of regional flood 

frequencycurves 24 

3.3.3 Bay of PlentY region 37 

3.3.4 Final regional curves 39 

3.3.5 Consistent regions 39 

3.3.6 Sub-regions 39 

3.3.7 Generalised flood frequency curves 42 

3.4 Flood frequencyaccuracy 4 

3.4.1 Accuracy of flood frequency ratio 

Qr/Q 

M 

3.4.2 Datalimitations 48 

3.4.3 Definition of flood frequency regional 

boundaries 48 

3.4.4 HomogeneitYtest 49 

3.5 Flood frequencY discussion 49 

3.5.1 Regional differences 49 

3.5.2 Comparison with the British Isles 50 

3.5.3 Variation within a region 50 

3.5.4 Secular climatic variation 50 

3.5.5 Extension method 52 

3.5.6 Catchment size 52 

3.6 Summary 52 

4 Estimat¡on of mean annualflood puge 53 

4.1 Introduction 53 

4.2 Proposed method 53 

4.3 Recôrds used 53 

4.4 Collection of characteristics 53 

4.5 Analysis of South Island data 

4.5.1 Preliminary examination of data 

4.5.2 Development of trial 

regional estimators 

4.5.3 Examination of residuals 

4.5.4 Finarl equations for South Island 

4.6 Analysis of North Island data 

4.6.1 Preliminary analysis of data 

4.6.2 Development of trial 

regi,cnal estimators 

4.6.3 Final equations for North Island 

4.7 Discussion of results 

4.E Comparison with other results 

4.9 Estimation of coefficient of variation 

4.10 Accuracy crf equations 

4.11 Summary 

5 Application 

5.1 Introduction 

5.2 Applicability 

5.3 Design straJegy 

5.3.1 General 

5.3.3 Estimation of the flood peak for a return 

79 

79 

Nelson area 

D Revised 1224 estimates 

E Comparison of method with TM61 

F Flood frequency analysis for Otago 

and Southland 

F.1 Introduction 

F.2 ' Data collection 

F.3 Analysis and results 

F.4 Conclusions 

ReferenceS 

58 

58 

58 

63 

& 66 

6 

69 

7t 

7t 

72 

72 

76 

poge77 

77 

77 

77 

77 

5.3.2 Estimation of the mean annual flood (Q) 

77 

period T (Qr) 

5.4 Examples 

6 Summary 

References 

page83 

Appendices 

A Tests w¡th frequency distdbutions poge87 

4.1 Introduction 87 

A.2 Gamma distribution 87 

4.3 Methods used 87 

4.4 Evaluation of the frequency 

analysis methods 88 

4.4.1 General 88 

4.4.2 Evaluation criteria and method 88 

4.4.3 First test 89 

4.4.4 Second test 90 

4.4.5 Conclusions 9l 

References 92 

B Summary of the flood peak data used in the 

regionalflood frequency analysis 93 

C Summary of the new flood peak data in the 

85 

r06 

107 

t22 

123 

t23 

t23 

126 

126 

t26 


Tables 

1.1 Risk ofexceedence for specified L and T pageT characteristics 

ó4 

4.E Stepwise regressions for all the North Island data 67 

l6 4.9 Stepwise regressions for first trial North lsland 

22 regions 67 

4.10 Stepwise regressions for final North Island regions 69 

4.ll Comparable equations for other countries 72 

4.12 Prediction errors and equivalent lengths of record 75 

5.1 Ranges of catchment areas used to derive regional 

flood frequency curves and mean annual flood 

equations 77 

3.1 The relationship between y and T values for the 

EVI distribution 

Flow stations used 

3.2 

3.3 

3.4 

3.5 

3.6 

3.7 

3.8 

Calculations for extending the set of average values 

for the Bay of Plenty region 37 

Summary of the regional curve characteristics 39 

Summary of flow stations in the Nelson area 42 

Calculations for extending the sets of average values 

for the generalised curves 42 

Summary of the cha¡acteristics of the 

generalised curves 44 

The regional regression equations for 

estimating Cp 47 

3.9 The grouping and the group equations for estimating 

Cp 48 

3.10 The CF equations derived for the 

generalised curves 

48 

4.1 

54 

4.2 

56 

4.3 

l+q 

¡1.5 

4.6 

4,7 

South Island catchment characteristics 

North Island catchment characteristics 

Correlation matrix for logs of the South Island 

characteristics 

Stepwise regressions for all the South Island data 

Stepwise regressions for the South Island regions 

Final equations for the South Island regionJ 

Correlation matrix for logs of the North Island 

58 

6l 

63 

g 

5.2 Summa¡y of example results using the Regional 

Flood Estimation method 

4.1 Details of the flow stations used in the first 

evaluation test 

^.2 Summary of the performa.nce of the methods 

in the first test 

4.3 Details of the flow stations used in the second 

evaluation test 90 

^.4 Summary of the performance of the methods in 

the second test 90 

E.1 

F.1 

F.2 

F.3 

Comparison of Q.¡ estimates with TM6l estimates 

(Qf) and regional flood estimation estimates 122 

List of catchments 

123 

New flood peak data 

lu 

Co-ordinates from regiona-l frequency curves 126 

gz 

g9 

g9 

2.1 Number of water level recorder stations in New 

Zealand and time distribution of water level data 

page 12 

3.1 pdf (part a) and the Of (part U) 

ution 13 

3.2 Fig. 3.1 as a function of its 

4 

Figures 

4.2 

4.3 

4.4 

4.5 

4.6 

4.7 

4.E 

4.9 

4.t0 

4.tl 

4.12 

5.1 

5.2 

F.1 

F.2 

F.3 

F.4 

F.5 

F.6 

F.7 

F.E 

F.9 

F.10 

!.ocation of the North Island catchments 57 

Q vs A$.EA, South Island catchments Sg 

Distribution of residuals from Equation 4.3 û 

Plot of errors (log Q - O.SZ log AREA) vs log 

MARAIN forEasr Coast Region 

Logarithmic residual errors for trial South lsland 

regional equations 62 

Logarithmic residual errors for fïnal South Island 

legional equations 

ó5 

Q vs AREA, North Island catchments 6 

Trial regions for the North Island 

6g 

Final regions for the North Island 70 

Distribution of Cy of annual maxima for the 

South Island stations 73 

Distribution of Cy of annual maxima for the 

North Island stations 74 

Flow chart of the design strategy using the Regional 

Flood Estimation method 


Location of the Motu catchment above Houpoto g0 

Location of catchments 127 

Plot of normalised flood frequency data for lake 

inflows and Shotover River superimposed on the 

West Coast data given in Figure 3.13 l2g 

Plot of normalised flood frequency data for the 

Pomahaka River and the Southland Rivers l}g 

Plot of normalised flood frequency data for East 

Otago rivers superimposed on the South Canterbury 

datagiven in Figure 3.15 

l2g 

Average points from Figures F.2, F.3 and F.4 

Regions inferred from plots of flood 

6l 

7g 

l2g 

frequencydata 130 

Frequency analysis of annual maxima derived for 

Clutha river tributaries and the lakes, Manuherikia 

and Waiau river tributaries. Regional frequency 

curves ¿ìre also shown 

l3l 

Hydrographs of Shotover, Cleddau and Lake 

Wakatipu inflow, 197l-1979 

l3l 

Hydrographs of two stations in the Southland 

region, 197l-1980 

ßz 

Hydrographs of three Otago stations, l97l-19g0 132

a 

A 

â¡, âz 

b', bt 

c 

C¡ 

Cp 

C¡ 

Cy 

Cvj 

cs 

df 

EV 

EVI 

EV2 

EV3 

E() 

F() 

f() 

GEV 

i 

J 

K 

k 

k 

L 

LP3 

M 

m 

fn 

n¡ 

N 

Nc 

NU 

P() 

pdf 

Pt 

a 

Qi 

Qr 

a 

Q.., 

Qrn"* 

Qmed 

Qous 

r 

R 

se 

S 

S¡ 

t 

T 

u 

var( ) 

x 

Xa 

i 

v 

YN 

a 

lL 

I 

02 

Notation 

Constant of regression equation 

Catchment area (km':) 

Constants of regression 

Exponents of regression equation 

Constant in a standard error equation 

3::ü:i:Tl :ÎiiÏ"Ià" or estimare or er/Q rrom a curve ror given r 

Coefficient of variation of prediction of Q 

Coefficient of variation of regression estimate of Q 

Coefficient of variation of annual maxima flood series 

Coefficient of variation of annual maxima at jth station 

Sample coefficient of skew 

Distribution function 

Extreme value 

Extreme value tYPe I distribution 

Extreme value type 2 distribution 

Extreme value tYPe 3 distribution 

Expected value 

Distribution function 

Probability densitY function 

General extreme value distribution 

Rank of a flood peak 

The additional påriod of record, in years, outside the continuous rec¡rrd 

Frequency factor 

GEV shape parameter (ChaP. 3) 

Number of stations in a region (Chap. 4) 

Projected lifetime of a structure (Chap. l) 

Log-Pearson tYPe 3 

Toial length of station years spanned by the data in a group 

Constant in a standard error equation (Chap. 3) 

Number of independent variables in regression equation 

Length of record at jth station (years) 

Length of record (Years) 

Average length of record in a region (yearÐ 

Period of recording necessary to estimate Qo6. with the same accuracy as Qest $ears) 

Probability 

Probability density function 

iainfall ráte (mm7t¡r) rãi-¿esign storm of duration t equal to time of concentration for catchment, and return 

period T 

Flood peak variate 

An individual annual flood Peak 

The flood peak estimate for a return period T 

The mean annual flood 

Q estimated from regression equation (m3ls) 

Maximúm annual flood Peak 

Median of the annual flood Peaks 

Q estimated from flood record (m'/s) 

iltt of one or more floods exceeding Qr in L years 

Rainfall factor (Chap. l), Multiple córrelation coefficient (Chaps' 3" 4) 

Standard error 

Catchmentshapefactor-(Chap'l)Samplestandarddeviation(Chaps'3'4) 

Standard error of logroQest 

Student "t" statistics 

Return period (Years) 

GEV location Parameter 

Population variance 

Variate 

Quantile estimate of variate x 

Sample mean of variate x 

Redúced variate for the EVI distribution 

Reduced variate for the Normal distribution 

GEV scale Parameter 

Population mean 

Intärstation correlation between annual maxima 

Population Variance 


Preface 


1 lntroduction 

1 .1 lntroduction 

Many works and structures associated with natural 

waterways are subject to flooding. These range from small 

farm dams and culver'-s on minor roads, through flood 

protection works and. major bridges, to major dams. In 

designing these works, engineers have to estimate the 

magnitude of the flood which is to be withstood during the 

projected life of the structure. An appropriate estimate of 

this "design flood" is fundamental to ensuring that 

economic engineering designs with adequate standards of 

safety are acheived. 

Flood estimation for design purposes can be carried out 

using either the deterministic concept of a "maximum probable 

flood" for a particular catchment, or with the 

statistical concept of a "flood magnitude with a probability 

of exceedence". The former (Dalrymple 1964) is used 

where exceedence of the design level could lead to 

catastrophic failure. The object is to estimate the flood that 

is unlikely to be exceeded. The method first estimates a 

maximum rainfall for the catchment and then the corresponding 

flood peak assuming the catchment to be in a 

condition which would lead to maximum runoff. Since 

neither the maximum rainfall nor the maximum runoff for 

known rainfall can be estimated with certainty, the word 

probable is used when no specific probability is given. In 

contrast, statistical methods attach specific probabilities to 

flood magnitudes. 

Recent decades have seen the widespread use of benefitcost 

analysis methods for assessing the relative merits of 

different projects competing for capital resources. For projects 

where flood magnitude is a design pararneter it is 

necessary to attach specific probabilities to this magnitude. 

Then the expected cost of flood damage can be balanced 

against the cost of providing enhanced protection. 

1.2 Return Period, Risk and 

Design Life 

In New Zealand the need to ensure the safety of major 

hydro-electric developments stimulated an early interest in 

flood estimation methods. Benham (1950) introduced a 

statistical flood estimation method that has been used ever 

since. In this method the design flood Q1 is defined as the 

flood which is exceeded on average once in T years; T is 

termed the return period, and Q.¡ is termed the T-year 

flood which has a probability of exceedence in any one year 

of l/T. Il the projected life of the structure is L years and 

assuming independence of annual maxima, the risk r of at 

least one T-year flood occuring in L years is; 

r=l-(l-l/T)L 

This expression is evaluated for a range of L and T 

values in the Table l.l (it is presented graphically by 

Ministry of Works and Development (1979) ). 

10 

50 

100 

20,0 

Table 1.1 Risk of exceedence for specified L and T. 

T=10 T=50 T=10O 

0.651 

o.995 

1.OOO 

1.OO0 

0.1 83 

o.636 

o.867 

o.982 

o.096 

o.395 

o.634 

o.866 

T= 

1000 

o.o10 

o.o49 

0.095 

o.181 

Thus, for example, the probability of the lü) year flood 

being exceeded at least once in a ten year period is 0.096' in 

50 years 0.395, and in 100 years 0.634. This reasoning ap- 

plies to one river, and the probability ofexceedence during 

a specified time inl.erval at any one of a number of rivers is 

much greater. If say l0 independent river basins and a l0 

year period are considered, the probability of at least one 

100 year flood being exceeded in any one of the l0 basins is 

0.634 and the protrability of at least one 1000 year event is 

0.095. Thus large floods are not remote events for consideration 

by a feur specialists, but real possibilities of concern 

to the whole community. Risk is a difficult concept to 

convey to the wider community which is easily lulled into a 

false attitude of complete safety. The risk of flooding to a 

community is perhaps best conveyed by comparison with 

the risk of other hazards that are tacitly accepted. Examples 

include the risks of earthquake damage, traffic accidents 

and nuclear power plant accidents. Pilgrim and 

Cordery (1974) and Burns (1977) provide useful discussion 

and further refere:nces on this subject. 

In practice, r and L are often unstated and a fixed value 

for T is used for a particular class of works. Thus in New 

Zealand hydro-electric earth and rockfill dams, and dams 

subject to the risk of progressive failure on overtopping, 

have been designed to pass the 1000 year flood, while concrete 

dams not sutrject to the risk of progressive failure on 

overtopping are dersigned for the 500 year flood. Similarly, 

state highway bridges are designed to pass the 100 year 

flood, while culverts for state highways are generally 

designed to pÍrss the l0 year flood without heading-up and 

the 100 year flood with heading-up to a maximum level of 

0.5m below the road surface. For some smaller structures 

no clear standards exist and in some cases there is a lack of 

rationality. Situations exist where authorities with 

statutory responsiìoility for one part of a catchment adopt 

higher design stanclards than a second authority in the same 

catchment for the same class of work (Heiler 1975). 

Selection of a design recurrence interval is a subject 

deserving careful attention. For the credibility of designers, 

its interpretation as a socially tolerable risk is information 

that should be carefully explained. 

1.3 Methods for Estimating 

Desiç¡n Floods 

The engineer must estimate a design flood in a range of 

design situations. This design flood is a hypothetical flood 

which results from a design rainfall over a catchment, 

usually assumed to be in an average state of wetness. It is a 

quantity with a probabilistic meaning defined in the 

previous section and must be distinguished from forecasts 

of actual floods which result from real rainstorms over a 

catchment and whose magnitudes will depend on the prior 

states of wetness of the catchment. This distinction is important 

because

annual flood Q (the mean of the annual peaks). Q 

may be estimated from measured catchment and 

climatic characteristics. This is the method used in 

this study. It is also known as the index flood 

method. Another version of the method relates Q1 

directly to catchment and climatic characteristics. 

It is pertinent to review the development of all these 

techniques in the New Zealand context. 

1.3.1 Empirical Methods 

Early flood estimation methods involved fitting an 

envelope curve to observed extremes for a region to give an 

empirical estimate of a maximum flood, usually with catchment 

area as a parameter (Schnackenberg, 1949). Envelope 

curve methods have been largely replaced by empirical 

methods involving probability; of these the best known are 

the Rational Method and Technical Memorandum No. 6l 

(TM6l) (NWASCO l97s). 

Although the Rational Method is in wide use, it is not an 

accurate deterministic description of the way in which a 

catchment modifies rainfall to yield the peak runoff 

(French et al. 1974). An alternative and useful interpretation 

of the Rational Method is statistic¿l. Here the method 

links runoff rates of given frequencies with rainfall rates of 

the same frequencies as follows: 

Qr = C.Pt. A/3.6 

where 

qt: peak discharge rate of return period T (m¡,zs) 

Pt = the design rainfall rate (mm/hr) for a storm of return 

period T and duration t equal to the time of concentration 

for the catchment 

A = the catchment area (km,) 

C = an empirical coeffìcient which provides the link between 

peak runoff and peak rainfall. It embodies the 

net effect of catchment losses, storage effects, etc. 

French et al. (1974) showed that the coefficient C increases 

somewhat with the return period T, and gave 

typical values for central and south-east New South Wales. 

Aitken (1975) found this ratio for a catchment to be 

essentially constant for different return periods. For urban 

catchments Schaake et al. (1967) suggested C could be 

estimated as a function of the portion of impervious area in 

the catchment and the slope of the main channel. 

The second quantity requiring estimation is the duration 

of the design rainstorm. The critical duration is closely approximated 

by the minimum tirne of rise for a number of 

hydrographs, These are not available for ungauged catchments 

and traditional time of concentration formulae are 

not reliable. Heiler (1974) developed an estimator for this 

time constant for catchments of peninsular Malaysia. Once 

a duration is established, storm rainfall can be estimated, 

and in Heiler's case C was estimated as a function of rainfall 

intensity; application of the method was restricted to 

catchments with areas in the range I km, to 100 kmr. Adaptation 

of this statistical interpretation of the Rational 

Method for New Zealand conditions would be a valuable 

contribution. 

Another well-known empirical method in New Zealand 

is known by its publication number, TM6l (NWASCO 

1975) and is an adaptation of various American methods. 

It is recommended for catchment areas up to 1000 kmr. 

The method is; 

Qr = 0.0139 CRSA% 

where 

C = coefficient dependent on the physiography of the 

catchment, 

R = rainfall factor dependent on the design storm, 

S = catchment shape factor, 

A : catchment area (km'z), 

The factor C is determined as the product of two factors 

ìV¡s and Ws. Wlc is determined from a table which has soil 

type and surface cover as parameters, and W5 is obtained 

from a graph having channel length and slope as 

parameters. R is the ratio of the design rainfall for the catchment 

to the adjusted standard rainfall at Kelburn, Wellington. 

As with the Rational Method, the rainfall duration 

must be determined by an empirical time of concentration 

formula. The shape factor is a function of the catchment 

area and length. The development of the method is discussed 

by Campbetl (1959). When first introduced in 1953 this 

method met an urgent need for a standard procedure for 

flood estimation for ungauged catchments. Its value was 

greatly enhanced by the publication of a probability 

analysis of high intensity rainfalls (Robertson 1963). 

1.3.2 Un¡t hydrograph methods 

The unit hydrograph method developed in the 1930's has 

become a widely used hydrological tool. The unit 

hydrograph (UH) is the flow record from a saturated catchment 

when a unit of rainfall falls uniformly for unit time. 

As part of each storm is required to saturate the soil, the 

UH represents only the "quickflow". 

The quickflow from a rainfall excess of various amounts 

over a succession of time units is calculated by superposition 

of the set of unit hydrographs that correspond to the 

rainfall excess. Thus the catchment is assumed to respond 

linearly, in that runoff from a particular portion of storm 

rainfall is unaffected by concurrent runoff from other portions 

of the storm. These assumptions have been tested in 

numetous studies and for small and medium sized catchments 

have been found adequate for most engineering 

design purposes. With a UH determined from a number of 

storms and for average ratios of excess to total rainfall, 

design floods for a catchment can be estimated from design 

storms of the same probability. An important advantage of 

this versatile method over those described previously is that 

the shape of the flood hydrograph is calculated, and not 

merely the peak rate of flow; this is of importance in 

routing studies, in drainage design and in other situations 

where it is necessary to know the length of time the water 

level is above a particular stage. Possibly the main limitation 

of the method is the subjectivity in determining the 

volume and distribution of the rainfall excess. Where the 

lack of flow records prevent the derivation of the UH, procedures 

have been developed for synthesising typical UH 

curves by relating characteristics of the hydrograph shape 

to catchment characteristics. These procedures include the 

well-known Snyder method and the US Soil Conservation 

Service dimensionless hydrograph (Linsley et al. 1975), 

These methods have been used successfully within two 

regions of similar hydrological characteristics (Hoffmeister 

1976). Also the Snyder method gave satisfactory results for 

ungauged tributaries for the Waikato and Clutha Rivers 

(Jowett and Thompson 1977), although Coulter (1961) 

queries the wide applicability of the methods. 

A guide to the order of loss rates that should be used is 

given by Pilgrim (1966), who summarised published loss 

rate information in New Zealand,. As most loss rates were 

low (5090 of loss rates were less than 2.5 mm/hr and 8090 

were less than 5.1 mm/hr), it was concluded that the inaccuracies 

in transferring these values from one region to 

another should cause only very small errors in design 

floods. Nevertheless, more work is needed on loss rate 

estimation in New Zealand as loss rates are important in 

situations where flow forecasts are required. For tributaries 

in the Motueka catchment Beable (1976) found loss rates to 

be related to antecedent wetness, storm intensity and the 

portion of catchment in exotic forestry. 

1.3.3 Simulation methods 

Under this heading is grouped a variety of methods for 

representing catchment response to precipitation. Cat- 


chments are simulated with "models" that are simplified 

representations of complex real-world systems. Models can 

be (a) physical, (b) analogue, or (c) mathematical. 

Mathematical models represent the behaviour of a catchment 

by a set of equations and logical statements expressing 

relationships between hydrological variables and model 

parameters, with an input of precipitation and other 

climatic nneasurementq and an output of stream discharge. 

Such models can be classified as: "lumped" or 

"distributed" depending upon whether variations in processes 

over the catchment are considered; "time variant" 

or "time-invariant" depending upon whether variations in 

time of the model are considered; "stochastic" or "deterministic" 

depending on whether probabilistic notions are 

included; and "conceptual" or "empirical" depending on 

the structuring of the model. 

Extensive reviews of these models are given by Clarke 

(1973) and Chapman and Dunin (1975). One use of such 

models is the extension of a record of streamflows given a 

record of precipitation. At present the model parameters 

are usually estimated by fitting a predicted output 

hydrograph to an observed output hydrograph over a 

period of concurrent rainfall and flow records. Future 

developments are aimed at enabling the estimation of 

model parameters from observed physical characteristics of 

the catchment without the need for a period of observed 

flow record for model calibration. 

1.3.4 Regional flood frequency methods 

Regional flood frequency methods have been applied 

widely, for example in North America (Thomas and Benson 

1970), in'the British Isles (NERC 1975), and in 

Malaysia (Heiler and Chew 1974). The index flood approach 

used in this study averages the chance sampling 

variation in flood frequency in a region, while preserving 

the variation due to differences in catchment 

characteristics. Development of the method involves: 

(Ð collecting annual maxima for a number of flow stations 

in the area thought to be homogenous; 

(ü) drawing frequency-magnitude curves for each station 

(Qr/Qvs T); 

(iii¡ drawing a frequency-magnitude curve giving a 

general Q1/Qvs T relationship for use in the region; 

(iv) obtaining a regression relationship to estimate the 

mean annua.l (or index) flood Qfrom measurable catchment 

and climatic Parameters. 

The regression relationship can- then be applied at 

ungauged locations to estimate Q. Knowing Q 

' the 

regional frequenc¡' curves (iii) can be applied to determine 

Q1 for a specified return period T. This method is one way 

of extending a data base from a number of sites to cover a 

region. Design flood estimates have to be made for many 

more sites than can ever be gauged. This is justification for 

developing the method in New Zealand, where it should be 

noted that no quantitative information is available on the 

accuracy of currently used empirical methods. It has not 

previously been applied on a New Zealand-wide basis. It 

has the advantage that it is based directly on flood records 

whereas empirical and unit hydrograph methods rely on the 

transformation of rainfall into runoff' 

With the quantity of new data available by the middle of 

the 1970's it was c,cnsidered feasible to develop the regional 

flood frequency method. Regional inferences about flood 

frequencies were made to provide a design flood estimation 

method for catchments having little or no recorded data. 

The frequency dirstribution which is most generally applicable 

to the annual maxima series has been determined. 

the first step was to assemble and check records of annual 

ma¡


2 Gollection of Data 

2.1 Climate of New Zealand 

The climate and rainfall patterns are strongly influenced 

by the location and geography of the country. 

A useful summarv is given in the New Zealand Year 

Book (1978). In particular the chain of mountains extending 

from south-west to north-east through the length of 

the country is a barrier to prevailing moist westerly winds. 

The effect is to produce much sharper climatic contrasts 

from west to east than in the north-south direction. The 

summary also indicates typical weather patterns that lead 

to heavy rain. 

2.2 Selection of catchments 

Details of the criteria for choosing the catchments used 

in the two sections of the study are given in Chapters 3 and 

4 respectively. Initially all available annual maxima from 

rural catchments with four years record and with flows 

largely free from the effects of impoundments were considered. 

Catchment areas were required to be greater than 

0,1 km', but more restrictive ranges for area were imposed 

later (See Chapters 3 and 4). 

Lake inflows are the sum of flows from a number of 

small catchments that contribute to the lake. Because of the 

lesser channel routing effects in small catchments, the summed 

instantaneous peak inflow may differ from the peak 

flow from a single catchment of the same area subject to 

the same storm. Although Gilbert (1978) describes a data 

processing technique that ensures that lake inflows 

calculated from level and outflow records have realistic 

values, his work was not available at the time that the 

criteria for data selection were determined. Lake inflows 

were not used because the necessary calculation was believed 

prone to error. However, recent work on the data 

calculated by Gilbert's method shows that it conforms to 

the same regional pattern as river flow data. 

2.3 Sources of data 

Although earlier developments were promising, the recent 

progress in New Zealand in revising and developing 

flood estimation methods outlined above has been disappointing 

in comparison with other countries. Some of the 

iag can be attributed to a lack of suitable data. Recognition 

of the lack of data led to the implementation of the 

Representative Basin programme under which more than 

70 flow gauging stations were established with digital 

recorders in the 1960's and'early 1970's. These stations, 

together with improved instru 

rs, 

have recorded large quantities 

ata 

are available from files of the 

ent 

Data) hydrological archiving system which has been 

developed by the Ministry of Works and Development 

(MWD). 

Inspection of the data held in this system (Figure 2'l) 

showi that relatively few records were available before 

1950, and that after 195ó an extremely rapid increase occured 

in numbers of records a four-fold increase occurred 

over the decade 1960-70. More than 400 records were 

- 

available from TIDEDA in 1978; many more were not 

entered into 

of 

recorders ope 

an 

MWD report 

i9d 

ln- 

of recording, 

dicates whether the data are held in the TIDEDA system. 

With approximatel'y 700 water level recorders on lakes and 

rivers listed in this index, inadequate flow data should not 

constrain regional hydrological analyses as it has in the 

past. 

Annual series da:a were collected from MWD and catchment 

authority ftow stations. At the time of data collection, 

comments were obtained on the accuracy of the data 

and on the nature and conditions of the catchments from 

the people in chargr: of the streamflow data processing, and 

their advice was hr:eded in the acceptance or rejection of 

data. 

Where streamflow information was stored on the 

MWD's TIDEDA system, plots of the streamflow were obtained. 

Each plot vvas then scrutinised for the reliability of 

the streamflow record before the annual flood peaks were 

extracted from the record. 

2.4 Oualfty of the data 

The standards o I accuracy of data will undoubtedly vary 

considerably front one catchment to another. Records 

from a number of smaller catchments monitored at fixed 

control structures may be expected to be of good standard 

of accuracy for all flow conditions. For larger catchments 

where the control lLs a natural river channel section, the accuracy 

of estimat() of annual maxima will depend on the 

stability of the cross-section, the frequency of gauging, the 

range of flows overr which gaugings have been carried out, 

and the general standards to which the recorder is 

operated. Even if a good record has been maintained, conversion 

of a recor,l of water levels into discharge requires 

maintenance of a rating curve. In cases where the river has 

large sediment loa.ds this is a difficult task. Judgement is 

needed to decide how to extrapolate a rating curve, often 

defined only for rredium or low flows, into a high flow 

regime. Although greater confidence can be placed in 

rating curves which include some flood gaugings, such 

gaugings are not zrlways available. 

Although Ibbitt (1979) describes a data processing 

technique that ensures extrapolation of ratings to flood 

stage is not upset by channel changes, this technique was 

not the general practice when the flood data were assembled. 

The inconsistency in flood flow ratings on the Rakaia 

River prior to lbbitt's work (and illustrated in Fig' 5 in his 

paper) are presumrably typical of the hydrometric practice 

used to derive all the flood estimates used. 

2.5 Historical information 

Where possible. historical information was collected for 

those flow stations with annual series data. Information on 

historical floods, occurring both inside and outside the 

period of continuous record, was obtained from: MWD, 

õatchment authorities; reports; and from the publication 

"Floods in New Zl,ealand l92O-53" (SCRCC 1957). The information 

consisted of an estimate of the historical flood 

peak together witlh the period of time over which the peak 

was known to be the largest, second largest, etc. Advice on 

the authenticity o1i many of the earlier historical flood peak 

estimates was sought from the relevant data collection 

agencies. The methods by which this additional informati,on 

was used in the frequency analysis are described in 

Chapter 3. 


ll

Doto ovoiloble on 

TIDEDA 

Figure 2'1 Number of water level recorder stetions 

Water in & New soil technical Zealand and publication time d¡str¡bution no. 20 (1982) of water level data filed on TIDEDA. 

l2

3. Regional flood frequency analysis 

3.1 Flood frequencY method 

3.1.1 General 

Frequency analysis is a method of inferring the magnitude 

of a design event from a given sample of recorded 

events. The method is statistical and involves the fitting of a 

frequency distribution to a sample of recorded events. The 

resulting frequency curve is then usually extrapolated in 

order to estimate the design event. In the case of a frequency 

analysis of floods, the sample consists of flood 

peaks taken from a streamflow record. The sample may 

also contain some historical flood peaks, if this type of information 

is available. Provided the streamflow record 

from which the sample is taken is sufficiently long, flood 

frequency analysis is generally regarded as the most accurate 

method of estimating a design flood peak. 

A flood frequency curve may be used for a catchment 

where there is little or no streamflow record by a regional 

flood frequency analysis procedure. Inherent in such a procedure 

is the concept of a flood frequency region, i.e., in a 

region which is reasonably homogeneous in terms of climate, 

topography and soil characteristics and within which 

catchments display similar flood frequency properties. 

The regional analysis method employed in this study is of 

the Index-Flood type, pioneered by the US Geological Survey 

(Dalrymple 1960) and used by NERC (1975); it averages 

the chance sampling variation in individual streamflow records 

for a region, while preserving the variation due to differences 

in catchment and climatic variables. An essential 

part of the method involves the combining of the flood 

peak data for a region to produce an average or regional 

flood frequency curve, This regional curve is assumed to be 

generally applicable to catchments in the region and may be 

applied to both gauged and ungauged catchments. Because 

the regional curve is based on a number of records from the 

region, it provides a more reliable basis for extrapolation to 

estimate a design flood peak than an individual frequency 

curve fitted to a relatively short record. 

Several frequency distributions have been proposed for 

flood frequency analysis, but no single distribution has 

been universally accepted. The fitting of a distribution may 

be done either graphically, i.e., by fitting a curve by eye to 

the plotted data sample and then extrapolating that curve to 

estimate the design flood, or analytically, i.e., by estimating 

the distribution's parameters from statistical characteristics 

of the data sample. The anal¡ical approach, involving the 

General Extreme Value distribution, was used in this study. 

3.1.2 Terminology 

A fundamental concept in flood frequency analysis is 

that of a statistical population. The population is made up 

of flood peak items, where each occurs in a separate partition 

in time of the streamflolv at a site. These partitions are 

Ù c. 

ô 

x 

\ 

E 

ë 

l! 

or 

f(x) 

= dF(x) 

dx 

F(x) = ¡x-f(x)dx 

where, by definition 

F(-) : Il- f(x)dx = t 

Characteristics of the two functions, and the relationship 

between them, are illustrated in Figure 3.1 using 

the well-known Normal distribution. As shown in 

Figure 3.1, F(x), the df, is the probability of a variate 

value (x, in Figure 3.1) not being equalled or exceeded' 

It may be expressed generally as 

F(x) : P(Xsx) 33 

P(xsxJ =/j'lt'lo- 

Vor¡ole x 

Port (o) 

partitions in the total population. The variable value of a 

hood peak in the flood record is called a random variable 

or variate x. 

The probability distribution of the variate x may be described 

by either: 

(i) f(x), its probability density function (pdf), which gives 

the probability or relative frequency of occurrence of 

x; or 

(ii) F(x), the corresponding cumulative or distribution 

function (df). 

Vor¡ole r 

Port (bl 

P(xs xt) 

Flguro 3.1 Charaster¡st¡cs of the pdf (Part al and the 

The two functions are related bY 

df (Part b) using a Normal distr¡bution. 


l3

P=45 

O= 15 

x4 

(l) 

'= 

o 

o 

t.25 2'.O ¡b zs sb loo rooo T 

-z.o -t'o 2.O 3.O 

o.f o.3 0.5 0.7 0.9 0.95 o.9986 

YH 

F(x) 

Figure 3.2 The plot of the df in Fig. 3.1 as a function of its ¡educed variate, 

F(x) =l-P(X>x) 

34 

where P( 

ote the probability of 

non-exce 

respectively. 

Allied with 

dence is the notion of 

recurrence interval or return period, which is the reciprocal 

of the probability of exceedence in a time unit. For instance, 

if a flood peak is exceeded on average 20 times in 

every 100 years, it has a return period of 5 years, or a probability 

of exceedence in any one year of 0.20. Thus 

P(X>x) = I T 

which, from Equation 

F(x) = I 

3.4, gives 

_l 

T 

whereT = returnperiod. 

The curvatu 

35 

36 

and the reliability of the extrapolation when the fitted frequency 

line is straight rather than curved. A straight line 

for the df can be obtained by rescaling the F(x) axiJ with a 

on the F(x) axis, using the relationship between y and F(x) 

and Equations 3.3-3.6. In this way different probability 

papers, e.g., Normal and Gumbel, can be constructed to 

produce straight line plots of their corresponding distribution 

functions. Figure 3.2 illustrates the use of a reduced 

yariate (y¡) for the Normal distribution shown in Figure 

3.1. In accordance with convention, Figure 3.1 has been realigned 

in Figure 3.2, so that the variate scale is now on the 

ordinate and the probability and reduced variate scales are 

on the abscissa; future mention of frequency curves is with 

reference to this type of plot. The actual application of a reduced 

variate is explained fully in section 3.1.3 with reference 

to the Gumbel distribution. 

typical ofthat Despite the use of a reduced variate, a straight line will 

for a Normal 

are plotted to not give a good fit when the data sample does not conform 

natural scales. 

curvature for, to the assumed distribution. However, it may still be possible 

to obtain a good fit with a straight line by first trans- 

when fitting ã 

sferred to as a 

relative frequency or simply a frequency distribution) to a forming the data sample. The most common transformation 

is the changing of each sample item to its logarithm. 

data sample, it is easier to visually assess the goodness-of-fit 


l4

3.1.3 General extreme value distribution 

Of the frequency distributions used in flood hydrology, 

many belong to either the Gamma distribution family or 

the General Extreme Value (GEV) distribution. In this 

study the GEV distribution is used for fitting the regional 

data. This choice was supported by tests in which several 

distributions were fitted to flood peak samples. The distributions, 

the tests, and the results are described in Appendix 

A. 

Although the GEV was found to give a good fit to the regional 

data, it appeared from the tests that the log-Pearson 

Type 3 (LP3) distribution (also known as the three-parameter 

log-Gamma distribution) may well have given an 

equally good description ofthe regional trend. Aspects that 

influenced the choice in favour of the GEV distribution 

were the following: 

(i) In a comprehensive comparative examination of the 

GEV and LP3 distributions, NERC (1975 pp. 135-60) 

found that the GEV performed more consistently in 

the various goodness-of-fit tests. 

(ii) The GEV distribution had been found by NERC 

(1975) to describe their empirically derived regional 

curves "remarkably well". 

(lii) The fact that the GEV distribution had already been 

used by NERC (1975) enabled a direct comparison of 

jresults between that study and this one. 

(lv) The GEV distribution afforded the more tractable 

solution e.g., there was no equation available for the 

LP3 that is analogous to Equation 3.14, wherein the 

three-parameter distribution is expressed in terms of 

the reduced variate for its corresponding two-parameter 

(in this case log-Normal) distribution. 

The pdf for the GEV distribution may be written as 

f(x) = _t tl -k(x- u)/a|rk-ts-{l-k(x-u)/a}r/k .....3.7 

ct 

where u : alocationparameter, 

d: ascaleparameter, 

k = ashapeparameter, 

and the corresponding df is 

F(x): s-{r-k(x-u)/ø}k 

Like the Gamma distribution, the GEV distribution describes 

a family of distributions, each member of which is 

characterised by the value of the shape parameter, in this 

case k. The GEV distribution may be divided into three 

types of extreme value (EV) distribution depending on 

whether k is equal to, less than, or greater than zero. The 

three types, and the corresponding range for which the pdf 

(Equation 3.7) is non-zero, are defined as follows: 

(¡) if k = 0, the rlistribution is type I (EVl) and the pdf is 

non-zero for x>0; 

(¡i) if k < 0, the distribution is type 2 (Ev2) and the pdf is 

non-zeroforu + S . * < *; 

K 

38 

and EV3 is also known as Weibull. The three types are also 

called Fisher-Tippett type I, type2, and type 3. 

Since k = 0 for the EVI distribution, the distribution is 

only a two-param€rter one and the pdf simplifies to 

(Ð=å 

exp [ - (x - u)/o - e-(x- u)/a¡ 39 

while the df reducr:s to 

F(x) : s¡t [-e-(t -u),za¡ 

If a reduced varÍate y is now introduced for the EVI distribution 

such that 

or 

,, _ x-u 

a 

X:U+cry 

then the df may be written as 

and 

F(x) = s-e-r 

x: u +f,tr-r-url 

Using Equation 3.14 it is possible to distinguish between 

the three types of EV distribution by plotting them on an 

x- y probability plot (see Figure 3.3), otherwise known as 

Gumbel probability paper. 

The EV2 has a lower bound but no upper bound; conversely 

the EV3 has an upper bound and no lower bound, 

while the EVI iS unbounded. 

If required, return periods and associated probabilities 

can be scaled on the abscissa axis in Figure 3.3 by recalling 

from Equation 3.ór that 

and by substituting for F(x) in Equation 3.13. This produces 

T- I 

l- 

l-e-e-Y 

Y: -rn ('- rn(t-å, ) 

310 

3ll 

3t2 

313 

which gives rise to the name of double exponential distribution 

for EVl. 

Because Equations 3.ll and 3.12 describe a linear relationship 

between x and y, the df for the EVI distribution is 

given as a straight line on an x - y plot. 

The GEV distritrution may also be expressed in terms of 

the reduced variate y by the following equation derived by 

Jenkinson (1955) 

F(x):l-l 

T 

314 

315 

316 

(ili) if k > 0, the distribution is type 3 (EV3) and the pdf is 

non-zerofor-æ

Êv2 

( ko) 

Reduced Voriote y 

I'O 

t1 

50 too 

ttl 

5to20 

, Return Period, yeors 

Figure 3.3 Differentiation of the three types of extreme value d¡stribution. 

I 

200 

Table 3.1 The relationship between y and T values for the EVI 

distribution. 

Equations similar to 3.15 and 3.16, but this time relating 

y and the probability of exceedence, may be obtained by 

substituting P(X > x), as given in Equation 3.5, into the two 

equations. This results in 

1.O1 

2.OO 

2.33 

5 

10 

20 

30 

50 

100 

200 

500 

1000 

- 1.53 

0.37 

o.58 

1.50 

2.25 

2.97 

3.38 

3.90 

4.60 

5.29 

6.21 

6.91 

-2.O 

- 1.5 

- 1.O 

-0.5 

o 

o.5 

1.O 

1.5 

2.O 

2.5 

3.0 

3.5 

4.O 

4.5 

5.0 

5.5 

6.0 

6.5 

7.O 

1.OO 

1.01 

1.O7 

1.24 

1.58 

2.20 

3.25 

5.OO 

7.90 

12.69 

20.59 

33.62 

55.1 0 

90.52 

148.9 

245.2 

403.9 

665.6 

1 097 

and 

P(X>x) = I -6-e-I 

y = -fn(- fn(l-P(x>x))) .....3.18 

3. I .4 Sampling properties 

317 

The data sample, from which a flood frequency analysis 

infers a design flood magnitude, must possess the following 

properties if the analysis is to make the proper inferences 

about the population's distribution. 

Sufftcient Length The data sample should be sufficiently 

long, i.e., it should contain a large number of items. Often 

l0 annual flood peak items are considered sufficient (Neill 

1973; Beard 1977), though even then the sample is of limited 

use in design (Linsley et al, 1975) unless supplemented 

with additiongl hydrological information, €.g., a correlation 

with a longer streamflow record from a nearby station. 

t6 


Nevertheless, data samples of about l0 years in length are 

common and are often the only data available. 

Completeness The data sample should be complete, i.e., 

it should be taken from a continuous streamflow record. 

Gaps in the record do not matter provided it is certain that 

the maximum flood peak in the corresponding time unit 

was recorded. However, where flood peak sample items are 

missing as a result of gaps in the record, the time units containing 

the gaps shortid be only a small proportion of the 

total sample length. And rather than concatenating the various 

recorded sequences together, it is preferable instead to 

omit altogether the streamflow record for the time units 

with the gaps (e.g., omit whole years for an annual flood 

peak sample) and to treat the sample as having a correspondingly 

shorter length. 

Homogeneity The sample should be homogeneous, i.e., 

all the items should have occurred under the same conditions. 

Factors which.can affect the homogeneity of a sample 

include: man's activity (e.g., construction of reservoirs, 

land use changes, stopbanking, channel realignment, flow 

regulation, and diversions); faulty records; and changes in 

gauging control conditions that re-rating has not accounted 

for. Only samples which represent relatively stable catchment 

conditions should be used. The homogeneity of a 

large sample may be checked by splitting the sample into 

two parts and comparing the frequency curve fitted to each 

(Beard 1974, 1977). 

Rondomness The time unit must be long enough that each 

flood peak item in the sample is from a different flood 

event, so that it is reasonable to assume there is no serial 

correlation between successive flood peak items. 

Reliability The sample items taken from the streamflow 

record should be reliable measurements or estimates' Measurement 

errors are generally small in relation to the year-toyear 

variance in the sample items and can therefore usually 

be neglected. The errors that are of concern result from 

large extrapolations of the stage-discharge rating curve and 

from the existence of an unstable gauging control. These errors 

reduce the reliability of the data sample and, consequently, 

the reliability of the fitted frequency curve, and 

thus a record needs to be checked for their presence. 

Representativeness The data sample should be representative 

of the long-term or population distribution of items. 

Clearly this is difficult to assess because the population is 

unknown. However, the representativeness of the sample 

can be tested statistically if there is a long-term streamflow 

record for a similar catchment nearby (McGuinness and 

Brakensiek 1964). Where tests show conclusively that the 

sample is unrepresentative on a long-term basis, there 

*ould be no point in applying frequency analysis methods; 

the resulting frequency curves would have little predictive 

value. 

3.1.5 Types of samp¡e 

In general three types of flood sample may be identified. 

Annual Series The most usual form of a data sample is 

the annual series, which consists of the maximum flood 

peak for each year of 

Pling generally 

produces items 

However, 

it is claimed that a d 

sample is 

that it may ignore some large flood peaks and emphasise 

smaller ones. 

Peaks Over a Threshold Series An alternative type of 

sample is the partial duration series, which seeks to overcome 

the disadvantage of the annual series by containing all 

flood peaks above an arbitrarily chosen base level. Sample 

items chosen in this way need to be checked much more 

closely for serial correlation than an annual series, because 

large floods often contain more than one peak above the 

base level. 

Historical Series l{istorical information on flood events is 

often available. rùy'hen it is reliable it should be used in conjunction 

with the data sample taken from the continuous 

streamflow record. The resulting data sample is called a historical 

series. The inclusion of historical information often 

significantly increases the length of a sample, thereby improving 

the reliabitity of the frequency analysis. Moreover, 

the information herlps to fix the top end of the frequency 

curve, the end in u¡hich there is generally most interest. 

In this study the: basic data sample used was an annual 

series, which consisted of the maximum instantaneous discharge 

for each year of record; historical information was 

also included where possible. The partial duration series 

was not used, even though it contains more items than the 

annual series for a given length of record. It was excluded 

because its advantage over the annual series is only when 

the design return period is less than l0 years (NERC 1975; 

Chow 1964, pp.8-i!.2,23). Furthermore, there is no guarantee 

that it is better than the annual series simply because it 

contains more data. As has been pointed out by NERC 

(1975, section 2.2.4 and section 2.1\ and by Cunnane 

(1975), the dictum "more data, better estimates" is not universally 

true, and in certain circumstances estimates from 

an annual series can be more efficient statistically than 

those from a partiial duration series taken from the same 

record. 

3.1.6 Plotting 

The probability plot, i.e., the x-y plot of the sample 

data, is an integral part of hydrological practice. Despite 

the numerous statistical goodness-of-fit tests now available, 

few engineers who have to make decisions which are based 

on the analytical fitting of theoretical distributions to sample 

data would do so without first inspecting the fit of the 

frequency curve on a probability plot. 

In order to construct a probability plot, it is necessary to 

know the return period or plotting position of each sample 

item. Various fonnulae are available for calculating plotting 

positions, witlh the following one the Weibull form- 

- 

ula 

- being the nrost popular: 319 

T -N+l rP - __ 

i 

where Tp 

and i 


N 

the return period plotting position of a 

fJood peak, in years; 

the length of record in years (e.9., the 

number of annual peaks for an annual 

sr:ries); 

= the rank of the flood peak in the series 

(r:.g., I for the largest and N for the smal- 

Iest of an annual series). 

The formula has gained wide acceptance, largely because 

of its simplicity and the fact that it gives results one would 

intuitively expect. For example, the largest peak in an annual 

series has a c,alculated plotting position only one year 

greater than the length of record. This is consistent with 

Gumbel's (1943) reasoning that the largest item in a sample 

of N items should not have a return period significantly 

greater than N, However, there is statistical evidence 

against such an inl.uitive line of thought. For example, Cunnane 

(1978), in a comprehensive review of plotting positions, 

has shown statistically that for samples of size N belonging 

to the EVI distribution, the largest item in the sample 

has a return ¡reriod in the parent population of about 

1.8N. In fact NEIìC (1915, p.67) and Cunnane have made 

the point that the Weibull formula gives biased plotting 

positions, which, on average, leads to an over-estimation of 

flood peaks for high return periods. 

Cunnane emphrasised the need to distinguish between the 

plotting position of a sample item and that item's actual ret7

turn period. A plotting position formula merely gives the 

position at which the item should be plotted in order to 

assess the goodness-of-fit of the frequency distribution. 

The actual return period of the item should be inferred 

from the fitted distribution. 

TP N + 0.12 

i-0.4 

Equation 3.20 also gives a reasonable approximation of 

the unbiased plotting positions for a GEV distribution displaying 

small or moderate curvature. It was therefore used 

in this study for the calculation of plotting positions for the 

methods involving EV distributions. It is possible to calculate 

exact plotting positions for the EVI distribution for 

small values of N but in practice, for N ) 35, the calculation 

is overwhelmed by ro 

a 

,N 

" a' iD=, 321 

320 

S). 

(section 

where Q¡ an individual annual flood peak, and 

N the length, in years, of the annual series. 

A dimensionless probability plot was then obtained for 

The annual flood 

3.2.1) for each flow s ¡sionless 

form by dividing through by the corresponding mean annual 

flood Q, defined as the arithmetic mean of the annual 

series. Thus 

mean annual flood Q standardises the series, permitting a 

direct comparison of the plot of one series with anothèr. 

Significant differences between plots are interpreted to 

mean that the corresponding ftow stations belong to different 

flood frequency regions. 

volved, namely whether 

(D the historical floods occurred outside the annual series; 

or 

(ii) tne historical floods occurred inside the annual series. 

Dealing first with the type (i) series, consider an annual 

period of J years, 

to have occurred, 

seri 

dur 

givi 

fN+Jyears.In 

this 

nnual seiies were 

based on a record length of N years, as before, while the 

plotting positions of the historical floods were based on the 

th of N + J years. Hence, for exorical 

flood had a return period plotby 

TP :(N + J) + 0.12 = 

i-o.4 

(N+J) + 0.t2 322 

0.56 

For the type (ii) series, consider the largest flood peak in 

the annual series, of length N years, which also is known to 

be the largest over a longer period of N + J years. Here the 

t8 

plotting position of the largest peak was based on the length 

of the historical series N + J years, giving a return period 

as indicated by Equation 3.22. The other flood peaks in the 

annual series were then treated as the 2nd, 3rd largest etc. in 

N years. 

In the special case where there were two historical floods, 

one outside and one inside the annual series of length N 

years, the plotting positions of these two floods were based 

on N + J years. Again the ordinary annual flood peaks 

were considered as the 2nd, 3rd largest etc. in N years. 

3. 1.7 Computer programs 

In this study flood frequency analyses were performed 

analytically using a computer program called FRAN 

(Maguiness et al. in prep.). The methods included in the 

program are outlined in Appendix A. Another program 

called FRANCES (Appendix A) was developed ro analyse 

the historical series data, which typically comprised an annual 

series and an additional period of unknown record in 

which one or more large, notable, and hence historical 

floods, occurred. The program FRANCES performs a frequency 

analysis of a censored sample, which may be defined 

as a sample which contains unknown flood peaks that 

all lie on one side of a given threshold value or censoring 

point. An historical series may often be regarded as a censored 

sample, where the unknown peaks are those which 

occurred outside the annual series and which were less than 

the known historical flood peaks. In using the program, it 

is necessary to specify the historical flood peaks and to 

assume that none of the unknown peaks exceeded the censoring 

point, which must be set at a value less than the historical 

peaks. 

same method. 

3.2 Flood frequency data 

3.2.1 Data collect¡on 

The collection of annual series data was restricted to 

thosè flow stations which satisfied the following conditions: 

(i) the catchment land use had not changed significantly 

over the period of record; 

(ii) the annual flood peaks were not substantially regulated 

or affected by impoundments, swamps or diversions 

within the catchment; 

(iii) there were eight or more annual flood peaks available; 

(iv) when historicat flood peak information was available, 

there were also at least five annual flood peaks; 

(v) the catchment was rural, or predominantly so; 

(vl) the catchment area was greater than 20 kmr. 

The first two conditions are consistent with the normal 

requirements for data samples (section 3.1.4). The third 

condition of only 8 or more years of record is slightly less 

than the l0 years that is generally recommended as the 

minimum sample length required for a typical flood frequency 

analysis. However, this study was concerned, not so 

much with flood frequency analyses for individual stations, 

as with the derivation of regional curves from mass plots of 

all the data for the regions (section 3.1.5). The reduction in 

this study of the minimum sample length to 8 years allowed 

the data for an extra 25 ftow stations to be used. It appeared 

that these extra data would reinforce the definition 

of the lower end of the regional curves. 

The fourth condition, specifying five or more annual 

flood peaks, was needed so that the mean annual flood Q 

could be calculated, thus permitting the station,s historical 

peaks Q to be expressed in the form of Q/Q and included 

in the mass data plot for the region. Unless there were eight 


or more annual peaks, however, the annual peaks themselves 

were not considered for the mass plot. 

Condition (v) was necessary because the flood estimation 

method sought was intended for rural catchments, not urban 

ones. 

Condition (vi) was imposed in the belief that flood frequency 

characteristics of the very small and the larger 

catchments would be markedly different. It was anticipated 

that the effect of catchment storage in dampening the flood 

hydrograph would be less in the very small catchments, 

producing a steeper frequency curve of Q/Q than that for a 

laiger catchment with the same rainfall excess. An area of 

20 kmt was chosen as the lower limit on the size of a catchment. 

It was later found, however, that catchments of 

smaller size could have been included in some of the regions 

(section 3.5.6). 

An exception to the lower limit of 20 km'z was made for 

the Northland-Auckland area. In this part of the country 

there are relatively few large catchments, and without a relaxation 

on the minimum catchment size any flood estimation 

method would have only limited application. Moreover, 

the presence of swamps had caused the rejection of a 

number of annual series samples for flow stations in the 

area. Therefore, to ensure that a reasonable amount of 

flood peak data was obtained for the area and to enhance 

the practicability of the resultant flood estimation method, 

the lower limit on catchment size was reduced in the Northland-Auckland 

area to 2 km'. 

The data samples collected were plotted on Gumbel 

probability paper and, after checks were made of their repiesentativeness 

(section 3.2.2), samples for 152 stations 

were finally accepted for use. For 148 of these stations 

- 

96 in the North Island and 52 in the South Island 

- 

the annual 

series was eight years or longer; the remaining four stations 

had historical information and an annual series of between 

fltve and seven years in length. Five of the stations 

were later omitted for the derivation of the regional curves 

(see Table 3.2 and Appendix B). The location of all the staiions, 

and their associated catchments, are shown for the 

North and the South Islands in Figures 3.4 and 3.5, respectively. 

Information on the stations is listed in Table 3.2' 

grouped according to the regions into which the stations 

were initially classified (section 3.3.1). The annual flood 

peak data for the stations, statistics of the data, and comments 

on the data and the catchments are summarised in 

Appendix B, again according to the initial regional classification. 

Attempts to extend short records by correlation 

with adjacent longer records for a sample of stations in the 

northern half of the South Island were unsuccessful and the 

approach was not Pursued. 

3.2.2 Minimum record length and outliers 

ferent distribution' 

on the use of an outlier are given by Irish and Ashkanasy 

are as follows: 


(i) lf 5

'o ,l\, 

I 

zl 

l- 

I 


l' 

cooxi: 

i- 

i - --l- ii 

'___-T--- 

ô¡ 

sì 

c 

o 

6 

ø 

ì 

-9 

It c66 

E 5o 

al, 

ro 

Gt 

a¡ 

-É ¡t 

I 

I 

--- 

ri 

| _,+ -- 

\ 

\ 

t 


Table 3.2 Flow stat¡ons used. 

SITE NO. 

FLOW STÀTION 

CÀTCHME{T ÀREÀ (KN2) 

NO. ANNUÀI, (ÀND 

HISTORICÀI) FI¡OD PEÀI(S 

NORTHERN NORTH 

REGTOIV 

3506 Maungaparerua Rl-ver at Tyrees Ford 

3819 Waiharakeke River at will@ Bank 

49OI Ngunguru River at Dugmorers Rock 

5809 Waiarohia River at RusselL Road 

8501 wairoa River at !{eir 

9101 waitoa River at [ihakahoro Bridge 

9108 Piako Rj-ver at whalahoro Road 

9203 waihou River at Puke Brjdge 

9204 ohinemuri River at criærion Bridge 

9213 Ohinenui River at KarangahåÌe 

9223 Waihou River at Shaftesbuly 

930I Kauaeræga River at Snithrs 

14627 Waiari River at Muttons 

43803 Papakura River at S.H. Bridge 

45702 waiwhiu River at Done shadow 

4661I Kaihu River at corge 

46618 Megal(ahia River at corge 

46625 Hikurangi River at Kæ-Hikurangi Bridge 

46632 Whakapara River at S.H. Bridge 

46660 Puketurua River at PuketiÈoi 

47527 Opahi River at Pond 

Ib. 

NORTH ISLAND WEST' COAST REGTON 

33IOl Whangaehu River at Kauangaroa 

33103 llhangaehu River at S.H. 3 Bridge 

33107 Whangaehu River at Karioi 

33111 Mangawhero River at Ore Ore 

33114 Waitangi River at Tangiwai 

33U5 l.,langaetoroa River at School 

33II7 ¡{akotuku River at s.H. 49À Bridge 

33301 fdanganui River at paetawa 

33302 Wanganui River at Te Maire 

33309 f.,fanganui-o-te-ao at Àshworth 

33313 Ohura River at Tokori.m 

33316 Ongarue River at Taringmutu 

33320 WhakaIEIÉ River at Foot¡ridge 

33338 l.langanui River at Matapuna 

3600I Punehu River at pihila * 

39501 Waitara River at Tarata 

39504 ¡,tanganui River at Tariki F.oad 

43433 WaiIÞ River at VthaÈawhata 

43435 WaipalÞ River at Ngarona Road 

LO43427 Mangakino River at Dillonrs Road 

1043461 longariro River at Upper Dan 

1043466 Vlaihohonu River at Desert Road 

Lc. 

MANAI,/A1I.'-RANîITIKEI RE1ION 

31903 Otaki River at hlapaka 

32502 Manawatu River at Fitzherbert Bridge 

32503 Manawatu River at Weber Road 

32514 Oroua River at Almadale 

32526 Mangahao River at Ballance 

32529 lirawea Rive! at Ngaturi 

3253I t4angatainoka River at Suspension Bridge 

32563 Oroua River at Kawa Idool 

32576 pohangina River at Mais Reach 

3270L Rangitikei River at Kåkariki 

32702 Rangitikei River at Manqaweka 

32708 Rangitikei River at Springvale 

32723 Maungaraupi River at porewa Road * 

32732 Moawhango River at Waiouru 

32735 Rangitawa River at Halcombe 

32739 Tutaenui River at Hmond Street 

Id. 

SOUTHERN NQRTE ISLAND REGION 

292OL Ru4ahanga River at wardells 

29202 Ruanahanga River at Waihenga 

29224 Waj-ohine River aÈ Gorge 

29231 Taueru River at Te Weraiti 

29242 Atíw}lakatu River at Mt Holdsworth Road 

29244 Whangaehu River at waihi 

29808 Hutt River at Kaitoke 

29818 HuÈt River at BirchviLLe 

2. BAY OF P¡NNTY REGTON 

11. I 

229 

L2.5 

L6.2 

L2.7 

433 

528 

1606 

308 

287 

984 

L22 

69.9 

57 

s.03 

tt6 

246 

I89 

L62 

2.4e 

r0.6 

t9t7 

I968 

492 

539 

63.5 

33.2 

20. I 

6643 

22I2 

332 

668 

1075 

184 

97L 

29.5 

725 

80 

2926 

r37 

373 

L74 

88 

301 

3916 

713 

3L2 

266 

734 

452 

570 

4'11 

3595 

27A7 

583 

25.6 

245 

62.4 

47 -7 

637 

2340 

ts3 

373 

38. B 

36 .3 

88. g 

427 

49 

10 

10 

I 

LO plus I hlstorical 

I5 

17 (includes I histolical) 

L7( 

19( 

13 plus 

L7 

L2 

18 

historl.cal 

t0 

I 

10 

I plus I hlstorícal 

17 (includes I hlstorical) 

I 

L7 

L2 

L2 

I plus I historical 

l0 

13 

9 

ó 

19 

L4 plus I hÍstoricaL 

t5 

I5 

14 plus I historical 

L7 

I plus I historical 

I 

I (includes I historica¡-) 

L2 

I3 

T4 

L7 

L4 


(includes !. historicaL plus l) 

22 

24 

24 

24 


lo 

I 

5 plus 3 historical 

(includes I historical pLus t) 

l0 


L7 

I2 

22 

2L 

22 

I 

9 

9 

9 


L4610 Utuhina River at S.H. 5 Bridge 

14614 KaiÈuna River at Te lltatai 

14628 ¡,tangorewa River at Saunderrs Fam 

15408 RangitaÍki Rjver at ¡turupara 

33307 l,llanganui River at Headwaters 

33324 Mangatepopo River at Ketetahi 

33347 Wanganui River at Te porere 

43472 Waiotapu River at Reporoa 

1043419 Pokaiwhenua River at puketurua 

1043428 Tahunaatara River at OhakurL Road 

:043459 Tongariro River at TurÐgi 

!043460 Tongariro River at puketarata 

), 

57 

958 

L79 

II84 

8I .3 

3t 

24.2 

22A 

448 

2LO 

772 

495 


I6 

20 

L7 

9 

2l 

9 

(includes I historlcal) 

II 

I 

IO 

(includes I historíctl) 

13 

L2 

(includea 2 historicat) 

('

SITE NO. 

FI¡W STÀîION 

CÀTCHT.{ENT ÀNEÀ (KN2) 

t¡o. ÀÀ¡NuÀf, (À¡¡D 

HISTORICÀT,) FI¡OD PEÀKS 

3. NORTH TST'AìID EAST COAST REGION 

15410 Whirinaki River at Galatea 

15432 Rangitaiki River at Kopuriki 

I55II waima River at vlaimÐa Gorge 

I55I4 Í¡hakatane River at whakatane 

15536 wainana River at Ogilvies Bridge 

15901 Waioeka River at Gorge cablesay 

I97ol waipaoa Rive' at Kanakanaia Bridge 

19?09 wharekopae River at Killarney 

I97tI waingaronia River at Terrace 

2I80I Mohaka River at RauPunga 

21803 Moha](a River at Glenfalls 

22802 E,sk River at WaiPunga Bridge 

4. CEI\¡?RÀ¿ HAWKES BAY REG¡ON 

23OOl lutaekuri River at PuketaPu 

23002 Tutaekuri.River at Redclyffe 

23102 Ngaruroro Rive! at Fernhill 

23104 Ngaruroro River at KuriPaPango 

23106 Taruarau River at TaihaPe Road 

2320f Tukitui

e process of examining the simtrend 

was repeated. Adjoining 

d a similar trend were combined 

together to form a flood frequency region. In this way ll 

regions were built up. 

In constructing the regions due recognition was taken of 

the many factors that would influence the floods in the different 

catchments. Attention was given to the climat€, topography 

and soils of the catcr,ments, and the aim was to 

have catchments with similar flood-producing characteristics 

located in the same region. The construction was 

guided by maps that showed countrywide climatic and physiographical 

patterns, e.g., a Meteorological Service ãvei- 

Survey topographical maps. 

The ll flood frequency regions that were fîrst decided 

upon are shown in Figures 3.6 and 3.7. Four of these regions, 

Regions la-ld, were later combined into one (section 

3.3.2). The list of stations within each region is given in 

Table 3.2. 

3.3.2 Development of reglonat flood frequency 

cutves 

The y values that were used in the regional plots were ob_ 

tained in the following ma¡ner: 

(i) For flood records less than or equal to 35 years in 

length, the y values were the exact ones for the unbiased 

plotting positions for the EVI distribution and 

they were taken from a table in NERC (1975, pp.g2_ 

3). 

(¡i) 

0.5 class intervals, and an average e/Q and y value was calculated 

from the data points falling within each class. This 

averaging process was the same procedure as that used by 

NERC (1975) and it produced a smooth trend in the regional 

data. 

The GEV distribution, namely 

In the second case no constraint was placed on the value for 

k, so that in general a GEV fit was obtained. However, because 

of the relatively small size of many of the data samples 

used, and in view of the findings in the evaluation tests 

(Appendix A) relating to small samples, the EVI fit was regarded 

as the regional curve unless the GEV fit produced a 

significant reduction (10 percent or more) in the sum of 

squares. 

It was not always practical, however, to fit Equation 3.14 

to a regional set of average values. Because of the limited 

amount of flood peak data available for some of the regions, 

the averaging process sometimes produced an unrepresentative 

or biased set of average values for a region, 

where the average values for low class intervals of y were 

based on many data points while for higher class intervals 

they represented only one or two points. To reduce the possibility 

of obtaining unrepresentative regional curves, 

Equation 3.14 was only fitted to a s€t of average values 

when: 

(l) the total number of flood peaks for a region was 

greater than lü); and 

(ll) there was no more than one average value for the region 

that was based on one data point. 

When these criteria were not satisfied, the regional curve 

was defined instead by fitting Equation 3.14 in the manner 

described ea¡lier to all the plotted data for a region. 

Except for the Bay of Plenty (see section 3.3.3), the regional 

curves were obtained from the procedures outlined 

above and are given in Figures 3.8-3.16. tilhere a regional 

curve wÍrs dehned from a set of average values, the plot of 

the curve fitted to these values is shown along with the corresponding 

regional probability plot, which contains all the 

flood peak data for the region. (The historical peaks in a regional 

plot are indicated with circles and the corresponding 

site numbers are given alongside). Where average valuei 

were not used, only the regional plot with the regional curve 

superimposed is shown. 

The regional curves derived for the North Island West 

Coast regions, i.e., Regions la-ld, are plotted together in 

Figure 3.17. Although there are differences in the trends of 

the data in the corresponding regional plots, it can be seen 

from Figure 3.17 that the flrtting of the straight-line EVI 

distribution to the data of each region masked these differences 

in close agree_ 

ment. 

seeme 

the curveS, it 

ction between 

four regions 

for the com- 

. Vy'est Coast 

region. Averages ofthe pooled data were calculated for the 

x=Q/Q 

= u*9(l-e-tv¡ 

k 

3t4 

24 

a :a 

=U*oy 323 

Support for pooling the data from several regions together 

is given by Stevens and Lynn (lg8) who used three 

statistical tests to analyse the variation amongst the regional 

curves derived by NERC (1975). They concluded that the 

curves for some regiôns of Great Britain, while not necessarily 

identical, were certainly very similar. On these 

grounds they pooled the data for the regions with similar 

curves to obtain more stable estimates of floods at high return 

periods. The data were pooled into two groups, one 

for the fïve south-east regions of Great Britain and one for 

the five north-west regions. A frequency curve was then fitted 

to the data of each group and extended to the lüXÞyear 

return period. 


I 

Fþuru 3.6 North lsland flood frequency regions. 


25

Iì_ 

t_ 

I 

I 

I 

I 

I 

I 

I 

t-. 

I 

I 

tñ 

I 

LÓ. 

I 

t¡l 

l\-' 

LØC' 

I 

South lslând west Coast 

l 

_l 

I 

T.- 

t-l-l 

\ 

\ 

i 

l 

\- 

\ 

\ 

\ 

\ 

Flguro 3.7 South lsland flood frequencV regions. 


26

NORTHERN 

to 

o 

o 

ñ' 

Þ 

o 

.,¡' 

c 

e. !:r 

NORTHERN 

NEIUNN FERIOD ÍYEFRS) 

N.I. BEGIONßL CUBVE 

.50 2.25 3.00 

REOUCEO Y VRFIRTE 

¿. t! É rb zb rb so z's roo 

RETUNN PEßIOO fYEÊNS) 

, Fþure 3.8 Region la: the regional plot and curve. 

27 


Þ 

I"IEST COFST 

0 

o 

I 

E 

6o 

o 

o 

25 3,00 

NEOUCEO Y VFñIRÎE 

r.btl 23t Ë tô 20 30 so ?5 loo 

REÍUNN PENIOO fIERñSI 

NEST COFST N. I . BEG I ONÊL CUBVE 

o 

o 

o 

lo 

g 

o 

6 

o 

i.so ¿."s i.oo 

NEOUCEO Y VFNIßTE 

É r'o zi s'o Eo ?-6 lôo 

RETUNN FEN¡OO (TEFFSI 

28 

Figun 3.9 Region lb: the regional plot and curve. 


MßNRI,.¡RTU-RßNGITIKEI BEGIONIRL CURVE 

o 

a 

"; 

o 

"; 

o 

Ð 

"i 

l@ 

G oo 

"; 

o 

I 

BEOUCED 'I VRH I ßTE 

5102030 

RETUBN PEBIOD (YEHFs) 

Flgurc 3.1O Region lc: the regional plot with the curvo superimposed. 


29

SOUTHEBN 

REDUCEO Y VRBIßTE 

NETURN PEBIOD (YEHNSI 

o 

SOUTHEBN N. I. BEGISNRL CUBVE 

Þ 

o 

Þ 

o 

Þ 

o 

lø 

@ 

o 

è 

o 

t,50 2.?s i.oo 

BEOUCED Y VFRIFTE 

s rò ao 3b sb ;'s röo ãõo 

RETUBN PEBIOO (YEFBS) 

30 

Fþuru 3.11 Region ld: the reg¡onal plot and curve. 


CORST 

BEG I ONÊL 

CUBVE 

REOUCEO I VRBIRTE 

l.ort 2.33 5 l0 20 30 50 .75 t00 200 

BETUNN PEFIOD (IERHS) 

Fþure 3.12a Region 3: the regional plot w¡th the curvo superimposed. 

CENTBFL HRhIKES BßY BEGIONFL CUBVE 

l.so 2.2s 00 

FEOUCEO Y VRBIRTE 

r.ótt 2'33 s to zo 30 so ?s lo0 ¿00 

BETUBN PENIOO (YEFNS) 

Fþur 3.12b Region 4: the regional plot with th€ curve superimposed. 


3l

SOUTH ISLFND HEST COFST I]ÊTR 

èo 

d' 

o 

I 

.ü' 

lct 

o oè 

o 

b 

.50 ¿.25 3.OO 

NEDUCEO Y VFNIâTE 

NETUNN FEBIOB (YERBs¡ 

Þ 

SOUTH 

ISLÊND 1,,IEST COÊST BEGIONRL CUBVE 

Þ 

o 

è 

o 

IG 

oo o 

o 

Þ 

0 

REOUCEO Y VFNIFTE 

NETUNil PEN¡OO fYERBS¡ 

32 

Fþurc 3.13 Region 5: the rog¡onal plot and curve. 


SOUTH 

I SLRNT] 

o 

ê 

Þ 

Þ 

Þ 

lo 

Go o 

Þ 

o 

00 3.75 {,50 5.25 

FEOUCEO Y VRNIFTE 

l.otl ?,9t s ¡0 20 lo s0 75 100 200 

BETUßN PEBIOO (IERFS¡ 

SOUTH ISLÊND EÊ5T COÊST REGIONßL CUßVE 

.so 2.2s 3.00 

REOUCEO I VßNIRTE 

Ë l'o io !'o so ?3 róo 

RE'TURN PEBIOO (YERNSI 

F¡gur.3.14 Regbn 6: the regional plot and curve. 


33

SOUTH CÊNTERBURY DRTÊ 

NEOUCEO Y VßFIFTE 

l.ott 2,33 s ¡0 20 30 s0 7s 100 200 

RETURN PEßIOO (YEÊNS} 

o 

SOUTH CÊNTERBI-JRY BEG I ONF]L CURVE 

t 

o 

o 

Þ 

G' 

oo 

o 

o 

t 

r.so 2.2s 3.00 3.75 q.so 

NEDUCED Y VÊNIRTE 

2.93 5 ¡0 20 30 50 7s 100 

RETUBN PER¡OD (IEß85) 

34 

Flgure 3.15 Region 7: the regional plot and curve. 


OTFGO_SOUTHLÊND BEG I ONFL CUßVE 

s0 -75 00 

BEDUCEO Y VßBJßTE 

00 q.50 s.zs 

l.0ll 2.33 5 lo 20 30 s0 ?s 

RETURN PEBIOO {YEßBSI 

Flgure 3.16 Region 8: the regional plot with the curve superimposed. 

N. I . I,'IE5T CORST BEG I ONRL CUBVES 

r00 200 

2.31 

00 3.75 r¡.50 

REOUCEO Y VFRINTE 

10 20 J0 

NETURN PENTOO --- (YERRS) 

50 7ri 100 200 

Flgure 3.17 Summary of the regional curves for Regions 1a-1d. 


35

COMB I NED 

,,IE5T CORST DRTR 

o 

rt 

€o 

o 

o 

NEOUCEO Y VFBIRTE 

?5 r¡.50 5.25 

t-0¡¡ 2.93 s t0 zo 30 so ?'5 róo eú¡ 

BETIJñN PEBTOO (YEßñS¡ 

j 

COMB I NED N. I . IÎEST COÊST ßEG I8NÊL CURVE 

o 

Þ 

a; 

o 

ê 

Þ 

ø 

rct 

o 

o 

o 

D 

o 

50 -'.75 1.50 2.25 3.00 3.75 r¡.50 5.25 

SEDUCED Y VßNIRTE 

t.oll 2.1! 5 t0 ¿0 !o 50 75 r00 200 

NETUNN FEBIOO (IEflNsI 

Figure 3.18 Region 1 the regional plot and curve. 


36

3.3.3 Bay of Plenty region 

Missing from Figures 3.8 to 3.16 is the plot of the regional 

curve for the Bay of Plenty region (Region 2). In defining 

the average curve for this region it was found that 

four large historical floods appeared to produce an unrealistically 

high degree of upwards curvature at the top end of 

the fitted curve. Fitting a curve to all the plotted data instead 

of just the average values made very little difference. 

Therefore in an effort to obtain a more realistic regional 

curve, an extension method was employed (NERC 1975, 

pp.l7t-2). 

The method involved splitting the dimensionless flood 

peak data for the region into three groups (Table 3.3a). 

Each group contained the data for stations whose catchments 

were not close neighbours, so that it could be assumed 

that a group's sample items were statistically independent. 

The largest four Q/Q values in each group, irrespective 

of station, were then treated as the four largest 

values in a random sample of size M, where M was the total 

number of station years spanned by the data in a group, 

and not simply the total number of flood peaks for the stations 

in a group. Hence, where there was an historical series 

containing a flood peak known to be the largest in N + J 

years, the number of station years for this particular station . 

was N * J years, the historical record length. In the special 

case where the historical series did not contain the largest 

historical peak in N + J years but, say, only the second or 

third largest in that period, the number of station years was 

not so straightforward and an equivalent length in years 

had to be determined. The return period of the second or 

third largest historical peak was calculated using the Gringorten 

formula (Equation 3.20) and substituted back into 

the formula, this time using a rank of one instead of two or 

three as before. The value of N resulting from this back 

substitution was taken as the equivalent length of station 

years. 

The number M varied from group to group, but an attempt 

was made to keep it reasonably constant. Values for 

y were calculated for the four largest Q/Q values in each 

group by taking M as the record length and using the Gringorten 

formula and Equation 3.16 (Table 3.3b). The 12 

pairs of Q,zQ values and their corresponding y values, i.e., 

the four pairs from each ofthe three groups, were averaged 

over the 0.5 class intervals of y (Table 3.3c), and the three 

largest averages were plotted along with those obtained 

from the original flood peak data. There is some statistical 

dependence between the two types of average values, but it 

was thought that, with M being fairly large for each group, 

the dependence would be small. Finally the regional curve 

was defined by fitting Equation 3.14 to the combined set of 

original and new average values. 

The probability plot of the regional data is shown in Figure 

3.19 (the four historical flood peaks are indicated with 

circles and the corresponding site numbers are given alongside). 

Also shown is the regional curve that resulted from 

fitting Equation 3.14 to the original and new average 

values. The latter values are indicated with squares. 

It was difficult to finalise the Bay of Plenty's southern 

boundary line which, from the probability plots, appeared 

to lie somewhere near the mountains in the volcanic plateau 

area of the North Island. Besides the problems caused by 

the geology and the uncertain Ìveather pattern in this area, 

there were also complicatións arising from the Tongariro 

Power Development Scheme which had altered the natural 

flow of some of the rivers. While the chosen southern 

boundary is reasonably consistent with the geology of the 

area and with the trend in the probability plots for the stations 

concerned, some further definition of the boundary 

line may be necessary at some later stage. 

The definition of the Bay of Plenty on its eastern boundary 

posed a problem of a quite different nature. The probability 

plots clearly indicated that the eastern boundary line 

TaHe 3.3 Calculatk¡ns for extending the set of average values 

for the Bay of Plenty region. 

(a) Grouping of statio,ns 

Group 1 Group 2 Group 3 

Mangatepopo @ 

Ketetahi 

t=8 

Utuhina @ 

S.H. 5 Bridge 

r=9 

Tongariro @ 

Turangi 

t=26 

Waiotapu @ 

Reporoa 

f=38 

Wanganui @ 

Te Porere 

l=10 

Kaituna @ 

Te Matai 

r=21 

Tongariro @ 

Puketarata 

t--26 

Tahunaatara @ 

Ohakuri 

t=12 

Wanganui @ 

Headwaters 

( = 11 

Mangorewa @ 

Saunders Farm 

f=9 

Rangitaiki @ 

Murupara 

t-_38 

Pokaiwhenua @ 

Puketurua 

¿ = 13 

M=81 M=69 M=71 

/ = the length in ye,ars spanned by the data for a station. 

M = the total length of station years spanned by the data ¡n a 

group. 

(bl The maximum O/O and y values 

Group 1 Group 2 Group 3 

o/o o/o O/o y 

2.870 4.972 

2.464 3.941 

2.044 3.440 

1.746 3.104 

2.649 4.811 2.994 4.840 

2.462 3.780 2.261 3.809 

2.008 3.277 1.993 3.306 

1.944 2.940 1.960 2.969 

(c) Classification and averages of the maximum O/O and y values. 

y interval 

4.5 - 5.O 

4.O - 4.5 

3.5 - 4.O 

3.O - 3.5 

2.5 - 3.O 


No. of values Average O/O Average y 

3 

3 

4 

2 

2.84 

2.40 

1.95 

1.95 

4.87 

3.84 

2.28 

2.96 

should be near th€ Rangitaiki River, with the catchments 

either side of the river displaying a noticeably different 

flood frequency trend. Support for this difference in trend 

can be found in the geology of the area. The area west of 

the river is a pumice and rhyolite zone, whereas the area to 

the east comprises sedimentary rocks, e.g., sandstones and 

greywackes. The dividing line between the two geological 

areas is abrupt and coincides almost exactly with the line of 

the Rangitaiki River: The problem then was not so much 

where to locate the boundary line, but in which region to 

put the flow stations for the Rangitaiki River itself, since 

the flow in the riverr represents the integral effect of the two 

geological areas on the runoff process. However, the trends 

in the probability plots for three stations on the river (i.e., 

sites 15408, 15410 and 15432) were consistent with the flood 

frequency trend of one of the regions either side of the 

river, and the bourrdary line was drawn such that each station 

was included in the most appropriate region. 

The same approach could not be applied to a fourth flow 

station on the river at Te Teko (site 15412), which is downstream 

of the othe¡ three stations. The trend of the Q/Q 

probability plot for this station lay in between the trends exhibited 

in the Bay of Plenty and North Island East Coast regional 

plots. This was presumably because the peak flow at 

the station contains very significant contributions from 

37

BÊY OF PLENTY DRTF 

o 

o 

o 

NEOUCEO Y VRBIßTE 

s r0 ¿0 30 50 7s r00 

FETUFN PEHIOO (YEßRS) 

BÊY ÚF PLENTY BEGIONÊL CUBVE 

o 

o 

lo 

o 

Þ 

Þ 

è 

t.so 2.25 3.00 3.75 

NEOUCEO Y VRNIßTE 

r.ô¡r 2.3! s ro ¿o !o 50 75 ¡oo 2oo 

nETUBq FEnI00 tYERnS) 

Flgure 3.19 Region 2: regional plot and curve. 


38

Tablo 3.4 Summary of the regional curve characteristics. 

Region Regional Curve Ordinates Regnl. Parameter Values 

for Eq. 3.14 or 3.23 

O, sglO O¡/O O,o/õ Oro/O O.o/õ O,oo/O OrooiO 

Regional Cuwe 

Equation,OO = 

NORTH ISI.AND 

1. Combined N.l. West Coast 1.OO 

2. Bay of Plenty 0.96 

3. N.l. East Coast 1.OO 

4. Central Hawke's Bay 1.OO 

SOUTH ISI.AND 

5. S.l. West Coast O.99 

6. S.l. East Coast 1.OO 

7. South Canterbury 1.OO 

8. Otago-Southland O'98 

1.30 1.55 

1.31 1.62 

1.43 1.78 

1.49 1.89 

1.22 1.41 

1.31 1.56 

1.52 1.95 

1.33 1.62 

1.78 2.09 

1.96 2.46 

2.12 2.56 

2.27 2.77 

1.59 1.82 

1.80 2.12 

2.39 2.94 

1.89 2.25 

2.32 2.55 

2.87 3.33 

2.89 3.21 

3.14 3.51 

1.99 2.16 

2.35 2.58 

3.44 3.91 

2.51 

0.804 0.330 

0.762 0.325 

0.726 0.469 

0.696 0.s32 

0.846 0.249 

0.809 0.335 

o.689 0.529 

o.762 0.380 

O.8O4 +O.33Oy 

-O.142 1.53O+2.292exp 

lO'142Y1 

O.726 +0.469y 

0.696 +O.532y 

O.846 +0.249y 

0.8O9 +o.335y 

-O.O52 -9.545+10.234 

exp (O.O52y) 

0.762 +O.38Oy 

both regions, and to have included it in either regional plot 

\r/ould bias the resulting regional curve; down\ryards in the 

case of the Bay of Plenty curve and upwards for the North 

Island East Coast curve. The Te Teko station was therefore 

omitted from the derivation of the regional curve for both 

regions. 

Clearly, in deciding which regional curve to use for 

points on the Rangitaiki River system, consideration needs 

to be given to such factors as which region contains the 

greater proportion of the catchment area, and whether the 

western or eastern part of the catchment contributes most 

to the peak flows at the point in question (see also section 

5.2\. 

The number of stations near the eastern boundary of the 

Bay of Plenty region permitted such a detailed examination 

ofihe boundary line. In general, however, there were insufficient 

stations to be able to do this' Most lines were subjectively 

defined and they should be regarded as broad dividing 

iines between regions. To define the regional boundarils 

more precisely will require more flow stations with 

more flood peak data. 

3.3.4 Final rog¡onal curves 

The final regional flood frequency curves that were derived 

are summarised in Figure 3'20. In general' the curves 

The excePtion is the 

minimal amount of 

gional curve Past 100 

years, and the curve is tentative only. 

The ordinates Q'¡/Q for the final regional curves are 

listed in Table 3.4 for selected return periods. As well, the 

the eastern South Island area identical to the annual flood 

regions defined f,or estimating Q (section 4.5). Regional 

plots correspondirng to the flood regions in the area were 

constructed, but the data showed substantially greater variability 

than was evident in the plots for the original flood 

frequency regions, i.e., Regions 6, 7 and 8 in Figures 3'14- 

3.16. Still pursuing the possibility of having consistent regions, 

all of the flood peak data for the three flood frequency 

regions were subsequently pooled together, forming 

a combined region known as the Eastern South Island region. 

The regional plot that was obtained for this area, and 

the resulting regional curve, are shown in Figure 3'21. A 

comparison of this plot with those for the original three 

flood frequency regions (Figures 3.14-3.16) shows that the 

variability in the data for the combined region is much 

greater. This is borne out by the standard error equation 

developed for the regional curve of the combined area 

which gave a C¡ I'alue at the 100-year return period, for example, 

that was 25 percent greater than that given by the 

group equation (llable 3.9) for the original regions (see section 

3.4.1). This greater variability was not surprising in 

view of the range in the ordinates of the regional curves for 

the three regions. For instance, at the lü)-year return period 

the difference between the South Canterbury and South 

Island East Coast regional curve ordinates is l.l8' or 50 

percent of the ordinate for the latter curve. Because of this 

iange, and the greater variability in the regional plot for the 

combined area, tlhe curves for the three original regions offer 

a more accurate estimate of Q/Q for sites in the area 

and the three regions were therefore retained as the flood 

frequency regions. 

3.3.5 Consistent regions 

For th 

the resul 

made of 

3.3.6 Sub-reglons 

It will be noted that two small areas in Figures 3.6 and 3.7 

have been specially identifl¡ed as sub-regions. The first is 

that area around Mt Egmont in the combined North Island 

West Coast region (see Figure 3'6). Flood peak data were 

available for onìly two stations in the area, although each 

was associated u¡ith a representative basin. The catchment 

for the station on the east of the mountain (site 39504, 

Manganui River at Tariki Road) was included in the North 

Island West Coast region after its flood peak data were 

found to conform very well with the regional flood frequency 

tr€nd. The second station (site 36001, Punehu River 

at Pihama) was located on the southern side of the mountain. 

Its flood peak data displayed distinct upwards curvature 

on a probability plot, a trend markedly different from 

the regional one,, Because it was uncertain whether this was 

ase ofaPPlication of a real trend, or simply the result of using a short record 

an examination was (eight years), the southern area of Mt Egmont was excluded 

frequencY regions in from the North ltsland West Coast region' More flood peak 


39

NOBTH ISLRND ßEGIONÊL CUBVES 

1.50 2.?S 3. OO 

REDUCED Y VRBIßTE 

2,33 sl02030 

BETUBN FERIOO (YE8BS) 

50 75 r00 

Flgure 3.2Oa Summary of North lsland regional cury€s. 

SOUTH iSLÊND REGIONÊL CURVES 

1.50 2-25 3.( 

BEOUCED Y VRBIFTE 

s r'o ¿'o g'o 

RETUNN PEBIOO IYERNS) 

1t.50 5.2S 

so 7s t00 200 

4 

Fþure 3.2Ob Summary of South lsland regional curves. 


EßSTEBN SÚUTH ISLÊND OÊTÊ 

00 3.75 q.50 

FEOUCEO I VFFIFTE 

l.Oll ?,33 s t0 20 30 50 75 rO0 

NETUFN FEFI OO f YERFS'I 

EßSTEBN SOUTH ISLßND REGIONÊL CUBVE 

o 

1.50 2.25 3.00 

BEOUCEO Y VRBIBTE 

5r02030 

NETUHN PEHIOO (IERBS) 

q.50 5. ?5 

s0 ?s r00 200 

Figure 3,21 Eastern South lsland regional plot and curve. 


4l

data for this area are required before a decision can be 

made whether to make the area a region in itself or to include 

it in the surrounding region. 

The second sub-region identified is the area south-west of 

Nelson in the South Island West Coast region (see Figures 

3.7 and 3.22). lt was of interest in that the flood peall data 

for two flow stations (sites 57008 and 57101) in the area did 

not conform at all to the regional flood frequency trend; 

these stations were omitted from the derivation of the regional 

curve. The non-conformity of the data was thought 

to be due to the fact that the area is in a rain-shadow, caused 

mainly by the Southern Alps to the west, and receives 

significantly less rainfall than the other parts of the region. 

These factors encouraged a detailed look at the flood frequency 

behaviour in the whole area, 

The flood peak data that were collected for the area according 

to the criteria in sections 3.2.1 and 3.2.2,together 

with extra data that did not meet these criteria but were 

nevertheless thought to be of some use here, were pooled 

together to form a probability plot for the area. All the data 

used in the plot are summarised in Table 3.5, while the extra 

data are listed in full in Appendix C. 

The probability plot that was obtained for the Nelson 

area, and the curve that was fitted to the plotted data, are 

shown in Figure 3.23. Despite the inadequacies with the 

data and the small number of flow stations used it would 

seem, both from the trend in the probability plot and from 

the large difference between the fitted curve and the South 

Island West Coast regional curve (shown as the dashed line 

in Figure 3.23), that there is some justification for treating 

the area south-west of Nelson as a separate sub-region, and 

not part of the surrounding region. A greater amount of re- 

Iiable data is needed to confirm this point and to define the 

area's own regional curve with confidence. In the meantime, 

however, it is suggested that the regional curve for the 

South Island East Coast region should be used for the area 

rather than the one for the South Island West Coast region. 

The former region is drier and has a steeper frequency 

curve and hence is more in keeping with the Nelson area. 

3.3.7 General¡sed flood frequency curves 

From all the flood peak data assembled for this study, 

two generalised flood frequency curves extending to high 

return periods were developed. In recognition of the differences 

in the characteristics of the regional curves for the 

west and east of New Zealand, one generalised curve was 

developed for the western areas (Regions I and 5) and one 

for the eastern areas (Regions 2,3, 4,6, 7 and 8). The development 

was based on the principle utilised by Stevens 

and Lynn (1978) of pooling regional data together to obtain 

more stable flood estimates for high return periods. With 

the large base of pooled data for each generalised curve, it 

was hoped that the curves could be extended to the 1000- 

year return period with sufficient accuracy to be useful in 

design. 

These curves incorporated many of the historical flood 

peaks that were excluded from the regional analyses under 

Rule (lli) of section 3.2.2. ln general, this rule was invoked 

in a regional analysis because a flood peak was an extreme 

outlier and the available length of flood record at the station 

concerned was insufficient for the computation of a 

plausible return period for that flood peak. However, there 

were good reasons for including here some of the previously 

excluded historical peaks: the large base of data for 

each curve, together with the use of the extension method, 

would help to prevent these peaks from exerting undue bias 

on the shape of the curves; and as the curves were to be extended 

to the 1000-year return period, the flood peaks with 

return periods approaching this limit should be used, where 

possible. 

All but four of the previously excluded extreme peaks 

were considered suitable for the development of the generalised 

curves, The remaining four peaks were truly extreme 

events, and even tbe large bases of data associated with the 

generalised curves were insufficient to enable realistic return 

periods to be ascribed to them. Two of the peaks occurred 

in the same storm in 1938 in the adjacent Mohaka 

Table 3.6 Calculations for extending the sets of average values 

for the generalised curves. 

(a) The Maximum O/O and y values. 

Western New Zealand 

Group 1 Group 2 Group 3 Group 4 

o/o 

4.58 7.13 

2.94 6.11 

2.91 5.61 

2.74 5.28 

o/o 

4.84 7.O7 

2.62 6.O5 

2.59 5.55 

2.45 5.22 

yo/OyO/Oy 

M= 7OO 661 659 

No. of Stat¡ons 

: 23 15 

Eastern New Zealand 

2.99 7.O7 3.90 7.13 

2.58 6.05 3.25 6.1 1 

2.46 5.55 2.81 5.61 

2.40 5.22 2.49 5.28 

700 

Group 1 Group 2 Group 3 Group 4 

o/o o/o o/o o/o 

3.12 6.68 

2.87 5.65 

2.74 5.15 

2.54 4.42 

4.31 6.68 

4.06 5.66 

3.65 5.1 6 

3.55 4.83 

4.62 6.69 3.85 6.83 

3.82 5.66 3.75 5.80 

2.99 5.17 3.53 5.31 

2.A7 4.83 3.06 4.98 

M= 444 448 450 517 

No. of Stations 

= 14 

19 

(bl Classification and averages of the maximum O/O and y values. 

t5 

t3 

Table 3.5 Summary of flow stations in the Nelson a¡ea. 

Site No. Flow Station Catchment No. Annual 

Area (km'zl (and historical) 

flood peaks 

56901 Riwaka River at Moss Bush 

57002 Motueka River at Baton Br. 

57006 Wangapeka River at Swing Br. 

57OOB Motueka River at Gorge 

57009 Motueka River at Woodstock 

571O1 Moutere River at Old House Rd. 

571OG Stanleybrook River at Barkers 

48 

'1647 

373 

163 

1750 

60.7 

81 

10 

18 

I 

9 

8 

10 

7 

y lnterval 

Wefem NZ: 

7.O - 7.5 

6.5 - 7.0 

6.0 - 6.5 

5.5 - 6.0 

5.0 - 5.5 

Eaetem NZ: 

6,5 - 7.O 

6,0 - 6.5 

5.5 - 6.0 

5.0 - 5.5 

4.5 - 5.O 

No. of values Average O/O Average y 

4 

4 

4 

4 

4 

4 

4 

4 

4.O8 

2.85 

2.69 

2.52 

3.98 

3.63 

3.23 

3.O2 

7.10 

6.08 

5.58 

5.25 

6.72 

569 

520 

487 

42 


7009 

o 

ELSON 

57tO6 

LOCALITY PLAN 

Scole O 5 lO 15 20 25 km 

Figwe 3.22 Some flow stations in the Nelson area. 

generalised curves' 

The development of each geleralised curve involved the 

calculation of the average Q/Q and y values, for the 0'5 

class intervals of y, from all the pooled data for the area 

concerned. Additional average values were then obtained 

using the same extension method as employed for the tsay 

of Plenty regiorr (section 3.3.3). This time, however, four 

groups of staticlns were considered fo-r each curve, with 

each group again comprising all the Q/Q values for the stations 

whose catchments were not close neighbours. A summary 

of the foul largest Q/Q values for each group is given 

in Table 3.6a. It will be noted from this table that the number 

of stations rvithin each group and also M, the number 

of station years spanned by the data in a group, were kept 

reasonably constant. The four Q/Q values per group ìvere 

treated as being the four largest in a sample of record length 

M, and their corresponding y values were calculated accordingly 

using the Gringorten formula (Equation 3'20) 

and Equation 11.16. The resulting sixteen pairs of Q/Q 

values for each curve and the corresponding y values, i.e., 

the four pairs fiom each of the four groups, were subsequently 

averaged over the 0.5 class intervals of y (Table 

3.6b). These new averages were later plotted on the same 

probability plot as the original averages. Finally, Equation 


43

NELSON REGIONFL CURVE 

BEOUCEO Y VRRIÊTE 

FETUNN PEBIOO (YEHRS) 

Figure 3.23 Mass probability plot and fitted curve for the Nelson a¡ea. 

3.14 was fiued ro rhe combined set of original and new 3.4 FlOod ffequency acculacy 

averages using the optimisation technique. 

Figures 3.24 and,3.25 show, for the combined western 3.4.1 Accuracy of flood frequency tat¡o Or/õ 

and eastern areas, respec 

was fitted to the two types 

the extension method arç 

tern generalised curve id 

marised in Table 3.7. 

T¡ble 3.7 Summary of the characteristics of the generalised 

curves. 

al curve, it is 

of statistical 

sets of flood 

peak data used to define the curye _ if different sets 

of records of equal length had been available the curve 

would be different; and 

(b) tne spatial variation due to the curve being taken as an 

of the flood frequencv relation- 

ï"t#iltriiLt iJerage 

Since in this study a regional curve is interpreted as the 

o./o_ 

o,o/_o 

Oro/O 

O.o/õo,@/_o 

O'æ/Q 

O¡æ/O- 

Oroo/O 

u= 

o= k: 

General 

Eq;ation: 

4 

Western N.Z. 

1.18 

1.42 

1.67 

2.O4 

2.36 

2.71 

3.23 

3.68 

0.788 

o.234 

-o.1s6 

O/O = -0.714+ 

1.502 exp (0.1 56yl 

o/o 

Eastern N.Z. 

1.49 

1.87 

2.23 

2.71 

3.06 

3.42 

3.88 

4.24 

o.724 

0.509 

=O.724+ 

O.6O9y 

var (a.b) = E(a),.var(b) + E(b),.var(a) 324 

where E ( ) denotes the expected value and var ( ) the variance. 

Errors of estimation in Q can be considered statistically 

independent of errors of estimate in the regional curve ordinate 

Q.¡/Q. Hence, applying the expansìon in Equation 


1ÎESTEBN NEhI ZEÊLRND DRTR 

Þ 

o 

Þ 

o 

t 

Þ 

ro 

ooo 

o 

ê ê 

l.0r t 

ê 

2.33 

hESTEBN 

1.50 2.25 3- 00 

BEOUCED Y VRRIRTE 

s 

t0 

ßEIURN PEN¡OD (YERNS) 

NEI,,I ZERLÊND GENERRL I SED CURVE 

o 

t 

o 

to 

ot 

E 

t 

I - 50 2.25 3.00 3.75 {,50 5.25 6,00 l. ?¡ 

BEDUCED Y VRSIRTE 

r.ort 2.t3 s l0 20 30 so 7s ir00 eoo 600 t000 

NETURN PEñIOD 

Water & soil technical publication (YEÊRS} 

no. 20 (1982) 

Flgute 3.24 Western New Zealand: the mass probability plot and the generalised curve. 

45

46 

EÊSTEFìN NEI,,I ZEFLÊND DÊTIì 

o 

Þ 

o 

o 

di' 

o 

tct 

a oê 

.ü' 

€ 

o 

o 

è 

t.0tr 

t .50 2.25 3.00 3. ?5 r¡.50 

BEDUCEO Y VRßIRTE 

2,33 S r0 ?0 30 S0 7s r00 200 

BETUNN PERIOO fYEÊNS) 

EÊSTERN NEIÎ ZEÊLRND GENEI-IRL I SED CUßVE 

o 

,to -.rr . s0 2.2s 3.00 !,75 lr. s0 25 6.00 a.?S 

NEOUCEO Y VFRIRTE 

l.otr 2.!t s t0 20 !0 60 75 t00 200 s00 ¡000 

BETUNN FENIOO ÍYEFñ5I 


Figure 3.25 Eastern New Zealand: the mass probability plot and the generalised curve.

3.?A, the variance of the flood peak estimate Q.¡ may be 

given as (NERC 1975, p.184) 

var(Qr) : var_(Q.Qr/Q) _ 

= E(Q)'.var(Qr/_Q) 

+ E(Qr/Q)'?.var(Q) 

325 

The quantity var(Q ) on the right han_d side of Equation 

3.25 depends on the manner in which Q is estimated (see 

Chapter 4). In practice Q is substituted for E(Q ) and, similarly, 

QrlQ for E(Q1/Q). This leaves only the quantity 

var (Qr/Q) unaccounted for. It is the variance of the regional 

curve ordinate Q.¡/Q at return period T and is the 

type (b) variation mentioned previously. 

The quantity var (Q1/Q ) was calculated as the variance 

of the individual station flood frequency curves for 

T=2.33,5, 10,20,30, 50 and 100 years. Given this variance, 

the coefficient of variation (Cp) of individual station 

curves about the regional curve is defined as 

c¡ = (var (Qr/Q) )k/(Qr/Q) 326 

and is a measure of the type (b) variation above' 

Regression analyses of C¡ against the return period T, 

and also fnT, were carried out and it was found that the relationships 

between C¡ and /nT were approximately linear. 

Regression equations of the form 

Cp=(c+m./nT)/100 321 

were therefore obtained, where c and m are constants for a 

reglon. 

The regression equations for the various regions are summarised 

in Table 3.8. The square of the correlation coefficient 

R was in the range of 0.946 to 0.992 in all cases but one, 

indicating that generally the equations explained at least 

9490 of the variation in C¡. The exception was the equation 

for the Bay of Plenty region where the R'z value was only 

0.380. This low R' value was presumably the result of the 

regional curve having a different trend from some of the 

frequency curves for the individual stations where there was 

historical flood information. Further, the Bay of Plenty region 

was the only one where the equation for CF was not 

statistically significant at the l9o level. 

While the statistical properties listed in Table 3'8 indicate 

that the equations would generally be satisfactory for estimating 

C¡ for a regional curve, some of the regions did not 

contain sufficient stations to enable truly representative 

equations to be determined. For instance, in three ofthe regiòns 

less than l0 stations were used. Since the equations 

were only a measure of the type (b) variation and were intended 

to convey only an order of magnitude ofthe standard 

error associated with an estimate of Q'¡/Q obtained 

from a regional curve, it was decided to pool together the 

individual station estimates of Q1/Q for different regions 

into larger groups and to derive a new C¡ equation for each 

group. These grou¡r equations could then be taken as the 

estimating equatiorrs for C¡ for the regions they represented. 

However, prior to the pooling of estimates, it was 

necessary to dividr: the individual station estimates of 

Qr/Q bv the corresponding regional curve ordinates. 

Group C¡ values were then calculated for the pooled estimates 

for the return period concerned. 

Two groups of regions were considered for each of the 

North and South Islands, with one group representing the 

western and the other the eastern regions. Grouping the regions 

in this mannen is supported by the overall trend in the 

value for the slope m of the regional regression equations 

(Table 3.8), with the value generally being greater on the 

east of an island than on the west. This trend indicates that 

the variance of the estimates of the regional ordinates 

Q-¡/Q is greater on the east than on the west, and it also reflects 

the greater variability in the flood peak data for the 

eastern regions (see also section 4.9). Further justification 

for this grouping of regions is given by the trend in the 

characteristics of ttre regional curves (section 3.3.2). 

The way in which the individual station estimates for the 

regions were pooled together into groups is shown in Table 

3.9. The estimates for the Bay of Plenty region were not 

used in the derivation of the group equations. The C¡ equation 

for this region was not meaningful in view of the low 

R2 value and it thurs seemed inappropriate to use the data 

for this region in deriving a useful equation for its group for 

estimating C¡. The combined North Island West Coast and 

South Island West Coast regions are the only regions in 

their respective groups, and thus their regional C¡ eQuations 

(Table 3.8) automatically became the corresponding 

group equations. 

Table 3.9 gives thre regression equations that were derived 

for the groups andt it also lists the regions to which each 

equation applies. The tabulated statistical properties indicate 

that the equa,tions are statistically acceptable, with 

each being significant at the l9o level. Table 3.9 gives the 

100-year C¡ value as computed from each group equation. 

The 1OO-year values range from 0.13 to 0.19 for the western 

groups and from O.24to 0.25 for the eastern groups. They 

compare very favourably with the value of 0.32 as given by 

the corresponding Cp equation recommended by NERC 

(1975, p.183) for use with all its regional curves. 

Each group equation was derived from station estimates 

for return periods only up to 100 years, even though most 

regional curves extend to the 2(Ð-year return period. Normally 

it is recommended that an equation should not be applied 

outside the range of data from which it was derived. 

However, in this case it was preferred to allow each equation 

to be applied up to the 2D-year return period, rather 

Table 3.8 The regional regression equations for estimated CF' 

REGION 

Coefficient 

c 

S ope 

m 

R2 

s.E. 

Est. 

No. ol 

Stat¡ons 

NORTH ISTAND 

1. Combined N.l. West Coast 

2. Bay of Plenty 

3. North lsland East Coast 

4. Central Hawke's Bay 

o.94 

6.19 

-2.21 

o.25 

3.93 

o.91 

6.O1 

5.38 

0.997 

0.617 

o.972 

o.989 

o.993 

0.380 

o.946 

o.979 

27.O* O.OO145 

1.75 0.Oo518 

9.32* 0.00645 

14.9* 0.00361 

65 

12 

12 

8 

SOUTH ISI-AND 

5. South lsland West Coast 

6. South lsland East Coast 

7. South Canterbury 

8. Otago-Southland 

2.46 

-o.37 

4.53 

-o.40 

2.25 

4.59 

5.90 

4.19 

0.996 

o.996 

0.981 

o.982 

o.992 

0.992 

0.963 

o.965 

25.2* o.oo244 

24.6* O.OO508 

1 1 .4* 0.10410 

11.7* O.OO974 

21 

14 

9 

t) 

NOTE: 

The regression is of the form C¡ = (c + m.fnT)/lOO 

* ¡ndicates significance at the 196 level 

S.E. Est. is the standard error of est¡mate of C¡ 


47

Table 3.9 The grouping and the group equations for est¡mation CF. 

GROUP 

West N.l. 

East N.l. 

West S.l. 

East S.l. 

NOTES: 

Regions whose 

Data were 

Regions Represented 

Pooled Together by the Group 

1 

3,4 2. Bay of Plenty 

3. North ls. East Coast 

4. Central Hawke,s Bay 

5 5. South ls. West Coast 

6, 7, I 6. South ls. Easr Coast 

7. South Canterbury 

L Otago-Southland 

Group 

C¡ Equation, 

C.= 

1. Combined N.l. West Coast (O.94+3.93/nT)/1OO 

(- 1.25 +5.74fnTl 

/100 

12.46 +2.25tnTll1OO 

(2.61 +4.54/nT)/1OO 

+ indicates significance at the 1 7o level 

S.E. Est. is the standard error of estimate of C¡ 

No. of stations is the total number used in the derivation of the group equation. 

S.E. 

R2 t Est. 

o.993 27.O* O.OO15 

0.984 17.7' O.O0g2 

0.992 25.2+ O.OO24 

o.985 18.1* 0.0068 

No. of C¡ value 

Stations forT=1OO 

65 

20 

2'l 

29 

o.1 I 

o.25 

o.1 3 

o.24 

than to obtain individual estimates of er/Q beyond a re_ 

turn period of 100 years, which would have involved a gross 

extrapolation with several of the records. 

C¡ equations for estimating standard errors associated 

with the application of the generalised curves were also de_ 

rived, and in exactly the same manner and with the same 

data as that used for the regional C¡ equations. Details of 

the resulting CF equations are given in iable 3.10. 

From a comparison of the coefficients of f nT in the 

le 3. 

can be seen that 

for 

rve produces CF 

thin 

given by the twô 

that 

area. This result 

was not surprising, since a generalised curve for an area 

represent 

that area, 

and so it 

erages the 

scatter in 

plo-ts. Be_ 

cause of 

d that the 

Nevertheless, some of the curves and the associated regional 

boundaries cannot be regarded as definitive because 

of small data samples, a lack of samples, and a poor areal 

distribution of the flow stations' catchmenti (section 

3.4.3). In fact, the study exposed a number of areas where 

efforts to acquire flood peak data should be concentrated 

in the future. 

In the South Island there were very few flow stations on 

the coastal plains of the east coast. Here there are practical 

difficulties in estabtishing flow stations because the alluvial 

3.4.3 Definition of flood frequency 

reg¡onal boundaries 

As mentioned in section 3.3. I , use was made of available 

3.4.2 Data limitations 

most 

ever 

data 

rves. 

Island regions. A difference in the flood frequency trend 

between the North Island stations in the west änd those in 

the east was also evident. 

Table 3.1O The C¡ equations derived for the generalised curves. 

Area 

Western NZ 

Eastern NZ 

cF 

cF 

Equation 

S.E. 

R R2 t est. 

= (2.06+3.59fnT)/1OO 0.991 O.9Bt 16.3* 0.0060 

= (1.79 +4.84hrV1OO 0.996 0.992 26.8* O.OO49 


No. of 

stations 

86 

61 

48

The regions that were chosen initiatly reflect the difference 

in rainfall behaviour in New Zealand, and each region 

can generally be distinguished by its own rainfall characteristics. 

Where there are pronounced regional rainfall characteristics, 

and where there are sound topographical reasons 

for this, the boundary line between regions was easily decided 

upon. For instance, in the South Island West Coast 

region, where the rainfall is greatest and is dominated by 

the orographic influence of the Southern Alps, the ridge 

line of the Alps was the obvious dividing line between this 

region and the other South Island regions. However, it is 

probable that the effect of the West Coast rainfall extends 

somewhat east of the ridge line, as indicated by the probability 

plots for the Shotover and upper Wairau catchments. 

The actual boundary line for the South Island West 

Coast therefore includes these catchments and some eastern 

headwater catchments in the Alps, e.g., the catchments of 

the Wilkin, Makarora and Matukituki Rivers. 

While the rainfall characteristics of different parts of 

New Zealand helped to identify the regions, the actual definition 

of the regional boundaries was not always as 

straightforward as in the South Island West Coast example 

the topographical features were not always as dominant 

- 

as the Southern Alps in influencing the rainfall. ln addition, 

there was sometimes a poor areal distribution of flow 

stations, so that often the definition of the regional boundaries 

was rather subjective. 

A striking outcome of the regionalisation work was the 

small number of flood frequency regions. In earlier work 

Toebes and Palmer (19ó9) divided the country into 90 

hydrological regions according to climatological, geological 

and topographical factors. However, in this study eight regions 

were considered adequate to define the variation in 

flood frequency behavioui in the country. This is an order 

of magnitude less than the number used by Toebes and 

Palmer, and suggests that climate is the dominant factor influencing 

floods in New Zealand and that geology and topography 

generally play relatively minor roles. 

3.4.4 Homogene¡ty test 

Some flood regionalisation studies have used the statistical 

test described by Dalrymple (1960) to identify the stations 

that form a hydrological homogeneous region. This 

homogeneity test involves the graphical or analytical fitting 

of a frequency distribution to each station's flood peak 

data and the estimation of peak discharge values for the 

2.33 and lO-year return periods, i.e., Qt ,, and Q,o respectively. 

The ratio of Q,o/Q, ,¡ is then formed, which is an index 

of the straightJine slope of the fitted frequency curve between 

the two return periods. The test places confidence 

limits on the ratio Q'o/Q, ¡¡ and stations with ratios lying 

within the limits are taken as being part of the homogeneous 

region. 

Although the test Provides a quant 

ing a region, it was not relied uPon a 

insensitive when tested on South Is 

served that the test was unable to detect even major differences 

in individual frequency curves past the lO-year return 

period. This deficiency ofthe test was also noted by Benson 

(r962a\. 

3.5 Flood frequencY discussion 

3.5. I Regional d¡fferences 

The most prominent characteristic of the regional curves 

is that the curves for the western regions of an island have a 


regions receive more rainfall more regularly than their eastern 

counterparts. Thus, the ratio of runoff to rainfall is 

comparatively high for the western catchments and does 

not vary markedly for the storms that produce the annual 

floods. The mean annual flood is therefore fairly large and 

there is little variability in the annual flood peak data (section 

4.9). As a consequence, the difference between the 

100-year and mean annual flood is not very great, e.g., in 

the curves for the two western regions the 100-year flood 

peak is less than 2.35 times the mean annual flood. 

On the other hanLd, the catchments in the eastern regions 

are usually drier and have a lower runoff to rainfall ratio. 

The mean annual Ilood for an eastern catchment is therefore 

less than that for a western one of the same size (section 

4.5). There is eLlso a greater range in the runoff to rainfall 

ratio fo¡ an eastern catchment and this is reflected in 

the greater variability of the annual flood peak data for 

such a catchment (section 4.9). The difference between the 

100-year and the rnean annual flood is therefore significantly 

greater than that for a western catchment, as is borne 

out by eastern regional curves being steeper than the western 

curves. It is worth noting that the wettest region (the 

South Island West Coast region) has the flattest regional 

curve and one of the driest regions (the South Canterbury 

region) has the steepest curve. 

While the slope of a regional curve is an indication of the 

variability in the individual data samples for the region, the 

curvature may be taken as an index of the skewness in the 

samples. As indicated by NERC (1975, p.42,47), the EVI 

distribution has a coefficient of skew of 1.14, and skew 

values greater or ler;s than this figure correspond to the EV2 

and EV3 distributions respectively. The majority of the regional 

curves in this study are described by the straight-line 

EVI distribution, implying that the average skewness in the 

data samples for these regions was small. This in fact was 

the case: for the regions with straight-line fits to the data 

the average skew of a region's annual flood peak samples 

was in the range 0.39 (S.I. West Coast) to 1.09 (Central 

Hawke's Bay) and the EVI distribution was found to give a 

good approximation to the regional data up to the 200-year 

return period. In the Bay of Plenty, South Canterbury and 

Otago-Southland regions the average skew of a region's 

data samples was greater than 1.2. For the first two of these 

regions, the EV2 dtistribution was found to give a good fit 

to the regional dat¡1. Because of the smaller number of data 

samples for the third region, however, less significance can 

be attached to the average skew (1.23) of the region's data 

samples, and the IlVl distribution approximated the data 

satisfactorily up to the 100-year return period. 

It is interesting to note that the two regions with EV2 regional 

curves can both be regarded as dry areas; the South 

Canterbury region because of its low rainfall, and the Bay 

of Plenty region because of its absorbent pumice soils (see 

also section 4.6.2) and its relatively low rainfall in comparison 

with its regional neighbour to the west. 

The pooling of the regional flood peak data to construct 

the generalised curves produced mass probability plots 

(Figures 3.24 and 3.25) that show very little scatter in the 

data up to about the l0-year return period. Beyond this the 

scatter is greater, but not excessively so, and is due in part 

to some of the uncertainty associated with the historical 

flood peaks. The averaging of the pooled data and the 

application of the extension method (NERC 1975) clearly 

defined the flood frequency trend for the fitting of each 

generalised curve. rühile the curves require some refinement 

using more and especially longer flood records, they 

should still provide the designer with a reasonable guide as 

to the magnitude of flood peaks past the 2(Ð-year return 

period, the maximLum upper bound of the regional curves. 

An assessment of the reliability of each curve can be made 

from an inspectiorr of the scatter in the corresponding mass 

probability plot eLnd by applying the appropriate North 

Island group CF equation (section 3.4.1). 

49

allowing curves rather than just straight lines to be fitted to 

the regional data with confidence. In this New Zealand 

curve and the eastern curve is the straight-line EVl. This is 

d generalised curves 

ynn (1978) for Creat 

given in Figure 3.26. 

curve and the corresponding regional ones, results from in_ 

clusion in the development of the generalised curve of some 

of the extreme flood peaks which had been excluded from 

the derivation of the corresponding regional curves. While 

there is a valid argument for the inclusion of these extreme 

e still been too 

thereby weightperiods. 

been described 

New Zeatand curves bear a remarkabl|t','"tJJr:i*t;tÏ:: 

to their Great Britain counterparts. 

Although the two countries have broadly similar cli_ 

mates, New Zealand has greater extremes of wet and dry. 

That the New Zealand curves do not reflect this with túe 

western and eastern curves be 

- 

tively, in relation to the corre 

- is possibly due to the ave 

ment of the curves, i.e., the i 

treme wet or dry climates is largely nullified by the lumping 

together of these areas with others which are noticeãblt 

drier or wetter, respectively. The fact that the western New 

was used to describe the generalised curve. 

ntinuity between 

Oing generalised 

" 

. ;;,f.tïi'l"i::; 

expectation. This may be viewed as taking a weighted aver_ 

age of the estimates. 

3.5.3 Vadation within a reg¡on 

3.5.2 Compar¡son with rhe Br¡t¡sh lsles 

; 

f 

these curves reveals some remarkable similarities with the 

curves obtained in this New Zealand study. 

First of all, the British Isles regional curves display the 

same trend of an increase in the slope of the curves between 

those for the western regions and those for the eastern re_ 

gions the curve for the western-most 

- region, the whole of 

Ireland, has the smallest slope, whereas the curve for the 

eastern-most region, East Anglia, has the greatest, 

Further, the range of the ordinates of the British Isles 

and New Zealand curves is almost the same at high return 

periods. For example, the South Island West Coast regional 

curve, which has the smallest slope of all the New Zéaland 

very dry in relation to 

is likely to be steeper 

catchment which is ve 

tend to have a flatter 

An extension of this argument leads to the concept of 

sub-regions which, although geographically part of a làrger 

surrounding region, display a e/Q frequency trend of thiir 

is 

E 

b 

50 

3.5.4 Secular climatic variat¡on 

-In th9 regionalisation procedure described by Dalrymple 

(19@), it is recommended that all the flood records should 

be brought to a common base length by correlating the re- 


o 

SOUTH AFRICA 

to 

o 

,s.E. BRtTAtN 

.,,' 

EASTERN N.Z. 

WESTERN N.Z. 

-N.W. BRITAIN 

23 

Reduced Voriote 

567 

2.33 5to2050 

-ffi 

roo 200 500 rooo 

Return Period ! yeors 

Figure 3.26 Comparison of the New Zealand generalised curves with those f rom the British lsles and South Af rica. 

- 

cords with the longest reliable one. The aim of this correlation 

is to remove the effect of any climatic variation that 

might exist amongst the records of differing length. However, 

the correlations are often so poor that there appears 

to be very little advantage in attempting this form of extension. 

Further it is uncertain at the present time whether 

there are significant climatic trends in annual flood peak 

records (ICE 1975, pp.76-80). For example, Cunnane 

(NERC 1975, pp.l25-32) performed a number of statistical 

tests on 28 long records of annual flood peaks. The tests 

suggested that the peaks were largely random, and therefore 

contained no noticeable climatic trend. A similar con- 

clusion was reaclned by Beard (1977) in an analysis of annual 

flood peaks in 300 long records for stations in the 

United States. 

In this New Ze:aland study it was assumed that there was 

no climatic trend in the annual flood peak records. This 

same assumptiorn was made by NERC (1975), and in 

Beard's (1977) flood frequency analysis work for the U.S. 

Water Resources Council. The possibility of there being climatic 

variations in the flood records is not ruled out, but 

this is an area ol'hydrology that requires further research 

before proper account can be taken of such variation in a 

regional study like this. 


5l

3.5.5 Extension method 

The NERC (1975) extension method proved very useful 

in developing the Bay of Plenty regional curve and the generalised 

curves. However, it was not considered necessary 

to use the method for the development of every regional 

curve. For instance, in a test on the South Island tr)Vest 

Coast regional data, the extension method produced a 

curve almost identical with that obtained by the usual 

curve-fitting procedure (section 3.3.2). There was also uncertainty 

in the method concerning the statistical dependence 

between the original and the new set of average values. 

In a sense it appeared that the same information on the 

large Q/Q values was being used twice. This would weight 

the curve-fitting process in favour of the historical flood 

peaks, the estimat€s of which are generally less reliable than 

those for the annual flood peaks. In addition, there is considerable 

difficulty in grouping the stations of a region such 

that neighbouring catchments are not represented in a 

group. While this condition can normally be satisfied, there 

are necessarily some catchments represented which are in 

close proximity to one another, which raises doubts about 

treating the flood peak data of a group as independent sample 

items. 

3.5.6 Catchment s¡ze 

Catchments less than 20 km'? were omitted from the 

study, except in the Northland-Auckland area, on the prior 

belief that they would have steeper flood frequency curves 

than the larger catchments (section 3.2.1). This was found 

to be true at times, especially for the very small catchments 

of the order of I km' in area. However, the initial curve for 

the Northern North Island region (Figure 3.8) refutes the 

general argument against the omission of small catchments. 

The curve was based on the flood peak däta for catchments 

ranging in area from 2.48 to 1606 km':(see Table 3.2), yet it 

is not steep nor does the corresponding regional probability 

plot show greater scatter than that for other western regions. 

The curve is a typical western one and flatter than 

any eastern regional curve. 

While it was quite evident that the flood peak data for 

some small catchments could not be tolerated in the derivation 

of a regional curve, it does appear from the Northern 

North Island example that small catchments could possibly 

have been considered in the derivation of some of the 

curves. 

3.6 Summary 

Eight flood frequency regions have been defined for New 

Zealand, and an average Q/Q vs T curve derived for each. 

It is suggested that these regional curves can be used to estimate 

Qr/Q for rural catchments within the region concerned 

for return periods up to 200 years. An exception is 

the Otago-Southland curve; it is only tentative and should 

not be extrapolated beyond the 100-year return period. For 

return periods exceeding the recommended upper limit of 

the regional curve, one of the two generalised curves developed 

for the east and the west of New Zealand can aid 

the estimation of Q1/Q. With all the curves it is important 

that they are not applied to catchments whose areas are too 

far outside the range of areas used in the derivation of the 

curve concerned. An indication of the reliability of a Q1/Q 

estimate taken from a curve is provided by standard error 

equations, which give values somewhat less than a similar 

equation determined by NERC (1975) for use with the British 

Isles curves. 

The most notable characteristic of the curves is that those 

for the east have steeper slopes than those for the west, reflecting 

the greater variability in the annual flood peak data 

for the eastern catchments. The same characteristic is evident 

in the British Isles regional curves. Also of note is that 

the two New Zealand generalised curves resemble their 

Great Britain counterparts (Stevens and Lynn 1978). 

52 


4 Estimation of mean annual flood 

4.1 lntroduction 

This chapter covers estimation of the mean annual flood 

1Q¡ tor sites with no flood record. A procedure is presented 

which estimates Q as a function of catchment and climatic 

characteristics. Where necessary, Q so estimated is designated 

Q "s 

distinguishing it from Q o5, calculated from 

observed flood records. 

The flood records used to derive the procedure were selected 

as outlined below. This selection was based on the 

length of record, the size and type of catchment, and the 

quality of record. Selection of the characteristics and their 

abstraction from maps and other published information are 

detailed. It was found that improved estimates of Q were 

obtained by forming regions. Delineation of these regions 

and obvious boundary problems are discussed. Catchments 

with records not fitting into regional patterns are identified 

and reasons for some anomalies are suggested. Best fitting 

equations are summarised with accompanyinig standard error 

estimates. 

4.2 Proposed method 

The relation between Q and measurable catchment characteristics 

was assumed to have the fo¡m of 

Q: a X' b'X, b' 4t 

where a, b,, b, ... are constants to be estimated and X', X, 

... are characteristics of the catchment having an influence 

on the mean annual flood. 

After taking logarithms, log a, b,, b, ... were estimated 

by standard multiple linear regression. There is good precedent 

in the literature for this type of multiplicative function 

(NERC 1975; Benson 1962b); thus other possible forms 

were not investigated. 

4.3 Records used 

Catchments used in the study were selected from those 

having an area within the range 0.22 to I 100 km'. The three 

smallest catchments have areas 0.22, 0.52 and 2.18 km'. 

Smaller catchments were excluded because flood discharges 

from very small (often ephemeral) catchments result from 

short duration rainfalls and are sensitive to infiltration and 

vegetation effects (Campbell 1962). The upper bound was 

imposed because estimates of mean rainfalls over large catchments 

can be unrealistic. In any case, since most large 

catchments in New Zealand are monitored, most ungauged 

catchment estimation problems occur in relatively small 

catchments. 

Records for catchments with significant impoundments 

or diversions were not used. This meant excluding a number 

of lake outflow records. However, outflows from all 

larger lakes are monitored for hydroelectric purposes and 

flood estimates for them are best derived directly from 

these records. Urban catchments, and others with areas of 

limestone country, or permanent snowfields or glaciers, 

were also excluded. 

Four years of re_cord were considered the minimum necessary 

to estimate Qou, md with the above constraints, data 

for 63 South Island (Figure 4. I and Table 4.1) and 97 North 

Island (Figure 4.2 atd Table 4.2) catchments were assembled 

for the study. The distribution of these catchments 

throughout the country was reasonable, except that there 

were too few in the southern part of the South Island' 

Tables 4.I and 4.2 contain the data used in this chapter. 

These are the mean annual flood Qo6, , the coefficient of 

variation Cu of annual maxima, the length of record, catchment 

area, and other catchment and climatic characteristics. 

Generally, flow data are complete to the 1976 or 1977 

calendar year. 

4.4 Collect¡on of character¡st¡cs 

A number of indiLces can be used as characteristics X,, X, 

... in Equation 4.1. However, if the relation to be developed 

is to be useful as a design procedure, the cha¡acteristics 

must be rea'dily obtainable from published information 

such as maps, climate summaries, etc. The characteristics 

can be subdivided into two groups; those which 

cha¡acterise the phvsical catchment, and those representing 

the climate over the catchment. The physical characteristics 

included the size arnd shape of the catchment and the embedded 

stream channel, the vegetation, and the hydraulic 

properties of the soil. The NZMS I (l:63360) map series is 

the most detailed map series giving a national coverage and 

was used to providr: measurements of the area, mean elevation, 

channel density, main channel length and slope, and 

percent forest cover. Hydraulic properties of the soil (e.g. 

permeability) are less easily defined; these depend on soil 

type, surface slope, vegetation rooting characteristics and 

underlying geology, and vary widely over most catchments. 

Much of this latter information is now available nationwide 

from the National Land Resource Inventory Iùy'orksheets 

which are plotted at the same scale as the NZMS I map 

series, but this was not available when the present study was 

undertaken. 

Climatic data available in Meteorological Service reports 

and maps include rnean annual rainfall, rainfall intensity of 

specified probability, distance of the catchment from important 

meteorological barriers, and measures related to 

the time and rate of snowmelt. Snowmelt is generally not an 

important flood-producing mechanism in New Zealand and 

in this study two rainfall parameters were used: mean annual 

rainfall for the catchment, and the 2-year return 

period 24-hour duration rainfall estimated for the catchment. 

Thus the following characteristics were estimated for 

each catchment: 

Catchment area. 


(i) 

(it) Main channel length. 

(iii) Main charurel slope. 

(iv) Mean catchment elevation. 

(v) Stream frequency. 

(vi) Percentagecatchmentforested. 

(vii) Mean annual rainfall over catchment. 

(viil) 2-year return period, 24-hour duration rainfall. 

The first six of these are physical and vegetation characteristics 

which were extracted from the NZMS I maps. 

Although recent nraps in this series are photogrammetric 

maps, earlier maps are based on survey records and plane 

table sketch surveys. Others are provisional without contours, 

so channel slope and mean elevation could not be defined 

for every catchment. The considerable variation from 

one map to anothcr in the definition of streams meant that 

estimates of the sl:ream frequency, that is, the number of 

stream junctions lper unit area, were unlikely to be consistent 

from one area to another. It was felt important to 

utilise all available information so stream frequency was included 

but, in the event, it did not assist in explaining the 

variation of Q between catchàents' 

The procedures for estimating the physical characteristics 

which were adapted from Benson (1962b, 1964) and Newsom 

(1975), and acronyms by which these cha¡acteristics 

will subsequently be known are given here. 

(i) 

Catchment area: (AREA) (km') 

Catchment boundaries were drawn on maps and the 

enclosed at'ea measured by planimeter. These areas 

are normally available with recording station information. 

53

Table 4.1 South lsland catchment characteristics. 

1rì 

11 

2It 

2(¡ 

27 

28 

21 

30 

51 

32 

51 

Jlr 

55 

l5 

37 

38 

lq 

h0 

41 

lr2 

ll'¡ 

qq 

b5 

46 

lr7 

q8 

49 

50 

51 

52 

53 

54 

55 

56 

57 

58 

59 

60 

61 

62 

6l 

o ^.- 

STATIoN tm{il 

5?tì16 tlÏ-.nni 

5 7008 l¡37.00 

57106 6S.20 

5750! 83t.00 

59001 77.nr\ 

6fìl 10 1161 .74 

601tli 260.00 

6fì1I6 59.f10 

62!.0t 133.f'n 

62104 -1.6.80 

621rì5 187.fllì 

64t01 524.n0 

6460C 89.2fì 

64610 1I.30 

651n4 540.00 

65q02 56.n0 

66409 0,27 

6660J 1.05 

66604 1,42 

67601 lt.?0 

6Î001 35.00 

68806 108.00 

69506 260.00 

696I lr 25 0 .00 

61 618 I 20 .00 

61621 72,7i 

717î2 tJ.0n 

7!LO3 11 2. 70 

71106 91.60 

71109 100,I0 

71116 227 .nn 

7lr2t 67.5tì 

71f22 7,Jtt 

lLlz? 16.10 

711 29 2b . nn 

711t5 6l .fio 

7!702 148.0n 

73501 37,80 

7rr5l,h 55,2rì 

TttSItE 22.F,rt 

74t5i 2.87 

7tt7Ol ,1-0.00 

75259 22.20 

7527 6 ll5 6. 0 n 

7850-\ t0.00 

73625 46.60 

78801 5.09 

80201 18.70 

th701 5h9,00 

86802 3725.00 

906 0tt 2132.0î 

90605 27 .iî 

91101 1588.00 

911102 lq.10 

9!lr0h 692.00 

91407 119tì.00 

9!206 1680.00 

91207 460.00 

9t'2on 7rB.no 

932u 974.00 

91212 196.00 

932t7 181.00 

94502 1 251 .flo 

cv 

0.1n 

0.85 

0.79 

0.tfj 

o.7n 

o.lrb 

0,¡0 

0 .10 

0.55 

0 .95 

n.lr8 

0.70 

0.27 

| ,17 

ll.t!7 

0.70 

1.54 

1.1i 

I .01 

0.fi8 

0.5'r 

0.71r 

0.75 

0¡98 

r.l5 

0.61 

0.81 

0.77 

0.58 

0.1 I 

n.5lr 

I .14 

o.70 

0.h7 

0,11 

n.75 

1.nt 

0.1 1 

n,56 

0.59 

r) .96 

0.30 

o.26 

0.lrl 

0.1)0 

0.81 

n.78 

o .2P, 

0.!.6 

0.10 

o.2tl 

0 .15 

o.2t 

o .27 

0.r4 

0.40 

0.28 

0.59 

o .?.7 

0.20 

o.32 

l-ength 

Record 

(yrs) 

8 

6 

15 

5 

16 

25 

11 

18 

5 

73 

t2 

10 

3 

10 

It 

5 

t2 

I2 

6 

16 

I 

40 

lll 

10 

5 

1l 

(; 

6 

L2 

7 

6 

q 

11 

10 

6 

72 

10 

10 

L3 

7 

7 

11 

7 

It 

ll 

7 

9 

6 

9 

1l 

11 

13 

IJ 

16 

11 

5 

AREA MARAIN 1224 LENGTH 51O85 

{km'¿) {mm) (mm} (kml (m/m) 

5lEû0 287r !.10 16.50 0.0198 

161.00 2100 Rl 25.10 0.(tr00 

B1 .60 1140 81 20,50 0.0134 

1164.00 1500 124 16.50 0. CI79 

_l1,fta 7620 9t 6.50 0,n210 

76b.00 14Lo 3t G1.so oi'riis 

505.00 L6L0 69 4C.00 0.0118 

192.00 24!0 69 29.40 0.0140 

q9?.00 1570 76 68.90 0.0092 

2n.00 7200 76 9.rlo 0.0600 

440.00 L720 7l) st.tO 0.0097 

464 .00 L23\ Lt2 49. q0 0.0109 

7r,.60 4300 7ß L7.tt} 0.0290 

41.60 030 74 10,50 0.0120 

1070.00 2000 0t 76.10 o;00i2 

tlz.2o 7\0 77 li,40 0.0270 

o.22 L4C0 8l O.lO 0.20r¡0 

?.13 1GO 63 2.50 0.1280 

1,2t |to GJ 2.70 0.1ir0 

5.20 l.rr00 !.04 Z.trO 0.1t¡00 

16r; .0 0 1100 6 9 10 .7 0 O, (07 9 

q?1.q0 L35o 6c 54.90 0.0140 

t20.00 1010 80 t,6.BO o.oijO 

456.00 1075 61 r¡6.40 0.0262 

41 2 .0 0 777 61 tti .ZO 0 .010 6 

2?.\9 800 52 7.eo UNDEF 

78.70 ejo q1 2t: (o úi¡óEÊ 

899.00 720 48 62.30 uilDEF 

150.00 s70 q1 29.50 0.0070 

23,7i lr30 3\ 9.10 0.0470 

11.40 tz(J bi 10.10 0.0160 

122.00 [00 J5 25.t0 0.0420 

108C .00 7022 75 06.00 0.005 6 

1!!.90 1010 rrr 2e.10 0.0020 

109.00 10t0 51 17.10 0.01ió 

36.80 10r!0 b6 17.!.0 0.0030 

, u 1.90 lt t0 66 L7 .70 0,0070 

155.00 6520 520 16,30 o:fì'riõ 

842.00 6920 tO2 7rr,00 0.0168 

152.00 731,0 ttl ,1.40 lt.0290 

3.99 1500 18s 5.20 0.0560 

99q.00 5700 226 65.90 0.0067 

_lq.qq 27\3 104 8.90 0.0190 

642.00 4010 81 66.s0 o.noõé 

790.00 l¡1r70 8l 62.50 0.OOBO 

99e.00 3580 81 69,50 0.0082 

254.00 2520 81 15.60 o,ollo 

980.00 2990 64 95.00 0.0091 

E:7.SS i250 64 75.20 0.0120 

-2!!.gg 1610 6b 

1e8.00 

2t.Eo ö:diii 

t070 64 th.1o 0:ótÉ,, 

694.00 \720 LS2 116-10 0.0170 

FOREST 

{%) 

4t 

4t 

62 

57 

22 

7 

19 

2 

0 

1 

2 

5 

25 

1 

32 

0 

0 

0 

9 

0 

11 

0 

0 

0 

1 

0 

0 

0 

0 

0 

3 

0 

0 

0 

0 

0 

0 

29 

0 

0 

0 

8 

0 

2 

0 

0 

99 

26 

49 

2f 

78 

56 

16 

76 

58 

76 

77 

7t 

72 

76 

67 

77 

STMFCY ELEV 

(km-'z) (m) 

0.16 Ln' 

0.48 1019 

0.89 52tt 

0 .71 587 

0.80 594 

0.87 785 

0 .2\ 1 qll 

0,21 t392 

0.62 1510 

0.02 11q0 

0,r5 1200 

0,72 500 

0,27 rb20 

0.41 5t5 

0. b6 960 

0.55 UNDEF 

0 .0 9¡¡5 

0.0 2E'1 

0.0 r18 

1 .60 t 0ll 

0.78 647 

0 .1¡r 100O 

0,51 .820 

o.ql 917 

0 .25 5lr0 

].10 UNDEF 

1.80 UNDEF 

O. 85 UNDEF 

l.tt 827 

L .72 1128 

0.85 12b0 

0.46 l0llr 

0.11 840 

o.25 970 

o.22 lt85 

0 .3t 1l¡90 

1 . 1O UI,¡DE F 

0. t5 288 

1 ,71 83t 

r.r1 913 

2 .62 3lr 2 

5. (l) L75 

L.3t 1t68 

0.28 tt88 

0,08 50 

1 .05 38' 

0.0, 69 

o.z\ 162 

0.15 8b0 

0,¡2 1050 

0.56 1150 

0.0 2\0 

0 . 74 8l+t 

1.08 L\2 

0.17 7 20 

0.21 710 

0.t3 610 

0 .26 860 

tr zE 'TtÌ 

0.25 971¡ 

0.50 679 

0.2[ 1168 

0.50 700 

(ii) 

(iii) 

(iv) 

Chsnnel length: (LENGTH) (km) 

The main channel of the stream was defined and extended 

to the catchment divide, and its length meas_ 

ured with an opisometer. 

Channel slope: (51085) (m/m) 

Two points were chosen at l0 per cent and g5 per 

cent of the channel length from the outlet. Channel 

slope was determined by dividing their difference in 

elevation by % of the channel length. 

Catchment mesn eleyrtion: (ELEV) (m) 

A grid was overlaid on the map, the grid size being 

selected such that at least 20 points lay within the 

catchment boundary. The elevation of each point 

within the area was noted and the mean of these 

elevations was taken as the catchment mean elevation. 

(v) Stream frequency: (STMFCY) (tns/km,) 

The number ofjunctions for all stream channels de_ 

fined on the catchment map was counted and expressed 

as the number per unit area. 

(vi) Forest cover: (FOREST) (Vo) 

The area of catchment defined as forest on the 

NZMS I maps was measured and expressed as a percentage 

of the total area. 

54 

(vii¡ Me¡n annual rainfall: (MARAIN) (mm) 

Mean annual rainfall for the catchment was estimated 

from records for rainfall stations within and 

adjacent to it. Where catchments had no such rainfall 

records, mean values were obtained by planimetry 

from l:500 000 isohyetal maps of l94l-1.} annual 

rainfall normals (NZ Met. Ser. (1977) ..Mean 

annual rainfall maps (1941-70),' unpublished). In 

mountainous areas having few raingauges and large 

rainfall gradients, the isohyets are believed to indicate 

only general trends and do not provide accurate 

estimates of catchment rainfall, particularly in the 

catchments draining the Main Divide of the 

Southern Alps. 

(vüi) Rainf¡ll intensity: (1224) (mm) 

At the time of the study the most recent source of 

published rainfall intensity data for New Zealand 

was Robertson (1963). This provides frequency analyses 

of rainfall intensity information available in 

the early 1960's, using data for 46 recording rainfall 

stations and 468 daily-read stations. As there were 

relatively few records from recording gauges available 

to provide short period rainfall data, the areal 

extrapolation of this information to catchments 

remote from gauges was considered unwise. It was 


Cobb. 

5291ó '\ 

Stonley Bkr \ 

57011. \ 

Moluckor \ 7 

57008 '. ¡. 

rWo i¡oo 

'P7so2 

I 

I 

I 

lnonoohuor \ \ 

93266 'r \' 

liåî";--- )-l 

lnonoohuo- \ 

932Õ7 -:- 

er96iyt- ) 

Eîidt" tn-- 

Toromokou 

9lrol --: 

Butchers Ck : 

90ó05 \ 

Hokitiko: 

?9ó04 \: 

-/ 

óó4O9 Hur Ck-- 

71.129 torksr - : 

Fiï!Ë'" t'., 'r_ f 

- Io-llie. '. \ 

7t135 \. 

ffiåä'"n.. 

"...! 

'r' 

I t 59003 

\ao,r,no 

' 

( \ óono' 

twoi¡ou 

\ óoìl¡ 

\ \wo¡rou 

,- r óOlló 

r \. rConwoy 

\. ó4301- 

\ \ 

'Achoron acha¡an 

\ ó2103 

I I \Sronton 

i r \ ó4ólo 

ì r i r'Áls9re ¡Ribblc 

'- 

ì !¡ ó2104 

\ L-Clo.cnce 

\ ó2105 

-Weko Ck 

t\- v¿ 6s902 ava 

*, -- coshme¡e 

- óóó03 

- sHoon Hov 

\ \- óóól 66601 

\ s.r*y.^R'vi#Éi 

Srh 

lwo¡hooo¡ 

Rowollonburn / 

80201 \ 

e ', 

\ wo¡hooo i 

78sOc 

- gå3g5' 

Fþure 4,1 Location of the South lsland catchments. 


55

I 

2 

t 

l¡ 

5 

5 

7 

I 

9 

l0 

t1 

,12 

I5 

1{ 

l5 

l6 t7 

18 

19 

20 

2t 

22 

23 

2lt 

25 

26 

27 

28 

29 

t0 

t1 t2 

t, 

5\ 

t5 

56 

,7 

t8 

39 

¡0 

¡1 tt2 

Irt 

4h 

Ir5 

It5 

47 

|l8 

It9 

50 

51 

52 

51 

5lr 

55 

56 

s7 

58 

59 

60 

61 

62 

63 

6lr 

65 

66 

57 

68 

69 

70 

7t 

72 

73 

74 

75 

76 

77 

78 

79 

80 

8t 

82 

It 

84 

fì5 

86 

87 

B8 

89 

90 

91 

92 

g3 

fth 

.,5 

96 

97 

TaHe 4.2 NoÉh lsland catchment characteristics. 

_ 

L€ngrth 

065¡ ^ Roco¡d AREA MARATN 1224 LENGTH s1085 

STATION lm¡s-r) (,v lyrs| (kmrl lfnm) (mm) (km) (m/ml 

t506 57.80 0.29 10 11.10 2250 105 

5819 

7.00 0.0260 

107.00 

11901 

0.¡4 10 229.00 1510 

83.90 0, l+lr 

109 ¡10.10 0.0014 

I 12.5 0 19 q0 

5809 

l2t+ 4.60 0.0091r 

63.30 0.67 10 16.20 l7 00 

8501 

102 7.L0 0.0510 

tL.20 0.55 15 t2.70 17 90 

s10t 

74 8.50 0.0150 

q2 .10 0.4s t7 455.00 15 00 

9108 

69 75.00 0.0010 

tl0.00 0.64 L7 528.00 L230 

9201¡ 

71 43.50 0.0020 

[92.00 0.28 

92QB 

t3 t08.00 ztr0 119 ,5 . lr0 0 .0010 

t 5. t¡0 1.05 7 7.90 t9 20 

9501 519.50 0. r+2 

llf 4.00 0.17 20 

18 l22.OO 5090 

15901 

8q 21.80 0.0177 

5.06 1.20 6 2.95 15r 0 

Ur6l0 20.t0 0.t8 

10tl t.80 0,01+50 

I 57.00 150 0 

Ltt627 

86 16.90 0.0100 

¡rt.40 o.37 10 69.90 2L20 104 2\.20 0.0170 

10528 147.00 0.52 I 179.00 22tt0 108 

151r10 

31.50 0.01q0 

120 .50 O.75 

15511 

25 53t¡.00 L730 84 

t87.00 0.60 

55.t0 0.010rr 

25 q¡0.00 17 90 

l55rl¡ 

12ì+ l0.2o 0.0130 

2.11 0.65 10 2.59 l5 t0 

15556 

95 2.66 0.0515 

218.10 0.46 

15901 

8 207.00 20¡0 

819.00 0,65 

lztt 28,70 0.02b3 

19t09 

19 640.00 217 î 91 50.70 0.0088 

14rr.00 0.29 t2 lst.30 1¡0 0 

19711 

79 21r.10 0.0216 

t70 .00 0,65 

21601 

11 175.t0 llr00 8l 27.tO 0.0158 

59.60 0.52 

218 05 

l0 20 .60 142 I lztt 7.00 0.02!8 

45 9.00 o 

22802 

.52 13 997 .00 22tO 

216.00 o.77 

99 72 .50 0 .0060 

23002 

13 25t¡.00 15 01r 

501.00 0.64 

99 31.60 0.0150 

2too5 

10 826.00 154 0 92 67.10 0.0070 

1,51 0.40 

2tl0tt 

10 0.52 2605 86 0.50 0.01180 

209.00 0.32 

2tL06 

t3 570.00 1450 9lr 62.10 0.0080 

66,30 0.48 

21209 

t0 259.00 160n 70 t4.60 0,0110 

10.50 0.90 

232LO 

t2 24.10 955 

48.70 0.57 

66 7.60 0.0086 

10 54.q0 t277 

2920t 

t02 t'.30 0.0040 

{29.00 o.27 

29224 

22 6t7.00 16 60 66 5q.60 0.0080 

532.00 0. 28 

29211 

22 185 .00 \t+7o 

156.00 

rrl 

99 

292\2 

I 

58.00 0.0210 

t|t .O0 

89.00 0.40 '9 

1110 7tt 68.10 0.00t1 

58.80 Ir00ll 

2921t4 

6l+ 

27.60 0.111 

16:70 0.0410 

I 56.t0 1090 

29250 

76 

31.70 0.87 

15.50 0.0064 

7 15.50 18 40 

29808 

107 5.70 UNoEF 

254.00 0 .t2 9 88 .80 2410 

29818 

99 14.60 0.02110 

546.00 0.28 

t0516 

6 427.00 2700 

7.86 0.112 B 

79 38.1¡ 0.0050 

0.t5 10t n 

,180t 

69 

1027.00 0.15 

7.60 0.0102 

l8 50r.00 2670 

t2so3 539.00 0 . ¡ll 

102 ¡9.90 0.0116 

32526 

22 71t.00 15 r0 

719.00 0. l¡0 

78 67 . t0 0. 0050 

24 266.00 2tt7 

12529 262.00 0 . ltg 

î 100 65 .20 0. 0060 

24 7t lr .00 15 70 6h 5t . l0 0.0010 

t25rt b3r.00 0.37 2\ [52.00 1780 8J 55.t0 0.00110 

t2565 18¡.00 0.26 10 570.00 12 60 60 92.00 0.0100 

32576 5t7.00 0.56 8 bt1.00 15 70 79 56. ¡0 0.0160 

12708 522.60 0.t2 10 58t.00 2t 00 76 76.00 0.006t 

52721 21.70 0.¡t 7 25.60 t1 l0 52 9.5 0 0.01t9 

32712 106. 00 0,35 17 285.00 2260 5l ,t.00 0.0140 

32711 182.00 0.]5 5 650.00 178 0 55 70.00 0.0110 

,273\ 5 .11 0.16 15.00 I 701 51 8.20 0.0550 

t2735 t2.\0 0.67 8 62. [0 920 55 20.90 0.0100 

J27t9 18.70 0. b8 t2 47 .70 I 100 52 1t.50 0.0087 

,5707 96.5 0 0,19 l0 1192.00 1650 58 51. .00 0.OL72 

3t111 240.00 0.35 lt 5t9.00 157 0 69 59.70 0.0168 

t1114 lr,18 0.18 9 6t.50 1101 55 15.20 0.0110 

StlLs 19.70 0.17 

ltll7 t3.20 1568 66 8. 20 0.0b70 

25.10 

ttt07 

0.51 I 21.04 2160 

h0.70 0.¡5 

7t 20.90 0.0400 

11 81.5u 2¡¡00 toz 7.70 0.0901 

3tt09 t21.00 0 .26 15 132.00 2220 7t t8.00 0.0326 

35tlL 265.00 0.11 15 207.00 219 0 89 60.00 0.0058 

35112 350.00 0.69 6 256.00 19 40 7\ 26.90 0.0159 

t33t3 268 .00 0 .5 0 15 668 .00 180 0 19 82 .40 0.0018 

5t316 259.00 0.24 14 1075.00 7770 74 72.00 0.0049 

31320 0.28 L7 181¡.00 1220 t02 2a.L0 0.0519 

tt324 '82.00 41.60 o.52 8 tl .00 2592 102 16.00 0.0417 

55538 512.00 0.15 I 971.00 2160 8lr 66.!0 0.0172 

31t47 125.00 0.20 5 207.00 18t 0 89 5tr.l0 0.0025 

50.90 0 .46 10 28 .00 2rt0 90 tq .60 0.0650 

'tttt7 ,6001 t8.90 0 .60 f 29.50 23L0 79 25.60 0.01110 

19501 572.00 0.29 8 725.00 2280 97 l[0.00 0.0005 

10504 175.00 0.12 t2 80.00 ,582 104 28.60 0.0298 

39508 (t7.2O 0.51 4 11.t0 1582 104 17.50 0.0580 

rl 07 0l 5 .24 0.2t 7 15.60 207 0 74 5.00 0.0280 

41601 7.\3 o.52 

t+3ttt5 

5 9.10 15 90 611 11.60 0.0520 

45 .20 î-25 t1 157.00 195 0 81 10.40 0.0502 

\1472 21.1 0 0. 61 16 228.00 t270 76 21.60 0.0050 

10¡3419 27.60 o.52 73 446.00 1500 66 q1.80 0.0120 

1043\27 58.90 0.1 7 14 t7t.oo 1880 72 t7 .3ît 0, 0102 

10¡t428 44.90 0.t4 72 210.00 1q00 90 21r.50 0.0100 

104tlt5lr 5.68 0.70 I 22.00 1¡t 0 76 11.50 0.0250 

1043459 î.82 20 772.00 2270 88 62,80 0.0120 

104t461 '65.01 241.01r 0.29 t7. 174.00 2980 89 11.80 0.0187 

104tt66 [7.50 0.25 25 88.00 5580 76 b.90 0.1010 

11113408 0.01 0.23 7 0.17 16 60 80 0.51 0.1500 

Llttt\zz 5 . tio 0.68 6 5.11 2000 66 lù.50 0.0820 

7145t+28 4,10 0. 44 B 17 .1¡0 llr 60 66 5.70 0.00llr 

\3602 2r.50 1.32 9 17.60 lt60 75 5.70 0.0092 

Ir3805 t9.90 0.66 I 52.60 1r4 0 69 18.50 0.0050 

45102 t2.70 0.lr8 10 8.00 15 70 109 5.70 0.0t20 

¡!6611 153 .00 0 .32 8 116 .00 16 20 117 22.70 0. 0190 

46618 4l+7.00 0.46 17 2[6.00 195 0 ll7 26.80 0.0190 

Ir6625 221.90 0.28 I 189.00 l5t 0 101 2t .20 0 .0040 

\6612 189. lr0 0.52 t7 162.00 lB20 1tl7 20.90 0.0070 

46660 9.72 0.t9 L2 2. b8 1540 t00 2.70 0.0210 

45662 2.t1 0.r5 r0 0.t9 11r 90 117 0.60 0. 1000 

tt7527 41.90 0.98 t2 10.60 I 800 llb 6 .00 0.0102 

FOREST STMFCY 

(%l (km{} 

0 0.90 

29 0. 45 

¡8 1. E4 

6¡ 1.70 

100 5. l0 

5 0.r1 

0 0.50 

tt5 2.10 

t00 1.t9 

82 2.t0 

0 2.00 

b5 I .00 

55 1.50 

57 0. 92 

95 UNDÊF 

89 UNDEF 

0 t.50 

100 l¡.70 

79 UNDEF 

O UNDEF 

2 1.91r 

o 2.13 

50 UNOEF 

12 UTIDEF 

5 0.90 

lOO UNDEF 

[¡ 0.E0 

Irl 0.80 

5 UNDEF 

o 2.\0 

14 0.16 

78 0.62 

t 1.00 

65 0, 49 

0 1,00 

l0 7.50 

q5 1.50 

55 L.rl 

0 2.10 

90 0.58 

5 U¡IDEF 

51 0. 66 

2 UNDEF 

t2 0.10 

7 0 .116 

22 0. lt7 

l8 0.59 

2 0i98 

7 L.1L 

5 1,t5 

tf 5.50 

0 0.69 

I 1.15 

t5 0.81 

2t t.'l 

0 0.6t 

E7 5 .50 

59 0.76 

L2 0.96 

56 L.77 

85 0.96' 

51 1.70 

28 r.61 

27 0.79 

E 1.62 

0 t.l¡8 

ql L.27 

58 0.71 

0 1 .1r2 

tt 0.q6 

59 1 .50 

2t 1.19 

51 0¡62 

16 1.10 

0 0.55 

55 0.65 

5 I UNDEF 

57 UNDEF 

¡t 0,t8 

t9 1.10 

16 2.45 

3L UNNEF 

50 2.05 

! 2.65 

0 2.70 

7 0.t2 

0.52 

0 1.20 

6 1.50 

57 r.00 

llr 1.5t 

ll 0.92 

16 0 .80 

[0 1.50 

0,0 

0 0.0 

8 0. lr7 

ELEV 

(m) 

2.50 

tL2 

180 

16t 

zilt 

80 

86 

275 

510 

3ro 

110 

t99 

lll6 

,72 

UNDE F 

48lt 

1t0 

660 

6q0 

450 

,20 

l¡ ¡r 

UNDEF 

UNDEF 

t92 

10 10 

1121 

965 

220 

200 

,0tr 

726 

265 

672 

280 

UNDE F 

6tr0 

t+7\ 

ztt0 

55' 

8trI 

Ir 66 

UNDEF 

29r 

1.95 

568 

10 ¡rf 

285 

11 70 

992 

119 0 

180 

2tl 

959 

680 

825 

5 

970 

869 

831 

392 

492 

581 

474 

1108 

861 

726 

t22 

111 0 

510 

286 

427 

778 

280 

200 

487 

4 5l¡ 

160 

527 

4lrl 

l+60 

970 

L202 

900 

610 

[00 l0 

50 

ft 

270 

t10 

t52 

155 

105 

80 

100 

2t6 


56

Ooohi 17527' 

Mongåkohio 46618'- 

Koihu 16611" ) 

Puketuruo 4óóóOl 

& Pukewoengo 4óóó2 

(z' 

,Woiwhiu 

a 

45 702 

,Kouoerongo 93Oì 

a 7/ ¡woit- gtol 

Pìoko 9l08- 

Ohote 1143428- - - 

Pokoiwhenuo lO43419- - 

\ Te Tohi 1143427-. - 

Oteke 4ìó0'l1 \- 

& Purukohukohu 'l143408 

-Woimono l55l I 

,Woimono ì553ó 

/' 

/ / Woioeko 15901 

Popokuro 43803'- 

Woiroo 85Ol- - 

Woitongi 13602'- 

- - -Woiotopu 43172 

-whirinok¡ l54lo 

--T 

- - -Woingoromiq ì97I 

- - -Whorekogoe l97O 

,1',/ 

lO43¿59 

rL 

Y- - - -Tongoriro 

:-- 

- .- --Tohekenui 2lóOl 

- --Wongonui 

-=ln --_-t 

333¡7 

- - -Mongolepopo 33324 

- - Whokopopo 33320 

It-L- 

\t- 

Mokotuku 33.l17 / 

Woipopo 4343* - 

Mongokowhoi 4O7O3- - 

Tohunootoro 1013128- - 

Mongokino 1C,13427-- - 

Ongorræ3331ó - - 

Mongoroo3334l--- 

Ohuro 333ì3- - - 

Tongorokou 333 I l- - 

Woitoro 39501 --; 

Mongonui 39504-- 

Mongonui 39508-- - 

Punehu3óOOl - - - 

Wongonui 33338- -. 

ñeørute 3g312/ 

Mongonui-o-te-oo 33309/ -. 

,' 

Mångowhero 33lll/ ./ 

üu-h""ã*h, 33107/ - -\, 

MoungorouPi 32723¿,/t 

Tuloenur 32739' / 

Rongilowo 32735/ 

Mongohoo 32526- - 

Mcngoloinoko 32531-' 

ì,fhonqoehu 29211- - 

Oroki 3ì803- - 

Monooloroo 33ì15 / 

-( j-îftx,t-t-\- 

-- 

--O,rouo 325ó3 

-Ti¡oumco 32529 

Aliwhokolu 29242 

ì,--loueru2923l 

\- --Woiohine29221 

/ -: -\Hutt 29808 

-:- --Hurt 29818 

-- - Ruohokopotuno 2'?250 

'rv\iil ck 3o5tó 

--- 

Rro-oho-ngo2.92Ol 

Êigutø 4.2 Location of the North lsland catchments' 


51

decided instead to use estimates of the 24-hour dura_ 

tion 2-year return period rainfall derived from the 

more extensive net$,ork of daily_read gauges, since 

these could be extrapolated to remotè catchments 

with greater confidence. 

The use,of a 2-year recurrence interval seemed ap_ 

propriate because the mean annual flood has a rècurrence 

interval only slightly greater than 2 years, 

2.33 years if the annual ma,rimã conform to the extreme 

value Type I (Gumbel) distribution. Estimates 

of this parameter (without the application of an 

areal reduction factor) were made from Robertson's 

data for each catchment using rainfall stations with_ 

in, or near to, the catchment. These estimates were 

not adjusted for effects of altitude. 

These eight characteristics were estimated for each catchment 

(Table 4.1 and 4.2 for the SI and NI respectively). For 

those catchments not contoured, channel slópe and mean 

elevation were undefined; there were 5 such bouth Island 

catchments and 7 North Island catchments. 

4.5 Analys¡s of South lsland data 

4.5.1 Preliminary examinat¡on of data 

table shows that the highest correlations of Q are with 

AREA and LENGTH, but that signifìcant correlations also 

occur with all other characteristics except STMFCy. Further 

strong correlations occur between AREA and 

LENGTH, between MARAIN andl2}4andalso MARAIN 

and FOREST. These are all physically plausible. Significant 

negative correlations occur between Sl0B5 and AREA and 

not well determined. 

The results of applying a, stepwise multiple regression 

program to the data are summarised in Table 4.4. The best 

fit equation is that involving the three variables AREA, 

I2A and FOREST and is 

Q = 4.40 x l0{ AREAÙ.¿'12241.27 (l +FOREST/lcf|/)t 6' 

.....4.3 

The coefficient of determination indicates that glgo of 

of errors of estimate is given in section 4.10. 

quently. For the present the data are considered as one. 

with AREA (Figure 4.3), 

rs of magnitude for Q for 

approximate equation for 

south of the island, and strongly positive residuals on the 

Q = I.9SAREAo eo 42 

where Q is in_m3ls. The linear correlation coefficient (R) 

between loe (Q) and log (AREA) is 0.85, and the stand;rá 

error-of_estimate of logarithms of Q is 0.45. Although this 

correlation is highly significant, the standard errorls too 

large for Equation 4.2 to be of much value, an obvious con_ 

clusion when the scatter for Q for any given AREA is con_ 

sidered (Figure 4.3). Equation 4.2 demonstrates two im- 

this systematic residual variation may be due to variation in 

the precipitation regime across the island not fully represented 

by the estimates of 1221. 

4.5.2 Development of tdal rcgionalest¡mators 

into four regions is 

of the high rainfall 

the Southern Alps is 

des the Nelson area 

with the \Vest Coast. The division of the East Coast is more 

tenuous, but is supported by the consistent underestimation 

of Q for the small catchments along the coast (Figure 4.4), 

and by the knowledge that some of the morè intenie 

from cyclonic 

inland. Specia 

third inland 

part comprises 

T¡He 4.3 Correlation matrix for logs of South lsland characteristics. 

MARAIN STMFCY s1 085. ELEV* 

o 

AREA 

MARAIN 

1224 

LENGTH 

FOREST 

STMFCY 

s1085. 

ELEV' 

l.OOO 

.846 

.612 

.448 

.799 

.464 

-.078 

-.473 

.383 

1.OO0 

.2e3 

.045 

.978 

.163 

,010 

-.673 

.460 

l.OOO 

.753 

.228 

.647 

-.390 

-.o51 

.ioz 

l.OOO 

.o23 

.424 

-.314 

.181 

.o98 

l.OOO 

.155 

.oo7 

-.733 

.424 

l.OOO 

-.259 

-.134 

-.092 

l.OOO 

-,049 

-.o47 

l.OOO 

.10,4 

1.OO0 

I lncomplete Sample 

58 


I ]n 

e 

d qgoinst CATCHMENT AREA for South Istond x 

64 

x+O 

¡XOs 

Xt 

x 

o 

74314 Toieri 

1é 

x V,/est CoqsT 

+ Eqst Coost 

O Intond Morlborough/ 

Conterbury 

O Mqckenzie, Inlqnd Ofogo, 

Southlond 

10 

Iotch me n I 

100 

A¡e u (kmz) 

1000 10000 

Fþure 4.3 O vs AREA, South lsland catchments. 

the inland hill country of Marlborough and Canterbury. 

The southern part includes the Waitaki River basin, inland 

Otago and most of Southland. This division is made on the 

basis that with the exception of coastal Southland, the 

southern part is a low rainfall area for which Q rvas overestimated 

by the equation. 

The regional division is evident in Figure 4.3. When the 

catchments were identified according to the region including 

them, it was found that data for West and East Coast 

regions tend to lie in an upper band. Those for Inland Ma¡lborough/Canterbury 

tend to lie in a central band, whereas 

those for Inland Otago and Southland tend to lie in a lower 

band. 

The data were grouped according to these regions and regional 

stepwise regressions were calculated (Table 4.5). In 

all cases AREA is the most important variable, although in 

all regions additional variation in log Q is explained by 

other variables. In the West Coast, and Inland Otago and 

Southland, rainfall intensity (I2Z)'signifïcantly improves 

the fit of the estimating equations. 

For the East Coast, MARAIN is the second most important 

variable. The reason this is more important than I2Z is 

therefore preferred. 


not obvious. It naay be that, because the East Coast catchments 

are relatively small (the largest, Station 64301 is 

464 km'z), the 2-hour storm intensity may be more important 

than the Z4-hour figure used. However, such information 

was not generally available. The appropriateness of 

annual rainfall for estimating a flood parameter is open to 

question, but it is supported by Figure 4.5. This figure 

shows that, with the exception of Station 65Ð2, there appearsto 

be a linear relationship between log MARAIN and 

the residual of log Q, after the effect of AREA is removed. 

This is the justification for including MARAIN in the estimating 

equation. 

For Inland Marlborough/Canterbury FOREST appears 

as significant in the best-fit equation. However, this is a little 

deceptive since only 4 of the 15 of the catchments in this 

region are more than l09o forested and the ma¡

\Í 

l{ 

I 

t, 

ìj( 

Fþurc 4.4 Distribution of residuals from Equation 4,3. 


60

3.1 

z 

Í ¡.0 

= 

t:' 

o 

2-9 

2-8 

2.7 --4 .2 

'l+ 

.ó 

(roc õ-.sz LoG AREA) 

Figure 4.5 Plot of log MARAIN vs (bg õ -.92 log AREA) for East Coast Region. 

Table 4.4 Stepwise regressions for all South lsland data, 

No, Var. Name 

Coef 

br 

se 

of coef 

R2 

se 

€8t 

Const 

log a 

Muhiplier 

a 

1 AREA 

2 AREA 

1224 

3 ABEA 

1224 

FOREST 

4 AREA 

1224 

FOREST 

STMFCY 

5 AREA 

1224 

FOREST 

STMFCY 

MARAIN 

6 AREA 

1224 

FOREST 

STMrcY 

MARAIN 

LENGTH 

0.90 

0.88 

1.58 

o.85 

1.27 

1.65 

o.85 

1.34 

1.75 

o.44 

o.82 

1.O4 

1.34 

o.54 

o.39 

o.95 

o.99 

1.35 

0.53 

0.41 

-o.25 

o.073 

o.046 

o,169 

0.041 

o.162 

o.364 

0.040 

0.163 

0.360 

o.229 

o.o42 

o.222 

o.412 

o.230 

o.202 

o.202 

o.236 

o.414 

o.232 

o.204 

o.373 

12.4', 

19,8* 

9.3* 

20.6* 

7,8* 

4.5" 

21 .O* 

8,2* 

4.91 

1.9 

19.6* 

4.7' 

3.2* 

2.4* 

1.9 - 

4.7' 

4.2* 

3.3* 

2.3' 

2.O' 

-o.7 

o.846 

o.940 

0.954 

0.956 

o.959 

o.716 

0.884 

0.910 

o.914 

o.920 

o.450 

o.292 

0.256 

o.252 

o.249 

o.0333 

- 2.866 

-2.351 

-2.571 

-3.195 

1.O8 

1 .36 x 1O-s 

4.46 x 1O-3 

2.69 x 1O-2 

6.38 x 1O< 

o.958 0.918 o.262 -3.071 8.49 x 1O{ 

' Significam at 5% level. 

Note: 1 The fitted relation is õ = a Xr h Xz b ... 

2 The multiple correlation coefficient (R) and standard error of ostimato quoted 8re for tho logarithmic form 


logO = loga + br logXr + bzlogX¡ * .,,

62 

Fþurc 4,6 Logarithmic rcsidual errors for trial South lslend regional equat¡ons. 


4.5.3 Examlnstion of residuals 

The geographic distribution of the logarithmic errors of 

the regional equations is shown in Figure 4.6. Except for 

some possible clustering of positive residuals at the southern 

end of the island, the errors appear to be randomly distributed. 

Before the regional equations were finalised, the more 

extreme errors were examined to see whether they could be 

attributed to known causes. Errors greater than t0.25 a¡e 

shown in Figure 4.6 for Stations 57008 (Motueka at Gorge), 

64ó06 (Waiau at Malings Pass), 65902 (Weka Creek at Antills 

Bridge), 68806 (Ashburton South at Mt Somers'),7ll02 

(Otekaieke at Stock Bridge), 71122 (Maryburn at Mt 

McDonald), 74314 (Taieri at Patearoa-Faerau Bridge), 

78625 (Otapiri at McBrides Bridge), 9ll0l (Taramakau at 

Gorge), atd9l4O2 (Sawyers Creek at High Street Bridge). 

The following reasons are advanced as possible explanations 

for some of these and other lesser outliers. 

(Ð Cstchment in wrong region 

For Station 64ó06 (V/aiau at Malings Pass) the error is 

0.32. This small catchment (74.6 km') is adjacent to 

the Main Divide and subject to the same heavy rainfalls 

that cause many rWest Coast rivers to reach flood 

levels. The West Coast region'should be extended 

slightly to the east of the Main Divide to include this 

catchment. Two other catchments (60114 and 60116) 

lie near, but not generally as close to the Main Divide 

and do not on the basis of their residual errors justify 

inclusion in the West Coast region. This adjustment of 

regions is supported by a rather abrupt cut-off of 

north-westerly rainfall which seems to occur a short 

distance to the east of the Main Divide. Also, Figure 

4.3 suggests that Station 64606 fits better with the West 

Coast catchments than with the inland catchments of 

the Inland Marlborough/Canterbury region. 

(it) Unreli¡ble e¡tlm¡te of Q from excessively short record 

The error for Station 65902 (Weka Creek at Antills 

Bridee) at 0,6 is the higlrest for all 63 stations. As an 

error of about 0.33 would occur if the bounda¡y between 

the East Coast and the Inland regions was 

shifted slichtlv to include the catchment in the Inland 

region, it-is óoncluded that Qo6, for this catchs€nt 

ba--sed on only fóùr'years of recdiã is an unreiiable estìmate 

and the station is not used in the subsequent analysis. 

(lil) Catchments wlth large pondlng effects 

The frrtted equations seriously ov€r-estimate Q for stations 

68806 (Ashburton South at Mt Somers) and Station 

71122 (Maryburn at Mt McDonald). Part of the 

Ashburton South catchment and all the Maryburn 

Region 

1 West Coast, Nelson 1 

Number Variable 

Variables Name 

2 

faHe 4.5 Stepwise regressions for South lsland regions. 

AREA 

AREA 

1224 

Coef 

br 

se 

of coef 

0.87 0.103 8.5* 

o.91 0.063 14.3* 

o.90 0.165 5.4* 

2 East Coast 1 AREA 0.92 0j42 6.5* 

2 AREA o.91 0.081 11.2* 

MARAIN 2.58 0.559 4.6' 

AREA 0.96 0.108 8.9t 

1224 1.62 0.557 2.9* 

AREA 0.93 0.083 1 1.2* 

1224 o.58 0.566 1.O 

MARAIN 2.O7 0.14A 2.8* 

3 lnland Marlborough/ 

Canterbury 

4 Mackenzie, lnland 

Otago, Southland 

+ Designated beet fit equation 

* Significant at 5% level. 

Notes: 1 

1 

2 

AREA 

AREA 

FOREST 

AREA 

FOREST 

1224 

AREA 

1224 

AREA 

MARAIN 

o.85 0.049 17.5* 

0.83 0.042 19.9' 

2.58 1.OO2 2.6'. 

o.82 0.044 18.4* 

2.58 1.032 2.5'. 

-o.23 0.402 0.6 

o.84 0.052 16.2* 

-o.22 0.4A2 0.5 

o.85 

0.34 

o.o47 18.z', 

0.238 1,4 

o.899 

0.964 

R2 

se 

est 

Const Muhiplier 

loga 

a 

o.81 0.2A7 0.560 3.60 

O.93 0.181 -'l .381 4.16x1O-'z+ 

0.899 0.81 0.359 0.1 1 1 '.|.29 

0.968 O.94 0.216 -7.600 2.51 x 10{ + 

0.946 O.9O 0.235 -2'891 

1 .29 x 1O-3 

0.971 0.94 0.177 -7.149 7'1O x 1O{ 

0.979 0.96 0.175 0.0363 1.O9 

0.986 0.97 0.152 0.O212 1.O5 

0.987 0.97 0.129 0.455 2.45 

0.980 0.96 0.162 0.454 2'84 

0.982 0.96 O,1 51 - 1 .O3 9'33 x 1O-2 

AREA 1.O2 0.131 7.8' o.89s 0.80 0.257 -0.706 1.97 x 1O{ 

1 

2 AREA o.91 0.098 9.3* 0.947 O.9O O.1A7 -2.A97 1.27 x1O4 + 

1224 1.40 0.367 3.8* 

AREA 1.38 0.249 5.6* 0.957 0.92 O.180 -2'122 7.55x1O-3 

t224 1.13 0,357 3.2' 

LENGTH -o.93 0.460 -2.O 

The form of fitted relation is O = a ¡¡'¡b' (Xzlb' "' 

2 The multiple cor¡elation coefficient and standa¡d error quoted are fo¡ the lcgarithmic form 

log O = log a + br log Xr + br log Xz '.. 

3 FOREST computed as (1 +FOREST/IOOl 


63

Table 4.6 Final equations for South lsland regions. 

Region 

West Coast. Nelson 

East Coast 

lnland Marlb, Canty 

McK, lnland Otago, Sthld 

No. 

Stns 

19 

11 

13 

15 

õ 

õ 

õ 

õ 

B€st Fh Equations R2 

Se 

est 

= 0,0233 AREAo...l224o.e¡ 

= 1,1 1 x lo-e AREAo ¡e MARA|N3.o 

= 0.964 AREAo.¡o 

=o.oo1 90 AREAo.el 12241,3 

o.971 

o.989 

0.992 

o.963 

0.94 

o.98 

0.98 

o.93 

Factorial 

se €8t 

0.1 48 1 .41 

0.117 1.30 

0.1 09 1 .28 

o.1 46 1 .40 

catchm€nt drain former glacial moraines on s,hich the 

surface drainage network is ill-defined. Considerable 

surface storage occurs in swamps and, in the case of 

the South Ashburton, the drainage divide with Lake 

Heron is ill-defined. Therefore, flood-flow levels are 

expected to be substantially reduced and it is uûeal_ 

istic to use data from these catchments to estimate 

flows for other catchments where similar ponding does 

not occur. On this basis the data are omitted from the 

final analysis. 

The central area of the Taieri catchment (Station 

74314) is a flat plain through which the river channel 

follows a meandering course. The recording station is 

situated downstream of a narrow gorge in which flood 

waters back up and inundate large areas of the plain. 

This ponding occurs to a much greater extent thãn on 

most other catchments. The resulting reduction in 

peak discharge is reason for rejecting data from this 

catchment in the final analysis. Note that this catch_ 

ment is an outlier in the Q against AREA plot in Fig_ 

ure 4.3 

(iv) Station wlth unreliable rating 

Because flow records for Station 9ll0l (Taramakau at 

Gorge) were derived using a theoretical rating the re_ 

cord qualìty was expected to be only fair andihe esti_ 

mate of Qo6, subject to more error than most values 

for most other stations. As the value used appears to 

result in a large error, the station is excludeã in the 

final analysis. 

(v) Remaining outliers 

(vi) Snowmelt 

Although snowmelt is not an important flood-producing 

mechanism in New Zealand, when it combines with 

rainfall it may cause floods greater than would occur 

through rain alone. However, snowmelt catchments do 

not appear aniongst the catchments listed earlier as 

outliers. Although data on the extert, depth, and 

water-producing capabilities of snowpack are sparse in 

New Zealand, it is known that in the Fraser catchment 

(Station 75259) five of seven annual flood maxima 

us€d in this study occurred in October, November or 

Decernber, and are likely to have been associated with 

snorvmelt. This may account for any underestimation 

of Q for this catchment (residual error equal to 0. 16). 

Snowmelt may also be a contributory factor to the 

underestimation of Q for other catchments in the 

island, paticularly 71116 (Ahuriri at South Diadem) 

and75276 (Shotover at Bowens peak). 

The final estimation equations were derived after shifting 

the boundary between the West Coast and Inland Marlborough/Canterbury 

regions slightly lo include the catchment 

for Station 64ó06 in the West Coast region, and excluding 

Stations 65902, 68806, 71122,74314 and 9ll0l for the reasons 

stated. 

4,5.4 Final equations for South lsland 

estimate is decreased compared with the first trial equations 

in Table 4.5. 

The geographic distribution of residual errors for the fin_ 

4.7. Yery good fit has been 

Inland Marlborough/Cantrs 

are +0.22, and their disdom. 

The fÏt for the W€st 

Coast and Inland Otago and Southland regions is satisfactory; 

one error exceeds 0.30 and t$¡o more exceed O.A. 

Although most errors appear randomly distributed in 

sDace, several positive errors clustered in the southern part 

of the Inland Otago and Southland region suggest ihat 

some consistent underestinnation of Q has occuried there. 

Table 4.7 correration malrix for rogs of North rsrand charact€rist¡cs. 

o 

AREA 

MARAIN 

t224 

LENGTH 

FOREST 

STMFCY* 

s1 085* 

€LEVT 

1.OOO 

o.830 

o.294 

o.2ö7 

o.815 

o.342 

-o.117 

-0.413 

o.247 

AREA MARAIN LENGTH FOREST STMFCY. S1085. ELEV' 

1.0O0 

o.040 

-o.110 

0.944 

0.189 

-o.121 

-o.576 

0.303 

l.OOO 

0.296 

o.o44 

0.506 

o.o69 

0.332 

0.454 

l.OOO 

-o.101 

o.312 

o.o60 

o.o09 

-0.149 

l.OOO 

0.191 

-o.187 

-0.598 

o.278 

1.000 

o.178 l.OOO 

o.o77 o.196 

0.348 o.157 

l.OOO 

0.348 

l.OOO 

¡ lncomplete Sample 

& 


West Coast 

õ= 0.0233 AREAeo I;? 

(R2=.la , se=0'148)--' 

I n land Marlborougþ/Canterbury 

õ = O'9ó4AREAo'88 

(i2=o're , se =Q'lQP| 

Mackenzie, lnland Otago, Southland 

õ=o.ootgAREA:to Ill, 

(.R2= o.rs, se =o.r4ó)"- 

East Coast 

õ = t. n x lo-ten¡Ätt¡nmAlN3'o 

(n'= 'ra , se=0.il7) 

Nole: R= Multiplle correlotion coefficient 

se= $1q.¿.rd error of estimote for 

logorithms 


Fþu]|'4.TLogarithmicresidualerrorsforfinalsouthlslandregionalequations' 

65

I 

++ 

++ 

* 

E 

4.6 Analysis of North lsland data 

4.6.1 Preliminary analysis of data 

10 100 

[otchmenf Areo ( kmz) 

Figure 4.8 O vs AREA, North lsland catchments. 

a : 1.87 AREA o sr 

(R': = 0.69, se = 0.442) 

44 

As with section 4.5 the object of this section is to devise 

estimators of Q ttrat are better than Equation +.+ Uy using 

variables besides AREA, and by choosìng a number of re_ 

grons. 

Stepwise regression results 

_ 

for all 97 stations are tab_ 

ulated in Table 4.8. The best fit equation obtained is 

a = 1.37 x l0-'AREA1 t3l2z4t,EeMARAIN¡ o? 

(R'? = 0.81, se = 0.348) 

45 

Examinati 

errors from 

which berter 

followed is s 

tion of residual 

it ïå'å:ì#i 

and. 

4.6.2 Development of trial regional estimators 

tween MARAIN and 1224 (0.30 compared with 0.75). phys_ 

ically this may be a reflection of the sparseness Water òf & the soil net_ technical publication no. 20 (1982) 

66

Table 4.8. Stepwise regressions for all North lsland data. 

No. Var. Name 

Coef 

br 

se 

of coef 

R2 

se 

est 

Const 

log a 

Multiplier 

a 

1 

2 

AREA 

AREA 

t224 

AREA 

t224 

MARAIN 

o.81 

0.84 

2.33 

o.83 

1.89 

1.O7 

o.o56 

0.048 

o.377 

o.045 

o.368 

o.270 

14.5 

17.7 

6.2 

18.6 

5.1 

4.O 

0.829 

o.882 

o.900 

o.687 

o.778 

o.810 

o.442 

o.372 

o.348 

0.271 1 .87 

-4.263 5.46 x 1O-õ 

- 6.862 1 .37 x 10' 

Table 4.9 Stepwise regressions for first trial North lsland regions 

Region 


Variables Name 

Coef 

b' 

se 

of coef 

R2 

se 

est 

Const Mult¡plier 

loga a 

Non-Pumice 

(84 catchments) 

1 

2 

AREA 

AREA 

t224 

AREA 

t224 

MARAIN 

o.74 0.049 

o.77 0.037 

2.13 0.271 

o.76 0.034 

1.77 0.262 

0.78 0. 1 91 

'15.2 0.861 0.74 0.341 

20.7 0.925 0.86 0.257 

7.9 

22.4 0.939 0.88 0.234 

6.8 

4.1 

0.507 3.21 

- 3.63 2.33 x 1O-a 

- 5.49 3.24 x 1O-o 

Pumice 

( 1 2 catchments) 

1 

2 

AREA 

AREA 

t224 

AREA 

t224 

MARAIN 

o.84 0.22 

0.90 0.11 

3.88 0.64 

o.79 0.o9 

2.41 0.73 

1.74 0.64 

3.8 0.765 

8.5 0.958 

6.1 

8.9 0.978 

3.3 

2.7 

o.59 0.359 -O.310 0.490 

O.92 0.168 -7.806 1.56 x 1O-8 

0.96 O.142 - 10.36 4.39 x 1Oi1 

of which catchments lay within it, presented difficulty. 

Several catchments (for example 9101, Waitoa; 21803, 

Mohaka) have their headwaters in this pumice country, but 

most of their areas lie outside the pumice region. Others 

(e.g., 15410, Whirinaki) are mainly pumice but have a substantial 

area outside the region. In still other catchments 

(those lying mainly on the slope of the central North Island 

volcanoes) the mantle of soil over rock is minimal and its 

hydrological influences were not known. After several 

trials, the pumice region was defined as comprehending 

three of the hydrological regions set out by Toebes and 

Palmer (1969). These were Taupo Pumice, Taupo Rhyolite, 

and East Raetihi which made up a discontinuous region including 

a total of 13 catchments, seven tributary to the 

Waikato River, four draining to the Bay of Plenty, and two 

tributary to the Wanganui River. Closer inspection of the 

data for these l3 catchments showed that 11432108 (Purukohukohu) 

was a distinct outlier in having the smallest 

catchment area and the least Q (by almost two orders of 

magnitude) for all 97 North Island catchments. For this 

reason, and because it was ephemeral, it was excluded from 

subsequent analyses. 

Taking two regions, pumice and non-pumice, trial regressions 

were undertaken. Stepwise results are given in 

Table 4.9 and the distribution of residual errors for the best 

fit equations is shown in Figure 4.9. This figure shows that 

within the pumice region the residuals seem randomly distributed 

with generally low values, but the remainder of the 

island contains very large residuals, some exceeding I 0.50. 

The southern part of the island including tributary catchments 

to the lower Rangitikei, all the Manawatu, Wairarapa 

and Wellington area catchments, have, with one small 

exception, positive residuals meaning that Qo5, for this area 

is underestimated. Similarly, positive residuals occur over 

much of the Northland and Auckland areas. The fact that 

tropical cyclone events tend to produce flooding in this 

area, and also the Coromandel and East Cape areas, may 

be a tentative basis for a region including these areas. Negative 

residual values occur in the central part of the island 

outside the pumice region. This suggests a division of the 


island into four regions, and if the central part is divided 

between east and west coasts, into five regions, whose tentative 

boundaries are drawn dashed on Figure 4.9. These 

five regions are taken as a basis for further study. 

A number of trials were undertaken with these regions to 

determine where boundaries should be placed. Catchments 

which appeared as outliers were checked, both for the correctness 

of data and for any features of the catchment 

which might influence flood peaks. Seven of the larger residuals 

could be attributed to special conditions of the catchment 

and were excluded from the final analysis. 

These were as follows: 

(i) C¡tchments with large ponding effects 

Serious over-estimates were made for Q for 9l0l 

(Waitoa) and 9108 (Piako). Two possible causes for 

this are, firslly that the headwaters for these catchments 

lie in the pumice region, and secondly that the 

catchments have amongst the lowest channel slopes of 

all the North Island catchments, and have a very flat 

topography with peaty soils and swamps in the lower 

reaches. This second factor also causes attenuation of 

flood hydrographs. Thus these two catchments were 

excluded frorn further analysis. Others having large 

negative residuals in Figure 4.9 were 33307 (Wanganui 

at Headwaters) and 1143428 (Ohote); these also were 

excluded on the basis that large parts of the catchments 

are swamps. 

(ii) C¡tchment in l¡mestone area 

Catchment 40703 (Mangakowhai), which drains Waitomo 

limestone country, also had a large negative residual 

and was subsequently excluded on the basis that 

the catchment topographic area may not be the true 

catchment area. 

(iii) Catchment with short record 

Catchment 39508 (Manganui) had only four years of 

record. It was excluded on the basis that the estimate 

of Q may have excessive sampling error. 

67

Non Pumice = 

õ = 3-24xto'6 AREA'7ó lr,o''" MARA|No'78 

( R2= 9.g3,- se= 0.228 I 

Pumice 

[ = a.39 ^ 

ro ll AREATe \r1'^' MARATNI'24 

( R'= O'9ó , se 

= O.lO5 ) 

Figure 4.9 Trial North lsland regions. 

68 


ln the trials undertaken for the provisional regions 

shown dashed in Figure 4.9 both 13901 (Mangawhai) and 

15534 (Wairere) showed as outliers in the regions to which 

they were initially assigned. As they fitted best into the 

adjacent pumice region, they were placed there for the final 

analysis. This required extension of the pumice region into 

the coastal Bay of Plenty area; in terms of the hydrological 

regions of Toebes and Palmer (1969) it includes Tauranga 

and Opotiki regions. This assignment is tentative because 

the soils in these catchments are not pumice to the extent of 

others in the Rotorua/Taupo area. Their better fit with the 

pumice region could be the result of inaccurate rainfall intensity 

statistics. 

4.6.3 Final equations for North lsland 

Table 4.1O Stepwise regressions for final North lsland regions. 

After a number of trials, final equations were developed 

for the regions shown in Figure 4.10. The stepwise regression 

results are givern in Table 4. 10. In all but one case the 

best fit equation includes AREA and one or two of the 

rainfall statistics. The exception is the Manawatu/WairarapalWellington 

region were the equation including AREA, 

1224 and FOREST provides a very good fit. However, 

when MARAIN is substituted for FOREST in the equation 

it is almost as good; this is preferred as it should provide a 

more robust estimator. The table shows that for every region 

the accuracy of estimate can be improved by including 

a rainfall statistic in addition to AREA, and also, that other 

catchment parameters with the possible exception of FOR- 

EST in one region are not of importance. It is possible that 

FOREST does not directly influence flood size; rather it 

does so indirectly to the extent that correlations occur between 

FOREST and the rainfall statistics (Table 4.7). For 

the Manawatu/Wairarapa/Vr'ellington region where FOR- 

EST was most dominant in these regional equations, the 

Region 

Northland/ 

Coromandel/ 

East Cape 

{21 catchments} 

Pumice Land 


East Coast 

(1 1 catchments) 

Manawatu/ 

Wairarapa/ 

Wellington 


West Coast 

(25 catchments) 


Varìables Name 

1 

2 

1 

2 

1 

2 

1 

2 

AREA 

AREA 

MARAIN 

AREA 

MARAIN 

ELEV 

AREA 

MARAIN 

ELEV 

LENGTH 

AREA 

AREA 

t224 

AREA 

t224 

MARAIN 

AREA 

t224 

MARAIN 

FOREST 

AREA 

AREA 

t224 

AREA 

AREA 

FOREST 

AREA 

FOREST 

t224 

AREA 

t224 

MARAIN 

AREA 

AREA 

t224 

AREA 

t224 

MARAIN 

AREA 

t224 

MARAIN 

FOREST 

Coef 

bl 

se 

of coef 

R2 

SE 

est 

o.70 0.06 10.8+ 0.927 0.86 0.237 

0.64 0.o3 19.5* 0.983 0.97 0.1 19 

2.33 0.31 7.6* 

0.62 0.o3 18.7* 0.986 0.97 0.1 10 

2.O1 0.33 6.2* 

o.22 0.11 2.O 

o.84 0.16 5.2* 0.988 0.98 0.107 

2.O3 0.32 6.4* 

o.21 0.11 2.O 

-o.39 0.28 -1.4 

Const Multipl¡er 

loga a 

0.807 6.42 

-6.66 2.18 x 10'+ 

- 6.OB 8.24 x 'l O-7 

-6.06 8.71 x 1O' 

0.67 0.12 5.5* o.a44 0.71 0.348 0.0933 1.24 

0.83 0.06 13.5* O.971 O.94 O.161 -7.94 1.15x1O-8 

4.O2 0.60 6.7* 

o.74 o.06 12.2* 0.984 O.97 Oi2A - 10.51 3.Og x 'l O{1 + 

2.54 o.72 3.5* 

1.75 0.64 2.7 * 

O.88 O.O9 9.9* 0.989 O.98 O.111 -11.94 1.15x1O{'? 

3.16 0.70 4.5* 

1.80 0.56 3.2* 

-o.17 0.o9 -2.O 

o.80 0.o8 10.6* 

0.76 0.o3 27.4* 

2.24 0.29 7.8* 

0.90 0.1 3 6.9* 

o.72 

0.46 

o.82 

1.53 

o.94 

0.06 12.2* 

o.o5 8.9- 

o.74 0.o4 16.7* 

o.34 0.o5 6.7* 

1.22 0.33 3.7* 

o.o5 15.8* 

o.19 4.O* 

o.39 4.9* 

o.85 0.o8 1 1.3* 

o.az 0.o5 16.7* 

2.18 0.38 5.8* 

o.82 0.o5 17.7* 

1.67 0.44 3.8* 

0.78 0.39 1.9 

o.79 0.o5 16.1 * 

1.6'l O.42 3.8* 

0.80 0.37 2.1 

0.1 1 0.06 1.8 

0.963 0.93 0.227 

0.996 0.99 0.082 

o.858 0.74 0.341 

0.978 0.96 0.144 

0.988 0.98 0.107 

0.982 0.96 0.1 18 

o.974 0.95 0.157 

0.977 0.96 0.1 50 

0.296 1.98 

-4.O5 8.84 x 10{ + 

0.232 1.70 

o.1 58 1.44 

-2.O5 8.99 x 1O-" 

-5.51 3.12x10-6 + 

0.920 0.85 0.258 0j82 1.52 

0.969 O.94 O.1 67 - 3.83 1 .48 x 1O-1 + 

- 5.41 3.87 x 10-6 

-5.51 3.13x10-6 

* significant at 5olo level 

+ preferred equation 


69

Northlond f C"roôndel f Eost Cope 

ö = 2.18 x lo z tRtlo'ó4 MARAIN2'33 

( R'= O'97 , se 

= O.ll9 ) 

West Coost 

_Á 

Q = l.48xlO ' 

( R2- o.94 , 

AREÁ t' \r1''" 

se 

= 0'167 ) 

Eost Coost 

õ g.g4 7ó 

= x lo-saREAo 

\rl'ro 

Pumice 

( R2= O.99 , se = 0.082 ) 

õ = 3.o9 x td't' IREA.''o lrrl- t', 

MARAT N 

( R'= O.97 , se = O-nB ) 

Monowotu /Woiroropo / Wellington 

Q = s.ts * ldo t" RREA' Irr''t MARAIN o'e1 

(R2=9.96 , se=O.ll8 ) 

Figure Water 4.10 & soil Final technical North publication lsland regions. no. 20 (1982) 

70

correlations between (logs oÐ FOREST and 1224, and 

FOREST and MARAIN were 0.90 and 0.65 respectively; 

this was one region where estimates of l2?A were suspected 

to be unreliable. 

The preferred equations of Table 4.10 are shown in Figure 

4.10 with their appropriate regions, and also the residual 

errors for logarithms. In general the equations seem 

more reliable in the north and east of the island, a situation 

also noted in the South Island. The distribution ofresiduals 

generally appears reasonably random in space. The region 

for the West Coast includes a number of catchments tributary 

to the Wanganui River and a number originating on 

the slopes of the central North Island volcanoes. Many of 

the larger residuals for the island are clustered here, presumably 

because of the variety of soil types, including pumice, 

and the sparse coverage of rainfall intensity measurements. 

The equations for the East Coast and West Coast regions 

suggest that they should be combined into one, but 

doing so resulted in regional biases. Hence the separate regions 

should be maintained. 

4.7 Discussion of results 

The equations derived in sections 4.5 and 4.6 are intended 

for application to rural catchments where flood 

storage is not excessive or where other dampening effects 

are not dominant. All the nine regional equations use catchment 

area, and all but one use area and one or two of the 

rainfall statistics; other physical catchment characteristics 

used in this study appear to be of little consequence. This is 

an important finding, since results obtained in overseas 

countries (see section 4.8) have suggested that these other 

physical characteristics are relatively important. The 

dominance of rainfall statistics is possibly due to the 

generally steep nature of New Zealand catchments (see section 

4.8). The two sets of rainfall statistics considered in the 

study have a large range of values; both cover more than 

one order of magnitude in the South Island, though the 

range is less in the North Island. 

Since this study was completed, an updated analysis of 

rainfall intensity data has become available (Tomlinson 

1980; Coulter and Hessell 1980). Tomlinson used 16000 

years of data from 940 manual daily raingauges and 3500 

years from 180 recording raingauges. Comparison of revised 

1224 estimates with those from Robertson (1963) for a 

sample of 87 stations did not reveal statistically significant 

differences. This suggested that the revised estimates may 

also be used for estimating 1224. Sirce the revision used 

more than twice the number of stations, more accurate estimates 

of 1224 lor individual catchments should be possible. 

For convenience, revised 1224 estimates for the 94O daily 

gauges used by Tomlinson are included as Appendix D. 

- The revised intensity data were also mapped by Tomlinson. 

However, in high altitude areas, especially along the 

Southern Alps, use of the mapped values is not recommended. 

In mapping, rainfall is assumed to increase with 

altitude, This increase was not allowed for when catchment 

estimates for l2A were made, so the maps will give catchment 

estimates of 1224 greater than the estimates used in 

deriving the equations for Q. Thus inflated Q estimates 

may result from 

The 2-year rec 

uration intensitY 

estimated from 

auges was used 

principally because of the better national coverage of daily 

iead manual gauges for observing this duration rainfall 

compared with shorter duration rainfall statistics estimated 

from automatic rainfall recorder data. 

As noted in section 4.4, estimates of catchment mean annual 

rainfall have a low accuracy for many South Island 

and this is possibly why inclusion of mean annual rainfall 

improves the estimate in three of the five North Island regional 

equations. 

Little can be saicl of the physical significance of the exponents 

for the regional equations. Whilst values of the intensity 

exponent around unity for two of the South Island 

regions might have some physical interpretation, the meaning 

of exponents of the rainfall statistics which exceed 2.0 is 

unclear, even though their statistical significance is undoubted. 

Obviousl),, in using the equations, particular care 

must be given to the estimation of rainfall statistics, because 

estimates outside of the range of the values of the 

sample used in developing the equations could result in 

severe errors in estimates of Q. Tables 4.1 and 4.2 are a 

guide to typical valtues of the rainfall statistics. 

Where a catchment lies near a regional boundary and 

each regional equation gives different estimates, the precise 

location ofthe boundary is bound to create difficulties. For 

some regions, dominant flood-producing weather patterns 

are thought to apply, and a decision about which region a 

catchment fits into could be based on the weather conditions 

which are believed to produce the most flooding. 

An example is a number of Marlborough and Canterbury 

rivers in the Inland region, where the flood-producing 

weather conditions are possibly southerly. Their headwaters 

near the divide flood in nor'westerly weather condi 

tions and fit in the West Coast region. The rivers flow 

through the East Coast region where flood-producing weather 

patterns are thought to be easterly. 

In the case of the North Island Pumice region, catchments 

have been included where pumice was thought to 

have a dominant influence on the flood hydrology, but two 

coastal Bay of Plenty catchments were tentatively included 

here because this was where they fitted best, even although 

pumice is not dominant on these small catchments. rÙVithin 

the Pumice region, there appears to be a gradation in the effect 

of the pumice. For instance, pumice lies to great depths 

on the Kaingaroa Plateau within which much of the catchment 

of the Rangitaiki River lies. The 28 years of record for 

this river at Murupara (AREA : ll84km', Station 

15408), but which was not used because it exceeds 

ll00 km', gives_a Qous : 41.6 m'/s but the estimate from 

the equation is Q"rt = 202 m3/s, representing a residual error 

of - 0.69. Clearly, the dampening effects of pumice are 

severe in this case. 

The annual flood regions delineated in this chapter are' 

in general, very similar to the flood frequency regions defined 

in Chapter 3. An exception to this is in the eastern 

area of the South Island (see Figure 4.7). From a design 

characteristics, on the other hand, is also concerned with 

the coefficients of variation and skewness of the flood record, 

and these can be regarded as the slopes and curvatures 

respectively of the individual dimensionless-magni- 

Therefore it was not unexof 

the flood frequencY chargions 

that differed in Places 

from the set deveioped for estimating Q. 

4.8 Compar¡son with other results 

Similar equations 

given in Table 4.ll l. 

favourably in terms 

ent of determination 

this needs to be balanced against the use of a relatively 

small range of catchment areas (0'2 to ll00 km'); poorer 

fits may be obtained if larger catchments are used' The 

other notable feature of Table 4'll is the range of expon- 

estimated with reasonable accuracy for the North Island, ents for AREA. The values tend to be less than the values 


7l

Table 4.11 Comparable equations for other countries, 

Est¡mat¡ng eqn R2 SC 

est 

Region 

Area Range (km,) 

Min. Max. 

Reference 

o 

o 

= 0.56 1 AREA 8s 

: 0.0765 AREAi o€ S1O85o s' o.841 

o.922 

o.1 94 

o.142 

New England 

New England 

: 2.42 AREA ss 

Texas and Sthn 

= o.o589 AREA 68110241 New Mexico 

50 

250OO Benson ('l 962b) 

90000 Benson (1 964) 

O :a AREAb 

0.267

Pooled 

Pooled 

Poo led 

Cy = 0.98 

Cy = O'óó 

Cv = o'3ó 

Figure Water 4.11 & soil Distr¡but¡on technical publication of Cv of annual no. 20 maxima (1982) for South lsland stations' 

73

Poo led 

cv 

Pooled 

o.40 

F¡guro 4.12 D¡stfibut¡on 

Water of & cv soil of technical annuar maxima publication for North no. 20 rsrand (1982) stat¡ons. 

74

Draper and Smith 1966). ln our case, the true value of the 

dependent variable Qnu. is not known with certainty. It is 

subject to time sampling error and can only be estimated 

from the period of flow record available. The relative magnitudes 

of time sampling errors are indicated by the pooled 

Cy values in Figures 4.8 and 4.12. 

A second difficulty is that within a region some adjacent 

catchments may be subject to the same storms of large areal 

extent and a pair of series of annual maxima for such catchments 

is likely to be cross correlated: errors in estimates of 

Qo6, will therefore not be random, but will also be correlated. 

In this situation regression analysis is still permissible, 

but estimation of the prediction error is more complex. 

An analysis of the situation is provided by Matalas 

and Gilroy (1968), and some practical examples are given 

by Hardison (1971). 

When a regional regression of log'o Q is calculated on a 

set of m catchment parameters, the standard deviation of 

the log,o Q about the regression expressed in log,o Q units 

is denoted by Sp. lf these deviations of the log,o Q from the 

regression are normally distributed, then the coefficient of 

variation of the untransformed Q about the regression, C¡, 

is given by 

Cä = .*p (2.303 SR)' - I 47 

When Q is estimated from a flood record that is N years 

long, and the coeffìcient of variation of the annual maxima 

is denoted Cy, the estimate of Q will differ from the population 

value (that would be obtained from a very long record) 

with a coel'ficient of variation of CylN.l. 

ci : ci /N" 

When Q is predicted using the regional regression it will As the quantity Nu could provide a useful guide for using 

differ from the population value, and the coefficient ofvar- the regression equations, it is evaluated for each of the reiation 

of the difference averaged over k sites, denoted by gions together with Cp for each region (Table 4.12). Esti- 

Table 4.12 Prediction errors and equivalent lengths of record. 

Cp, is calculated from Equation 4.8, which is derived from 

Hardison (1971). 

c'p : ch(t - + - 

tf+-, ) + ci (2q - r)/N6..... 4.8 

where p is the average cross-correlation between annual 

maxima series from pairs oi catchments in the region, and 

Nç is the average length of record. When there are many 

uncorrelated records such that sampling errors tend to cancel, 

and the average record is short (k large, p small, N6 

small), then Cþ can be less than CilNc, so rhat a better 

estimate is obtained from the regression at a site than from 

the record at a site. 

Note that Cp is an average prediction error, and will 

over-estimate errors on predictions for ungauged catchments 

whose parameters are near the mean value used in 

calculating the regression, and conversely. In New Zealand, 

no estimates ofthe interstation correlation coefficient q are 

available, but typical values may reasonably be expected 

within the range 0.2 to 0.8. Three values of p (0.2, 0.5 and 

0.8), were therefore used in evaluating Equation 4.8. 

Given the coefficient of variation of the prediction error 

Cp, ân estimate can be made of the length of record necessary 

to estimate Q with the same degree of accuracy as is 

given by the regression equation. If Nu is this equivalent 

length of record, anLd the prediction error is expressed as a 

percentage, then 

49 

Region S¡ 

(for regression 

of logarithms) 

Cvkm 

(no. of (no. of 

stations) regression 

variables) 

Nca 

(av length 

record) 

cR cP 

(Eqn 4.7) (Eqn 4.8) 

l"l,\ l"/"1 

N, Typical 

(Eqn 4.9) Nu 

(yrs) 

(yrs) 

Northland/ 

Coromandel/ 

East Cape 

Pumice 

East Coast Nl 

Wairarapai 

Manawatu/ 

Wellington 

West Coast Nl 

West Coast Sl 

o.119 

o.128 

0.082 

o.118 

o.1 67 

0.148 

o.54 

o.54 

o.54 

o.40 

o.40 

0.36 

21 

14 

t1 

19 

25 

t9 

1 1.6 

12.O 

13.O 

13.5 

110 

9.4 

o.2 

o.5 

0.8 

o.2 

o.5 

o.8 

o.2 

0.5 

o.8 

o.2 

o.5 

o.8 

o.2 

o.5 

o.8 

o-2 

0.5 

o.8 

27.9 

21 .9 

27.9 

29.9 

29.9 

29.9 

1 9.1 

1 9.1 

1 9.1 

27.7 

27.7 

27.7 

39.9 

39.9 

39.9 

35.O 

35.O 

3 5.O 

27.5 

30.1 

32.5 

33.7 

35.8 

37.7 

19.4 

22.6 

25.4 

30.0 

31.1 

32.3 

41.6 

42.6 

43.6 

37.1 

38.1 

39.3 

39 

3.2 

2.3 

2.6 

2.3 

2.1 

7.8 

5.7 

4.5 

1.8 

1.7 

1.5 

o.9 

o.9 

0.9 

0.9 

o9 

o.8 

lnland 

Marlborough/ 

Canterbury 

East Coast Sl 

Mackenzie/ 

lnland Otago/ 

Southland 

o.1 09 

o.1 05 

o.146 

0.66 

o.98 

o.66 

13 

1'l 

'I 5 

18.0 0.2 

0.5 

o.8 

8.4 0.2 

o.5 

o.8 

89 02 

o5 

o8 

25.O 

25.O 

25.O 

24.5 

24.5 

24.5 

34.5 

34.5 

34.5 

24.4 

27.2 

29.8 

12.5 

29.O 

39.1 

34.6 

38.6 

42.2 

7.3 

5.9 

4.9 

61.6 

11 .4 

6.3 

3.7 

2.9 

2.4 


75

mates of Cp typically range between 2OVo and 44go for different 

regions. They are generally somewhat greater than 

Cp, and are generally not greatly influenced by the values 

assumed for p. 

Values estimated for Nu given in the right-hand column 

of Table 4.12 range from one year for the West Coast of 

both islands to about seven years for the East Coast of the 

South Island. Such results are in accord with intuition. 

Where the Cy is low_(as on the West Coast) a reasonably accurate 

estimate of Qo5, may be obtained from a relatively 

short period of rec 

on 

is of limited valu 

is 

greater, a longer 

to 

estimate Qo6. with 

on 

equation estimate, and the regression equations may be of 

greater utility. 

tühere only a short period of record is available for a site 

for which a design flood estimate is required, a decision 

var (Q) 

weights for combin 

in a best estimate. If 

its variance can be e 

_l 

var (Qo6.) 

I 

var (Q.,x) 

4t0 

4.11 Summary 

_ The country was divided into nine regions lbr estimating 

Q using regression analysis. The physical justification lor 

these regions was discussed. Apart from the south of the 

South lsland, the study used a good distribution ol catchments, 

and the range of values covered for Q, area, and 

other parameters was very large. 

The results demonstated that generally catchment area 

and the rainfall parameters considered are sufficient to predict 

large differences in flood magnitudes within the nine 

regions delineated and that the other physical characteristics 

used for the catchments do not improve that prediction. 

Apart from the Southern Alps of the South lsland, 

the mean annual rainfall can be estimated with reasonable 

confidence from isohyetal maps. Rainfall intensities were 

estimated from data available in Robertson's (1963) publication. 

Updated intensity data are now available (Tomlinson 

1980; Coulter and Hessell 1980) and, with more extensive 

intensity information, better estimation equations are 

anticipated. 

Preliminary results of the study enabled identification ol 

catchments which did not fit into regional trends. Where 

reasons for anomalies could be identified, the catchments 

were excluded from the final analyses since their inclusion 

could have led to biased results. About 790 of catchments 

were in this category. Designers should be aware of factors 

likely to modify flood peaks and if in doubt seek specialisr 

advice. 

16 


5 Application 

5.1 lntroduction 

This chapter collates the applicable results and findings 

from the preceding two chapters and formulates them into 

what is subsequently reierred to as the Regional Flood Estimation 

(RFE) method. Rules for the applicability of the 

RFE method are given, a design strategy for estimating the 

T-year flood peak is suggested and a number of examples 

are given which demonstrate the use of the method. 

The RFE method is intended as a procedure to be used 

for estimating design flood magnitude in situations where 

insufficient flood records are available for conventional 

fiequency analysis. It is one of several design flood estimation 

methods in such situations and other methods should 

be used and compared with it. It has been derived from 

tlood records by: 

(¡) defining regional flood frequency curves of Q1/Q vs 

T, where Q1 is a design flood with return period T and 

Q is the mean annual flood; and 

(ii) developing a set of equations for estimating Q based 

on catchment area and measures of rainfall. 

A comparison with Technical Memorandum No' 6l 

(TM 6l) is reported in Appendix E. 

5.2 Applicability 

The applicability of the RFE method is necessarily constrained 

by the restrictions that were applied to the data 

used in deriving the method. The following constraints 

therefore apply. 

The method should only be used for rural catchments. 

The method should not be applied to catchments in 

which snowmelt, glaciers, springs, lake storage or 

ponding significantly affect the flood peak characteristics. 

The ranges of catchment areas for which the regional 

flood frequency curves and the regional mean annual 

flood equations were derived are listed in Table 5.1. 

These are a guide for the size of catchment to which 

the method should be applied. 

Because of the subjective and rather broad definition of 

regional boundaries, it is suggested that, for catchments 

near boundaries, floöd frequency curves and annual flood 

equations for the regions either side of the lines.should be 

used in estimating Q1/Q and Q respectively. As in a design 

situation where different methods yield different estimates, 

the different Q1/Q and Q estimates then need to be 'compared', 

i.e., the merits of each should be assessed and the 

choice of an estimate should be made after a rationalisation 

of the relevant facts. Alternatively, a belief probability can 

be attached to each estimate and their expectation calculated, 

which is akin to taking a weighted average of the estimates. 

5.3 Design Strategy 

5.3.1 General 

The strategy for the use of the RFE method in design is 

dependent on two main factors: N, the length in years of 

the flood record if a record is available, and T, the design 

return period. The influence of these factors on the two 

parts of the RFE method (i.e. the regional mean annual 

flood equations and the regional flood frequency curves) is 

explained in the two following sections and summarised in 

Figure 5.1 . 

5.3.2 Estimat¡on of O 

(¡) N(Nu 

Where there is a flood record and its length N is less than 

Nu, which is the 

is equivalent to the 

prãcision of the r 

on (see Table 4. l2)' 

the mean annual 

imated from the regional 

equation and the available flood record. In applying 

the equation it is particularly important to estimate values 

for the rainfall variables 1224 and MARAIN in a similar 

manner and from the same data base as used in the equation's 

derivation. Specific points to note in estimating 

values for 1224 and MARAIN are outlined below. 

1224 Estimates ol the 1224 rainfall intensity statistic used 

in deriving the equations for Q were obtained by taking the 

arithmetic mean of the 2-year 24-hour data listed by Robertson 

(1963, Table 9) for rainfall stations located within, 

or near to, the catchment concerned. Estirrates can be 

made from the tabular results (Appendix D) obtained by 

Tomlinson (1980) in a recent revision of the frequency an- 

Table 5.1 Ranges of catchment areas used to derive regional flood frequency curves and mean annual 

flood equations. 

Flood frequency 

reglon 

(Fis. 3.6, 3.7) 

Combined N.l. 

West Coast 

Central Bay of PlentY 

N.l. East Coast 

Central Hawke's Bay 

S.l. West Coast 

S.l. East Coast 

South Canterbury 

Otagoi Southland 

Catchment area 

(km2) 

(Table 3.2) 

fntn max 

2.5 6643 

28.2 2893 

171 2370 

24.3 2424 

48 6350 

74.6 3430 

22.4 899) 

lo9 

) 

18321 

Mean annual flood 

feglon 

(Fig.4 7,4.1O) 

Northland/Coromandel/ 

East Cape 

West Coast 

Manawatu/WairaraPa/ 

Wellington 

Pumice 

Northland/Coromandel/ 

East Cape 

East Coast 

West Coast 

lnland Marlborough/ 

Canterbury 

East Coast 

(Mackenzie, lnland 

(Otago, Southland 

(East Coast 


Catchment area 

(km') 

(Tables 4.1, 4.2) 

min max 

o4 640 

3.1 1075 

9.4 734 

2.6 534 

o.4 640 

o5 

997 

4.O 998 

o.2 1070 

2.2 464 

36.8 1088 

2.2 464

-J 

æ 

'll 

o Eo 

!¡ 

Assemble llood prák dåta 

lncludlng âll hletoslcat 

flood ln?ornatlon. 

lrha¿ lr th. I.ngÈh N of th. evallsblr flood rscord? 

.õ 

-3 

J 

! 

o 

{ 

o t 

o 

f 

o*æ 

o 

CL 

o 

2. 

c¡ f 

Øñ 

o 

@ 

c 

2. 

f 

(o 

è 

o 

Ðo 

e. 

o 

to, 

f! 

o 

cl 

m 

ø 

d. 

:t 

0t 

4. 

o 

f 

o ê 

, oo. 

Apply the Generallsed Curve 

Esttnato0arauelghtad 

o? tho âstlnãtls fron3 

I Calculating th€ n€an ol 

avall¿ble annual serleo ( 

graphically interpolatlng 

0¡.¡¡ fron an histo¡ical 

:cri ee ) 

2 Applylng the roglonal 

squation 

Ooes I 

exc.ed th! llnlt 

of th6 Rsglonal 

Cu¡ve? 

obtaln 0t snd 

det€rñiñs the stãndg¡d 

arror ol oltlnata 

NsNu 

Apply the RBglonåI Cu¡ve 

N>Nu 

E¡tlnate D ¡¡ th¡ arlthfr.tlc 

taån o? th¡ annual ae¡L¡s 

fo¡m e frequency anelysia ui 

tuo-Farsm6tsr distributioñs 

except for sitEÊ j.n rhe South 

CanteEbuDy snd 8ay of Plsnty 

flood l'¡6au€ncy rBgioñs. uhers 

I. 

hl6torlca¡ ftood p.ak 

infq¡ñatlon 6våilablo 

Is 

N ¿20 

o! 

1>100 

? 

EeÈlnate õ uy grephic;Ily 

lnt!¡pol3t¡ng Ê¡.¡¡ frm 

th. historlcal s.¡l3s 

Perforn a frequgñcy enalysis 

ulth tuo and th¡3e-paranrtsF 

di BtriSuti,oñ3 

ConpBr€ ths frsqu6ncy analyale rs6ult! uith ths rstinatr 

obtafn€d from the R€gional Curv¡ (o¡ the Gener€lla6d Curva 

\¡hen I excs€ds the reglonaÌ curve llnlt) ônd obtðin 

s uelghted flood p.!k ..tlnatr' .Epeclslly ll I > 2N 


alysis of the country's rainfall intensity data. As this revision 

used data for twice the number of stations used by 

Robertson, more accurate estimates of 1024 for individual 

catchments should be possible using Tomlinson's results. 

Note that an areal reduction factor should not be applied 

to an 1224 estimate. Further, the rainfall stations used in 

the estimation of 1224 should not necessarily be the nearest 

but should be the ones that record weather patterns that are 

of most relevance to the catchment. 

In the Southern Alps, Tomlinson's (1980) maps of rainfall 

intensity assume that the intensity increases with altitude. 

This increase was not considered in the estimates of 

1224 used to obtain the regional mean annual flood equations. 

Thus the use of the estimates of rainfall intensity in 

the equations may lead to overestimates of Q for catchments 

running into the Southern Alps. Therefore, when 

calculating 1224, poinr estimates of intensity should be 

averaged for the raingauges which receive rainfall typical of 

that for the middle and lower parts of the catchment. 

MARAIN The mean annual rainfall for a catchment may 

be estimated directly from rainfall records for stations 

within, or near to, the catchment. Where only short rainfall 

records exist, or where there are none, estimates of 

MARAIN should be obtained from the l:500 000 isohyetal 

maps of l94l-1970 annual rainfall normals published by 

the NZ Meteorological Service. 

When there is at least one year of flood record available, 

we suggest that both the available record and the regional 

equation be used to obtain separate estimates of Q. These 

estimates can then be combined to form a weighted average 

estimate of Q , with the weighting of the Q value estimated 

from the record being based on the length ofthe record relative 

to Nr. Hence, for example, if N : 3 and N, : 4' the 

weighting factors for the estimates taken from the record 

and regional equation should be 

3/'7 lì.e. 

(ii) N > Nu 

NN 

N+Nu 

N*N, 

When the flood record length exceeds N' Q may be estimated 

as the arithmetic mean of the annual series. It could 

also be estimated f¡om a partial duration series (NERC 

1975, pp. 185-213) when N is less than l0 years. In the case 

where an outlier or historical flood peak Q."* occurs in an 

annual series such that Q*"*/Q.e¿ ) 3, it is suggested that 

Q be estimated graphically from a probability plot of the 

annual series as the flood peak with return period T : 2.33 

years. 

more flexible frequency curves, it was found in the evaluation 

tests (Appendix A) that a two-parameter distribution 

gives a good approximation to a three-parameter one up to 

T : 100 and that it can give more sensible results, even 

though it may not produce quite as good a fit to the annual 

senes. 

(iii) N > 20 

V/ith a flood record of 20 or more years in length, both 

two- and three-parameter distributions should be fitted to 

tbe annual series for the estimation of Qr ' A visual inspection 

of the goodness-of-fit of the distributions to the series 

should then be made and a distribution chosen for estimating 

Qr . When it is difficult to decide between two or more 

fitted distributions, the Q.¡ estimate should be determined 

by averaging the estimates given by these distributions. 

In applying frequency analysis methods to estimate a design 

flood peak Qt, care should be taken to ensure that 

they are not grossly extrapolated. For example, if N < 20 

and the two-parameter EVI distribution is fitted to the annual 

series, its extrapolation past T : 100 years for catchments 

in some of the eastern regions, e.g' South Canterbury, 

may lead to an under-estimation of Q1. 

It is recommended that the fitted distribution should not 

be extrapolated beyond a return period T : 5N' This limit 

is less stringent than those often recommended in other 

tests (e.g. a limit of T : 2N is suggested (ICE 1975) for the 

NERC (1975) study) and extrapolation beyond it is unwise 

on the basis of present evidence. The safest course of action 

when T exceeds the extrapolation limit is to use the regional 

curve, or the appropriate generalised curve when T exceeds 

the upper limit of the regional curve. 

Finally, when the record length N is sufficiently great to 

warrant the performing of a frequency analysis, the resulting 

Q1 estimates should be compared with that using the regional 

(or generalised) curve, with Q being calculated from 

the annual series. A, decision must subsequently be made as 

to which estimate to accept for design. This may involve 

taking a weighted average of the estimate from the frequency 

analyses of the site data and the estimate obtained 

using the regional curve, and this procedure is suggested 

when T > 2N. In making this decision on the final Q1 

value it should be lemembered that variations are inherent 

in all flood records, especially small ones, so that the trend 

in the probability plot should not be over-emphasised, even 

though it may depart significantly from the regional one. 

Instead, the emphasis should be placed on the regional 

curve, for it represents the trend of all the flood peak data 

for the region and its construction involved the averaging 

out of the variations in the individual flood records. 

5.3.3 Estimation of 01 

(i) N

Year 

1958 

1959 

1960 

l96r 

t962 

1963 

t9& 

r 965 

1966 

1967 

1968 

Pe¡k (m¡ls) 

2238 

562 

1506 

702 

1552 

1644 

2201 

2859 

2689 

I 802 

1082 

Year 

t969 

t970 

t91l 

1972 

1913 

1974 

1975 

t976 

1977 

1978 

Peak (m3ls) 

6t3 

2387 

20t9 

t9u 

t094 

1357 

1690 

l3l I 

865 

2875 

The following four examples estimate the 100_year flood 

peak Q,oo and the corresponding 68,3g0 confidence limits 

lor the site, assuming that: 

(¡) no flood record is available; 

(ii) only the first 3 years of record, from l95g to 1960, are 

available; 

(¡iD l¿ years of record from 1958 to l97l are available; 

(iv) the full length of record from I 95g to I 97g is available. 

5.4.1 Example 1: N:e 

e estimated from the regional 

Figure 4. 10, the catchment lies 

ellEast Cape flood region and 

a = 2. 18 x l0-? AREA o ó1 MARAIN ,3! 

Substituting the values for AREA and MARAIN as given 

above produces: 

a = 2.18 x l0-? X 13930 64 X 2550, 13 

= l94O m'/s 

(b) The regional curve ordinate should now be obtained. 

The site is in the North Island East Coast flood frequency 

region, i.e, Region 3 in Figure 3.6, and hence, lrom Table 

3.4, the regional curve ordinate is: 

Q'oo/Q = 2.89 

. Alte^rnatively, Q,oolQ can be computed from the equa_ 

tion of the regional curve in Table 3.4: 

Q/Q = 0.762+0.469y 

For T = 100, y given by Equation 3.16 is 

y : -ln(-ln(l- I ) ) 

= 4.60 

100 

(This result could also have been obtained irom Table 3.1.) 

Substituting for y in the regional curve equation gives 

Q'oo/Q : 0.726 + 0.469 x 4.60 

: 2.88 

(The difference of 0.01 is due to rounding effecrs.) 

(c) Combining the estimates for Q and e,oole produces 

Q'oo. 

Thus Q,oo = 1944. x 2.89 

= 5607 m3,/s 

(d) The corresponding standard error of estimate is ob_ 

tained from Equation 3.25, namely 

var(Qr) = E(Q),. var(ea/Q) + E(er/Q),. var(e) 

The RHS terms of this equation are estimated as follows: 

E(Q) 

-- l9¿lo 

From Equation 3.26 

var (Q1/Q) : (Cr . 

Qt )' 

o 

where, from Table 3.9 

CF 

(_t.zs + 5.74 tnT)/100 

= 0.25 

Thus var (Qr/Q) = @.25 x 2.89), = 0.522 

Also E(Q'/Q) = 2.89 

]tr9.ti1a! 

term var (Q) is obtained from rhe p estimates in 

Table 4.12. lf p is assumed to be 0.5, Cp : b.¡Of for the 

Northland,/Coromandel,/East Cape flood- region. Since, by 

definition, 

cË = uar (Q)/Q' 

.'. var(Q)= C'..Q, 

: (0.301 x t940)' 

= 3.410 x l0' 

Reverting to Equation 3.25 

var (Q'oo) = 1940'z x 0.522 + 2.89, x 3.410 x 105 

= 4.813 x 10. 

Therefore the standard error of estimate of e,oo is 

Se (Q'oo) = (4.813 * 1gc¡t/z 

= 2194 m,/s, which is 39Vo of e,on 

Figure 5.2 Location of the Motu catchment above Houpoto. 

1435 ml/s 


80 

5.4.2 Exampte 2: N:3 

(l) W¡th N = 3 = Nu, Q should be estimated from both 

the flood record and the regional equation. Using the flood 

record: 

Qobs %Q238 + 562 + 1506)

Using the regional equation 

Qest 

1940 m'ls, as in Example I 

Combining these estimates from the record and regional 

equation, using a weighting factor of 0.5 for both (see section 

5.2.2), gives 

a = 0.5x1435+0.5x194O 

1688 m',/s 

(b) As N< 10, the regional curve should still be applied to 

estimate Q,oo. The curve ordinate is unchanged at 

Q,oolQ : 2.89 

(c) Combining the estimates of Q and Q,oolQ results in 

Q,oo 1688 x 2.89 

= 4878 m!/s 

(d) In obtaining the standard error of estimate, the RHS 

terms in Equation 3.25 changed from Example I are 

E(Q) = 1688 m3,/s 

and the variance of Q estimated from the flood record is 

given by 

E(Q) 

and 

var(Q) 

1704 m'ls 

(cu.Q)' 

N 

= (0.54 x 1704)' = 6.048 x 10. 

t4 

Therefore, from Equation 3.25 

var(Qroo) l1M' x 0.522 + 2.89' x 6.048 x l0' 

= 2.021 x 106 

Thus 

Se(Q'oo) : (2.021 x106)v, 

1422 m3/s which is 2590 of Q,oo 

5.4.4 Example 4: N:21 

(a) As in Example 3, Q can be estimated directly from the 

annual series. 

var(Qo6) - (Cn'Qou')' 

2t 

N 

i]r 

where C" : 

The Cn for the 0.54 from 

2l years of record is 0.43, which compares 

Figure 4.12 

well with the regional estimate of C" : 9.54 

Thus 

var(Qo6) : (0.54 x 

(b) Since T ) 5N and N > 20, frequency analyses may be 

1435)' : 2.002 x l0' 

performed on the annual series using two- and three-parameter 

distributions. The EVI distribution fitted by the 

3 

The variance 

maximum 

of 

likelihood method gives 

Q estimated from 

a good fit to the data 

the regional equation is 

the 

and yields 

same as in Example l, i.e., 

var(QesJ = 3.410x105 

Q'oo 

: 4l7O m'/s 

and an approximate standard error of estimate of 800 m',/s. 

From Equation 4.10, the variance of the combined estimate (This 

of Q is 

standard error is based on a formula used by NERC 

(1975, p. 170), assuming Cu : 0.54). 

l:l+l 

(c) The corresponding estimate using the regional curve is 

var(Q) var(Qo') var(Q.r¡) 2.002 x l0r Q,oo 1665x2.89:4812m3/s 

and the associated standard error of estimate is obtained 

+ 

from Equation 3.25 as 

3.410 x l0r 

var(Q,oo) 1665' x 0.522 + 2.8g'z x 

(0'54 x 1665)'z 

so that var(Q) = 1.261 x 105 

2l 

Hence from Equation 

1.769 x loó 

3.25 

so that 

var(Qroo) 1688' 0.522 + 2.89'? x 1.261 x 105 

: 2.541 x Se(Q'oo) 1330 m3,/s which is 2490 of 

106 

Q,oo 

and 

Se(Q,oo) = (2.541 x l0ó)/z 

1594 m!/s, which is 2890 of Q,oo 

5.4.5 Results Summary 

Table 5.2 summarises the estimates of Q and Q'oo obtained 

in the four examples using the RFE method. 

5.4.3 Example 3: N: 14 

The reduction in the standard error of estimate in Table 

(a) As N > N"( = 3), Q can be estimated directly from the 5.2 with increase in record length illustrates the value of increasing 

lengths of flood record. In Example 4, a second 

annual series. 

Hence 

estimate of Q,oo : 4l7O m'ls (by frequency analysis of the 

l4 

2l years ofrecord) is available and a designer would choose 

a = I a weighted mean of the two. 

I ei =1704m',/s 

It will be seen that the estimate of Q in the second example, 

obtained by combining the estimates from the re- 

14 i-: I 

gional equation and the three years of record, is closer to 

(b) Applying the regional curve produces 

the Q estimate using the full flood record than that in Example 

3 which is based on 14 years and, as a consequence, 

Q'oo :1704 x2.89 

= 4925 m3/s 

the corresponding Q,oo estimate is also closer to the Qroo 

estimate determined from the full record. Although this 

may be a chance result it does emphasise that even a short 

(c) The new RHS terms in Equation 3.25 are 

flood record is useful. 


81 

a 

2t 

= I )- Qi:1665m'/s

The estimate of Q from the regional equations is as 

accurate as an estimate from about three y€ars of record 

(Table 4. l2). If the typical variability is checked by drawing 

samples from the Motu data listed earlier, or by considering 

the standard error of the regional equation, it will be seen 

that this particular estimate from the regional equation is 

fortuitously close to the estimate from 2l years of record. 

Table 5.2 Summary of selected results from the RFE method. 

Example 

number 

1 

2 

3 

4 

Length of 

recor.d 

(yrsl 

o 

3 

14 

21 

Estimate 

ofO 

(m3/s) 

39 

28 

25 

24 

82 


6 Summary 

In New Zealand little progress has been made in flood 

estimation techniques over the last 25 years despite an upsurge 

in the amount of streamflow data that has been col- 

Iected over this period. This study has attempted to improve 

this situation by 

al flood frequency 

analysis procedu 

the available 

annual and historical flo 

I catchments' 

The procedure, known as the Regional Flood Estimation 

(RFË) method, is applicable to both gauged and ungauged 

iural catchments which in general are greater than 20 km' 

in area. Since the method was developed by averaging the 

sampling variation that exists in individual flood records, it 

should provide a more reliable design flood peak estimate 

than that determined by fitting a frequency curve to a relatively 

short record. 

The RFE method comprises a set of eight regional flood 

frequency cu 

vs T, and a set of 

niné regionat 

when there is little 

or no flood ¡ 

S the T-Year flood, 

and Q is the mean annual flood. The most important independent 

variables in the equations are catchment area 

and an index of the catchment rainfall. 

The regional curves may be used up to the 200-year return 

period to estimate a design flood peak, except in the 

Otago-Southland region where the upper limit on return 

period is restricted to 100 years because of the limited data 

in this area that were available for analysis. The curves are 

defined by the straight-line extreme value type I (EVl) distribution 

for all but two of the regions the Bay of Plenty 

- 

and South Canterbury regions, where the extreme value 

type 2 (EV2) tlistribution was found to give a better definitión 

of the regional trend in the data. Although the general 

extreme value (C 

gional curves, th 

of the log-Pears 

tion tests carried 

that the LP3 distribution may well have given an equally 

good description of the curves. 

It is evident, both from the regional mass probability 

plots and from the standard error equations derived for the 

iegional curves, that the variability in the regional Qr/Q 

data is well within acceptable limits. A quantitative indication 

of the confidence that may be placed on values of 

Q1/Q estimated fiom a regional curve is obtainable from 

the standard error equations which give estimates comparing 

very favourably with those given by the equivalent 

NERC (1975) equation. 

A feature of this study is the dependence of the results on 

climate. This is illustrated by the regions, which are partially 

consistent with recognised climatic boundaries, and 

by the difference in slope of the western and eastern regional 

curves. The latter curves have greater slopes, which 

ãre uttributable to the greater variability in the flood peak 

data for the eastern regions where the climate is drier and 

the antecedent conditions more variable. Further indication 

of the climatic influence is given by the regional equations 

for estimating Q . ¡.lo physical characteristics, other than 

catchment area, are included in the equations, the only 

other important parameters being catchment rainfall estimates. 

This suggests that climate may be the dominant factor 

affecting flood peaks with magnitude equal to or 

greater than the mean annual flood. Other factors often 

considered important, such as geology and topography, 

have been accounted for to some extent in the regionalisation 

of the country. 

The country is divided into two sets of regions' one set 

for estimating Qr/Q and one for estimating Q. These are 

very similar 

t 

tempts were 

e 

purposes, b 

t 

regions is a 

a 

Q1/Q and Q. 

The application_of the method to a catchment for the 

estimation of Q1/Q and 

ted 

in Chapter 5 with four 

the 

advantage, when only a 

of 

combining the estimates 

uation 

and the flood record to obtain a weighted average 

"best" estimate of Q . t¡e precision of each equation is expressed 

of record and, 

àepend 

estimate of Q 

from a 

he error of estimating 

od record. Thus 

when an important waterway project is being considered, a 

recorder should be installed as soon as possible to record 

the flood peaks. 

In addition to the regional curves of Q1/Q which extend 

up to a maximum of 200 years, generalised curves, one for 

the west and one for the east, are given. These curves were 

derived from all the flood peak data collected for this 

study, excluding four extreme flood events, and they can be 

applied from beyond the limit of the regional curves up to 

the 1000-year return period. Of interest is the marked similarity 

of these curves with those derived by Stevens and 

ing too many regions. lt is envisaged that as more flood 

p.ãk dut" become available, revisions and refinements will 

te made to the RFE method' especially for the estimation 

of Q. 

In all cases, we recommend that other methods for estimating 

design flood magnitude also should be used and the 

results compared before a final figure is selected' 


83


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Pilgrim, D.H. 1966: Storm loss rates for regions with limited 

data. Proceedings of the American Society of 

Civil Engineers 92 (Hy 2): 193-2-06. 

Pilgrim, D.H.; Cordery, l. 1974: Design flood estimation 

- an appraisal of philosophies and needs. Reporl 

No. 140, Vl/ater Research Laboratory, University of 

New South Wales. 

Robertson, N.G. 1963: The frequency of high intensity 

rainfalls in New Zealand. NZ Meteorological Service 

Miscellaneous Publication I I 8. 

Rosenbrock, H.H. l9ó0: An automatic method of finding 

the greatest or least value of a function. The Computer 

Journal 3: 175-84. 

Sangal, B.P.; Kallio, R.W. 1977: Magnitude and frequency 

of floods in Southern Ontario. Technicol 

Bulletin Series No. 99, Inland Waters Directorote, 

Waler Planning and Management Branch, Fßheries 

and Environment, Canadø. 

Schaake, J.C.; Geyer, J.C.; Knapp, J.W. 1962: Experimental 

examination of the rational method. Proceedings 

of lhe American Society of Civil Engineers 93 

(Hy 6): 353-70. 

Schnackenberg, E.C. 1949: Extreme flood discharges. proceedings 

of the NZ Institution of Engineers 35 

376-427. 

Soil Conservation and Rivers Control Council 1957: 

Floods in New Zealand, 1920-53. SCRCC, Wellington. 

Stevens, M.J.; Lynn, P.P. 1978: Regional growth curves. 

Report No. 52, Institute of Hydrology, llaltingford. 

Thomas, D.M.; Benson, M.A. 1970: Generalisation of 

streamflow characteristics from drainage basin characteristics. 

US Geological Survey lüater Supply 

Paper No. 1975. 

Toebes, C.1972l. The surface water resources of New Zealand. 

Paper presented at Xll NZ Science Congress, 

Palmerston North. 

Toebes, C.; Palmer, B.R. I969: Hydrological regions of 

New Zealand. Water and Soil Division, Miscellaneous 

Hydrological Publication, No. 4. Minisrry of 

Works, Wellington. 

Tomlinson, A.l. 1980: The frequency of high inrensity rainfalls 

in New Zealand, Pact l. Water & Soil Technical 

Publication /9. Ministry of Works and Development, 

Wellington. 


86

Appendix A : Tests with frequency distributions 

4.1 Introduction 

The General Extreme Value (GEV) distribution is detailed 

in Chapter 3. The Gamma distribution, another general 

distribution from which several other specific distributions 

derive, is outlined below. Then a computer program 

(FRAN) is described. This program was developed to 

enable an evaluation of different lrequency analysis methods 

on New Zealand flood data. It was found that the extreme 

value type I (EVl) distribution fitted by the Jenkinson 

method generally fitted the data well, but that in many 

cases the EVI distribution l'itted with Gumbel's method of 

leasl squares also gave satisfactory results. 

4.2 Gamma distribution 

The three-parameter Camma distribution is the same as 

the Pearson Type 3 distribution. It has the pdl 

f(x) : I (x-xo¡r-le-(x-xo)/li .....A.1 

0rr(r) 

which is defined for x > xo, 

where xo 

ù_ 

l)- 

I'(r): 

a location parameter, 

a scale parameter, 

a shape parameter, and 

the Gamma function, equal to ("y- 1)! for 

positive integer values of -y. 

lf "y : ¡, (x) describes an exponential distribution; and if 

xo = 0, f(x) describes a two-parameter Gamma distribution. 

Like the CEV distribution (section 3.1.3), Equation A.l 

describes a tämily of distributions, with each member characterised 

by the value of the shape parameter, in this case 7. 

This parameter is inversely related to the skewness of the 

variate, and as the skewness gets smaller, "y increases and 

Equation A.l tends to the Normal distribution (NERC 

1975). When the skew is zero the symmetrical, two-parameter 

Normal distribution applies, with the pdf 

f(x) : I s- /tl(x- pl/ol' 

"F 

where ¡,r : a location parameter, and 

o : ascaleparameter. 

A2 

The parameters ¡,t and o are, in fact, the population mean 

and standard deviation, respectively, of the variate x. 

An analogous situation to that described above applies 

tbr the three-parameter log-Gamma distribution. This distribution 

is the same as the log-Pearson Type 3 (LP3) distribution 

and has a pdf of the form 

f(x) : I (l'nx- xo)?- I e-(r)nx-xo)/B ..... 4.3 

x0zf(r) 

which is defined for x > e"n. 

Like Equation A. I, Equation 4.3 describes a family of 

distributions, with each member being described by a particular 

value of 'y. When the skewness of the variate is zero, 

the two-parameter log-Normal distribution applies, with 

the pdf 

f(x) : I s- 

xoF 

/,1 (t'nx- p\/ øl' 

A4 

which is defined for x > 0. The parameters p and r are now 

the population mean and standard deviation of the natural 

logarithms of the variate x. 

The df for Equations A.t to 4.4 must be calculated numerically. 

A.3 Methods used 

The GEV distribution described in section 3.1.3 and the 

Camma distribution outlined in section 4.2 have up to 

three parameters: a location, a scale and a shape parameter. 

These parameters must be estimatcd in the fitting ol a distribution 

to a data sample. The various techniques of parameter 

estimation, together with the choice of the parent distribution 

that may be used, give rise to the dilferent frequency 

analysis methods that are available. 

This study considered seven different frequency analysis 

methods. They were chosen on the basis of being the most 

common or the most useful, and they were incorporated in 

a computer program FRAN (Maguiness ef a/. in prep. a). 

(Another computer program FRANCES (section 3.1.7) was 

developed for use where historical information was available 

(Maguiness e! al. in prep.b).) The methods used in 

FRAN were the lollowing: 

(1) the three-parameter log-Camma or LP3 distribution 

fitted by the method of moments; 

(2', - 

the three-parameter log-Gamma or LP3 distribution, 

with an adjusted coefficient ol skew fitted by the 

method of moments' 

- 

(3) log-Normal distribution - 

fitted by the maximum 

likelihood method; 

(4) GEV distribution - 

fitted by the maximum likelihood 

method; 


(5) EVI distribution fitted by the maximum likelihood 

- 

method; 

(ó) EVI distribution - 

fitted by the least squares method; 

(7) EVI distribution - 

using the Jenkinson (1969) 

method. 

Each of the methods is briefly described below with reference 

to an annual series. In the case of methods I and 2, 

the distribution involved is subsequently referred to as the 

LP3 distribution. For a detailed explanation of the seven 

methods, refer to the report on FRAN by Maguiness e/ a/. 

(in prep. a). 

Method I This method was recommended by the United 

States Water Resources Council (1967) to be uniformly 

adopted in that country as the standard method for flood 

frequency analysis. The method in effect applies the threeparameter 

Gamma (Pearson) distribution (Equation A.l) 

to the logarithms of the annual series. The resulting frequency 

curve is a flexible one; it can plot concave upwards 

or downwards on log-Normal probability paper. It also incorporates 

the two-parameter log-Normal distribution, 

which plots as a straight line on the same paper. 

The fitting technique is the method of moments, which 

involves the calculation of the mean, standard deviation 

and the coefficient of skew of the logarithmically transformed 

series. These statistics are then used in the following 

equation to obtain the desired flood estimate. 

log'oX1 : X +K.S 

A5 

where X1 : flood estimate for return period T, 

X : mean of the transformed series, 

S : standard deviation of the translormed 

series, and 

K : afrequencyfactor. 

87

The liequency factor K is a function of the coefficient of 

skew and the return period and may be obtained from 

tables (e.g., Harter 1969; USWRC 1967). The form of 

Equation 4.5, which is based on the use of a frequency factor, 

is preferred to the more formal type of LP3 equation 

(e.g., Equation A.3) for the method of moments fitting 

technique, as it makes the computations very much easier. 

The frequency factor idea has heen propounded by Foster 

(1924) and Chow (1951), and the derivation of the factor 

for the LP3 distribution is explained by NERC (1975, pp. 

39-40) and Kite (1976, pp. 198-204,2291. 

Method 2 This method is the same as Method l, except 

that an adjustment is made to the computed skew coefficient. 

An adjustment is warranted because the computed 

skew value is likely to be unreliable for a data sample of 

typical size. Indeed, it has been suggested (Beard and Frederick 

1975) that at least 100 sample items are needed to obtain 

a skew value that is representative of the population 

statistic. Since most hydrological data samples are much 

smaller than this, various efforts have been made to improve 

the reliability of the computed skew value through 

the use of generalised skew coeflficients (Beard 1977). One 

example is the use of a regional skew value taken from isolines 

of computed skew values. 

ln the early stages of this New Zealand study, computed 

skew values lbr flow stations in the top half of the South 

Island were plotted on a map to determine if there was any 

pattern in the skew coefficient. None was evident and, 

hence, the possibility of using generalised skew coefficients 

in this study was not pursued. Instead, the following tactor 

Fu, recommended by Bobée and Robitaille (1975), was used 

to adlust for the bias in the skew value that is due to the 

length of the data sample. 

Fo= 

where CS = the computed skew coefficient, and 

n : the number of sample items. 

The adjustment is made by multiplying the computed 

skew coefficient by Fu, but only when Equation 4.6 is 

applicable i.e., for samples with 20 or more items. 

Mefhod 3 This method is often referred to as the log- 

Normal method and uses the two-parameter log-Normal 

distribution, as distinct from the three-parameter one (see 

Kite 1976). The method has long been advocated for use in 

hydrological frequency analysis (e.g., Hazen l9t4), and appeals 

because of its simplicity the fitted frequency distribution 

plots - 

as a straight line on log-Normal probability 

paper. 

The application of the method involves the same computations 

as for Method l, except that the coefficient of skew 

of the logarithms of the series is set to zero. 

Method 4 This uses the maximum likelihood (ML) 

method to fit the CEV distribution to a data sample. This 

method of fitting is generally recognised as the most efficient 

for estimating the distribution parameters, and its use is 

recommended when the design events must be extracted 

from a small or irregular series (WMO 1969). However, the 

ML method involves equations that have no explicit solution. 

The solution is complex and requires the use of an 

iterative numerical scheme, and is only worthwhile attempting 

with the aid of a computer. 

Method 5 Although the GEV distribution incorporates 

EVI as a special case, only rarely will the application of 

Method 4 result in the EVI distribution being fitted to a 

data sample. To ensure that a fit was obtained with the EVI 

distribution, this distribution was fitted separately (by the 

ML method) to the sample by setting the shape parameter k 

in the CEV distribution to zero. 

88 

¡ 16-11- *ry i.i,* 

.Tì"... ou 

Method ó This method is often called the "Gumbel 

method" after Gumbel (1941, 1954) and is probably the 

one most commonly employed in hydrology. lt has had 

wide use in New Zealand and was the method adopted by 

the New Zealand Meteorological Service (Robertson l9ó3) 

when determining rainfall depth-duration-f'requency relationships 

from New Zealand data. 

Melhod 7 This method follows the procedure devised by 

Jenkinson (1955, 1969) and also described by Samuelsson 

(1972). The method emphasises the extreme part of annual 

series and as shown by Samuelsson, it can be applied as the 

standard one to extreme values which belong to several different 

kinds of frequency distribution. A larger series of 

S-year maxima is produced from the annual series by considering 

all possible combinations of items of five in the 

original series. The EVI distribution is then fittcd to rhe 

series of 5-year maxima by the ML method. 

If an annual series is used in a lrequency analysis instead 

of a series of 5-year maxima, it is quite possible that the 

series may be non-homogeneous in that, for example, the 

smaller items may belong to one distribution (e.g., EV2) 

and the larger ones to another (e.g., EV3). Further, it can 

be shown mathematically (WMO 1969) that the lower parr 

(37V0) of the series may not even belong to the extreme 

value distribution as it is defined. The advantage of the Jenkinson 

method is that it generally overcornes this problem 

of non-homogeneity of data. The use of 5-year maxima can 

be thought of an increasing by fivefold the degree ol independence 

in the data, so that these maxinra should then 

form a homogeneous set of data that confbrms to EV 

theory. 

4.4 Evaluation of the frequency analys¡s 

methods 

4.4.1 General 

Prior to the development of the regional curves, two 

evaluation tests were carried out on 42 flood records altogether, 

using the seven frequency analysis methods described 

in section 4.3 and contained in the computer program 

FRAN. The purpose of the tests was twofold: 

(¡) to observe, and to indicate to users of FRAN, the relative 

merits of the seven different methods on individual 

New Zealand flood records; 

(ii) to assist in the selection of a frequency distribution 

that would adequately describe the regional curves. 

This section describes the tests and discusses the results 

obtained. 

4.4.2 Evaluation criteria and method 

Most studies that have attempted to discriminate between 

frequency analysis methods have relied, at least to some extent, 

on objective goodness-of-fit indices. Recent examples 

of such studies are those carried out by Benson (1968), 

Beard (1974), Kite (1976) NERC (t975), Kopiuke ef ø/. 

(1976) and Bobée and Robitaille (1977). However, as is generally 

acknowledged (e.g., Benson 1968), the classical 

goodness-of-fit indices such as Chi-square and Kolmogorov-Smirnov 

are not sufficiently sensitive or powerful 

enough, because of the small samples found in hydrology, 

to distinguish between the worth of different frequency analysis 

methods. Moreover, NERC (1975) found that other 

goodness-oi-fit indices had major weaknesses and concluded 

that, because of the deficiencies ol goodness-of-fìt 

indices, a visual inspection must be made of the probability 

plots. The judgement on the performance of a method is 

then a subjective one, "... but the objective tests that are 

available are so ineffective that their objectivity alone is insufficient 

to recommend them" (NERC 1975). 

In the evaluation tests, much more emphasis was placed 

on the probability plots than on the Chi-square value, 

which the computer program calculated. F-ollowing an ex- 


amination of the probability plots for each station, the perlormance 

of each frequency analysis method was classified 

into a good, reasonable or poor category according to the 

following four criteria: 

(i) the frequency curve should fit the whole of the series 

well, but particularly the upper half of the series; 

(¡i) the frequency curve should not necessarily pass 

through the very largest items in the series, since there 

is a far larger sampling variation with these items; 

(¡¡¡) the frequency curve should appear to produce a good 

estimate of the 10O-year flood peak; 

(iv) the Chi-square value should not be abnormally high. 

Criterion (iii) needs some explanation. Although a 

method could perform well under criterion (i), it could not 

be automatically assumed that the method therefore gave a 

sensible estimate oI the 10O-year flood peak. Because of the 

small-sample effect with some of the samples used, a method 

could produce an extremely good fit to a data sample 

but a 100-year value that was only minimally greater (e.9., 

less than l-290) than the 2O-year value. One hundred years 

was chosen as the return period for the flood peak estimate 

on the basis of it being the most commonly used maximum 

value in bridge waterway design (MWD 1979). It follows, 

therefore, that the subsequent evaluations of the methods 

for fitting individual station data are with reference to this 

maximum return period and they should not be interpreted 

as being applicable beyond the 100-year return period. 

Afler the classification of the performances of the 

methods they were then quantified, by allotting a score of 2 

for each good fit, I lor each reasonable fit and 0 for each 

poor fit. 

A.4.3 F¡rst test 

The first evaluation test was made midway through the 

data collection phase when all the annual flood peak data 

had been collected for the South Island stations. The results 

of this test were presented and discussed by Maguiness et al. 

(1977). Of the 50 stations for which data were available, 28 

stations were selected for the test (see Table A. I for 

details). These stations were considered to have reasonably 

reliable streamflow records and each flood record was l0 or 

more years in length. Altogether there were 377 station 

years of rccord, giving an average length of 13.5 years per 

station. 

The performance of the different methods is summarised 

in Table 4.2, which shows the number of times each 

method gave a good, reasonable and poor performance. It 

also shows the final score for each method after the performances 

were quantified. The adjusted LP3 method is 

not included in the table, since in only one case was the record 

length long enough (20 years or greater) for an adjustment 

to be made to the coefficient of skew using Equation 

4.6. 

As can be seen from Table 4.2 the Jenkinson method 

performed best, scoring 52 out of a possible 56. lt produced 

Table 4.1 Deta¡ls of the f low stations used in the first evaluation 

test. 

Site No. 

56901 

57502 

60110 

60114 

621 03 

621 05 

64301 

64602 

64606 

65104 

65107 

69302 

69506 

69614 

6961 I 

6962 1 

71 103 

71116 

71129 

7'l 135 

93203 

93204 

93205 

93206 

93209 

93211 

93212 

93217 

Flow Station 

Catchmenl Record 

area, km' Length, 

Years 

Riwaka at Moss bush 48 10 

Wairoa at Gorge 464 15 

Waihopai at Craiglochart 744 16 

Wairau at Dip Flat 505 25 

Acheron at Clarence 997 18 

Clarence at Jollies 44O 

'l 3 

Conway at Hundalee 47O 12 

Waiau-uha at Marble Point 1980 14 

Waiau-uha at Malings Pass 74-6 10 

Hurunui at Mandamus 1 O7O 1 I 

Hurunui at Lake Sumner 342 1 5 

Rangitata above Klondyke 1495 10 

Orari at Silverton 52O 15 

Opuha at Skipton 456 12 

Opihi at Rockwood 412 12 

Rocky Gully at Rockburn 22.4 10 

Hakataramea at M.H. Bridge 899 13 

Ahuriri at South Diadem 557 12 

Forks at Balmoral 13O 

'l 1 

Jollie at Mt Cook Station 1 39 10 

Buller at Te Kuha 6350 14 

Buller at Berlins 5960 16 

Buller at Woolfs 4560 11 

lnangahua at Land¡ng 1000 

'l 3 

Maruia at Falls 980 1 1 

Matakitaki at Mud Lake 857 13 

Mangles at Gorge 284 16 

Glenroy at Blicks 198 1 1 

377 

what were considered good fits on 24 occasions (or more 

than 8590 of the time) and, significantly, gave no poor fits. 

Next in order of performance were the LP3 and the 

Gumbel methods, scoring 4l and 39 respectively. The former 

method gave only slightly more good fits than the latter, 

and both produced only a minimal number of poor fits. 

At the lower end of the performance rankings were the 

EVl,log-Normal and GEV methods. Little distinction can 

be made between the EVI and log-Normal methods, with 

both giving on average about the same performance. In 

comparison, the CEV method gave fewer poor fits, but at 

the same time produced only three good lits - 

less than 

half the number achieved by each of the other two 

methods. 

The flood records used in this first test were relatively 

small samples. Although each record was at least l0 years 

long, this is the minimum acceptable length for a flood frequency 

analysis. The average record length of 13.5 years is 

only a marginal improvement on this and is still less than 

the minimum length of l5-20 years recommended by some, 

Table 4.2 Summary of the performance of the methods ¡n the f¡rst test. 

Method 

Performance 

Categories 

No. 1 

LP3 

No. 3 

Log-Normal 

No. 4 

GEV 

No. 5 

EV1 

No. 6 

Gumbel 

No. 7 

Jenkinson 

Good 

Reasonable 

Poor 

Number Score Number Score Number Score Number Score Number Score Number Score 

16 32 

99 

30 

Total Score: 

4'l 

27 26 

Note: Score calculated as 2 for good fit, 1 for resonable, O for poor fit. 

Maximum possible score: 2 x 2a :56 

8 

'l 6 3 6 11 22 13 26 24 48 

11 11 20 20 7 7 13 13 4 4 

9 0 5 0 10 0 2 0 0 0 


89

e.9., Linsley et ol. (1915); lrish and Ashkanasy (1977). 

There was, in fact, only one station with more than 20 years 

of record. However, these relatively small samples reflect 

the situation the design engineer is often faced with 

- having 

to estimate design figures from records of barely adequate 

length. 

Most of the findings of the test could only be regarded as 

preliminary ones pending further investigation with larger 

samples and covering a great'Jr part of the country. The 

findings are a guide to the design engineer using a small 

sample in flood frequency analysis, but the test itself was 

not very helpful in the choosing of a distribution for the regional 

curves. A second test was therefore carried out at the 

end of the data collection phase using larger data samples. 

4.4.4 Second test 

The second evaluation test used annual series data from 

14 stations with 20 or more years of record. Details of these 

stations are listed in Table 4.3. As shown in the table, there 

was a total of 366 station years of record, giving an average 

record length of 26.1 years per station, almost double the 

figure for the first test. 

The performances of the different methods on the second 

set of data were evaluated in exactly the same manner 

as tbr the first test. The results of the evaluation are summarised 

in Table A.4. 

Table A.4 shows that the Jenkinson method again performed 

best, but this time the Cumbel method gave a pertbrmance 

that was almost as good. Notably, neither 

method gave any poor fits to the data. At the second level 

of performance were the GEV and LP3 (unadjusted and 

adjusted) methods, all with the same score of 22. The performances 

of the unadjusted and adjusted LP3 methods 

were indistinguishable and the two methods are collectively 

referred to as the LP3 method. Last were the log-Normal 

and EVI methods. Both methods gave good fits at least 

5090 of the time, but also a noticeable percentage (2190) of 

poor fits. 

As in the lirst test, the Jenkinson method performed the 

best ot'the methods, and in this second test could rarely be 

faulted. ln the one instance where it gave other than a good 

performance, its frequency curve still fitted the data well 

and produced a realistic 100-year flood peak estimate. 

However, its performance was reduced because of its Chisquare 

value, which was high and more than twice that for 

any of the other methods. Some allowance was always 

made for a higher Chi-si¡uare value with the Jenkinson 

method, but in this particular case the value was excessively 

high. The higher values for the method are caused by the 

fact that the frequency curve does not always fit the lowest 

four items in a series, since these items clo not form part of 

the generated 5-year maxima to which the method fits the 

EVI curve. 

The Cumbel method improved on its first test ranking 

giving an overall performance almost the same as the Jenkinson 

method. However, a surprising aspect in both tests 

Tabþ 4.3 Details of the flow stations used in the second evaluation 

test. 

Site No. 

Flow Station 

Catchment Record 

area, km' Length, 

yeafs 

14614 Kaituna at Te Matai 958 21 

1551 1 Waimana at Waimana Gorge 44O 25 

1 5514 Whakatane at Whakatane 1 557 20 

29201 Ruamahanga at Wardells 637 22 

29202 Ruamahanga at Waihenga 2340 21 

29224 Waiohine at Gorge 183 22 

32502 Manawatu at Fitzherbert 3916 48 

32503 Manawatu at Weber Road 713 22 

32514 Oroua at Almadale 312 24 

32526 Mangahao at Ballance 266 24 

32529 Tiraumea at Ngaturi 734 24 

601 14 Wairau at Dip Flat 5O5 25 

92216 Buller at Lake Rotoiti 195 26 

93213 Gowan at Lake Rotoroa 368 42 

366 

was the difference in performance between the Gumbel and 

EVI methods. Both fit the same distribution (EVl) to a 

series yet the EVI method did not perform as well, presumably 

because the ML fitting technique, in comparison with 

the least-squares technique, puts relatively greater weight 

on the smaller items in a data series (Gumbel 1966). Consequently, 

if the upper half of a series exhibited a different 

trend. to that for the lower half, the EVI method, especially, 

did not always produce a good fit to the upper half 

and its performance suffered accordingly. In addition, the 

visual inspection of the goodness-of-fit of the frequency 

curves may have given the Gumbel method an unfair advantage 

over the EVI method, since curve-fitting by eye can 

be considered as a least-squares fit (Chernoff and Lieberman 

1954, 1956). Thus, although the results may indicate 

that the Gumbel method may be a worthy substitute for the 

Jenkinson method when a computer is unavailable, the 

evaluation may have been weighted unfairly in favour of 

the Gumbel method. 

The methods using three-parameter distributions, i.e., 

the LP3 and the GEV methods, displayed their greater flexibility 

over the two-parameter methods by always producing 

a curve that fitted the data particularly well. However, 

occasionally this was to their detriment, because the 

resulting 100-year flood peak estimate was sometimes not 

very realistic. For example, in the case where the LP3 

method gave a poor performance, the curve fitted the data 

very well; so well in fact that it was almost horizontal at the 

high return periods. The difference between the 20 and 

10O-year flood peaks estimated from the curve was less than 

0.690, indicating an implausible 10O-year flood peak estimate. 

Table A.4 Summary of the performance of the methods in the second test. 

Method 

Performance 

Categories 

No. 1 

LP3 

No. 2 

Adjusted 

LP3 

No. 3 

Log-Normal 

No. 4 

GEV 

No.5 

EV1 

No. 6 

Gumbel 

No. 7 

Jenkinson 

No Score No. Score No, Score No. Score No. Score No. Score No. Score 

Good 

Reasonable 

Poor 

9 18 I 18 9 18 8 16 7 ',t4 12 24 13 26 

44442266442211 

10103000300000 

Total Score 

22 

22 20 ?2 18 26 

27 

Note: Maximum possible score = 28 


90

In the first test the GEV method was often affected in 

this manner, producing many curves that fitted the data 

very well but giving 100-year flood peak estimates that were 

not always sensible. For example, the trend in the lower 

half of the series would cause the GEV curve to flatten off 

at the top end, impþing that there was a limit to flood 

peaks of about twice the mean annual flood. While there 

may be an upper limit to flood magnitude, it is certainly 

more than the figure implied (see Tables 3.3 and 3.6). 

In comparison, the straight-line fits of the Gumbel and 

EVI methods were often a good approximation to the data 

and gave more sensible 100-year flood peak estimates. 

However, this better performance by the t$'o-pa¡ameter 

methods can be attributed to the small samples used 

(NERC 1975; pp. 159-60). The fact that the Gumbel 

method still performed better than the GEV method in the 

second test suggests that the samples in this test may also 

have been small. However, it is also likely that the leastsquÍues 

fitting technique of the Gumbel method influenced 

the evaluation test in the method's favour. 

The two-parameter log-Normal method also gave good 

approximations to the data at times, producing a reasonable 

proportion of good fits. However, the method assumes 

that there is no skew in the logarithms of the series, an 

assumption which was rarely true. Hence the method did 

not perform as well as others in the test, including its parent 

method, the three-parameter LP3. 

A.4.5 Gonclusions 

The evaluations in the two tests involved a good deal of 

subjective judgement, but this typifies the present situation, 

with the objective goodness-of-fit indices not providing rigorous 

enough criteria for discriminating between different 

frequency analysis methods. 

From the findings of the tests, the following conclusions 

were reached: 

(¡) the Jenkinson method was the superior method in both 

tests and should be used in flood frequency analysis, 

especially when the sample is small; 

(iÐ the Gumbel method improved in performance with increase 

in sample size, and should be a satisfactory alternative 

to the Jenkinson method on the larger sam- 

Ples; 

(ii¡) the GEV and LP3 methods were more flexible than the 

two-parameter methods, with their frequency curves 

geneially following the trend in the data extremeiy 

well; 

(iv) on small samples, in particular, the straight-line fits 

from the two-parameter methods can give good approximations 

to the data and sometimes more sensible 

results than those obtained from their parent threeparameter 

methods; 

(v) on small samples the LP3 method appears to perform 

better than the GEV method, being influenced less by 

the trend in the lower part of a series; 

(vi) on larger samples the GEV and LP3 methods can produce 

similar shaped curves and give a comparable performance. 

These conclusions apply for individual records and up to 

References 

Beard, L.R. 1974: Flood flow frequency techniques. Center 

tor Research in Water Rnources, Univercity of 

Texas, Austin, Technicøl Report CRVR-|19. 

1977: Guidelines for determining flood flow frequency. 

U.S. Water Resounaes Council, Bulletin No. 

I7A of the Hydrologlt Committee. 

Beard, L.R.; Frederick, A.J. 1975: Hydrologic frequency 

analysis. .In Hydrologic Engineering Methods for 

Water Resources Development Vol. 3. The Hydrologic 

Engineering Center, U.S. Army Corps of Engineers, 

Davis, California. 

Benson, M.A. 1968: Uniform flood-frequency estimating 

methods for federal agencies. Water Resources Reæørch 

4(5):891-908. 

Bobée, B.B. Robitaille, R. 195: Correction of bias in the 

estimation of the co-efficient of skewness. Wøter Resources 

Research I I (6): 841-4. 

1977: The use of the Pea¡son type 3 and Log- 

Pearson type 3 distributions revisited. lfoter Resoutces 

Research I 3(2): 427 -41. 

Chernoff, H.; Lieberman, G.J. 1954: Use of normal probability 

paper. Journøl of the Americøn Stotisticol 

Associotion 49: 778-85. 

1956: The use ofgeneralised probability paper for 

continuous distributions. Annals of Mathemoticol 

Statistics 27:806-18. 

Chow. V.T. l95l: A general formula for hydrologic frequency 

analysis. Tronsactions of the Americøn Geophysicol 

Union 32(2): 231-7. 

Foster, H.A. l9A: Theoretical frequency curves and their 

applications to engineering. Tronsactiotts of the 

American Society ol Civil Engineen 872 142-73. 

Gumbel, E.J. l94l: The return period of flood flows. ánnols 

of Mathemotical Stotistics 12: 163-X). 

1954: Statistical theory of extreme values and 

some practical applications. US Bureou of Slondards, 

Applied Mathemotics Series 33l. 15-16. 

l!Xó: Extreme value analysis of hydrologic data. 

In Statistical Methods of Hydrology. Proceedings of 

Hydrology Symposium No. 5, McGill University, 

Canada, Z,-25Februw. pp. 147-69. 

Harter, H.L. 1969: A new table of percentage points of the 

Pearson Type III distribution. Technometrics Il(l): 

177-81. 

Hazen, A. l9l4: Storage to be provided in impounding reservoirs 

for municipal water supply. Transøctions of 

the American Society of Civil Engineers 78: 

1539-641. 

Irish, J.; Ashkanasy, N.M. 1977: Flood frequency analysis. 

I¿ Australian Rainfall and Runoff. Chapter 9' The 

Institution of Engineers, Australia. 

Jenkinson, A.F. 1955: The frequency distribution of the 

annual maximum (or minimum) values of meteoro-. 

logical elements. Quorterly Journal of Royal Meteo' 

rological Society 87: 158-71. 

Statistics of extremes. Iz Estimation of 

Maximum Floods. Chapter 5. VMO Technicql Nole 

No.98. pp.193-227. 

-1969: 

Kite, G.W. 1976: Frequency and risk analyses in hydrology. 

Inland Waters Directorate, Water Resources Branch, 

Dept. of E 

Kopittke, R.A.; 

e, K.S. 1976: Fre" 

quency an 

in Queensland. Ia 

tion of Enginæn, 

Hydrology 

Austroliq, Notionsl Co4ference Publication' No. 

76/2. pp.2È4. 

Linsley, R.K.; Kohler, M.A.; Paulhus, L.H. 195: Hydrology 

for Engineers. McGraw-Hill, New York. 


9l

Maguiness, J.A.; Blackwood, P.L.; Broome, P.; Beable, 

M.E. (In prep. a): A report on FRAN, a computer 

program for the frequency analysis ofextrernes. Ministry 

of lVorks and Development, lVellin$on. 

Maguiness, J.A.; Blackwood, P.L.; Beable, M.E. (In prep. 

b): A report on FRANCES, a computer program for 

the frequency analysis of a censored sample. Ministry 

of Works and Development, Wellington. 

Maguiness, J.A.; McBride, G.B.; Beable, M.E. 1977: 

FRAN a computer program for the frequency analysis 

of extremes. Presented at the New Zealand Hy- 

- 

drological Society Annual Symposium, Christchurch, 

November. l6p. 

Ministry of Works and Development 1979: Code of practice 

for the design of bridge waterways. Ministry o! 

Works and Development, Civil Dìvision publìcatíon 

CDP 705/C (Prepared by lVater and Soil Division). 

72p. 

NERC 195: Flood Studies Rcport Vol. l, Hydrological 

Studics. Natural Environmental Resea¡ch Council, 

London. 

Robertson, N.G. 1963: The frequency of high intensity 

rainfalls in New Zqland. New Z¿stand Meteorologicol 

Semiæ, Misællaneous publicotion II8. 

Samuelsson, B. lï12: Statistical interpretation of hydrometeorological 

extreme values. Nordic Hydrologlt 

3(4): 19D'-213. 

US\VRC 1967: A uniform technique for determining flood 

flow frequencies. Hydrologt Committee, US llater 

Resources Councí|, Eulletin JVa 15. 15 p. 

IVMO l%9: Estimation of Ma¡rimum Floods. llorld Meteorologicol 

Organisøtion Tæhnicøl Note No. 98. 

92 


APPENDIX B 

Summary of Flood Peak Data used in the 

Regional Flood Frequency Analysis. 

CONTENTS 

Northern North Island Data 

North Island West Coast Data 

Manawatu-Rangitikei Data 

Southern North Island Data 

Bay of Plenty Data 

North Island East Coast Data 

Central Hawke's Bay Data 

South Island West Coast Data 

South Island East Coast Data 

South Canteibury Data 

Otago-Southland Data 

Prge 

93 

94 

96 

97 

98 

I 

100 

l0l 

103 

104 

105 

NOTE: The rules mentioned for some stations concerning 

the rejection of data refer to those given in Section 

3.2.2. 

1A. NORTHERN NORTH ISI.AND DATA 

srtr 350 6 

ClrCÍilll rRE^. s0 t(É = 

¡trlEEl o? rf,[urL PEtÍs = 

tllB PEr( tElR 

1958 q7. S 195c 

1912 r¡C.9 l97l 

1976 5q.6 197? 

iElI = 

PEIK 

38.9 

56. C 

36. 6 

57. B sTD. Dtlv. = 

ntuNGAprRERÍrÀ R IT TynFzs Fonn 

11. 1 ilÀP REFEFtT¡CE 

1T PEAIOD OP PNC. 

YEIR PFTK 

1970 69.3 

88 . c 

19"r¡ 

YEÀR 

1971 

197s 

¡t l: 39 1555 

1968-77 

PE¡ K 

69. 6 

?0. 1 

17.0 coFF. oF sXE¡ = C.3?66 

S IlE 9101 rÀITOI P TT IISTI(¡HOFO DRIDGF 

CtrcElElll lEEt, SQ Kll = 433 llÀP BßPEFDfct = tl53:082804 

fUlEE¡ 0P t[Xnrl PEtrS = 17 PEATOD OP PrC. = 1952-6Ê 

ts¡R PEÀK TEÀR PEÀK IEAR PBTI( tEÀR PEIX 

1952 25.1 t9S3 t¡6.C, rc 5¡ 68.0 1955 20.6 

I 956 q1.7 1957 38.5 1958 26.2 t959 22.Ã 

I 960 58.0 1961 9q. i '1962 05.0 1C53 10.n 

t 96tt 29.5 196s 52,6 1966 11.5 1961 47" 0 

1 969 qB.2 

IEli = 

q3.6 srD. DEV. = 19.5 CoEF. oF SKU¡ = 1.4380 

IOTES: 

1. îßE 1961 PLOOD Ptf,t( ÍÀS ÎÀKElt THE I.ÀPGEST rI THP 

Pfnron 1908-7?- 

^S 

SITE 9118 

Prtio ! À1 38tfl80lo tolD 

CÀlcHllPlll ÀREl' s0 l(lt = 528 llP FEIEREtIcE r57:005700 

l{UllBER oP riÍûtL PEt(S = 17 PERIOD 0F REc. = 1953-69 

YEIR PEÀI fE¡R PBT¡ tEÀ8 PEÀf, YUIN PI¡f 

1953 r 1 3.8 195¡t 12,7 1955 35.5 1956 100.9 

1957 l¡c,8 19t9 1 33.5 1959 38.1 1960 265.0 

1961 295.6 1962 I 28.3 1963 19.6 196¡ 71.2 

1965 8f,2 1966 143.2 '1961 2 13.5 1968 10f.0 

1969 15,2 

IiEt[ = 120,0 STD. DEV. 16.7 cogl. o! sß¿9 = 1. l9l5 

¡otEs: 

1. THE 1C6I PLOOD PEÀK ¡ÀS ÎÀf,EN ÀS ÎR' LIRGEST ¡' 1¡I 

PFnton 1908-77. 

SITE 9203 

ctTcññEIÎ t8P^, SQ Kll = 1606 ËrP REFEBE¡cr = 153: ll¡9tz 

lgIBER oP ¡ùr0ÀL PEÀKs = 1a PTRIoD 0P REc. ¡ 195È76 

IETR PTÀi YEÀF PETK YF¡R PBIR rEr¡ Ptlr 

t 958 611 1959 652 1960 920 196t 330 

1962 637 1 96 I 32C 1964 184 1965 397 

1 966 595 1967 283 t968 tr87 1969 290 

1 970 260 191 1 397 1912 3¡8 1973 2a1 

1974 291 1913 330 1976 736 

ñt:Àl¡ = 450 sTD. DEV. = 

:1113:-:-!1-::ï-::i:: 

2C0 COEP. OF SXtl - 0.7068 

tolEs: 

1. TffE'1960 PLOOD P?Àr ¡àS TrKEll 15 lEE L¡RGn5î rl lEl 

PERTOD 1929-76. 

sI?t 

38 19 

TTIHÄRIKEXP R ÀT |ILIOI BIIIi 

5II E 

OIIIf,ÈIORT R 11 CRITEIIOT II 

cÀTcRlE[T rBEr, SQ K11 = 

IUÉBER oP tflN0ÀL PElKs = 

IEIS PF.AK IPÀ R PEÀK 

t968 201.0 1969 6?.5 

1912 115. 1 l97l ?4.0 

1916 97. 0 .t911 81. 0 

tEtr = 1c7,3 sîD. DEV, = 

srTE 

q901 

IBT¡ PETÍ IBTE PE¡Í 

1910 31 . 6 1971 69, rl 

1 9tr 62.6 1975 121 .5 

lBll = 83.9 sTD. DEv. = 

srts 5S09 

229 

1a 

llAP REPERtI¡cE = ll1:,:52936] 

PliRIoD oP FFc. = 1968-77 

YEIR SEÀK YEIR PEÀ¡ 

1970 54, s 1971 163.5 

197tt 1t!2.5 1915 11 . O 

47.7 COEP. OP sÍE¡ = 0.9620 

IIGUIIGORTI 8 TT DÛGIIORES ROCX 

cÀrcñ;Exr ÀREr, s0 I(ll = 12.5 rAP REFBREIICE = r20:9q2120 

IftãBER OP tr¡0ÀL pElÍS = I PESIoD oF FEc. = 1910-11 

IEÀR PETK ÍETN PEIK 

'1972 4a.1 1913 I 13.0 

1916 I 31 . 1 1911 94. 6 

36.5 coEP. oP sKE¡l E -0.0788 

Tï:ï1_:_1I_ l::::11-l9ll 

CttCEüELl tBEt, S0 [i = 16.2 llÀP REPEREIICP 

v20.a279a2 

f0rBr8 oF lrlotl PEÀÍS = 10 PERIoD 0F FEC. = 1958-6" 

IITE PTIÍ I?IR PEÀ¡ rltR PEtx YE¡N PEÀX 

1958 73.3 1959 4C.2 1960 113.9 19n l 66.5 

1962 63,1 t96l 23.6 1964 16.8 1965 14,6 

1966 146.7 1961 87.5 

iE¡i = 64.6 ST¡. DEl. = tr3'3 COEP. oP SrEr = 0.6302 

TOT'S: 

1. lEE t956 ¡LOOD PEltr OP 210 cÛllEcs 

LI¡GEST Ir TEE P9RroD 1850-1967. 

sITt 8501 

rts Tl(E[ rs TflE 

TIIROÀ R À1 ¡EIR 

CtTCriEIl tREt, sO lá 12.6? rlP REPEFPTICB X4€:631301 

roqrtn oF r¡roir, p¡rrs = 15 PERToD oP REc' = 1960-74 

T!À¡ PEIi TETR PET( YETR P8¡K II'TR PE¡X 

iioo 37.q 1961 3o.s 1962 33.2 1963 21,1 

ti¡c 33.8 1965 26.r ß66 5?. I 196? 15.4 

1968 19.5 1969 11.9 1970 J2-'t 1"11 9' 6 

1972 1 3. 6 1,9ai 22-5 1914 36.6 

iBtI = 31.2 sfD. DEl. = 17.0 COEP. oF SKEI - l'l'382 

ctT:ñtEl¡T tBE[, sQ Kll = 

ll0liBEF 0P t[¡Uf,L PEtXs = 

IEIR PSTK 

195rr 619 

1959 656 

1963 300 

1968 538 

lEÀI = 112 

308 

1l 

ütP BB?EREÍcs = I53: ttt95t 

PERIoD 0! 8Ec. - t95l-68 

fEtt PElf rt¡t Pllr 

r 9 5? ?.55 1950 515 

l96t c56 1962 501 

1966 592 1967 33¡ 

taoTEs: 

1. lEE 1036 FLOOD FElr, ESlrllllED T0 BE e9? CUiECS, l¡5 

lIKEII ÀS TF¡ LTRGEST III TIII PESIOD 18?5-196E. 

2. [O DrTr CÀS tVArttALE P5R 1955 lltl 1951' 

sfrE 9211 

IETN PPTK 

'1951 218 

1961 112 

1965 120 

196 9 rrTd 

197 3 ?o5 

IBÀf, = 

r¡l5 

fEI R PEIÍ 

1956 53F 

1 96 ! 52tt 

1965 31q 

STD. DEY. = 

cÀÎctillEflT ÀREr, S0 Kll 

rauü8ER oF rù[[ÀL PEtKS 

YEIR 

195I 

1962 

19 66 

1 I'C 

= :87 

PTIIK 

q63 

50c 

67C 

184 

STD. ftnv. = 1? 1 

loTEs: 

1. îfiF 1916 FLOoD PEAK OP 9r¡C C0ñECS 

LtFGESî rÙ lHE FERTOD 1875-1977. 

srlE 9221 

crlcElllfl rall, s0 rl = 

¡olBlR oF lliûlL Pltf,S = 


IEIB PETtr IEI R PETi 

196q 10 1965 130 

1968 124 1969 12C 

1972 14¡ 19711 142 

trlt . t53 sro. oÉs. = 

98q 

12 

130 CO!F. OP sßll = -0.1680 

oHrrPinF¡ n lr f,t¡llGlllil 

itP Rf,PgFrtacE = Ã5322OA922 

PFFIoD ol RqC. = 1951-73 

YEIR PEÂT IEIS 

1959 61¡ i960 

1 96f 2c0 t 961 

1967 336 1968 

rq? r 6'11 1912 

coEr. oF srE¡ = -0.0389 

cls TlÍEx ts TnE 

PtlI 

¡50 g0 

650 

357 

cttEou R rT s8ÀPlFsBt¡Rt 

lÀP RErBnlXc¡ I57:263663 

PERIOD OP REc. = 1960-76 

TEÀR PE¡X TEÀR PETf, 

1966 l?C t967 200 

1970 16C 1971 155 

1975 135 t976 200 

28 COE!. oP sl(P¡ = 0.7875 

tolBs: 

t. î[t t960 PLOOD PEIK 0l 250 C0llECS l¡S TIXEN rS T¡rE 

LIBGESÎ Il llB PESTOD 1960-1976. 

2. to t¡¡otL PEtÍ 9¡S ItlrLÀBLE FOR 1973, 

93

sltt 930 t [rûltRÀict ¡ l? s;¡tts S IlE q66 25 IIfr¡rltcI ¡ ¡1 rrro-Írrot¡tsI 

cl?cttttl rllt, sQ ft 

tuiDt¡ o? l¡fnll PEris ' 

ttln Pttf Il¡¡ pt¡( 

t959 598 1960 533 

t96l 8?6 t96r 213 

t96t 759 '1968 151 

tgtt 507 1972 1t5 

t9?5 5¡8 1976 623 

lltf - 087 sîD. D?t, - 

lolls: 

'122 

t8 

ItlP ¡E?lRlIcE ! f¡9:088235 

ÞEIIOD o? Flc. - l95q-76 

IB¡N PBIÍ ITTA PDIÍ 

1961 366 1962 120 

1965 355 1966 59C 

1969 284 1910 339 

1973 326 197¡ 259 

200 COEF. OP SßEÍ = 0.09¡5 

t, rtB 1936 PLOOD PAlf, Op 98C CtrrECS tts Trlrt ts TRE 

stcofD Llf,otlir rt îEE pEnroD 1899-1977. 

c¡lcctltf trEf,, sQ ft - 189 ltP ¡Et.!nBfCr Ê !19:553051 

tltfDtfF Ol lrloll Þulis . I P?¡IOD DP rtc. . t96l-60 

ttl¡ Prtr fElR PEtf( YBts Ptl¡ tlln Plri 

195 1 2.t3 1962 211 1963 113 r96t t?l 

I 965 212 1966 285 196t 27! 1968 2t5 

iltl = 222 sTD. DZu. = 6t colr. ol srP¡ - -0.5óll 

slrr 46612 fíl¡lPl¡t R lI st B¡ÍD6E 

CÀÎC¡liElT tREt¡ SQ Íll = t62 irP AEltEElCl - a20z102l92 

fúiBEn OP rll0ÀL PEtrS = 11 PE¡IOD Ot PUc, . t960-76 

:I::______::::l 

¡¡IttI B tî ioTtots IE¡R PETf, rglR PETI( IEÀ8 PETT ttl¡ Pt¡f 

1960 I 1r¡ 196 1 I 1¡ 1962 t28 t!t63 r05 ¡ 

Cltctllll lRll, sQ Íi Ê 

196¡t â9 t965 1tt 1966 29t t967 103 

69.9 lllP ¡EIEFE¡cE 

l0llr¡ oÈ trl0rl, DE¡ßS . 

¡67:799¡30 1968 2t2 196 9 235 1970 111 l9r I 3t9 

r0 PEaIOD oF FPC. = t967-76 1972 15¡ I 973 370 197r¡ tr9 1975 159 

1976 ?50 

ttlt PEIR tBln PEtÍ IETR PETT IIIR PETX 

1967 58 1968 70 '1969 2g 1970 q6 lizll STD, DEf. - 

1971 30 1972 

= 184 

97 cogl. oP sREt - 0.6lll 

36 l9?3 25 t97rt 38 

1975 38 1976 55 

ill!. ¡13 sfD. Dll. . 16 CO8F. OP SÍE¡ . 0.?¡65 

sIlE 4666C 

PUtrElO¡OT R ¡T PTÍITI'TOT 

ClTcñtlElll 

s¡!t 

tR?1, s0 Ãll 

PIPIIIIRT 2.08 llÀP BEP?REllc? 

& = f19:5830(2 

T1 SE BIIDGE ItrllBER ol tllfttll PE¡I(S = 12 PERIOD Op REC, . f965-76 

IE¡R PETI( YBI R 

CltC[lltl llltr 

PBT( TETR PEIX 

S0 f,i ¡ 

I!¡¡ PBIÍ 

51 ãlP nElraEIct I 

f 965 9.77 I 966 

rûill¡ 8.rr7 1961 

OF lllorL Pl¡Ís . 

t¡?:¡23382 

10.75 t96B ¡,70 

PEnIoD oF R?c. = 1970-77 1969 1,18 't 9"0 17,28 t9?t 5.72 1972 8.76 

t 973 6. Ê5 I 97q 1 

tll¡ Itlr tE¡R 

1.65 t9?5 

Pttß 

15.81 1976 9.05 

lEtn ÞEÀr IE¡F PETT 

I 970 ¡9.8 't971 ¡1.9 1912 35.0 1973 2¡. 

15.t 

I lElI 

t975 95.0 

' 9,72 STD. DEv. . 

I 97r 

3,7< COBF. OP sXEc 

1976 ¡6.5 

= 0.912t 

1977 11.2 

iBll - 39.9 sTD. Dtv. - 26.3 coBp. o! sßEr . 1.317¡ 

!t152'l 

0Pr8r R rî Poffi 

srrt t5702 ¡lrrSIIt R ÀT Dollt S¡lDOr 

cllc¡il¡Î tREt, s0 Í! - 8.03 nrp REFEAE¡CE - ¡3q:tt?209 

l0;¡l¡ ot llfltll P!¡fS t l0 PERIOD Op aEc, = 196¡-?7 

fEl[ PEtÍ tBta Pllß IEIN PETR tEf,R DETK 

t968 27,70 1969 29,35 r9?0 

1972 tt2.60 

21.35 19"1 St, tto 

1973 2a.20 197¡1 8. 80 1975 38.20 

1976 67,r0 1977 26.60 

tllf . 32,73 STD. DPl. = 15.7¡t coFp, oF sKE¡ ' 0.936ß 

torts ? 

l. LttD ûst cEltgtD It 19?¡ ?ROr cB¡Ss 10 Exorlc loRasl 

ottt rBo0l 601 o? TE? c¡ÎC8iErt, lBB EptRCI O! TEÉ 

PO¡ISÎ 0f Tf,t ?Lot ?toÁ 191tt-77 ¡Às ltoT cofsIDERFD 

10 Et slctl?IcrrT, 

Cllc8it¡T tREl, sQ ft¡ = 10.6 ñtp FE?EFEIICE = 

IlrllBER oP t¡lltÀL PPÀXS = 12 pErIoD ,p iEc. . 

il5:2 313¡E 

1966-71 

IEÀR PETÍ fEI R PEIT IETR PEÀß 

'1956 lEtn Pttr 

t63.3 146? 4q,5 t968 51. r t969 10.5 

1970 28.9 tg?l 2r¡,5 1912 25,9 1971 10.9 

t97¡ lq. c 1975 56. I 1976 26.1 ,t971 19. 5 

lEttl = r¡1.9 STD. DEv. É 41ì, I CO?p. OF Sßpt - 2.7595 

ÙoTES: 

l. THE 1q66 pLOoD nEltr ta¡s Io? pLoTlEfì ol|DÌp nûLE xo.2, 

BÛ1 rts IÙcLttDpD II îHE !ìEFM'IIOI CF lEn GttlRtl,rsDD 

CUEÍE POR îNE I8PI. 

18. NORTH ISI-AIID WEST COAST DATA 

slrr 166 I 1 

f,¡rEo R rT Gotcr slrt 3310t 

cEltGrEEt F t1 ñÀütIcÀRo¡ 

cllc¡lltT r¡lr, Se rr = r16 årp REI9EEXCE . rt9:206912 

lolBtn Ot rtfoÀL PE¡ÃS E I pE¡toD op Frc, ¿ lg?,Û-'7 

ÍEIS PEIK IEÀR PITI( 

1972 203.3 r9?3 151.4 

1976 100.0 1911 1 0?.5 

ll¡¡ PEt[ tBt¡ PEIR 

19rO 181.6 1971 138.3 

t97r 65.3 1975 89.3 

iltr ¡ 139,6 STD. DEy. . ¡l¡,8 COEF. OF SiEt = -0,¡271 

totts: 

l. tEE t962 ?¡,OQD pElK Or 303 CLËECS CtS ltxEi tS TíE 

LTRCZSI ¡f TflE PERTOD ß61-77. 

c¡lclr8lî ¡nl¡. s0 ri . 19rt 

lútBtl o? ttfttÀL pzrÍs - ß 

tzt8 PEt[ IIIE PE¡Í 

1970 467 t971 ¡8¡ 

t97t 6¡8 t9?5 640 

llll ¡ q85 STD. DE.. 

l¡P BEPEREIICE . tr1:lF:?9087q 

PE¡IoD 0F REc. - 1970-77 

IEIR PEIß TETR PE¡r 

1912 326 1973 t3e 

t976 558 1971 316 

127 COP,?. OP 'sREr - -0. 0f95 

totts: 

l. t¡t t96t FLq)D pE¡r Op l¡08 coiEcs tls ÎÀKEI tS 

în? LÀrcEsT r¡ Îf,E PttIOD 1936-?7. 

sITt 466 18 itf,crKl¡trt R lt €olBt srrr 33103 

TÍI|G¡EIII' R ÀT SN .ì BRII'GE 

cr?cHiEùr r8Dr, sQ Kt = 

luiBPn oP rftotl PPtK:i = 

IEIR PEIÍ 

1961 0¡7 

1965 40t 

t969 48? 

1 9?3 2A9 

'1977 3tt2 

iBtL = ll5 J 

rBt n 

1962 

1q56 

19rC 

l97q 

PPIÍ 

961 

808 

395 

378 

246 

11 

¡rP REFERTICT f19s366077 

PPRfoD 0F REC. = 1961-71 

YEIR PEIi IttE Ptlf 

1963 2r7 19ór tó8 

196t 190 

19?t 382 .1972 t968 ¡t6 

t29 

1975 643 19t6 t80 

sTD. DEl. = 21\ coEP. oP srtt . l.ttt¡ 

lolBs: 

l. ?n9 t962 ?L(þD pEÀf, tls T¡f,Ef ts 1[r L¡8GESÎ 

If TID PERÍOD 1959-77. 

94 

CllcBllll tllt, sQ ri s t968 l¡P AEPIRE|CE . ìrr¡3:689t76 

ll¡lll¡ Ol Àrrt¡L PEIIS = 7 PE¡IOD ol REc. = 19?0-?6 

tlt¡ Pllt IP¡N PEÀK IEÀR EETT IBTR PEÀtr 

t9?0 50t 1971 rt56 7972 3t1 r9?3 ¡33 

19?t 680 r9?5 722 197ó 5û9 

lEtl ! 522 SîD. DEt. = t¡3 coBr. or strE¡ E 0.1212 

tolts i 

1. lrt 1961 tLooD pt¡tr op 1168 ctiEcs rts TtrE[ ts 

lil LrnçtsÎ tt lEl p!ÌIoD t935-77. otDla BûLE ro.1 

otlt t[¡3 ptlt tot T¡¡s stTE ¡ls oslD tt lEr 

¡to¡ottL PLor ¡lD It ?Et DERITÀTIOi Ot ÎñE 

cErlttl¡stD ct¡tD tot rEB lnBr, 


stlt 33101 

crtcltttr 

lûtBlD Ol 

t¡El, s0 Ír 

llfoll. PEIf,S 

= 

= 

539 tÀP RA?ÊRE¡CB = rlll:?78308 

13 PERIoD 0F REC. r 19ó3-75 

SIlE 3l3lr 

CEI|GIEXI' I TT ÍIRIOI 3f109 

CrICE;llÎ r¡lr' sQ rl = 

fltltl¡ oF lft0ll Pll[S = 

q92 ItlP ¡EFEREICt = I131:965389 

10 PEnIOD oP REc. = 1963-76 

tll¡ Pg¡f, rtla PElf fEÀR PBTÍ IBIA PBIT IU IR PlTÍ 

196¡ 83.80 r96¡ t20.35 1965 112.19 1966 97. ¡9 

t96r 't21. 35 1968 86.8e r969 65.06 1970 82.84 

t97t 93,90 1976 r01.50 

tlll = 96.54 SlD. DEr. - 17.93 colP. or srEt = -0.0964 

::::--_-- _::: ll 

I|ITGICNPEO R IT ORB ORE 

tt¡t PEtr 

t963 r{9.35 

7967 296.00 

19?t 208.00 

t9t5 345.00 

llrr = 2¡0.28 stD, DBY, = 

:r::_-____::1:: 

CtlCElErT lEtr' S0 I! 63.5 

lolDl¡ Ol llllt¡l Pltfs = 9 

IITD PBTtr fE¡R PEIK 

t968 5.69 t969 3. ¡9 

1972 5. t0 1973 3.39 

t976 4.O7 

lll¡ = 4, t8 SÎD. DEv. = 

srtt 311 15 

IEIR PEIß 

t964 207.00 

1968 162.00 

1972 153.36 

CItCE;llT tBBt, 50 frll 33.2 

fltlBEl oF tltttll, PPÀrS = B 

ftl8 PEtÍ rEI¡ PETK 

1969 9.2tt 1970 I 8. C0 

f9?1 1¡-49 1970 22.97 

iEtf = 19.68 S?D. DSV. = 

srtt 

3lt t7 

¡IITÀXGI R TT TIIGIÍII 

C^TCEitlll rREf,r 5Q Kú = 

ItiBFR OP tittÀL PÞt[s = 

c¡lcnllExî tREt, s0 Ktr = 

¡I'IIB?R OF TT[UÀI, PETKS = 

TEIR PT¡T YEI R PE¡K 

SIÌT 333 16 

c¡TcftfFlt? rREÀ, SQ Kü = 

IIUiBPR OP ÀÙXI'ÀI, PEIÀS = 

tu ÀR P9Âf 

PETK 

1962 3tt¡.66 'EIR 1963 168,88 

1965 zit.92 1957 393.39 

1970 27A.57 1911 31q.71 

197q 365.00 1975 3s6.00 

lEtX = 324.77 sTD. DEv. = 

J32 

15 

it¡€tlol-o-Tz-to E lt ¡!¡¡ortt 

ll¡P RE?ERrlcE t12't.72t621 

PEnIoD oP nEc. = 1962-76 

YEIR PEIÍ IITR DIII 

19611 463.47 1965 q10.35 

1968 317.57 t9ó9 r93.t8 

1912 266.59 19?3 2t.t.90 

1976 332,00 

82.61 COPP. OP sil¡ ! -0.2315 

IBTR PETf, lBln PErr( 

668 

1965 256.00 1966 204.00 

l5 

r969 1t5.75 r9?0 29 3. 00 

1973 112.21 1974 362.00 

YPÀR PEIÍ 

1962 .251,61 r96l 190,87 19 ó4 402. r¡8 

r 966 229 .',10 1961 20C .7C 1968 259.79 

8r¡.73 CoEF. OP StrEr -- 0.2112 t9?0 213.35 19a1 233.1¡ 1912 233.10 

1914 239. R3 1975 130.22 1916 207.25 

ËE¡il = 268.21 SlD. DEv. - 

ËlP nEIERZùcr = t1222011811 

PERToD 0P R¡c. - 1968-76 

IEIR PEIÍ IETR PEÀK 

1970 3.75 1971 {. rl 

197q 3.74 19?5 3.90 

0.77 coEF. OP sÍEI = f.1780 

lllxct?ToRot a tT scflool 

lÀP ABPEREIICE = Xl21:743458 

PERIoD OF REC. = 1969-76 

YEÀR PEIX 

PEìß 

1911 20.01 'PIR 1912 13.52 

1975 28,32 t976 30.50 

7.35 COEP. oP sf,E¡ = 0.2075 

ñÀKOlI'TÛ R IT SB II9T BRIDGF 

CllcEiE¡î rRPl, S0 ri = 21,8 ttlP RETERB|CI = X121:83rt547 

IolBlE OP t[X0lL PPI(S = I PEIIOD 0P FEc, = 1969-76 

tllB PEri IE¡R PEIX rEtt PllK IETR PETT 

1 969 1 8.63 1970 26.49 1f171 21.46 1972 1 8. 50 

1973 15. ¡t 't 974 33. 05 1975 16.24 1976 30.8n 

lEti = 25.12 sTD. DEg. = ?.70 ConF. OP sR¡r = 0.221q 

19n3 412 

1967 2!A 

1 971 1C6 

1975 32tt 

ãElL = 259 

r7t 8 

196 tr 

196n 

191 2 

197 6 

oE0m R lr Îofo¡Itì 

r¡P iEFEFB¡cE - lt0r:556097 

PERIoD OF PEC. ' 1962-76 

tEtB Pt¡t 

1965 ¡09.2f 

1969 t85.2¡ 

'r973 r 1t.62 

80.r¡1 coEP. of sfE¡ = 1.0021 

otctRrrE P l1 tl8ltc¡iúlo 

1C?5 t1ÀP nBPIREÍCE = tt01:751165 

1l¡ PEPIOD CF REC. = t953-76 

PEÀf, 

24t 

224 

284 

245 

STD. D¡9. = 

YEIN PEIi YE¡R PIIi 

1965 330 1966 2ta 

195c 162 1970 21A 

1913 21 J 1974 212 

6¡ CoEF. oF sf,EÍ = 1.0385 

lÌolEs: 

1. 1H!'t9r¡0 FLOOD pE¡K OF 525 Cril'ECS CIS IIXFI tS lEE 

SECONT, I,ÀPGF5T IlI TIIF PîRIOD IAO5-"". 

srtt 3332c IETTIPÄPT R IT POOTBRIDGF 

C¡lCBfBlT tBEl¡ sQ Ãl = tBt¡ llÀP RtFPRFI¡CE = N111:960859 

ÍtlBER OF Àfi0ÀL gEl¡s = 11 PERIOD oP REc. = l96C-76 

IETI PBTi 

P?AK TEÀR PETK YEÀF PETÑ 

1960 26tr.61 'EI[ 1961 419.05. 1962 296.25 t963 369.56 

196¡ ¡63.39 1965 563.00 1966 446.93 t967 532.3¡ 

't968 ¡12.19 1969 3r8.0C '1970 246.68 1971 5q2.40 

1972 417. t4 1971 2q5.J5 19?q 230. 15 1975 259.68 

,1976 399.6¡ 

Illt = 382.08 sTD. DEY. = 108.03 coEP. oP strEI = 0.1963 

torts: 

1. ¡O COITECS ETS BEEI TDDED 1O ETCE PETK TFTFR 1972 10 

IILOT POI lNE EF'ECIS OP lNE ÎOIGTRTRO PO9EE PNOJECT. 

31301 ctlctilol R lT Elt?lfl 

clfcfillEIT ÀREÀ, 50 Kll = 

NUll8rìR oF ÀI¡tttL PEÀKS = 

YETR PEÀf 

PEÀI 

66lll 

t9 

1958 3960 'BIA 1959 1q80 

1962 2330 1963 11?C 

1 966 20F0 1957 2610 

1910 1r¡80 1971 2390 

197t¡ 3100 1975 318C 

Ittll = 23!7 sTD. DEÍ. = 

ËlP REFEFETc! lt38:56?055 

PERIoD 0P FEC. = 1958-?6 

PBIf, 

PBIÍ 

'EIF. 1960 1830 'IIR t96t 22AO 

196{ 29 30 1965 33¡0 

f968 2840 1969 1040 

1912 t8t0 r97! 2630 

1975 19ß0 

?76 coEr, o! srtl t 0. t601 

IOTES: 

l. 4C CUIECS 8lS BtEt tDDEt, lo ercn Ptli rPftl 19?0 IO 

TLIOU 'OB 

TEB EPIBCTS O? lNE ÎOIIGIRIRO POÍBB PI(NIC?. 

333 30 ltlcr¡of R lr ËrTtPr¡fl 

CrrcEllrf t8lt¡ SQ f,ã 911 ¡¡P RBFEFEHCP 1t101:81510(ì 

rotDrB OF tilfrtl PBtf,S = I PDBIoD oP FEc' = 1965-?2 

IETi PPIÍ YDIÀ PEÀI( TEIS PETf, tEÀ8 PATÍ 

1965 862.95 r966 693.73 196? 659.?9 1968 407.93 

1969 258.95 1970 372.06 1911 s71.26 1972 591.26 

lErt - 552.99 sTD. DEY, = 196.31 co?P. oP sÍE¡ - -0'0130 

IOçt5: 

1. ÎÍE ',l9r¡o PL(þD PEtÍ OP 1628 COIBCS ¡ÀS rÀRFr ÀS TfiF 

LrRGrSl Ir TEI PIRIOD 1905-77. 

2. l0 cùrPcs Rls B9B¡ tItDBD 10 fnE 1972 P?li 10 TLLOY 

lOB ÎE' ITTECîS OP TEE IOíGIRIBO POÍEN PBOJBCT. 

13t02 

srfc¡fot n ¡l 1l lllll 

cÀ¡CElE¡r rREÀ, sO Íü 2212 lttP RETEBETCE lt0ls?050ó7 

¡lttBEB oP rlt0rL PU rls = 14 PERfoD ot RBc. - 196Þ76 

fE¡B PEÀ¡ IEIR PETÍ YEIR PErr ttll Plll 

1963 ?l¡9 1964 1160 1965 1213 1966 t00l 

196? 869 1968 7q6 f969 r42 l9t0 619 

1977 851 1912 7tt9 1973 871 t97a 560 

't9?5 843 1916 679 

It Eli = 818 sTD. DEv. = 221 co'l. o¡ Sitr . 0.5176 

LOTEs 3 

1. 40 CUãPCS ÍÀS BEZX ¡DDED 10 E¡Cñ PE¡f, rPrER 1971 

?o trlor PoR 188 t?PtClS OP TEIÌ lolclnrRo Poltl 

PROJECl. 

2. lHE 1940 FLOOD PEltr OF 2294 CtlEcS ¡lS TrfEI lS lll 

LÀRGESÍ TT THE PIRTOD 1905-77. 

:Iï-____::991 


POIPHI' R ¡T PIEI;T 

C¡ÎCEÉtlT ¡BEt, S0 ßl = 29.5 útP BE"EFEIICB Nl28:5C7187 

lúlBtn Ot Àttltll PEIIS = I PERIOD o? REc. = 1910'17 

ttl¡ PBtf IETS PB¡K IEIA PEIÍ Y¡ÂR PEIÍ 

r 9?0 25.3 1971 33.5 1912 21 -3 19''3 l?. 1 

t9?¡ 26,7 19?5 ?9.0 1916 64,8 1971 111.8 

Íl¡l . 39. 5 STD. DEt, - 2't ' 6 coE?. oP Strt = 1.1{41 

¡otts: 

1. tSrs sllllol ¡ls rol t¡sED I¡ luB Rlsrortl. lllÀLlsls 

BlclttsB ol Drslrlcr 0P¡tRDs cttRYllûnB rÙ 1ÍA 

PiOEIBILITÍ PLOÎ, ¡ TREÍD iTBKEDLI DIF'E8EIT TO TEE 

RBCTOiTL OlS. r1 tls ûllcll?lr8 lÉETllPR Tñrs l^s ¡ 

RrlL DIPFEREÍCE, TXD îtrBEEPORE POSSIBLI I¡DICITIVE 

ot TEE riPr.ttB¡cE oF lT, Ecloll, on sIiPLr TIR 

ttsûLr oP osllc I sroRl RFCoRD- 

95

3950't 

flrlÀRt R tr îlt¡Ît 

;tP RIFEFEICE . Il09:92t805 

PlSIoD oP Fle. = 1969-76 stlt 3r801 

"ar""r"rn ttrl¡ sQ ßt . 725 

tlttt¡ o? trtotl. Pzlks - I 

rtlt PEtß ttlR PEIÍ IBTR PETtr TEIB PEIÍ 

t969 ¡51 19?0 q90 197 t 9q4 1912 t¡10 

l91t 5?8 r97{ 59t 1915 568 1976 114 

llll . 593 STD, DEl. = r70 CoEr. oP siEr = t.3ltto 

tolt3: 

T. ?EI T97I PLOOD PITÍ TI5 TÀilX 15 THF Lf,EGESl 

rt iE¡ PErroD 1900-76. 

Cl?CElEll l¡El, Sg Íi t 80 

IûlBll Ol lllltlt. PBlrs - 12 

ttl¡ Pgrf tElR PPIÍ 

7962 110.97 1963 16r.09 

1966 rf5,7¡ 1961 236,97 

t970 203,66 19"1 2tr0.23 

llr¡ . 17q.57 sTD. DEv. = 

srrE 

l¡343-1 

cÀlcRiEIT ÀREt, S0 KË = 

tolBEA OP ÀIl¡UtL PEÀXS = 

YEÀ8 PFTtr 

1 970 587 

I 9?q 3{0 

lEtx = 41? 

srrE 43015 

TET F 

t97t 

t9a5 

SlD. DEÍ. - 

2826 

PETT 

332 

370 

cÀlCRlrIT ÀREt. S0 [i = 137 

úllllBER oP rñ¡UtL PEÀI(S = 13 

IEIR PETK IEI¡ PEÀK 

1965 43.9 1966 46.6 

1969 25.9 r9"f 55.1 

¡973 10,8 r9t0 35.9 

1977 55. s 

iElf, = q5,2 STD. DtlV. E 

F 

::t:llT-r_lr_lIII]_::ll 

ntP REITREtlcE . ¡10q:0¡3?27 

PERIOD 0P lEc. = 1962-13 

tFtR PSIß 

196q 137.6C 

'1968 113.62 

1912 141.24 

YETP PFTF 

r 965 2 69.9 I 

rc69 1 33.61 

't9?3 78.0c 

55.10 COEP. OP SKEI - 1.1907 

fllPr ¡ lT tttllttllt 

ËlP RETEBE¡CE ' 165:5ó¡¡56 

PERIoD oF FEc. ' 1970-77 

YE¡N DEIX I'IE ÞI¡f 

1972 4t6 f9?3 tS2 

1976 576 1977 362 

104 coEF. OP SÍEB a 1.2112 

lC. IUIAÍTAWATU-RANGITIKEI DATA 

c\rcrlrrr t¡rl, so rt - 

301 

18 

lotDtB o? ttttttl. pElfs . 

tBr¡ PEtf tEra PEIß 

f958 tt25 t959 1t3C 

'1962 1360 1963 65r 

t956 558 1967 t¡?0 

t970 59¡ 1973 991 

r9t6 1250 1917 690 

lElf . 970 srD, I,EY. = 

tolls: 

o?lrr I rr rotPtft 

ilP lErgBttct 11512119192 

PERIOD 0P REc. = 1958-77 

IEIR P'Itr IEIP PE¡Í 

1960 t0t0 1961 1130 

196tt 1 r90 1965 1580 

1968 1090 1969 1020 

197tt 615 19?5 711 

339 COt?. O? sfPl = 0.0865 

1. rltu¡¡. tlooD Pstf,s poR tlrE GoRGt srÎE,3t80l, crRE usED 

tol lit ÞtRtott 1950-??. 

2. 18t t955 pLæD PElf Op 25¡0 C0;ECS lts TrrEi tS ltP 

LltGBSl rl ÎfiE PEnIOD 1920-17. 

3. lo tr¡oÀL PrtÍs ¡BFE rvrILrBLB roR t971-72. 

srtt 32502 itft¡tÎû R l1 FrrzHERBEnl BA 

Crlciil¡l lglr, S0 Rl . 3916 ñlP REPERE¡CE x1¡9:115331 

IEIEE¡ Ot tflûr'. Petls = 49 PE¡ÎoD oF FEc. = 1929-71 

tBt¡ gElf lEli PErß tErR PErt rEln Ptlf 

1929 1655 t930 1450 1931 tr50 1932 1795 

t933 t 4 t0 1930 1280 1935 1850 1936 2580 

t937 755 1938 1625 1939 1850 1940 t280 

l9lr 3260 1942 2090 t90l l?t5 190t t2q0 

t9¡5 2335 19¡6 1700 1947 2580 19t¡8 2000 

t9r9 2'35 1950 2045 195'1 1110 7952 t¡to 

1953 r5¡5 t95¡ 1284 1955 1810 t956 3t85 

t95? 1565 r95B tq90 1959 1715 t960 950 

t96r 2110 1962 950 1963 12¡0 196rt 2580 

t965 33¡5 1966 1110 1961 t765 1968 t380 

1969 560 1970 1060 19?1 2235 19a2 r33o 

t97t 930 t97q 1380 1975 t4t0 1916 2380 

1977 1260 

cttPtPt I lcl¡otl lolD ll¡l - l7¡8 SÎD. ItEf. = 7¡¡6 COEP. OF SIEÍ = 1.50¡¡2 

¡otts: 

lltP ¡EltRElcE = tgls 15t820 l. rtt t953 rl(xtD PErf op r¡5rr5 cnãEcs cts TÀfEf ts Tf,E 

PEIIoD 0P ¡Ec. ' 1965-77 Lltersl Ir In¿ PBBIOD t88t-1977. 

2. t¡t t902 rL(þD PllK ot ttotr cuitcs rts rlrE¡ rs 1ñg 

rEÀR PEIÍ rtlR Ptlt stcotD LlteBsr 

1967 55.5 t96g 

It 181 Pt¡tor, 1881-t977. 

31.5 3. llru¡l. 

1971 5q. q 

?LooD PEtf,s FoE ?f,E 

1972 rr.2 

¡olflrfE slnEEl SITE 

(fo?325801 9ERE oSlD toR TRE 

1915 58.5 1976 51.3 

pERrOtr 1912-77. 

11.2 coFP. oF sßE¡ - -0.1091 

srr! 32503 IttlftTrr R À1 IEBES Rotrl 

s1îE 

r0ql427 

CtTCllñPlÎ rREÀ¡ SQ (l = 

TOiBER OP TTXf'ÀL PEIKS - 

IETR PETI( IEIR 

t96q 62. r 1965 

1968 58,3 1969 

1972 11.A 1973 

1976 51. 9 ',1911 

iErI - 

IAIIGTÍIf,O R TT DTÍLOI IOID 

373 ñÀP REPERgIIcE = f8t!22l7tl 

'14 PEBIOD 0l AEC. - 196U77 

PETÍ tETR PETT 

51. 8 1966 6¡. q 

Ir1.? 1970 69.0 

53,2 197q ¡9.2 

65. C 

tll¡ Dtlf 

196? tl.0 

197 I ¡7.3 

1975 ót.5 

CIlCE¡lfT lRBt¡ SQ Íl * 713 ilP ¡BllREIct = fl50:5?3q91 

f0llll ol Àlt0ll EEÀIS . 22 PERIoD Ol REc. . 1955-7? 

Ilr¡ PEIK IBI R Etlf ISIR PIIK IEÀ.B PIIÍ 

t95s 905 1956 960 1957 ¡95 t958 395 

1959 625 1960 255 t96t 560 1962 550 

t963 ¡60 196¡ t?5 1965 6t5 1966 530 

1967 ¡75 1968 Slao 19?0 225 1971 1015 

1912 520 19?3 315 r9?4 ?40 t9?5 320 

r9t6 ¡70 1977 4t0 

llll - 539 gTD. DlY, = 23¡ coE?. oF sxE¡ = 0.5673 

rofts: 

1. ¡O lt¡tttl PE¡t ¡rs rtÀILtBLr loR 1969. 

srrE 1C03461 lOfEÀRfRO R IT TPPII DI' 

3251t¡ 

OEOTII R ÀT ILIIf,DILE 

c¡rcHlBll rAEÀ, S0 Ktl = f7À ¡¡p RB?EREICE - 1112a23672O 

llollBFR OP t¡ltt^L PEIÍS . 17 PERIOD Ol RBC. ! 1960-?6 

Prtf IEIF PEIT YEII PEri ttll Ertf 

198 1951 134 1962 198 t96l 222 

350 1965 228 1965 292 19ó? ¡81 

1{0 1969 246 1970 260 r97l 252 

't32 1973 108 t97¡ 264 1975 224 

264 

I EÀA 

1960 

I 964 

t 968 

1912 

1916 

IBlt = 

241 

STD. DEY. = tl cosP, oF s[E¡ - 0.3ó96 

cttc¡tttl rtlt, s0 tt = 

lplllr Ol llllttl. PBlfs = 

tt¡¡ PBrÍ ttrR Pr¡f 

t95¡ I t0 1955 155 

1958 125 1959 135 

1952 t70 t963 225 

'1966 190 1967 260 

t9?0 215 r97t 220 

197a 100 1975 250 

ñlll. 

lgl STD, DEl. = 

293 itP REI'REIICE = f,100:148573 

2I PEEToD or PFc. - 1954-77 

IEIN PEAT TETR PET¡ 

1956 32C 195? t45 

1960 70 196 r 100 

t964 55 re65 325 

1969 225 1969 r05 

1912 t80 t9?3 135 

19?6 17C 1911 r15 

89 COEF. oF SKEI . 0.95¡8 

srlE 

rc43(65 

grrfloÍoffr R tT DBsttt lorD 

ct?cBiE[Î tRst, s0 ßË = F8 rlÀP RE?ERElcE = t112r221715 

¡lliBER Ol t¡rrtÀL PBIÍS - '14 PERToD 0P ¡r:c. . 1962-76 cllc[ll¡Î rlEÀ¡ SQ fl = 266 

Iolll¡ Ol llloll PE¡[s = 24 

I ttR l,ETÍ TBTR PEII( rErR PnÀÍ tÄn Pllt 

t962 46.0 1963 10.2 1965 09.3 1966 37.5 lltl P'If IEÀR PEAK 

I 96? 55.1 'to68 ¡r9.9 1969 1973 53.8 19?0 7t0 1955 26.4 

39.0 

1 95¡ 

152C 

1971 62 5 1972 q6.8 

t9?¡ 28.9 I 950 385 1959 1305 

1975 53.6 tq?6 63. q 1962 705 1953 685 

1 966 580 1961 720 

iBli = l¡7.5 STn. ÞPY. . 11.8 COPF. Ot SfSl - -0,5\22 t 9?0 a20 1971 7ss 

I 97r 730 1975 600 

IOlES ! 

I. TO ITf,UÀL PETi TTS ÀVAILÀBLE IOR 196I¡. 

lllf. 719 SrD. DEr. = 

96 

srll 

t2326 


IÀIIGIEÀO R ÀT BILL¿¡CD 

ItlP REI¿REICE lt49:2?0251¡ 

PE¡IoD Op RÌC. = io54-77 

PETÍ YgTR PETÍ 

'E¡R 1956 235 1957 620 

1960 89C 1961 305 

1964 10!C 1965 60n 

1968 FlS r96q 6?0 

1972 9tC l9t3 110 

1976 7U5 1911 ¡¡50 

29d coEP. oP srB¡ = o'961R

SIlE 12 5 2!ì frRÀotll R ¡1 tc¡lnt¡r 3270ß RÀIGIITTEf B AT SPRTIGVALE 

cÀÎcñlu¡l tR?I, s0 Kr = 

xutlEFR 0P À[ilúIL PErxS = 

P¡ÀK TEIE 

IETR 

l95r¡ 

1 95€ 

1962 

t 966 

1 9?0 

1 974 

ItEIX = 

734 

PEII 

1rr5 1955 310 

250 t959 315 

160 1q63 195 

265 1967 325 

295 191'1 350 

315 1975 295 

262 sTD. DEY. = 

IttÞ REP?8EICE . l1¡9:392215 

PEIIOD oF ¡Sc. = 195¡-t7 

IEÀR PETI ttlR Ptlf 

1956 10 1957 155 

1960 s5 r961 610 

196ra ¡30 't965 335 

1968 215 1969 75 

1912 t50 1973 2ts 

1916 370 1971 310 

128 coEF. O? SKEÍ . 0.3?¡8 

cltcÍlBllT t[EÀ¡ SQ fl = 583 lllP EEPEREIICE , [123:50?q16 

rttBlB oP Àittttl PEtfs = t0 PBEIOD 0P RFc. = 1964-71 

IIIR PEIf, TEIR PEIÍ IEIR PEIX YEIR PEIII 

t96q 530. r0 1965 30f.0û 1966 382.20 1967 rr3?.31 

19ó6 249.2A 1969 203. Í5 1910 30 t. 01 1911 284.66 

1972 3r0.58 t97l r9?.33 

lBrf = 322.6? stD, DEv. = torr.24 cotP. OP SÍlc = 0.79?¡ 

srtt 32723 

rro¡cÀRrûPr R rf Pont¡t RotI) 

2\ 

rll¡ 

s Ilr 

325f1 

ClrCEiE[1 rREÀ' SQ Kl tt52 

ùlrlBER oP rxIûll ÞElf,S = 24 

IETR PP¡I( YETR PEÀK 

1954 Cr¡o 19,

S ITI 29202 RuNttiltcl I ¡t tllEttet 

cllcE;!¡I tnEl, S0 fi È 23qC rtP REtERFtCt r t16t:91¡t29 

llu;Bl¡ O? lfllttL PEIßS ! 2l PPRIOD OF REC. . lt57-71 

IETR PEIÍ IEIN P'TÍ YEÀR Ptf,f tllt ?tlt 

195? 630 1958 1025 1959 765 t960 lr0 

1961 t050 1962 82C 1961 7¡5 t96t rt!0 

t965 1075 1966 tllC 1967 850 t960 r00 

1969 .585 1970 t02C 1971 1 r80 1972 97J 

1973 6q0 r97q 935 r9?5 980 1976 965 

1971 t t60 

ñEltl = 896 sTD. DEv. = 211 

CorF. OP Sßlr . -0.619¡ 

2. 

stll 

BAY OF PITTTY OATA 

It6t0 

crtcEllt¡Î t¡tÀ, sQ fi l0llDlF ot llloll PE¡fs . 

tEl¡ PPtx frt¡ 

r960 r1.58 

1972 18.2r 

1976 27,35 

iEll. 2C.10 

PEtf 

1969 13.95 

t 973 r 3.85 

SrD. Dtl. . 

57 

9 

nllrtlrt ¡ lt s¡5 ¡ttDel 

ñtP ¡EttRttcl . 176t71O032 

PERIoD Ct l;C. = 196;-76 

YglR P;lf rrll ztll 

197C 21 .18 1971 23.t2 

1974 35. ¡6 t9t3 t3. t¡ 

7.81 cOtF. O? 3ßlr . 0.r0t6 

s rlE 

2922r 

CtlcEllllÎ rEEl, S0 Íi . 183 

XttrBER oP rrlútl PEtrS = 22 

IBIR 

1 955 

'1959 

r963 

1967 

197 1 

1975 

ñE¡I = 

P¡|IK 

PIÀÍ 

223 'E¡B 1956 81r 

?30 1960 42tt 

'.37 tq64 ¡71 

110 1968 555 

42t4 197? 322 

400 1976 566 

532 STD. DEc. E 

srrr 29231 

¡troBrtE ¡ ¡1 €otel 

lltP REPEnEtcE I161:90?508 

PEFIOD Ot REC. . 1955-76 

ÍPÀR PBrtr tt¡t Ptlf 

1957 156 1958 l9r 

1961 ¡¡56 t962 68t 

1965 531 1966 7r0 

1969 537 t970 r?3 

19?3 662 197¡ ¡56 

'147 coEP, ot StrEt . 0. 1738 

T¡OERO R IT ÎN TIRIIîT 

s¡1t l¡6 r¡ 

ctlciltf? rMr s0 Ít ¡ 

tüllB¡ Ot ¡ltorl PEIÍS B 

tEtB PEtf ttt¡ Pt¡¡ 

958 

21 

ftrlllr¡ 

R rt tl tlttl 

ilP ¡trt¡ErcE . t67ttt2¡59 

P'BTOD o? tEc, . 1956-76 

frl¡ PEtt( ttlt ¡lll 

1956 22a 1957 69 t958 t'r 't93' l?a 

1960 102 196 r 98 1962 368 1963 77 

t96¡ 12 1965 96 1966 86 1967 27O 

196e 116 1969 12C 1970 187 19?t r!0 

1912 150 19?3 12 r97¡r 122 tyts 96 

1975 r r0 

lllt - ll9 STD. DEt. È 74 coEl. oF SÍEl . 1.t:mt 

toÎts: 

l. TtE OüÎttî pBOi Lr[t ¡o10r1l rs 38,8Ri opslrrlr. 

CllC8ltfl tllr¿ SQ lf - 

r¡t{llr Ot tlloll PIIIS . 

tttt Pll¡ IEIR 

t9t0 r15.0 191 I 

'19?¡t 211.0 1975 

.llll ' 156.0 

sttr 29212 

STD. 

PIÀÍ 

3?3 llP REItREIIcE = ll62:239578 

I PERIoD 0P FEc. - 1910-'11 

YETS 

203.0 1972 

t?t. c 1916 

Pttf 

41.9 

173.0 

;trGoREr¡ R rT slúrDtlJ tllt 

IETR PE¡I 

t973 87.9 

19?7 225.0 c¡lcÍill ¡Elr sQ fl ¡ 179 rllP lltlPBlcE . 167r8l6¡ta 

¡ltlBtR Ot ltl0ll PE¡fs = 9 PrRfoD or ¡Ec. - 196ç76 

ttl¡ PEtf fB¡n PETf tt¡R PEt( rtll Pt¡¡ 

t969 292,0 1969 86.0 r9?0 t57.0 1971 86.0 

1972 10¡.5 19?3 53. 0 r97¡ rç0-0 1975 12t.0 

t976 222.0 

rll¡tlrtflt R rT iÎ Eo¡,DStORlt llt¡ Ê l¡6.5 sTD. Dtt. ¡ 

76.7 COll. oP sfll . o.totl 

ctlclltfÍ rr!t, S0 fi c 38.8 

l0ilE¡ O? ¡lf[rl PSIIS q 

= 

ttll ?ltf ttlR PEtÍ 

ttó? 63.9 '1968 r0.5 

r9?1 76.8 1972 t 55.2 

t975 173.2 

rl¡l . 

srtr 292¡f 

89.0 Sllr. DlV. r 

cllclittT r¡ll, s0 tt . 

tltl¡t¡ o? ltfoll. Pr¡3s. 

36. 3 

9 

lt¡t tEtf tttt PBI¡ 

t968 2t.20 1969 7. {9 

1972 2t.80 1973 ?9. 80 

19t6 2a.29 

Itll . 27.56 srD. D!t. . 

itP BIFEREICE = !158:022696 

PEI¡OD oP ¡lc. . 1967-75 

ttr¡ PEtr YtlR 

1969 62.5 t9t0 

1913 6¡. t t974 

¡3.9 COE'. Ot SÍll - 

PETi 

84. I 

50. 6 

1. ¡687 

¡f,¡.¡GttEo I tÎ ¡lIRl 

l¡P REllEExcE r158:25577lt 

PE¡IoD oP aEc, . 1968-76 

tEtB Ptlf ll¡R PEltr 

1970 25.20 1971 ¡7. ¡0 

197¡ 29.60 1975 39.30 

11.25 COEP. O! sÍtl. 0.lt6t 

5r1l 15008 

ctrctlltll rREÀ, sQ fl llg¡ 

IolBt¡ oP t¡f0tl, PEr[s . 28 

IDIR PETi IEII PEII 

t9{9 3t.8 t950 19.t 

1953 3a,2 195tr 26.0 

1957 27.3 r9s8 58,5 

r96t 21,0 1962 ¡7.9 

1965 63.8 t966 ¡9.0 

1969 3C.9 1970 60,9 

197! 26.8 19?¡ 36.¡ 

ñEtl r ¡r.6 SrD, DEt. .. 

slrt 

r5¡1? 

RlrGIlÀ¡f,I ¡ lt tot¡tlt¡ 

itP tarBBatct 

PII¡OD OF REC. 

?tlR Pttñ 

1951 2r.6 

1955 26.8 

1959 ¡9.8 

1963 3?.5 

196? t2r. I 

19?t ¡6.5 

t975 36.8 

¡ tl6: ll!51¡a 

. t9l!F76 

tllt PItr 

1952 ¡9.O 

1956 a2.7 

t960 29.9 

196¡ rO.0 

1968 15.6 

1912 36.7 

r9t6 56.2 

20.2 colP. oF srBl. 2.6gla 

¡oTts: 

l, ÎÍE tq67 TLOOD PEIK r¡s rE! FESULÎ Or CICIO¡E DItl[ ltD 

rls TtrBx Às llrF Ltnctsr r¡ î88 pERIoD 19¡0-77. 

8[rGIlÀIfI B tî 1r ttto 

c¡tclllr? lrll, sg ¡! 89.8 

lu¡lll Ot rllull. Pllf3 . 9 

ftll Pllr rllt PtlÍ 

1968 38r t969 28r 

1972 329 1913 15'l 

1976 255 

Ittf ¡ ?Sa sTD. Dlt. . 

rrrr 298 18 

tm? R tÎ Í¡r10Ítt 

ilP lE?ltgrcl . 1t61r71630? 

gIllOD ot ¡lC, . t9ó0-7ó 

llln Prtr tät Pt¡[ 

't9t0 19t r9tt 327 

197¡¡ 20r 't975 171 

8l COll. ol sfEl ! 0,2¡¡l 

H011 R l? ttlctttltt 

cllc¡illT rIEt, sQ ll = 2091 ltP EEPEREICE = l7?:2aâ153 

¡ltltllR ot ÀIfolL PE¡Ís ! t6 PEsroD oF lEc. . l95t-66 

llt¡ PErfr fErR PEIß rDrn Þtrk ttl¡ Dtlt 

t95t 309 1952 t9t 1953 33 I 195¡ tt9 

1955 t89 1q56 212 1931 370 r95t 3t9 

t959 219 1960 t9t 196t 235 1962 37t 

1963 190 196¡ 272 1q65 595 19ó6 2t; 

Ilrl . 293 SîD. DEl. . tl1 Co!t, or slEs - 1.62¡2 

torBs: 

l. TÍE 19tq pLOOD pttr op 784 CUiBcs rts Ttfli rs T8r 

IIFC'ST tX |!|llB D?RloD 1925-66. 

2. T[tS S1¡lrol fls tot rsED Ir TRt 8lcrotÀL rtrLtsls, 

BECÀûS! TEERE tnF SIGirPfCtIl ptRrs o? THp crîc[;?tÎ 

III BOTII IEÌ: BIT OP PLT¡ÎY IID XOBfB :SLIFD EIST COAS' 

RFGIOilc, ttlD !H!: lBEilD rX Tfi! pROSrBtllûy pLoT ¡,lt 

lx-EETrEEr TÍOS! PoR ÎñE lfo B'GIOIS. 

cllctlltr rlll¡ 30 ri - 027 irP nErlnlrcl t r1ól!52r¡40 

l0llll ol ¡ltttll PtIIS ! 6 PB¡¡oD 0? ¡Ec. . l97t-76 slr! 33307 

¡llctiol R rr f,EtfrÍllBts 

t¡lt Ptlr rlt¡ Pl¡f IEf,f P?l[ rttt Pf,IT 

19?t t26 1972 636 197! 329 r97¡ 837 

19t5 39r r9t6 636 

Crlclllll rllr' S0 ñl - 81.3 llP nl?zRt¡cE - I1l2:0899q0 

f0lllt ot lfr0rl PEtrs . 1l PERIOD 0t REC, . 1960-10 

rl¡l . lto 51n. Dll. . t3¡ Cott. Ol Sfll - 0.6212 IEI¡ PEÀß I'I¡ PEII YI¡R PIÀi IETR PBTT 

tolrl: 

1960 ¡6.7 t961 ) 97.5 1962 32,a 1963 2a.2 

1. ltt t9¡t ?L(þD Dl¡f ot 1237 cortcs rts llrtr ¡s Î¡t l96t ?1.8 t965' t¡2.8' t966 5T.8 196? 69. B 

l'llelst It ttr P¡¡loD 19¡0-77. ûrrlrR RnLE fo, I orlt 196t ¡r.9 1969 :16.6 r9t0 21.3 

ttrg Dt¡¡ ?o¡ tE¡s sÎll ll3 oslD li lFr BEGrollL Prol. il¡t - 09.7 STD. I'EY. . 22.2 coll, oP SFES É 1.0221 

98 


sllt 333 2[ i¡[e¡TEPOPO I It rElEltfir 3. ÍIOßTH IsI¡ITD tr¡sT COAST DATA 

CÀtCEtElT rBEr, SQ fl = 31 

llliBER OF tffttll PEtfS r I 

I8¡8 PETf, TE¡R PEIf, 

1960 ¡9.79 1961 8{.9q 

t96¡ 35.42 r965 29.79 

il¡t = ¡1.56 s?D. DEv. = 

srlr 33307 

itP BEIERltcD = I1122062921 

PEBIoD cF FEC. - 1960-67 t54 t0 

IETB PE¡Í IBTR PPTI( 

1962 21.25 r 963 1 6.50 

1966 42.84 1967 51.97 

21.63 coPF, OF srEt = 1.0182 

¡IIGÀIUT R IT TB POAERE 

crfcEiEfT rntt, sQ rt = 28,2 lltÞ SElBlE¡CE - ¡112:087904 

l¡tlDlr ol rlfûrl PEÀÍS = 1n PBBIOD oP REC. . t967-?6 

rlt¡ PEtr 

PEIK 

IBIR PEIÍ 

1967 5A,O2 'EIR 1968 31.53 1969 26.20 t9?0 11.20 

1 971 r0. ¡9 1912 16.01 19?3 r¡9.39 1974 1R-22 

t 975 21.6t 1916 29.69 

lEtl . 30.86 SrD. DEY. = 14.33 coEP. oP slEr = 0.8759 

tE^n PEtß 

srtr 43112 

clTcFrgtT tBlt, s0 rr = 228 ItP REtEnE¡cl . f,85:r101680 

folBl8 Ot ll!ûÀL PEltrs = 16 PEnIoD oP RBc, = l'161-76 

rtlt PEtr tElR pElf, IETR PBIX TEIR PBIf IETR 

196r t6.2 1962 36.5 1961 11.4 t964 12. 1 I 967 

1965 33.5 1966 19.9 1967 1 1,2 1968 17.1 197 t 

t9ó9 19.1 1970 L2.7 191 t 21,9 1972 11.2 197 5 

t9?3 17.O 1974 26.2 1915 lq.3 1976 15. 6 

¡Etf{ = 

15.2 CoEF, OF sRE¡ = 2.1165 

llll = 2¡.8 sfD. DEv. = 

rotts: 

1. TEB 1967 PLOOD PPÀr 9ÀS rFE RESÛ¡,Î 0P CICLO¡E DrlÀft À¡D 

tÀs Tl[ut Às ?EE LtacEsr rx rtE PEBToD 1940-77. 

q48 

tl 

CIlcllllE¡T lnsl¿ SQ Il = 

X0lBß8 OP ltltrlL PBIÍS = 

IETR PEI( fE¡R 

1953 67.3 195C 

1957 r¡9.7 1959 

1961 27,t 1962 

1965 33C.0 1sC,6 

1969 59.7 1970 

1973 54.1 19"4 

1977 5?.0 

IrrorrPr R rr REPoBoÀ srtE 15¡32 

srrE t0¡34 19 POf,II¡ñEÙUT R TT PUKEÎIIROÀ 

cllc8lltl lf,Er, sQ Ki = 

ItlBES 0? ¡ftnÀL PEtÍs = 

IEIi PEIß IB¡R PEàK 

1951 20.0 t96s 62.3 

t968 12.7 1969 11.9 

1972 21.8 1973 18.3 

1976 33.7 

iB¡Í = 27.6 SID. DEV. = 

srlE 1003428 

--------ï----- 

IIIS PBTÍ 

1965 3¡.0 'EÀR 1956 

1969 31.2 t970 

1973 59.0 197tr 

CÀTCFÉEII! TRET, SQ RII = 

IUIBEF OP r¡fûrl. PE¡KS = 

lltP RE¡zREIICE = ¡75:213145 

PEEIoD oP REC. = 1964-76 

fEÀR 

19 66 

1 970 

19 74 

PETf, fÈTA PBÀK 

15,2 1967 41.6 

24.6 l9?t 32.0 

19,3 19?5 \0.7 

14.4 COPP. oF sßE¡ = 1.1932 

CllCSllrT lEll¡ SQ f{ll = 210 lltP FEPPREIICE = n85:54t802 

¡0!BER Ol Àltûrl PEIÍS = 12 PERIoD 0F REc. = 1965-76 

NOlES: 

1. lHS 1958 FLOOD PE¡Í I'¡S 18E ITRGZST III lFE PI¡IOD 

t870-1977. 11 ¡als EICLI'DED PROË TIE Àüf,LtSrS olDt¡ 

R0Lt ¡o.3. 8tt1 ¡ts rfcLttDED rr r¡B DE¡lvlrro¡ ol 

r8E GEIIERILISED COFYE PCR 188 TREA, 

2. TRE 1964 FLOOD PEIK tts PROBIELI 1f,8 SECOID LlSCtS? fl 

üE¡OR!. IT ¡ÀS lttElr ÀS lnt SECOID LTRGEST l¡Oi 1905 

(¡flB[ TBE rtfE RFCORDES ¡ÀS TITSTILLED) TO 1977 

If,CLT'SIYE. 

53¡ 

25 

¡EIRIrtiI I rr cllt:tl 

tlP BETBRI¡C! Ê 186:191C23 

PEnIoD 0F RBc. - 195Þt? 

PEIÍ TE¡R PEItr ÍITR 

64.9 1955 52.6 1936 'III 79.6 

211.1 1959 ?r.9 1960 5?.t 

113.2 1963 64.8 t96a t33.0 

183.1 1961 310.{ 1968 t3t.? 

306.9 t97t 1t7.3 1972 66.3 

.8ß.4 1975 65.1 .r9t6 tt6.0 

ËEt[ s 120.5 STD. DÊy. . 90.9 COEp. Ot S¡!¡ - 1.!rt8 

¡rrG¡r¡I¡I I ¡1 ¡ODûlt¡I 

CtrcllEf,T lREr. sQ Kll = 2318 irP altl8Efct . a862222A22 

NUIBEn oP lf¡ûÀL PEÀI(S = 10 PERIOD 0t lzc. r t96?-?6 

PEI ( 

498 

325 

147 

260 

tEtF PSIX 

1968 185 

1972 112 

1976 339 

SÎD. DEÎ, = 

CÀTctrlllll¡ ÀlEt¡ SQ Kll = 

IIU;8ER OP ÀT¡OT.L PEIKS = 

I ETR PIIK TDTS 

jt 

951 262 1952 

1 955 272 1 956 

1959 283 1q60 

1963 1111 1964 

1967 !c9 1968 

1971 3F6 191? 

1 975 450 

ctlcBl!|Î ÀRErr sQ Il . 207 

llllDll O? tlto¡L P¡lf,S E I 

ttl¡ PEIR ttlB PEtr 

1969 327 1970 385 

1973 62 1970 rs5 

illl - 218 STD. DBY. = 

YEIR PElf rtlR tt¡l 

1969 9t 1970 t95 

1913 117 19t¡ 212 

148 coEl. oP sflÍ = 0.7157 

:11ïl-:_l:_::*:l_1::: 

l¡rl0 lÀP nEFEnElcE - ¡?8:17¡076 

25 PERIoD oP FEc. = r95t-75 

PEÀT IEÀR 

219 1953 

258 r95? 

136 196t 

616 1965 

289 t969 

1tt7 19?3 

PETK PII¡ 

1 rto 'ETN t95¡ 2¡0 

160 1958 tt7 

3?C 1962 2t2 

19c 't 966 76a 

"?0 

t970 t93 

2c¡ t9?4 t2â 

TT8O8AÀTTRÀ F TT OEÀXfTRI R'ì IEII = ?Bt STD. DEV. = 234 coEF. oP sflB = 1,50t2 

PEII YEIR PFAI( IBII 

17.9 1961 F2.5 1968 

42.9 19"1 28,C 191?_ 

ò8.6 1915 30.8 1976 

PEIf 

35. 0 

47. c 

54.1 

iEIl = q4.9 STD. DAg. = 15. 1 CoEF. oP sXEí '= 1.4881 

srrB 1C4345C TOIGIRIRo I l? ltttltcl 

112 

2C 

lilP ¡ElERPfCr . it02:30000¡ 

PERToD oP REc. = 1937-76 

Pll¡ 

280 

1225 

3t5 

r20 

J27 

IEIR PEIK ?BTR PEÀf, ÎETR PEIÍ I'I¡ 

1957 2tt' 1958 1915 1959 245 1960 

1961 270 1962 345 1963 300 t96¡ 

1965 54C 1966 r¡',t0 1967 826 1968 

1969 110 1970 457 1971 188 1972 

f973 230 1974 386 1975 :113 1976 

;BÀII = 497 sTD, DEv. . r¡07 CoEF. oP SklÍ . 2.735a 

srlE 1043460 loHclnrEo F rr Pûfll¡lltl 

SITI 

155tq 

8lIÀf,tTtÍE I t1 8ñtr¡?tIF 

C¡lClü811 lll¡r S0 Kll = 1557 llÀP nEF¿nEilCE = 

¡ltllgl O? ll¡t f,I. PEIKS = 20 PERIOD C! nEc, = 

flt¡ 

I 957 

1961 

I 965 

1 969 

197:t 

ll78:43619¡¡ 

't9 5t-76 

ÞETf IE¡8 PEAI YEÀR PB IR tElR PStü 

638 1958 1166 1959 367 r96C 657 

27t 1962 8',r6 1963 r¡90 1964 2110 

22\O 1 966 550 1967 r 711 1968 520 

620 19t0 2C6A 197t 1 289 1912 642 

350 197tt 580 1975 1t5 19?6 7¡0 

lEtl = 9¡3 SÎD. DDV. - 639 coEF. oF skrc = 1.2069 

sltt 15536 

¡¡I;ltrt I tT oGILtIts EnIDca 

rlP REFBREIICE = i8?:55r818' 

PEIÍOD 0P REC, = 1969-16 

PEÀT tIÀR PETR 

'BÀI 1971 196 1972 142 

r9?5 187 1976 251 

101 COEF. OF SKE9 = 0.334¡ 

CtTCSllE¡î ìRBt, SQ Íll ll95 ttP BgFERBTCE - 1112:31i1910 

IUTBPA oP Àxtfttl. PEIßS = 11 PERIoD oP REc. á 1960-t6 

YEIR PE¡f 

PE¡i IEÀR PTTf, ttl¡ Elll 

1960 212 'EIR t96l 181 1962 2g I 1963 21' 

t 96{ 869 1965 619 1966 302 1961 ?09 

1968 261 196q 272 1970 370 1t71 2a9 

1972 3C6 1973 192 1914 3 19 tt?s 260 

1976 360 

lltf = 353 STD. DE!, - 19q coEP. o? sßlr ' 1.7tlg 

lrofES ! 

r. ÎÍE 196¡ PLOOD PEIÍ f¡S îtßEr lS SECO|D Lrloltt ll lll 

p?Rron 1905-77 (SEE tOlPS POR Srft l0r¡3t59t. 

CllGllllr llllr SQ ftl = 

lûllll ot llt¡llL PEIrS = 

ttll Ptrtr tttR 

t95t 1068 1959 

t9n2 800 1961 

1956 555 1961 

1970 r î57 r97r 

t97l . 660 1975 

PEII 

256 

475 

2058 

705 

617 

llll - 920 SrD. DEl. . 

6q0 t9 

lÀlOERl R tT GoRCE C¡rBLBllr 

ItP BtPlFEllcB f?8:7 37921 

PERIOD oP RBc. = 1958-t6 

tPÀR PETÍ IETR PSIK 

1 960 6\2 196't 209 

1964 217A 1965 t0t5 

1968 5?6 1969 tr26 

1972 8r¡3 r9r3 342 

1976 920 

529 COPP. OF S¡Er = 1.6132 


99

ïI-'_____ ::19: 

lt¡IPt0r n À1 i¡¡lÍt¡lrt BF 4. CENTRAL HAWKE'S BAY DATA 

c¡lClllll t¡ll, S0 rl = 

totll¡ Ol lllotl' Pllfs . 

1580 itP sEPlaExcr t89:268623 

15 PERIoD oP REc. = 1960-7q 

PEItr IEII PETÍ 

1750 1963 568 

976 196? 11tt 

r 1t5 r97t r4¡5 

517 

llr¡ PElt ttrn PEr( rEtn 

1960 28s0 1961 tqts ß62 

t96t 550 1965 1820 1966 

t968 1100 t969 qt6 l97o 

1972 998 1973 t239 197tt 

llÀt . 1167 slD. DEv. = 6ql COEF. ot sf,E¡ = 1.2631 

¡otts: 

l. tt! 1876 ¡tD t9¡8 TLOOD pEtÍs OF 3058 trD 3172 C0iECS, 

¡lsPtctltl¿t.rERz ltftf ls lEp 1¡O LlncESr pBtÍs 

¡¡ TÍB Pr¡IOD't876-19?7. 

SITE 

23001 

cÀÎc8íEIT tREr, S0 Ktt = 193 

lluãBEF OP t¡¡UÀL PETKS = I 

IETR PETK fETs PE¡T 

1969 n5 1970 298 

1973 365 1914 f q I 

T0lrBÍ0RI R tÎ ÞrftllPo 

llP ¡ETERE;CE . t134:21t367 

PEAIOD 0P RBc. = 1969-76 

YEÀ8 PU ÀÍ 

1971 805 

19?5 771 

IETR PETÍ 

1912 250 

1976 811 

ItEÀtl = 47 2 STfi. f)Ey, = ?87 coEF. oP srEr = 0.2559 

sIll 

C¡qcllBft llEl¡ S0 il = 18t 

IOltlS or ll¡orl PE¡rS = 12 

trl¡ Ptt[ tE¡a PElr( 

r955 r9!.29 t966 117.60 

1969 95.33 r9?0 rq2.09 

1973 1t2.71 r97[ 175.73 

rlrt = 'l¡¡.01 STD. DE9. - 

r8¡REEOPII R ¡T ÑfLLTR¡EI 

llP REFEnEßCE = i97:061529 

PARIOD 3P REC. - f965-76 

YEAR PET( 

I 967 127 . 10 

1971 1¡1. c2 

1975 t¡3. 1 1 

tEta PEti 

1968 142,4t 

1912 90.38 

1976 226.20 

38.79 COEF. OF SkEg = 0.7724 

SIlE ?3C02 lOT¡EXÛRT I TT REDCLII?E 

cllcBlEìtT AnEÀ, S0 fl - 826.1 Ëtp RE?ERElcE ¡t3¡t:255320 

ttlBER oP tùtûf,L PETIS = 3t PERIOD f,p FEC, .t92¡-65 

= 

srtt 

t9711 

C¡lClllfT tlBr' S0 Íl = 171 

lúiDtR Ol tllltll PtlÍS = 

IETI PETT TETR PB¡R 

1965 335.?? 1966 138.51 

1959 103.64 19r0 336.01 

l97t tq8.62 1974 4e.22 

Í¡IiGIROIIII R TT lBRRTCF 

ËÀP aEPEBEICE 'tt [89:325746 

PERIoD oF nEc. = 1965-75 

IEIB PE¡T IETR PETtr 

1967 97. 00 196A 221 .9?. 

1971 285.61 1912 125.91 

t975 I 9.09 

lll¡ - 169.85 STD. DEg. . 1t0.92 COEP. ôp sßF¡ = O.¡q76 

218 íì I iontxÀ R tÎ nloPûfel 

C¡lCHllBlll tREt, S0 KË = 237î ðtp nEFEFEXCE = ¡tt5:5¡t2895 

NCüBnP oF llrutL PEAÍS = 19 pERtoD op FEc. = t95g-?6 

YETR PXÀX I?IF PEÀK IETR PEAR IEIR P'Ti 

195S 926 1959 ?16 1960 1229 t961 36ß 

1ç62 q35 t963 495 1964 450 1965 120 

1966 l1¡5 t967 14t9 1968 768 t969 ¡03 

1 970 6 t0 1911 163 1972 {01 1973 920 

1974 t 397 t9?5 4tO 1916 t¡48 

ItEl¡ È 818 STD. Dgs. = 167 coEP. oP sxEr . 0.¡t701 

TOTES: 

l rBB t93A FLOOD pFÀK rts FS?rrtî8D rT 5371 C0'DCS. r1 t¡s 

FICLTIDFD pROt lFp ¡tatLtsrs 0¡tDER Rtt¿E to.3, r;D ?BOtl lir 

DERIfIIIOII O! IIIP GEf,E¡II,IsED CITRYE POR T8E T¡lI. 

:l:_"______3ll 9: 

TIOHTßI E ÀT GLE'?ILLS 

cÀîcEÍEIÎ r¡Pr, S0 iñ = 9q7 ñtP nEPEREI¡CB 1114:072775 

lUlBFn oP Àf,IûIL PE^¡S = t3 PERIoD oP REC. = 1961-76 

PFIK IEI R PEÀT IEIR PPIX lErl Pl¡f 

q03 t96 5 tút2 1966 511 1967 6a2 

tc0 t 969 t3c 1970 62A 1971 290 

tF7 1 971 316 197¡1 606 1975 290 

q 34 

I ¡t8 

1 96¡ 

t96B 

1912 

1976 

ItBt i = 

05 9 

22s02 

crScHÍEiÎ rREt, s0 Rt - 

LûlBF8 oF ttfutl PEtfS = 

rEta PEIX t?t¡ Prtß 

sTD. DA9. 240 COEr, Or SkBt - 0.7261 

25tt 

1l 

BSr R lr srlPutel trIDet 

FIP EE'ERBICB z t124.241523 

PE¡iOD oP REc. = t96t-?6 

rBrn PErÍ ttlR Pllf 

1966 125.21 r967 213.5t 

r970 126. 30 1971 372.06 

r974 rt99.98 1975 91.72 

't96¡r 27.Ctt 1965 2¡2. ¡6 

r968 528.90 1969 31. tq 

1912 q2. ?1 1973 1?0, ¡8 

1976 281.30 

lEtl = 215.63 sTD, DEr. E 164.90 cOtF. op sxrr E 0.06t6 

IOIES: 

l. lEt 1938 pL(þD pEt( ¡ls tSTrñtlED 10 BE tr Erclss o! 

1931 Ctrttcs. Iî 9¡s lxcLoDlD FBO! TßÌ tttltsrs ûtD!¡ 

altlE fo.3, ttD ptot tÍB flERrttTror op tfp GBIEBILTSID 

contE ?ot rllP ¡REl. 

üEtI = 614 SÎD. DEV.

slrt 2¡201 

lOf,ITO(T R IT 8ED BRIDGE 

ioîûtRt F IT tooDsfocr( 

CllcÍlltr rBll¡ SQ Il = 

lúlBg¡ Ot rl!ûll. Pll¡s = 

tt¡t Pttf tE¡B PEIÍ 

1923 l\12 1924 1727 

1927 2265 1928 t 161 

1912 1tt12 1933 1172 

1936 2548 1937 I 161 

19¡7 931 19118 1897 

1951 þ3q 1952 1076 

'1955 1\12 1956 2237 

't960 1019 1961 1359 

195{ !l¡ 1965 1557 

1969 333 1910 1090 

r9t3 626 1911 2500 

iBll = 1380 sTD. DEv. ' 

srlE 5690 1 

cÀlcfillEllT tREl, S0 fr = 

IIÛ;BER OP ¡XÍI'ÀL PEÀKS = 

IEÀN PEÀK YEIN 

1967 19 1 958 

197f ttl 1912 

1975 s3 1976 

59 SrD. DEY. ' 

2380 q¡ 

rÀP !E!EnZÍCE = Ít30:338119 

PEBIoD 3F PEc. = 1921-16 

IEIR PETT IETR PBIÍ 

1925 1112 1926 2432. 

1929 291f 1931 178ü 

193rt 1133 1935 198? 

't 9 38 2e13 19q4 8q9 

19q9 2898 19511 2690 

1953 1115 t95r¡ 1q16 

1957 1218 1959 1415 

1962 764 1963 't472 

1966 1tt1 1968 1695 

1971 2243 1972 5A2 

1915 1 585 1916 1244 

837 cOEr. oP SIE¡ = 0.ltlll5 

tolEs: 

t. tttotl Ptl(s mR TEE BLICi BRTDGE SÍTE([O.232i{21 íERR 

nsED POA Î[E lEl85 1923-60. 

2. TEt rlfûll FLOOD Pgrf,S POR 18S lEtns 1939-46(EXCLllDrllG 

191¡{l rtD 1958 ¡EBE f,to¡r rO BE LBSS T¡lt¡ 283 C0iECS 

(1OO0O CUSBCS¡ rrD 'EFE 

rSSBIED rO BE 255 C0iECS (9000 

c[srcsl. TIESE PBlfs IERE 0sED rf, T8E FRBogBrCt tl{lLYSrS 

POB lRE SiTE BI'T ¡OT III lII' BEGIOIIII ÞLOT. 

3. fo tirûll PEtßs ¡lRE lrtILIBLE FoR 1930 tfD 1967. 

t. TRS 1917 PLOOD PPtf, OF 3964 CUüACS lls TÀf,EÙ lS lRE 

LIBGBSÎ fr rñE PERTOD 1868-1976. 

srlE 

232Cq 

OTÀI¡E I Iî GLE'DOT 

c^TcftiSl¡T AREÀ,5Q (ü = 24.3 ürP nEPEFEÍCE . [141:015921 

Nlt;BER OP ÀilUnÀL PEAKS = 12 PEaIOD 0P ¡EC. = 1965-76 

YEAR 

1 965 

1 969 

1 973 

¡Etil = 1ñ.51 slD.0!Y. = 

SrrE 

PEÀT YEI R PEÀK ÍFTR PETß 

1.19 1966 15.0C 1961 6.89 

4. 11 1970 \.51 1971 16.5c 

7,86 1974 37,31 1975 7.06 

2321î 

IEIS PP¡K IEIR PEÀI( 

1966 43. t1 1967 r¡1.57 

1970 14.75 1911 95.53 

1974 115.40 19?5 24.88 

ItEtX = 48.71 STD. DEV. = 

IEIR PETI 

1968 9.68 

1972 1.53 

1916 8,32 

9.qq CoEP. oF srE¡ - 2.3603 

crTcfiiEìT ÀREt, 5Q KË 5q.{ rÀP BETEnENCB 

llUlBER 0P t¡|flûÀL PEIKs = 1C PEaroD ot REc. 

YEÀR PTiÀK 

1968 55.83 

1912 r9.87 

5. SOUTH ISLAND WEST COAST DATA 

srrE 

s2916 

CÀlCfltlEllT IREt, s0 Kl = 5C.8 

X0iBEF 0P ÀtlNoÀL PEIKS = 

B 

IEIN PEÀK ÍEIR PETK 

1969 61.7 1970 B3.q 

1911 110. 1 1974 15e.0 

oËIKERE r lT POSDlf,t 

= 1106:'l¡1751 

= 1966-75 

IEAR P'IR 

1969 31.8t 

t9?3 t¡.55 

t2.71 coEP. OP SKES - 1.2578 

coBE B lî TSILOtrlE 

lllP REFEREIICE = St3:020¡82 

PERÎoD oP R?c. = 196976 

reÀR Pfrx IEIE PEIÍ 

1911 98.0 1972 94.3 

1975 142,5 1976 131. 5 

lEÀX = 110.1 SÎD, DEV. = 32. q CoAP, oF SßB¡ = 0. l3lt 

ËDt¡ 

sri¿ 

s7009 

ctTcHl:IT À88À, SQ Kll = 

llUltBEn oP ¡.ù[0ÀL PFÀxS = 

P EÀÍ 

6tt 

46 

74 

ÌETF PEÀK YEIP PEIT 

1968 r¡13 t96q 255 

1972 392 19?3 112 

1976 163 

ËBrI = 

345 5T¡. D¿V. = 

t¡8 

tc 

163 

FrcrKt R lT toss BosB 

ItAP REEFRPIIçE = S13:307569 

PEnroD oF PBc. = 1961-76 

YEAR PEAR 

1969 60 

1913 19 

fttR PEli 

1970 6¡ 

t9?¡ 4¡ 

21 coEP. oF sFEc = -0.3054 

IIOTODKI R If GORGB 

irP REF F¡:{CE = 526:288863 

PERIoD 0F BEc. = 1968-?6 

YEÀR PDÀT ÍEIR PITÍ 

1910 16C 1971 ?00 

1a"4 95? 1915 233 

176 coEF. oP sKE¡ . 1.1262 

IOTES : 

1. TTIIS STITTOÙIS PSOBÀBiLIFY PLOT DTD ilOT COTFORII 1O TÍE 

SOUTH ISLÀND IEST COÀST REGIONÀL ?RPIID. I1 ÍAS O'TITID 

PFO| lHE DtRMÎlO¡¡ O? ?UE nEsIOIIL CT RVP lllD lls usaD 

INSTFÀD IO IiJEPTil' À ¡IELSON Sf'B-FFGIOI{. 

Crlc¡lttr lRElr sQ Kll = 

totBt8 0? l¡Í0ll, PEtrs = 

t¿t¡ PEtf tttn PEÀr 

1969 145 1970 ?99 

1973 1054 197t¡ 1 600 

lE¡l = l01B sTD. D!Y. = 

Srll 57101 

17 50 

I 

CllCElltT ÀRErr SQ Il = 60.7 

|UIIBEE OF lt¡lrÀL PEIÍS = l0 

PETtr IETB PEÀT 

ttl¡ 

1967 

t 971 

1 975 

96 1968 95 

39 1972 toq 

29 1976 153 

llAP REPEF¡ilcF = s13:21232C 

PERIoD 0P REc. = 1969-76 

1EÀR 

r971 

1915 

PETK f?Tß PEAI( 

?83 1972 1223 

n81 1976 1062 

288 COEF, 0P Sf,Bt = 1.2661 

IOOÎE¡E N ÀT OLD HOÍISE ND. 

ilP BEPER!¡CB = s1l¡:37?347 

PBRIOD oF RPc. = 196?-76 

IE¡R PEÀX YEIR PEIT 

1969 9 1970 5.3 

1973 5 19711 18 

llll ' 68 SID. DEV. = ¡ú6 COEF, oP s[El = 0.2¡45 

toîts: 

1. r Dri ¡rs cotstRttcTBD oPslnBti oP ÎÍE sTrrrot r[ 1973 

801 I1 IS COtS¡DlBtD 10 ntVE FO SrCIrPrC¡ìfr EPFlCl 

ol lEB ttrtrt¡' FLooD PEtÍs. 

2. IEIS StttloÍis PB0BIBlLIlt PL01 DID lfol ColPoRli 10 Tñt 

so018 lsllft ¡Esr eolsT SEcforfÀL TBBnÞ. r! cls o;rTlED 

?RO' lEI DEBI'IIIOII OP ÎñE REGIO¡¡L CIIRY9 À[D ¡¡S ÛS?D 

I¡SIETD 1O DB?T¡T ¡ IELSOII SOB-REGIOII. 

3It! 51502 

I'ÀIROI R AT GOBGE 

cllctrEr? ltEr¡ sQ rr = ¡6¡¡ ilP SEtERE¡cE S20:¡93149 

tl¡tBll Ot lll0¡L PPÀf,s = t5 PERIOD oP REc. = 1962-16 

ttr¡ PEIf, rElt PEII IETR PEÀF IUIR PEI¡ 

195 2 879 1 963 7527 1954 1016 1965 ¡¡t5 

I 966 7t3 1961 t002 1968 1 102 1969 720 

1970 86t 1971 l¡46 1912 1003 1973 316 

197¡ ?00 1975 887 1916 852 

llll - 

302 COEP. OP SÍEr = 0.2891 

srlt 

â33 sfD. DEg. = 

601 l lt 

cltcf,ttlt tREl, sQ K; = 

¡ÀIRTO R À1 DIP PLT' 

505 iÀP BBFEFE¡CE = S33:29054t 

t¡tlltB Ol ¡¡ltll' PE¡f,S = 25 PERfoD 0F REc. = 1952-76 

IE¡¡ PET( IEI R PEÀ[ ÍETR PEItr tEtn PrÀK 

1952 12,{ 1 953 223 1954 211 1955 320 

t956 16S I 957 ¡30 195S 273 1959 280 

.t 

1 960 60 196',r 270 1962 305 1963 116 

I 96¡ 262 1965 190 1966 ',l8f 1967 244 

1968 30q 196 9 202 19a0 309 1911 231 

1972 237 I 973 248 1914 348 19?5 451 

1976 249 

llll " 

sltt 

260 STD. DEV. 

' 

601 16 

CrÎCEtlll rlll¡ SQ f,l = 

¡tllll ol rttoll PllRs = 

tEl¡ PBt¡ fttÊ 

t966 43 

1970 62 

197¡ 59 

illl = 61 

rotts: 

PEIß 

192 

11 

78 COEP, oF srEI = 0.7396 

ctrRlû R lT ltELLs GllÊ 

ItP REPERFTCT = s¡0:26535? 

PeBIoD 0F REc. = 1966-76 

YEIR 

f968 

1912 

1916 

sTD. DEV. = ¡EtX = 5tt 9 

121 cOE¡. ot sfiE¡ = 0.6130 

PEÀ( fEIN PETß 

1967 5l 

65 1969 {c 

'191 1 51 

51 1 973 43 

1975 100 

88 

sTD. DEV. = l8 CoBF. OP Sf,Ec = 1.3649 

1, 18' I97$ PETT ¡IS TTf,E¡ àS ÎIIE LIRGgST TN ¡88 PERIOD 

1951-76. 

sltl 15276 sgolovEn R tT Borxlrs PElx 

crtcEtlrr t¡lÀ, s0 fü 

ioiElE E 

OF llfltlt. PElf,s = 

10 8S 

I 

l!ÀP REPEREùCr = S132!589786 

PEnIoD oP REc. = tc68-75 

tElB PBIÍ IE¡R PETK YETE PBIÍ fEÀR PTÀX 

I 968 569.7 t969 60q.0 1970 371.0 1911 291.4 

1972 39¡.0 l97l 210.0 19?4 rt58.5 r9?5 508. n 

Ittl = q3¡.8 SrD. DEY. = 121.8 CoFF. or s(Bc = 0.039C 

S IIE B4f0t 

CLEDDTO P 11 fIILIORI) 

CtTcStlEllT ¡REÀ, sQ Xr = 

ÍUIIBEF OT INIÛIL PEÀKS = 

155 tllP RflFEFEllcE = Sr13:908106 

11 PE¡IOD OF REC. = 1965-?5 

lulR PPA K YEÀR PEIK YEAR PEIf, YEIR PEÂf, 

1966 422 1967 1\7 

1 965 u23 

1958 400 

t969 5q0 197C 512 19?r 572 1912 533 

197 3 52U 1974 675 19?5 461 


t0l

9100r 

GNE? R ¡T DOBSO| s¡18 93207 

IXÀllclllltt n ÀT Bl.Àcrs Potli 

CllctiEll rREl, SO Xtl - 3830 llÀP RE'EFEIICE : 

¡ûllln 

crlcñiltr rlEl, S0 [ü 23q I'tÀP 

oF lI¡[lL pFÀf,S 

S¡¡:8tOO?7 

REPFnE[cE s38:340281 

= 9 PERIOD 0P RBc. - t96O-?6 lolEER oP tlitÀL ÞEtÍs = 11 PBRIoD oF FEc. = 1965-?5 

IEIR PETT IEIE PEÀK tElR 

t968 

PrtÍ 

36s0 

tElR IEI¡ PP¡I P8If, fEÀR PPTi 

PEÃr 

1969 qr13 

Pr¡f 

1965 272 'E¡8 1966 290 1967 428 'ETR 1968 q34 

1972 lt0s0 

r9?0 q800 t971 233S 

t9?3 3935 1974 1969 579 1970 412 .t9?1 

1976 

3695 1975 aO38 

338 

33S0 

1912 l8? 

1973 498 1974 975 19?5 534 

iEtt . 37?8 STD. DFv. = 669 coSP. op SÍEt = -.1.02f7 lB¡l = 073 SID. DEV. = 193 cogp. OF Sl(Et = i.BBrtF 

xolEs: 

l. TFE iql6 pEil( totts: 

or 6660 cuüEcs frs ÎtÍEf ts TnE 

rr 

Ltnclsr 1. TEE 19?4 

TIF 

PEIÍ fÀS T¡IEII IS TilB 

PE8IOD LrrCESl If 

1900-76. 

lNE ÞEFIOT) 

1 

2. TIE lq40 pErx 

887- 1976 . 

oF 5300 CÛrlECS ¡tS Î¡ttl¡ Às lEE rErBD 

LTPGSSI TT TÍE ST'E PESIOD. 

srlB 93209 

iIßOIA R TT PILLS 

s¡ 1? I 140? 

lll:: l_:_11-::::1 

cllcflllT 

cttCf,iEiT 

rBBl, S0 [l . 980 

l8rt, 

irP RETEFEICE 

sQ Kr l¡P 

= S32:683596 

?90 RE¿'nErcE S¡5:2Ot9Orl ¡otEBa o! tlfttll, PPtf,s 

¡û;E?R OF tt¡otr. = 13 PERIoD o! REc. 

PBIIS = PllIoD ' r96q-76 

9 oP REC. = f96B-76 

IEI¡ 

IIIS 

P?IX 

PBTß IEIB PPTÍ TEIR 

IEIR 

PETß fETR PETÍ 

PBÀr 

1968 

YEÀR 

1700 

PEIÍ 

PrT[ 196t g¡7 1965 277 1966 ¡6 r 1967 758 

t969 1051 

1972 

1970 1260 'ETR t971 589 19ó8 

lc2q 

995 1969 808 1970 10r¡1 

1973 

1971 6¡? 

t{09 

t9t6 .r7¡ 

1974 1039 19?5 t3r6 1972 8¡¡ 1973 685 197¡ 836 1q75 855 

1976 667 

iEll = 1199 STD. D¡ìy. = 328 cosF. oP sÍpt - -O.aZS2 lgtl s 7¡8 sTD. DBt, - 207 CoE?. OP sf,EI = -0.9q91¡ 

toTts: 

l. lrr t9q0 p,tìtÍ oF 2320 cullDcs cÀs ÎÀKEr ls rEE sBCOtD 

L¡RC?ST rf Î¡E PPRTOD rEtO_19?6. 

srrt 932t1 Ë¡ftßITtÍt R tT ilnD LÀf,F 

srTl 9320 l 

B0LL!RRrlr!foÍr cllclltlT lttl, s0 fi = 857 irp RErtFtfcE s32:?4r6tl 

llllBl¡ O? rfloll Pltfs E 13 PERIOD OP RSc. = 1964-?6 

C¡lClllEXT tBEt, 5Q fl 

635C ñÀP BEpERUItcE s3t:lAt629 III¡ PI¡f IEIB PEIT ÍEIR PETÍ YETR PETI( 

¡oltlll OF ¡¡ù[tL PFIñS = tq PEBIOD O? RDc. = 

196tr 843 

1963-?5 

t965 q48 1966 575 1967 7A1 

1968 981 1969 518 1970 1655 1971 1095 

IEI¡ PFTI( TET¡ PETK rEÀR PEIR rBlN PrIf 1972 1430 r9?3 818 1974 8Ê4 1975 ttt66 

1963 {qol 1964 359C 1965 2150 t9ã6 t976 r 161 

1950 

1967 ogôC t968 5800 1969 4745 1970 E23O 

t97t r¡7-

S ITE 91211 GLEIIROI R 11 ELICÍS 

cÀTcfËr¡Î tRPt, 5Q Kll = 198 rlÀP REPBFE¡cE s39:?5335¡ ctlc¡tlll lllt¡ SQ r! '1980 i¡P REPERBICE s54:1r¡2602 

llolBER oP tNllg¡.L PErf,S = PERIoD 0P REc. = 1967-77 

Itllt¡ O? lllttll' Prlfs = l¡ PEBIoD 0P REc, = 1962-75 

IIIR P:[ß YEIR PE¡X TBÀR PEIß TEIR PlIf tll¡ PEIÍ IET¡ PEIÍ IETR PEItr IE¡R PEIT 

1961 159 1968 208 1969 1¡16 1970 t96 

t962 855 1963 tt?tt 196q 10¡1 t965 633 

1911 180 1972 183 1973 131 t9?|[ t¡5 l9ó6 771 !961 1300 1968 19q6 1969 661 

1975 197 1976 178 1971 262 

t970 1555 t97t 1073 1972 1423 1973 l1 19 

I 9?r 1120 1975 1436 

lEÀI = 18 1 srD. nEv. = 36 coEF. oP sÍ?¡ = 0.8ó08 

lllf - lt5t sTD. DEf. . 365 coEP. oP sKEe = C.512? 

tolls: 

1. IIB 1968 PLOOD PEIÍ ¡TS lf,fEX IS TEÈ L¡FGFST II¡ îIIE 

Pr¡roD 195?-75. 

lt 

stlt 61602 gÀIln-ÚÍt R 11 ttSBL¿ PT. 

S IIE 

¡lltÛ-0fft R tT itl.rlcs PÀss 

6. SOUTH ISLAND EAST COAST DATA 

SIlE 601 08 ¡lfRtn R 11 TtttttRrtÀ 

C^lCFxEllT ÀREÀ, S0 Kü = 3431 llÀP REPÞFBI|CE = 522.253077 

NúllBER 0P À[t¡UÀL PEIiS = 3¡l PPRIoD 0P RtC. = 193ó-t5 

TEIR PEIK IEÀN PEII( 

1 935 r 920 1 93? 1754 

1940 1 100 1942 209tt 

19ft5 125tt 1947 tq24 

1 950 1 8?0 1 95 1 2494 

1955 3q-1C 1956 20J7 

1959 1213 ',1962 3qCC 

1 965 1 030 1 966 1412 

1969 2 380 1970 354a 

1974 2830 1915 436C 

¡ElI = 212" sTD. DEV. = 

IOTES: 

fETR P¡:¡Í ÍEIR PE¡I 

t938 2011 t939 3396 

19rt3 1330 19¡¡t 1510 

1948 208n 1909 2010 

1953 t613 t95¡ 3820 

'1937 2201 1958 192q 

1963 3000 196¡ t800 

1967 3113 tq68 3000 

1971 192C 1972 25AO 

923 coF?. OP Srgr = 0.1919 

1. STX ÀIINUIL PEItrS CTl8TN THE IBOVE SFPIES CERE T.PSS lEIi 

1000 cuËEcs ìID SESE ÀssÛiED Âs 900 cil¡Ecs. TEE ¡sslttED 

PEÀt( VAL0ES rERF 0SED r[ 1ñE FSEoUBICI tìrÀLySIS ?On TnE 

STTE BI'T C¡FE ¡¡OT PLOTTFD TÌ DENIYTilG TNÈ RPGIO¡II 

CIIRYE. 

CAICItIIEII' ÀREÀ, S0 KF = ?t¡4,4 

NÛIBEP oP ¡¡¡g¡¿ Pg¡¡5 = 16 

fEÀR PEIK YE¡ F PEÀ¡( 

t 96 1 250 1962 69- 

t965 lt¡l 1966 525 

1969 .144 197C 53: 

1973 2C3 t97rr 139 

ItEÀl¡ = 462 sT9. DEV, = 

srlB 6 21 03 

srlE 62105 

CltC¡lltÎ l¡B¡, S0 ßÍ rl40 

t¡¡¡BEl Ol rlIUrL PEIrS = 13 

tBti Ptf,; rBlB Psrf 

t96¡ 95 1965 126 

t968 310 1969 52 

1972 r5r 19?3 109 

t975 20r¡ 

lElf = 187 STD. DZ9. = 

cÀrfloPrr R tT cRllcloc¡t81 

FAP RtÌPFnqùcE S28:99¡865 

FERIoD oF RPc. = '1961-76 

YEÀR PETK YETR 

1q63 395 196¡ 

196a 707 1 968 

1911 214 1q72 

1975 8C? 1976 

PEAK 

3 3t¡ 

45q 

432 

531 

2C.l colP. oF srEl = 0.2385 

ÀcfiEROF n À1 CLtFr:ùCE 

clrcñ;BlT tBEt, 50 f,t = 991 IÀP RE?ER!IIC! 

54?: :119961 

¡0tEzB Ol ll¡otL PEIIS = t8 PERIOD OP R¿C. = 1959-76 

IETR PEIK tuÀR PEtÍ ÍEIA PEIK IEIE PEIF 

t959 2AO 1960 202 1961 117 1952 236 

1963 198 1964 22C 1965 171 1966 308 

1967 378 1968 736 1969 321 1970 356 

1971 361 1912 365 1973 201 197¡ ¡87 

1975 199 1976 26i 

lBtr = 33 3 sTD. DEg. = 182 coEP. oP sKEc = 1.5906 

sr?r 

6430 I 

CLÀREIICP R IT JOLLTgS 

flP REFEREIICE = s41=265862 

PERIoD O! REC. = 19611-76 

rEIR 

1 966 

1970 

19?0 

PEAK tEÀR PEIX 

320 1961 121 

150 1971 152 

266 1915 166 

91 COEP. OP sKE¡ = 0.4401 

colr¡Àt R À1 ltfrÍDlLtt 

CllCEil¡T lBlr¡ sQ fl ¡6r¡ ttP RBFERE¡cE s55:7166?7 

l0lBll Ot ¡tl0rl PEIrS = lt PERIoD oP REc. = 1956-66 

ttls Pllf, rElE PEtf YEIR ÞEÀÍ ÍBTB PE¡I( 

t956 540 1937 355 1958 210 1959 720 

t960 , 670 t96r ssc 1962 122 1963 1300 

t96r 58 1965 580 1966 1000 

ttll - 555 sTD. DPl. - 373 COEP. oP SIEI - 0.6019 

tolts: 

l- tEr 1923 rLooD PE¡f Ol 1700 C0IECS ¡ÀS Ttf,Er ¡s r¡B 

Lr¡Glsl rr lFE PIIIOD 1A69-1971. 

cllc¡lllT ¡¡lt, S0 f,l - 70.6 ltP REPEREÙCP = 540:018154 

f0lllf Ot ItlOlL PEIf,S = 10 PIBIOD oP REC. = 1966-15 

ITI¡ . PE¡f IE¡R PEIÍ YEÀR PEIß TEÀF PEAÍ 

1966 66.5 196? 86.2 1960 11q.0 1969 66.9 

t970 98.0 197 1 17 .6 1972 86.7 1973 82.0 

t97¡ 93. ¡ 1915 123.7 

llll = 89.3 sTD. DEv. = 18.9 CoEP. oF SßEf = 0.5772 

slrr 6510¡ E0Rol¡ilr R l? itIDtËfts 

Ctlcliltl Àßllr.S0 [Ë = 1070 ;lP BEFERE¡CB = 56l:932u62 

l0lBll Ol llttll PEtfS = 19 PEIIoD CP REc. = 1957-75 

ttlB Ptlr ItlR PETI IETA PEI¡ IETR PEÀÍ 

t95t r1¡5 1958 562 1959 611 1960 r¡47 

t96 1 559 1962 192 1963 665 196tr 465 

t965 291 1966 241 1967 q60 t968 67|¡ 

1 969 2¡¡ 1970 858 1971 585 1972 83r 

1 973 175 1974 5r1 1975 743 

lElt = 500 srD. DE9. 253 COEP. oF sf,EI = 0.¡1991 

S ITE 

65107 

crtcEllElIT ÀREAr SQ Kll = 3tt2 

llUltBER oF À¡¡llllÀL PEIKS = 15 

tETR PPTK YEì8 PEIK 

1937 2t 2 1958 160 

1961 ql 1C62 78 

1 965 92 1966 56 

1 969 12t 1 a7C 235 

iErÍ = 138 SîD. DEY. = 

SITE 66401 

8ûRoFrr: R rT LÀrZ Sotttn 

lltP SElEnBllCE = s53:6855¡9 

PEBIoD 0F RBc. = 1957-71 

ÍETR P'¡R PI¡i 

1959 120 'B¡B 1960 122 

19 63 1tt 196¡ 135 

1961 163 t968 t8? 

19?t 176 

56 CoEF, OF SÍz¡ . 0.q875 

¡Àr¡lxt8t8: F Àr oLD E.t, 

cÀtcflllElT rREt, sO Kl 3210 iÀP BE?EREÍCE = 576:020?02 

IolBER oP t¡iotl PEt[s = 46 PEBIoD 3P BBC. . 1930-75 

PPIK IEIF PETÍ YEIR PEtf tEt¡ Pll[ 

'EIR 1 930 I 33 t 193 I 2039 1932 1303 1933 2209 

1934 1501 1915 1303 1936 3112 1937 2209 

1938 2t11 1939 l01q 1900 3738 t9tl 1612 

19q2 1699 l9¡l 1076 t9q4 1 303 t9¡5 1¡¡¡ 

19¡6 1614 19117 2095 1948 1812 t9¡9 t359 

1950 3C87 1951 2095 1952 1 218 1953 1303 

1950 161¡t 1955 2322 1956 2209 1957 3993 

1958 1044 1959 10q8 1960 1 388 t961 963 

1962 tl.rr 1963 1214 t96rr 1416 1965 1232 

t966 850 1967 2o5lt 1q6S 1Cl8 1969 ',1100 

19?0 2501 1971 1190 1912 1676 t973 t000' 

1974 1121 1975 1773 

iEtl = 1694 sTD. DEY. = 709 coEP. o! SRB! = 1.5790 

XOTES: 

I. lSE 1957 PI,OOD PE¡Í fIS lTÍE¡ TS lNE LÀRGEST Tf lEB 

PERTOD 1¡159-1977. 

srlE 661102 rtlñÀf,tRtBr a tr 6('¡61 

ctlcftEllT AREÀ, S0 rñ = 

xurBER oP lIÍoÀL PEÀKS = 2C 

rEIR PBÀÍ IT:TR PDÀf, 

1953 1 3Cl 195q 1586 

1957 42q7 1958 906 

1961 934 1962 1303 

1965 12tr6 1966 ll89 

1969 16q2 lc?tl 26A5 

iElI = 

168? ST¡. DEv. = 

2r¡ 6C 

llP nEFEFEIICE 575:089775 

PERIoD o? REc. = 1951-72 

ÍEÀ8 PEI( TETB PIIf, 

1955 2319 1956 2350 

1959 1 557 1960 l¡¡r¡ 

1963 t303 196¡[ 195¡ 

1C67 2605 1968 1869 

1911 1611 1972 2209 

534 COEF. OF s(rl = 0.¡231 

TOlES: 

1. ?88 1c5? PLOOD PEÀK CrS TrKEh tS T8E ¡,tnGESf lr l¡E 

PEnron tg69-1977. 


r03

6800 1 

sBlrri R tT SrITEC¡,tttS 6Itt 696 r8 oPrñr I ÀBorE Roct¡ooD 

Ctlclãlll ll9l¡ SQ [l - 

lt itB¡ or tffoll PEtfs . 

r ttt 

196 t 

t 965 

| 969 

I 97¡ 

l6¡ t6 

i¡P ¡lrERlrcE 3 S7a:3t96t9 

PE¡IoD 0F REc, = 196t-76 

ÍETR PETi rB¡R PIIÍ 

1963 r6r,8 1964 39.5 

196? 66.0 1968 ¡8.3 

197 I 3?. ¡ 1972 t73.0 

1975 79.2 1976 6t. r 

PTTT TETF PEIT 

r84. 0 1962 37.6 

t85,0 1966 12.C 

1 r. ¡ 1970 58.8 

52.1 197¡ 96.2 

;Dtl " 85.11 StD. Dtt. 57.? CoEP. OF srEB - 0.891¡ 

ClTcÍiE¡1 lREtr SQ ill = 

¡lllBEF ot t¡lotl PEIßs ¡ 

III¡ PPIÍ IDTR PP¡i 

t96t t7t t968 9C 

19tt 65 1972 167 

19t5 ¡5 

iEtl . lt8 StD, D¡:V. - 

s ttg rt9t 02 

tsFEoRlor SlE R tt iT. so;rns 

RÀIcIltll R tBot! fLotDt¡r 

CltcllllEl? tnsr. SO ft ' l¡cs itp ÀEppFBrcE 

lüi0EB 59t:752290 

oF tffott. pEtfs - l0 pEETOO oi n¡è. = ßG1_i6 

?ttt Plrt tEtt PEt¡ YEIF P¿If 

1967 tq29 

IE¡R 

t96S 

DIIi 

639 1969 tt15 

t97t 3.tt 

19?0 t599 

1912 517 1973 1201 

1975 t 159 

r9t¡ 

1976 75¡ 

576 

lEtl = 959 StD. DEr. = r¡29 CoEF. Op SrEt = 0. f253 

toTls: 

601 ¡ÀP RE!EnErCE . s8r:820{tt 

9 PEnroD 0F FDc. = 1957-75 

ÍEIR PFTI( 'EIR 

PrI¡ 

1969 ?9 197A 204 

19?-ì 5t tc?¡ 96 

58 CoEP. OP St(El = 0.6t80 

t. lrt tqSt ploon pttk op 1950 au;Ecs ets ltrEt rs T8! 

L|RC!5T tf ?f,t PEFTOD 1936_?7. 

cl?c[;Ex? lB!1, sQ fr ¡ ¡12 rrP nEtr8zfcE = Stct:5t2792 

IttBtR o? tt¡[t[ PPr¡s : 41 PEIIoD CP ¡tC. - 1936-76 

II¡R PETtr TEIR 

't9¡6 

PETÍ TEIR PEIÃ tE^R PEtf 

t41 1937 62 1938 80 1939 33 

1910 121 19¡l 126 1942 r03 1943 t19 

19¡¡t 120 t9t5 663 1946 ¡3 r9¡7 33 

t9r8 39 t9C9 50 1950 50 r95t 562 

1952 200 1953 ó¡¡ 1954 69 1955 29 

r95ó 69 1957 227 1958 1 19 1959 11 

1960 t19 1961 466 1962 ?¡ 1963 28¡ 

t96¡ ¡0 t965 tt73 1966 t¡t 1967 10t 

t968 15¡ 1969 65 t970 1 18 1971 92 

1972 162 1973 39 1974 166 1975 t¡8 

t976 61 

ll¡l = 15¡ sÎD. DEV, È 151 COEP. OP Sf,Et - 

lorts: 

1. 1¡I PLOOD PETTS P¡¡O¡ TC 1965 ¡ERE DBRIY'D P¡OII OLD 

II?EÊ-LE'EL IECORDS. |IO ¡ÍICI I COITRI?ED R¡TI¡G 

COT'B CTS ¡PPLIED. 

2. T¡t 19t5 rfD 1951 ?r,ooD pE¡is ¡B8E ît[Et tS lnr LlrcEsr 

ItD SBCO|D Lt86ES1, RESPBCTTyEL!. It îfl8 

1902-76. 

pERTOD 

s¡tt 69621 

ROCtrf COLLT P ¡1 ¡OCiBU¡r 

ttlgllu!î t¡El, s0 ¡r . 22.0 i¡p REprBrrce slrc:367601 

lolDll O! ¡ttolL PEIIS - r¡ pE¡IoD oF ¡Ec. = 1966-76 

Itr¡ PEtr rBtS PEli tu ta PEIÍ tEtS PEtf 

19ó6 to.z 1967 tr.l 1968 19.3 t9?O j.2 

lltl 7.3 1972 51.6 1973 3.9 r9?q 9.¡ 

1 975 7,8 1976 9.6 

llll | 12.7 STD. Dll. . ltr.q COE!. Ot S¡EC - 2,63¡0 

lotls: 

1. 1!! 1972 plooD pPttr sts 6.0 ftrEs Tf,r t¿Dltt rttorl, 

?LOOD PITT I¡D ¡IS îEB¡ETO¡E 

ptollttlM 

O;IITED FROi 

pLot 

l8g 

ttDsB noLE ro.2. f,o¡ztER, rT 

II3 ITCLIIDED ¡I î!E DENTVIIIOi O' TIE 

oltt¡lllstD cÛErE POR 1ñg lREr. 

2. to tfltttl pElr gf,s ¡vÀILIBLE ron 1969. 

7. SOUTH CANTERBURY DATA 

ïï______u:9: 

cttclttlr l¡lt, so i; = 

tolltt ot Ittrrll 9E¡rs = 

l8t¡ Ptl¡ rE¡B 

t96¡ tl. 52 1965 

r968 32t.53 t969 

19?2 296.83 1973 

1976 5r.56 

PETI 

t2 1. 14 

63.98 

98.16 

llll . tl2.?0 sTD. DE . . 

srlE 69506 onÀRr n 11 srLvEltot 

crlcÍiErT t8Et, SQ fi . 520 lltP REPEnETCE 

TO'IE8 O? IIIOIL 591:730081 

PE¡ÍS E 15 PtRIoD o? RBc. = 1960-tt sltt 7rrt6 

tEli PDil( tÊtn PPri rE^t 

1960 r70 

PEttr fElr P!¡f, 

196 I 4SC 1962 I 

1961 

lC 

l¡0 

1963 ¡t95 

f965 1tt7 1966 

1968 

63 

2t9 

1967 

cltcRtrfl t¡!1, s0 rl . 

29a 

t96ç 5: 197C 

1972 ¡t5 

317 197i lolllR or tttûll PE¡Ís 

98 

= 

1973 125 '1974 263 

tll¡ PEtÍ Ittn 

iEl¡ . 26" sTD. DEY, 196¡t tB¡ 

" 197 COEF. OP SrEt É l..tO?2 

1965 

t968 1¡5 1969 

to?Es: 

1972 t86 197 3 

l. tfit to¡5 ?Læn ntti op lo0o.cfrtEcs gts llfpf, ts ?nE 

L¡¡GEST III THE PERIOD 1871-1976. 

llrl = 227 StD. DEl. . 

PEIf 

234 

380 

228 

899 

13 

557 

12 

IllllIlïl-:-11-l:I:l: 

iÀP ¡ElEnBict - Sltß:125t12 

PB¡IoD ot [Ec. = 196¡t-t6 

f 8IR PE¡T P'II 

1966 41.21 'Ef,R 1967 65,77 

1970 65.20 t971 q8. r0 

t97¡¡ r10.0¡ 1975 lOr.06 

93.13 COZ'. O? sÍ!¡ . 1.7422 

lto¡r¡I R tÎ sottîf lrItDEi 

llP IEPEFE|CP = Sl0ß:¡50406 

PE¡IOD Ot ¡BC. = 196¡t-?5 

fE¡A 

1 966 

1 970 

t97ll 

PEIß TEIF PETÍ 

259 t967 39¡ 

262 t971 t05 

13? r9?5 208 

90 COPI. OP s(Et = 0.8171 

sIrE 596 t¡ 

crTcf,is¡r t¡rt, sQ ft = 

lofBEP O? tftutl PElf,s: 

rlr¡ PEtf tEtR 

¡56 

oc 

oPoÍt F lDotE stlDlot 

lltP RE¡ERn¡C! = s10t:54t902 

PEnIOD 9P n!c, r 1917-76 

I¡IR PRTß IETR PElT 

1939 s0 194C !23 

19f¡3 1a2 19¡rt 218 

1947 q0 19¡8 216 

1951 666 1952 5ó5 

1955 111 t956 

1959 50 

230 1960 124 

1963 542 1964 t3 

1967 293 1968 It9 

1971 175 1912 306 

t9?5 30? 1916 147 

PEII( 

r9l7 25 1938 19ll 

l9¡l 36â t9¡2 46( 

t9¡5 e¡t t9¡6 91 

t9¡9 r90 t960 5q: 

r95t ¡00 t95¡ t52 

1957 , 666 1958 2(,¡t 

196t 36t 1962 69 

1965 520 t966 7t 

1969 127 197C 321 

lgtt ¡5 19t¡ 1¡' 

l¡¡f = 270 ST'!. ¡Et, = 2C2 COp.p. Op SiE¡ - t.Ol57 

TOT'S: 

1. T[9 lqIfs PRIOF T: T965 IERE DERTVEÞ FROIi OT.D 

fllEF-LEttL 'LOOD RECORfTS, TO rFrCfl t collRrvEn Rlrrtl6 

crttv? fls tPPLIS¡. 

2. .ilr l1¡5, t,rst rxD 195t FLOOD pEtKs fpnF lrf,pI ts !8t 

7T:?ST, S'COllD tttÞ 1fiIÂfi L¡Rersl pEtf,s. REspEcTIvELt, 

Ix .rfF PSR:OD 17C2-16. 

71128 

IRISIIIX CREEI IT 3ITDT RIDGP 

CtlclillT ll¿t, sQ ti = 1tt2 lllP REPERBICB = St00ro92880 

tûlllR ol tflûtl PEttS E 9 PEBIOD oF RDC. = 1963-71 

tll¡ Pttf rE¡t PEIÍ 

1963 

IETR P¡ITT 

31. t '196¡ 

PE¡T 

18.4 

1967 

1965 20. 5 

79.3 

'ETR 1966 11. r 

1968 31,2 1969 c6.5 

r97t 197C 73.0 

t3.3 

¡Btl ¡ 36. I srD. DEr. - 25.2 COEP. OF SXE¡ = 0.95rc 

srrr 71129 

FORßs P I? BILttORTt. 

c¡lcnlllT lllt¿ sQ f! = tr0 itP ¡DIERricE = sR9:035017 

lÚltll o? ttttttl PP¡rs s tt PESIOD Ol R!c. ' 1965-75 

lll¡ Ptrf, tttn P!ÀK .'EIR PEÀÍ 

't965 16.7 

tslR PEtr 

t966 25.q 1961 50. I 

1969 

t968 19.1 

12.6 1970 3¡.0 1971 12.6 1972 22.3 

t9t3 20.6 t97¡ 12.0 19?5 r8.5 

lE¡l . 2¡.0 STD. Dtt, - lt.z COEP. Ot SrE¡ = 

104 


.i.

71t35 

JOLLTE R lT 11, coox slllfo¡ SIIE 7850't 

clIcElBrT [R?1, SO tr¡ = 139 lllP REIEnFICE = s89:8tl1164 ctICHiEllT tBEr, sQ xí 160 

tOiDlR OP ltt0ll PEIÍS E t0 PERIoD oF REc' = 1966-75 t{0llBEF OF tlllûtl PETKS = I 

trlE Ptl( fEl¡ PElf tETR PET( YETR PETI( IETR PPIK IEIN PETI 

1966 97 1967 106 1968 49 196q g0 1958 r¡l.C 1969 26,6 

t9?o 72 1971 31 1972 ¡9 1973 62 1912 55.7 1973 19.8 

r9t¡ 30 1915 60 

liPttl = 10.0 S1D. DEY. = 

rBll = 6¡ SrD. DEf' = 25 COE?. OP SrE¡ s 0.t¡152 

8. OTAGO.SOUTHIAND DATA 

sltr ?¡337 trlEB0Rll À l1 ll.E'B. 

cltcttrrrl llEr, sQ fl = 

IÛIEEB Ol t¡ittll, PB¡ÍS = 

376 

I 

ËrP REPERUfcE = sll5:935593 

pEBIOD Op EEc. = 1969-?6 

rll¡ Pt¡i rElR PEIÍ 

t969 13.2 1970 22.6 

19t3 23,6 197¡ ll3. ¡ 

ll¡f . 4t.5 STD. DEv. = 

tEÀB PEIK IEIR PETT 

1971 79.5 1912 ó4.4 

t975 t10.5 1976 62.1 

23,2 coE?. or sf,E¡ = 0.1372 

srrE 14625 

ctTc¡tiEltl ¡nBr, sQ Íl = 

I0IBEB OF txiûl¡, PEÀÍS = 

rrta PEtf lEtl 

1964 21,3 1965 

1958 84.5 1 969 

1972 65.5 1973 

1976 ¡r3.1 

lEt¡ = 45.9 sTD. 

srlE 78633 

PETf 

30. I 

59. l 

25, e 

1C9 

t3 

ctT¡roPtr I tr fPftrfcfot 

IIP nEttREllC? = Sl77:4310r¡5 

PElIott ol nEc. = 1968-75 

IEIS PEIf, I'TB PEIÍ 

1970 25,0 r97l 17.1 

197r¡ 31.9 1975 22.O 

12.8 cogî. oF sit¡ = r.3586 

:11::11_l_ll-:"'ll3ll l!: 

lÀP BllERPrcE s169:122516 

PEnroD 0r ABc, = t96¡-?6 

rE¡n P¿lÍ rt¡R Ptlf 

1966 30,2 1967 32.O 

1970 67.8 t971 t2.ø 

1974 34.5 1 975 33.2 

18,5 coPP. oP SÍEI = 0.8196 

ilÍ¡BBcr B tr l¡EEurl6 lÍs.8. 

slll 7t3 r6 

I.OGTIBI'8¡ I ¡T PÀERIO cttcfltrfl rBrt' sQ ri 13q0 

loiBER ot lfl0l¡. PEIRS = 9 

iBlt = 359 sTD. DEY. = 2tl9 coBP. oF sfBt = 2.3010 

Cr!CI!E¡T l¡rl, s0 trã r5O rtP AEFSRE¡CE Slq4:624217 IETB PEàf IETS PEIi 

rutB!! oF r¡¡sít isrrs = 10 PErroD cP nEc. = 1967-76 1968 ¡t1.0 1969 t7q.7 

1972 269.2 1973 tlr6. I 

r!18 Pltf rEta PEIÍ rEtR PEIX fE!! PElr 

i,at s.r t96s 20.6 le6e 12.2 le?o 

1976 248.0 

22.e 

t9t1 35.5 1912 50.1 1973 21.8 197q 15' 6 rEtI = 216.5 sTD. DEv, = 

1975 26.5 1976 15.8 

rrll = 22.6 sID. DtY. = 12.7 cog?' oF SiEl = r'0925 

srll 75212 

POIITHIXT R ÀT BÛNÍES PORTI 

CllcÍrErT lRElr SQ Kl 1332 

tûrErB oP rlroll PE¡rs = 13 

Ílp gEpERt¡cE s,11.1.22t¿r12 

PBRIOD o! FEc. = t963-75 

tlIT PEII 

PEÀÍ f8ÀR PttÍ tLlR Pllß 

1963 337 'gIR 1964 8¡ 1965 310 1966 276 

1967 ¡66 1968 536 1969 2t9 l97C 255 

1971 370 19a2 1068 1973 170 1974 201 

't975 318 

tolBs: 

I. TIB 1972 FLOOD PEÀI( ¡TS ?88 LTREBST IÍ TgE PEEIOÍ) 

1958-?5. fT CÀS OirrTED FROü TEB lItLrSfs ttllDlR 

BÚLB TO.!, BOT ÍIS IIICLI¡DED 1I¡ lEE OERTYTÎIOX OF 

lEE GEXBATLTSED CURVE FO8 lBE IRET. 

itP REtEREXct S177:331139 

PDSloD o? RUc. = 196C-76 

tEÀA PETK IBIE PIIß 

1970 168,4 1971 201.2 

1974 1:t5, ¡¡ t975 t9¡1. 1 

05.1 coEP. o? slBt. 1.605¡ 


105

APPENDIX C 

Summary of tho data for the 

Nelson area 

NETSON DATA 

srlt 57002 

tloÎUErt n l1 8¡10t BIIDOT 

c¡IaEllE¡r ¡8Et, sq [ü 164" 

¡úiBEA OP trtotL pEtis = iB 

ll!! PEIK rErR PErf 

!!93 7s7 reso s83 

!?18 s83 tese 75c 

1963 561 1966 325 

!?!? s6r 

1973 

rsze izt 

r 159 197¡1 2622 

ItElll = 1078 stD. DFv. = ' 

lloTES: 

lllP SEP9REÍCz . St9:2O33OO 

PEAIOD OP REC. r lg5¡-l¡ 

ïiìt i3|T üi; !¡äT 

i¡ï ,¡33 t3:3 iil; 

t9?t 

t. ¡o-rtrltolL pEtßs ¡aERp tvìrLtBrE poR r956,1960, 

1964 tID 1965. 

2. olrlt of,E ?¡r¡îÀîM R¡ÎIÙc c089E I5 tvtrf,lB¡,E, 

s16 1972 rjes 

70t¡ COEP. OF SÍEt = -t.6331 

IÀIGTPEÍ¡ N IT SIIIG ERIDGD 

c¡1c8llE¡1 rREt, SO Ftt - 373 

IU||EPB OP ÂXllftÀL PEIÍS ¿ o 

!9!R P¡At( rErR PErf 

!9qt 467 1e62 467 

1966 q7 196? 3¡0 

1970 2â9 

lllP REFEREnCE = Slo:072t¡l 

PERIOD 3P REC. - 1961-?0 

iiåi 'ååi i3åt "åi5 

1960 607 re6e iì ¡ 

ËÈtl¡ = 39¡ STD. DEv. = 

l¡oTES: 

174 coEP. o? sßFt = -0.24?5 

l. io--Àrilut¿ pE¡t( 9ÀS ÀVtILtBL? ro8 1965. 

-'. ôtrLr o[E TFrrtrrvE FÀTfrc coav¡: ¡i-ii¡rrrg¡,g, 

srtt 57106 

slrrLtfBROOR I tî BtErr¡s 

cllcãttEÙT ¡RBÀ, SO K[ = 81 

¡ollBDR oP Àùt{rrtL PE¡KS = 7 

M! 

P ¡ÀK rR¡ F FnrÍ 

!?10 48,r¡ tq?l c8.s 

197tt 96.8 t97q 3n, c 

iEt[ = 60,6 sTD. DEV, - 

IAP REfpRt:t{cE = St9:2Og2tF 

PERIOD 0p FEC, = t97O-76 

ïll! PPrr rE¡R PErrl 

l?1? 103,6 te73 it. t 

ta76 50.0 

27.9 COEF. ot sÍEt = 0.9692 

106 Water & soil technical publication no. 20 (1982)

24 HOUR Í(AINFALL P OF RETI.R,N PERIOD 2 YEARS AND ITS STANOARD ERROR' E (III4I 

NUMB ER 

Nur'IBER 

-o 

ãt 

f. 

Ø 

CL 

ñ NÞ 

Þ !!m 

z I- 

x I 

É? r-r' a, Âa 8e 12 t2 f{ÄñGnNUl I{ANGOf\¡UI 

43950L 34 59 173 t2 r01 1? 

HAIHARARA 

439201 34 51 l7J 12 

87 e r{AiAmi- BnY- 35 2 t-t3 53 999 

856 RANGIT IHI 531301 35 6 L7? 2A 9t 1l 

KAITAIA AERODRDTTE 530201 35- 4---113 17 

triËîmilunr- -- ---si67az-tt 

z--îrtr 

ìîiiåìä--u u rv'r'-- -nl-zît- :z {'i- -irã-fz-- eo--i 2 

ruaffi o r 35 I 173 30 

--91-TT 

AI{I PARA --sallt¡f -- t5-Tõ-T¡t 

5a28ll 35 13 L73 52 L5¿ 15 KÉRI KER.I 532SOt. 3' L4 173 5? 

el I 

g¡¡g¡1P0LL5328L13513L73?_1--L5¿15KtsKIl\trKL)2L7wLJ¿!-LlJ'l 

-¡to 

TÃ-rrAN-Gl rdRE-si- - - -542õor ãá-i'ç -i1e 137 t3 

--llggl- i: l: ìl: i: ee L5 

RUSSELL 542LO1 35 1ó L-t4 q - 

108 1 HERÊKINÛ 

532202 35 1ó L73 13 

EEOIõÍõOD-- ltzzli ;,; i¿ ltz-2T---ca 1ó 

- 523502 35 l8 113 33 89 13 

-uHnwenr-¡¡o.z 

OKAIHAU 53319t --il zl- 

TaI- -1-i OPONONI 

534402 35 29 173 ?6 

KAIKOHE AERODROMI ME 

----8151ùI--a-; 

5348ii1 35 27 L73 t3 49 l?? 13 

ti- Ir14 t6 r35 6 

PUH I PUH I 

a462A2 35 36 174 150 Zl sANDsTWHANGAREI AREÂ 546411 15 36 l7+ 26 1?0 30 

HIKUR ANG I 

RUDER9{ OVRE --5767I t-- -$ -17--1ar4l- -- --12õ-"0- -TÍ-EFñCF;¡FANGARÊr. 53óó11 35 38 173 te t2r 13 

TÃImTElrlÚI---_-strtoT_35=ila77?ã---t'iÀIr'tAT¿ruÚ 

I{AIPOUA FORËST 536501 uJv t 35 39 L-t7 la a75 GLENBERVIE FOREST 54ó3C,1 35 39 L14 2l 139 9 

5 369ü ;óüi 1 zò I,¡ t13 5e-- - e5 ro ----P-Úk-rTÚRÙA NoRTHLAND 546 

5 91 r4 

a tâ 

-PIPI--FÃT_ RUATANGATA \ NO.2 N0.2 ja62o3 35 4t 11! I 3988 THË GLEN N PAKÙTAI 

537801 35 43 L?l 49 90 11 

^- - -- .'---' ¿ 

531aç¡ a5 41- l-7-1 51' -- 1ô5 -1¿ - 

-T-4i-õ6T-3r-45--74 

T rTo-i

oæ ON LAT. STATION NA ATION LAT. 

NUHBER 

NUI{BER 

ÇWIER I5LAND 

EKUf,[-FOTñT----- TIRI TTRI LIGHTHOUSE - ó4ó901 3ó I74 54 85 ð64'1102 

_,461a2-364I__I14_43-__-_B7-I1_-__trtjoDFitl-'.FoREs-T--Ã 

15 DAIRY FLAT 646602 36 4L L74 39 82 .- ¿. 9- 6 9 

36 45 L74 43 100 12 

ALBANY 

65-47-ft---36-27--T7r-4-T Trr-l24-'--*--r.Ã-r-R-r¡r¡¡- --r+s3ET- 

l{ûoD-FiLl- 

RI VER,HEAI 

AL B ERT PAW--ã6-íI--F[4--86 rîr 9--- --Ãuü(fÃñD-cTrv-----6trS7ffi 

IIECHANI CS BAY 648702 3ó 51 L74 

829 

41 73 1 HËNDER,SON 

;ñn--- ersuY¡ ó48óOt '" 36 '-a-jLffaa---ji* 

174 38 8ó 14 

rl¡^ 

^llÊrrr ONEHUNGA^ 

649702 36 55 L14 41 '1 

84 g ONEHUNGA ö4e7Ð+ 64970+ 36 A6 56 L74 47 

rr^-trÃ;T'u-cK-tÃñD------64r8-cr--l6-T1--r14- 8g L2 

5z--- -t¡---¿---__ Fr_rcRtÃxD- ÀTR-po-RT.-- ä;;: 'r7 'i i#oå Þ-t ó 

ffi 

-7ã010''-- ir- T-f74 -5e-- 

KINGSEAT ?4laaz 37 I 17+ 48 lt4 24 PITKEKoHE 

TffiEFõ.- -- --152-oo-t-- 74zsa3 3? t3 LT4 i4 69 6 

3TT5_-TIE--r- ----ÐÃfù -------- 

l,tAIoRo FORËST 1437At 

7-4¿6ùI--7Tre 

37 2t tTL 43 93 6 

'Frir{fTsr-riFu rfi sT{isT 

SANDY BAY 

Ti{ANGAPOUA FOREST 

ROCKV BAYTI{AIKEKE 

TAItsUA 

THA14ES 

TAIRUA ronesTl,lARA¡TARUA__EQR 

EST 

O{EIIHERO 

P 

TE KAUI{HATA 

65540L 

ó 57ó0 ID.6 5800 I 

750802 

36 32 t75 27 

36 46 L75 36 

36 175 4 

37 'O 0 L75 5r 

75 1502 37 I L75 37 

75tBO2 37 t0 175 51 

_ _ -751_2_ol__3_7_L_8__t7_1 15_- 

74390L 37 20 174 57 

75t60L a7 

754L02 37 25 

t7t 34 

L32 t4 

102 18 

, 153 2¡_ 

95 L2 

L23 9 

786 

99 18 

99 

879 

COROI,IANDEL 

CHILTERN 

HHITIANGA 

997 

at6 

6r7rot 36 46 t'rs 30 L6g 27 

ó58501 36 49 t75 32 L66 26 

ó58702 76 5t L75 42 t29 2L 

KAUAERANGA FORESI__311_é9.¿_j 1?5 38 134 " 

18 

ITHAREKAI{^ 751801 t7 9 L75 51 153 20 

TURUA 

-t525tt 37 t4 L75 34 115 24 

trEBE?-F,I1I 

GLENIFFER,oNÈ}THERo 

}IA IH I BEA CH 

1_s_3sol_ _gl_r_g L75 33 87 l5 

74394? 37 ?L t74 54 88 L2 

753 I 

754901 175 56 t50 28 

ll^lrlgf :rl ^..^ ^ --- !7:79\ 1! 29 L75 47 1o2 e -- Hoe-o-rArNur 175 24 t LL' r.e 3L 

Tr 754bo2 2l 

?t-29-L!Þ +o 15 E_Lsro_H 755óor 3z 31 rr,- 7s 90 13 

te rnoxÀ ----------- 755?ol--n z{ 175 43 ñ7-z---äî-rür¡ =ffiftn-ffi 

HAITQA _ 756602 ?l 36 L?5 t6 -r_o_ó__ 88 15 

ffi-?5ó 

ffi 


TE PI'NA 766002 37 40 176 4 123 l8 TAURANGA AERODROI{E 16620I I7 4A 1?6 L2 TOO 6 

RIVER R0AD _llé!_qz 37 4r t75 LL ---- 

8e-13-- NGAß-uA--- 7s670l 3-7-ri-r- 175 42 87 )6 

KIITITAHI 1575Ot 37 44 L75 ?4 97 l7 I{HAKAHARAT¡IA ?ó7OOl 37 44 17ó 0 L66 27 

TAU¡fHARE 757401 3? 45 t75 2? 94 15 DUNROBIN,OKAUTA 757801 37 46 175 51 115 l? 

È{AKETU T674OL '7 

46 L76 27 I18 21 RUAKURATHAMILTON 7s'ttfJl 37 47 175 le 69 5 

RAGLAN 748801 37 48 174 53 e2 l? HORRINSVILLE DAH 758503 11 48 L15 15 96 L7 

758ó01 37 48 t't' 4A_____!49 18 -- TE PUKE 7ó8302 37 48 l7ó 19 ll5 L2 

758001 31 49 175 5 83 

? itaTÂHÀ1Â f,tATAr,tATA 758703 A1 11 49 t't5 L75 46 107 1ó ló 

PoNGAKATaA 76840L ?1 19 176 29 L25- 20 RUKUHTA 758301 37 50 I75 l8 69 4 

TE PUKE NO.z 7ó8303 37 50 L76 29 135 L2 I¡IANI ÂTUTU 768402 A7 5L t76 2'l r3l 2l 

HAIIILTON AÊRODRCIHE 758302 5? T75 20 

716203 3? '1 57 t75 L4 

85 15 

81 13 

t{HITEHALL'CAf{ERIDGE 758501 t7 52 115 3+ 93 15 

CAHBRIDGË- 75940,4 37 s4 176 29 89 l? 

76920t t7 54 17ó tô L53 L2 ROTOEHU FOREST 76e50L 7? 54 t76 ?1 130 9 

THORNTON 769601 31 '6 

176 52 9' I 

74 52 ?5 lt KUIIANUI 76eSO2 t7 5T 176 51 108 l4 

EDGECUI,IBE 7tsso3 

-¡t =8 -TÈ 48 9E ll I{HAKATANE 166 

ROTO-O RANGI 

Tiño-EiTF 

75e401 37 5e 

iÈ ieio HunsEni eoo_gq ?? 4 lI9 1? l3-9 ?l HAIN9I'I{HAKATANE 9?9901 1l =2 IJI =1 llt }g 

TAUi{ANA @ 3s T lre ¡o loo 11 

KAI'HIA 840801 38 4 L14 49 78 t? NGUTUNUT 850003 38 4 1?5 5 Lze L29 2L 2l 

ffi--8-66oéi-'aã-=5- -rTr-2T------RAnEmu -- 

ffi---Ér4õr-18-1- -ii 

ARApUNI pohÉR sTN. 85có01 3g 4 ?8 5 NootrGltnxA 8ó0101 38 4 17ó. 10 132 lô 

OpOURIAo s?oocz 3s 5 LT7 o 1?ó 4u LA{E aKATAlx¡- 8ó1401 38 6 1?6 26 l2l l2 

ROTORUA AERODROHE 8ó130t 78 , 7 175 le 114 16 LllHFIElQdglfepRU 8518Û1 38 I 175 50 e9 17 

8?1003 38 e L77 5 110 e 

ÎARAIIERA FOREST 8ó1óOI 38 8 176 39 L49 1ó }IA IHANA 

-G[EñERõõR- -Bl7zfi+ 18 f0 175 t2 - ---?5 -t-t--- 

I,IAIAHINA 8ól7cl 38 l0 -T-zr-- 1l-t6 +7 

-wnã(ÃEEx¡ RE¡¡A -_------ 86 12õã- 38 To Tt-r 6- lr0 9 

r50 zo HATAHT 8?2102 38 ró rJ? . 

re 

? rÍ1 

r)0 

?=r 

|TATPAPA PoþrER ffi fB 1?5 41 90 13 

s6?4a2 38 18 176 24 lIe 24 0PoKoTUTAR.IRUA 8ó3803 38 18 l?ó 50 L24 23 

ROTOIIAHANA 

-mmTTOlo --8t3ãõT- as 2o 

GRANT RttTKOPURTKI 863!02 38 2L 

ã ffi---E4tð01---38 2- 

TAIOÎAPU FOREST 8ó3401 38 19 176 25 8l 7 TË KUITI 853104 3g 20 175 s 66 5 

176 48 LZ3 24 NGAKURU 

só3I02 j8 22 t7ó 10 eo t3 

KAINGAR0A_ F_orq9_r 9q1æl 29 2-l 17c 5Z- - -tl - 

Water & soil technical e- AT TAI{UR I POWER sTN. 864003 38 24 17ó 1 IO8 I5 

r_7_6_ 3_! j publication no. 20 (1982) 

\). ?!_ - ___quMEl4!_rProPIo ,=_ 844801 1s-4¡ L-t4 5t tol e

o 

NUI,IBER 

HHAKAIIARU 854801 38 L7' 

EIIITEI- 

--T-646s1 '36-25' 

48 93 13 OHAKURI POI{ER STN. 8ó4002 38 25 176 5 97 I-E 

tT 

4t-----r,T8 21- -.- --ùun-uprnÃ 

8ó470t ,8 21 l7ó 42 t4l 30 

GALATEATNO.2 8ó+704 38 28 t?ó +6 9ó 1ó PUREI]R,A FOR,Ë ST 855501 38 31 1?5 33 195 

L-t4 52 91 I llA I RERÉ 855002 t8 ,2 

rA¡RAPUKAO FOREST 

LT' 

8ó5501 38 32 l?ó 34 91 6 TAHORAKUR I 

865202 38 14 1?6 L4 e9 ló 

PT.INI¡IA¡ ARIA 

85500 I ?8 35 

-TfmFEI¡F¡nU 

t75 0 78 e HAIRAKFIT SOIL.CON.RFSgóó102 

-ao6-e-01, tB- 37 Í71-5T - -ttä2_t- --- -nu-aT-- 38 31 17ó 7 97 l4 

A 

sóóeoz 3¿ 37 17ó 58 -64-6_ 8l 

¡IA¡RAKEI POIIER STI-I. 8óó1OI 3838 

l4 

l?6 ó 8t 1 TAÜHARA FÛREST 8662A1 38 38 176 t3 96 L4 

ffi-85E9õT 

' 

z6- r-irt-ET- -- -E.4 f 5- ---- -- riI-ñõrNuT-FÐ'{ESr 8óó701 38 39 L76 44 887 

lAUPO 86ó002 38 4l t76 4 75 ó TAUPO 

8ó6001 38 4t 176 5 óó4 

IIO{AKAT INO STN,I.IOKAU 

ffi__- 

847601 

86 8001 

38 

38 

43 

57 

174 37 94 

t76 5 t21 

14 

Tç- 

I{AIMIHIA FÛREST 8ó8201 38 50 17ó 1ó 81 

ilAPTER ilITD DISTRICÍ 

LOTll{ POINT 

-IIÃT-ARTU-- 

IIAUlOTARA 

GATE ST ATION 

RUTÎORIA 

HHAKATANE 

-rmmR-EIlü-sTÃT1-oNiloTU' 

IAIFASA 

-7¡r-ó-0öf 

785101 ?1 33 t78 10 tló 15 

-3-t-4: -1-?€---E - -T3r -6--- 

7812A2 37 43 178 14 180 16 

-7EE-00r 37-5T--178-5- - -T4r-T0- 

78e301 31 54 178 19 

tO8 lt 

TË ARAROA 78ó301 37 38 178 20 ttz 9 

- E-Ã S f-e ÃÞ E- [T-GFTt.|o u_s tr_ 7-s750T--îT- 42 - -TT8-5T -----TT5-T 

KATOA,hHAKAANGIANGI 787303 37 43 178 18 150 9 

--TíÃRÃEMII-S.CEOEI- T- st ,¿ Lrt 5> llr z, 

?8e201 t7 57 178 L2 112 15 

TAOROÀ STATION 

769eO3 J1 58 L76 57 100 I OPOT 

-88trI-0-1- 

IKI 8702û3 

ãB -3- t-7-B 

-l0_ - -If7-T7- .----fE-ÞltÌÃ-SÞ.qr¡ùGS --- 38 0 L77 t7 rO0 ? 

--BB-03-0f -ãE-t-r-7FT9- --TtT-Tr 

sl2505 38 16 tTt 33 115 t4 ITAN6ATU 

-TE_ 

Ftq,EST 812904 

T7-I7î--r-¿ - -EÃî¡U-r-ÎÃr-Tõ¡t 

------EE3-0-o-t- 38 r7 r77 51 847 

67T8'0r 

38 18 t78 I rrTr 

IIANGAfUNA I TOLAGA 8AY 88320t 38 te 178 16 1û2 L2 t.IATAT{A I 

873501 18 2t t77 32 t03 I 

KORANGA STAT¡ON 

--RTFõT;ÎE[ãGÃ_B-AY- 

PT.tHA 

' ñõR-^-IRAU r Þ¡rÄqÂs 

IIA IHIRERE, BEC KINGTON 

HAERÉNGA O KURI 

GISBORNE HARBOUR, 

874301 38 25 

B$4ãUI- 36 25 

874841 38 28 

884201 3e 28 

815903 38 35. 

t77 20 

-f7gre-- 

L11 50 

' 

l?8- 15 

L17 56 

87ó801 38 41 l-?7 48 

88ó001 38 41 t?8 I 

PARIKANAPA 811701 __ 38 _4å_J77__!?_ _-_ . 

oNEPOT0TItAIKARET,TOANA 878lOt 38 48 L11 1 

PIHANGA 878401 38 48 L77 26 

--89---E--- 

131 2t 

586 

846 

?89 

102 7 

824 

11ó l5 

lL4 I 

108 l5 

I,IOANUI STATION 

ðT-ol(E-- - 

TË KARAKA 

EãsTI{ooD HILL 

GI SBORNE AÊRODROI¡IE 

IlANUTUKÊ T GI SBORNE 

EREPET I 

874342 38 25 L77 

814-d0Z- 1E-2-7 ---TT? 

e74805 3A Z8 L77 

8?t701- -38 34 - 171 

s76902 38 40 L77 

876803 38 4t 

9?7301 38 44 

TUAI 878102 38 48 

Í,IARUMARU 8?95û2 ag 54 

36 

52 

43 

59 

L-t? 53 

L44 2l 

90 tl 

83 12 

- B¿ TO- 

775 

8l ó 

177 l8 eO 9 

177 48 L3t 25 

t77 9 109 14 

L77 ?2 L46 23 


8??20! ,3-q- 

--E[-LLçB.E-SI-ÂBD-K-EE,|,I- -5Þ !17 r-! I09 1-3 _TARE_!,,A_- 

-cr.voesAH(rrnl5ÈãrlwN s7s4Ù2 38 5't L71 2e 

- 8-?-e-q9? ---33--19- W -+9--.-r-8-6-28 

144 ZL rcÀNeAfo¡o siñrtronrnç sleltz 38 57 L77 47 L68 2e 

HAUI{GAlAN I}IHA _8þ9-9_L?_ V8 59 L76 es-I2---- FRASERTOHN'IIAIROA 91O4O2 39 O _ L71 24 LL' L5 

'4 126 1 HAIHUA VALLEY e7}20t a9 3 L77 14 11ó 15 

HAIROAT HA IPUTAPIJTA 9?0301 39 1 1?7 19 

HAIRoA __- e70403 

-L3-]- -!fl-ZE --- 

-93 þ _8AUzuNGÀ --9-?q!q1- !?--.1_'-L-71--8 123 18 

ll-2- l?_---=-SLENEAÊE-d!olEt'lÀqBt-lfqg93--- 3e---2 r71 2 L4? lr,. 

t16 29 Ll7 24 

116 42 ll8 9 

L76 ?3 L47 22 

!7_6L2_ L38 L3 

rE RANGr_[AUxqAHA3VßU9-éoqqL-:-9 BEA6H l-VLz?--_ 

e?osol 19 5-171 s¿--- is tz BLAcK sTur.tp srATroN eó1401 3e 1Û 

'AH'A BAIRNSDALE eó2502 3e t? 1J9 19 -- 

eó 16 

--- 

ESK FOREST eó27o2 3e 15 

TAREHA e(,zsoz ?9-16 L76 i{-- tot zz fË I{ATRERE e62501 39 17 

TRELII!X_0_E__- - ?6-?1OL 19-t7 -t-t-e +5 - lr-s -1â -t¡l!golq---- ?óæ-Q-2---39--l-s 

çL$'¡qÂBB-Y-SIAf'-I-0-IL 

- --e-éÏol 4? r38 -3-e--L-e- -1-26-- 

_p!BT!Â!p__Isrô!l_D__ __9_?380I - 3e 18 

-]11 2+ 

82 I4 

?l 

-T-E NGARU eó3801 j9 19 l?6 50 L49 L9 

¡TA IHITI 

9ó4?10 39 22 1-T6 4' t39 24 

4301 t9 

IÉ HAU 

9ó4501 3e t76 34 IOL \? 

ESKDALE 

9ó4803 ?9 24 L76 t13 

RrssIxg-IoN -- -lé4191_--.7-e--21,,11þ -!3-'--115 l7 16 

- _-N4P¡E8lE-8qp8eË-E--- I{A IHHARE 

e644tl 27 "4 1?ó 29 114 l8 

5A 

eó4801 '9 3?,-2Q- t?6 52 8L 6 

SHERETþEN ____2-þ5Lo-L 3e 39 -Lf-g:9----l-u--1-q ---NA_?I.E& 

--9q??91--?e-99- r?ó 55 81 5 

*HANAI.HANA e654ot t9 3t-:,:.(, z6--__-104-tã cor-onsri Þooío 39 35 176 30 e0 1ó 

x¡ururu qoszgl 3g ¡¡ llg !9 lo3 20 TE KATAÎA eóó3ol 3e 37 L76 23 82 LO 

RosE H¡LL s665o? ffi s4 Lt xlsr¡nc,s - 

9óó8oL 3q 39 1?ó 5l ó8 o 

HAvEL_ocK N_o¡¡Tll_-- -e66soe 

3e 40 L16 it 82 I 

---- eó6901--3-e-41- l7ó 55 - ?3 5 

-IE-x¡I4dÂll-E-LocK 

r{HA_r(A.!uô_ _ e6!29t ?2 !? }I9 ?-5 eo 11 7e 44 t76 27 83 5 

TIHAKARA 

Illâl\^ñA tvtLvL ¿' -' 

----EI-A!¡-s--Eg-tsËlT- 

-?6!!9t 

HoKoPEKA _- e91?9? le 46 17ó 5ó Lze z4 

GHAvAs þlAvå) 

cl'tlõt ; 

-- 

::::ll * i3 ,aA Eo o? A 

j-rqrq¡N-D- -- 

jt-r9- ãi s--- 

-11É- - -J7- -- ¡rA-rrAB¡-lA e68eol 2-e-4e L16 5e et 6 

--e6Bó03 

TLL 9ó8410 39 5l L16 22 90 ló S ILL 

9ó8802 39 l7ó 

BLACKB N 

232 

71 

A1 

9ó8 39 16 

92lJ 57 14 

liiirjårñU__' _ ____qqlgf-jg a \16 32--þt--!- 

HAK 

HOUNT VERNON 

|{ATPUKURAU 

---9ó 

968303 39 5l L76 23 89 l5 

s3 

lo3 l7 

9 

969 

39 I 

CLIN ó0502 400 L76 32 72 13 

rA¡?UKURAU6A5g340c1?633--TIgROTOI|AIóo?o24o0t?ó43e',15 

FOROALE 

ôu 6o7d6--1Í fu+ 

120 t9 RANGITApU óOB1l 40 2 L76 49 Lz't 24 

Pt KERANGT _-_ TTZ-TiffiTATION ó0602 q 

KopuA q 11_ __i__z_ _ _TËHpLEts ILAT_- __- _ 60?ró _ aa---5 ---!1Q-iL 

t32 le 


- 

-

l9 

AT 

NU¡IB ËR 

AR',tËtlANA ÂRAIIOANA 

ó1801 40 9 176 50 90 t3 RED OAKSTFLËMTNGTE¡I 

1õ 

6L4O2 4A 

ñ 

-i----a1-î 

10 1?ó 

l+6 TË rF RE|IUNGA RFí{uNcÂ z 7 69 l0 

-arooi 626a2 40 -----

955902 39 32 I75 5T 54 7 MAUNGANUI IVIOAþIHANGO 

-TIf_fa'_=9-ã' -T14-1I------¿I-1--6 -- _-- o-FÃFtr----- - e55801 !9 t4 175 5l 578 

s+szo-r tT 7'---T74-TZ 64t 

955?01 i9 t5 l'75 47 ó0 9 KOHHAI HLSIPUKÉOKAHU 

95ó701 3e 40 LT:2 +2 

- -5e 

eóóoûL 1? -3-7^JLó_=¡.^-- 70 J9, 

I HITFI'TAIHAÞE. Þ1636i- '17 -lí---1,75-ÈÕ: - 54 3 

HÊSSElTrlAûR0A e5?eot ae 42 L75 55 64 LO 

95640L 79 4l L75 25 ó4 10 

UTIKU SLIP 

e57S10 19 44 1?5 50 óo 6 

PAßI},IAÜHAU 

957ZOl 39 43 115 14 78 13 

Ërltr 

947402 39 +5 r74 28 90 L4 UPOKOPOITO s57to2 39 45 1?5 9 78 tl 

F.^VZÁ 

foqtç EsrArEs 

ffio = ??I?gi gsleoz a2 1+_+++__:+ *__ __:++t*:1ËË¿t¡uc_HuK_s-e4z4o!- 39 47 L7, 59 67 lO ?7ffi 

GL EN}IOOD eó8211 3e 52 t?6 l2 206 ?5 

TAf,UA 

ìffi;ööil"^': _jésspz=_ _zZ_iz _Lal 7s 

--, --i-.a- 

J-, -- -o-xl-Qrr- eÞsf,-o-l -19_-51- -175 20 

---- 

IAterilul 

-9-59OOl 

ic SO L75 3 54 4 OKOIAT|TANGAONE 

nARToN FTLTEBITA¡ToN 50407-- +0 

-rÐ-- -- 

IURAKINA 

O¡¡Vgrf Sft¡'flnfOH 

FE¡ ùp¡NG 

- - - ,- 525AL-- 40 13 

--L1Þ-33 --- 14 l-2- 

50501 -4a 

12 LL 

2 L75 tt 67 I 

uÄ8Â!A- -lq-gQ-!- 40 L L75 LL 66 ,? 

KOI{AKO 509A2 40 5 17, 55 81 L2 

TE AHA 51?q,!, 40 I r75 4? 48 3 

OHAKEA 52101 +O 17 17' 23 ,74 

FAI-TÄIÁP-IJ--- 52tO2 40 lL4_ 175 Le 4s 2 

-- 

WHARTTE PEÂK TV SIN!- 529-9?----40 lf-- J-7¿JL 94 L2 

FlEtDlt{G SEHA-EË-?-L4N-I-¡¿å04 40 15 t!2 ?2 1?-12 - 

TLoeKHotrsE,BtJLLs- 

- izzot 40 16 175 17 50 z gÚÑr.¡yrHonpE- aot ¿o 17 115 38 78 L2 

6?.¿r'rr LO ?õ 175 24 6 

53ó05 40 23 L75 77 

r ^ ^t 

t tÊ at 

HIIATANGT 54301 40 24 175 t8 58 -6 -- -L¡$]gN--ì$-LrT-@ ia--4--]11-ZÞ-- 7? 

54442 40 26 ]31_ 28 51 TIRITEA NO.2 54604 40 26-_ I75 40 92 L? 

_3 

HILL r L If'rTON 54502 4 o 

ielltHeroN {t{D DrsrRrcr 

28 175 35 7-7 L3 ilA KOI{AKO 54701 40 28 L75 42 a2 10 

4 HAITARERE FOREST 55201 40 33 I75 12 ó6 8 

775 I.IANGAT{AIRE 

t{ANG^t{uTurPAHIATUa-54801 +o zl tts r'c 55?01 +0 3l L75 45 96 1ó 

FltlNl'lmulvtr,{n¿¡ 

55óot {,o^2. .r? Êr * rr 

ËêxE^Hôq-lqHEr 

- -r_979? - 'g:+ -++! -l+ l.9 E_AsrRy_5I¡_r_r_9! - ----åóre!_--401!- t1?- ?l--- 7? r2 

IIANGAHAO UPPËR Sç+O¿-?O 38 -ttS Zg Lz6 tó LEVIN 5ó?02 40 3e 175 tó ó0 ó 


l1 

L?

A ON LAT. STATION NA 

NUMBER 

AHUNA 

5ó701 40 19 t75 + 

MOUNT BRUCE 

7t 01 1õ 46 175 9 532 

I{A TRER HURAUA 

I(tPÎHANA STN. IIATATKO 612ÚL 40 47 KOPU 

ROSEBANK'BIDEFORD 58891 æ 5l 175 51 69 9 AGSHOT STA 

PARAPARAUÍTIU AIRPORT 4990I 40 54 174 5e_ 6ó _5 __ HARANGAI STAÍIÛN 

TINUI DOI{NS STATIoN 69AC2 40 5+ 17ó 4 102 1 

llAIltcAHA'HAS-IFRT0i\|-- 5q6-04--¿¡--5e - r7'-57----6t 5 -- 

GLADSTONE,TE KOPI I5O?01 41 L L75 42 69 L2 

PAEKAKARTKT Hr LL T4o-06T--4L---T-'r71-'6--só t2 

IIOODSIDE 

L503A2 4t 5 t15 23 -- 

TITAHI BAY 

ffiunñrFloõf 

GLADSTONE IARAHURA 

KAPTTI ISLAND 

LIlIOEN 

AYAI¡0Nr LOI{ER HUTT 

IIARTINBOROUGH 

IfADD¡NGTON 

L4L8A2 

I 5tó03 

LOI'ER HUTTTTAIIIA ST L4?9TZ 41 13 L74 

c - +î-r+ -L-74- 

PURUITINcA.t'tARTIN30R. L52501 4I 14 1?5 

ffi---I4TeTÇ--fi-Io-I?ã 

HIKAUERA t526t? 41 16 t75 

KARORI RESERVOI fì 

-Offi¡ñõÃ-rA-YcLENBUR,NI 

TE I{HARAU 

IETCON HILL 

BAR¡NG HEAD LIGHl. 

STATION 

NUT'IBER 

57501 40 45 175 

5780t 40 TÃ 

5 8óOt 40 48 

587A2 æ ñ 

69001 40 54 

t75 7' 

I 

176 

35 

FI 

40 

æ 

o 

t09 t3 

8 

a2 

CASTLEPOINT LIGHT. ó9201 +A 54 17ó 13 69 t0 

¡{A TRARAPA CADEI FARI{ t5Gó01 4t o l7s -€--T-I-T' 

r5080t 4L 2 tT5 53 959 

1502orc 

r15 

82 t2 GR€YTOhN 

150401 . 41 5 t75 2S 61 10 5 

41 6 174 51 _q e q!{L_LÅGFTP0NATAHI 151501 4L 6 t75 33 72 t2 

.r 6 l?t 't----a¿ 

rz- nrn-u-li-(-S¡imi-r----Éiffi-ffi 

4l r I75 66 I 

4T-E_r.z-zi=T--r3--E--ffi "o @ lll?94 41 7 r75 23 z3 to 

t5too4 4t t?5 3 72 e 

1l_- _8___1Þ, _1q___ JL l? F_ËR]!__E!EN 1ó1001 41 I 1?6 0 74 L2 

43e01 40 51 t74 s6 7t 6 TRENTHAM 15tOO3 4l e tT' 2 - 8? v¿ 15 a¿ 

f+TEõI---+T-fil--I74 - 76 e ---Iõr'¡oeu-SH ERrñef-Sri,¡. -ffi 

r+r"/u) 141905 4L +I II ll rt4 174 56 1þ- 16 5 TAITATLOWER TAITÀ.LOWER HUTT HIJTI 14l9OZ t¿)tqo2 4t tt lL tt I74 Tz¿ 58 qq 93 o", lO rn 

- L5t4oz 41 11--T75-e-- aa àr clirvsto¡ L4zsol 4L Lz L74 4e eo t5 

-- -!l??07 !!- \2 L't4 51 7_l É I{ATKQUK0U,LONGEUSi{ 1526ü3 4L L2 L15 36 58 s 

5+ 18 e hrA¡NuroRU vLY.rNAGATAl526ol +l 13 t7i 4t ?z 

--_......:---_ 

13 

,> a+ 9 ËAHAKI t524A4 4l t4 175 

306û9 

25 57 I 

t{AKARA L42143 +L 15 L?4 42 83 9 

L4270L 4t 17 174 45 

rz3601 4i Ia Í74 tl- 

153801 4L le 175 5l 

5 s - r 1A-r ¡- - 

--fÃTõRmc-õ-,rTT-- r5210r 4r r6 I-75---9 

J1 80 14 ¡{AIHOANA TE }II{ARAU L52tO2 4L 1ó t?5 53 

9Ce 

8C L2 

82 13 

---TB66T - 4T-26 - T74--5õ ---T a--t-5 - 

144891 4t 25 t14 52 78 L7 

FAREI'ELL SPIT LIGHT. 35OOI +A 33 N3 L 74 3 

-TlITEEnt--- 26401 40 4-I -11-I -z-Ç - 75 -1 

tArftA AERODROT4E 28701 40 4q t72 46 

lO7 I 

ffi - -T2osor-4- T- r - - i-tz-E c- -fr c z s- 

llos3 BUSH 120elo 41 3 L72 55 t14 12 


KËLBUTINTWELLINÈTON 142702 4L 17 t?4 46 71 5 

noNogr-lr --_ r+aeTe 

-a[lg-il{-l! 7l tz 

-- ?9 ll 

IlÇsEût-H¡ - 

__ _ TETLINGTON A¡RPORT 143807 4t 2g L14 +9 

8? 

EE IZ 

ó9ó 

CAPE PALLISÉR LIGHT. 156301 41 37 I?5 t8 789 

STEPHENS ISLAND LIGHT 4óOOI 40 40 

- - aÃlñ¡rIr.r ---r15õt -4O-"6 - 

UR,UTHËNUA 29801 40 59 

TITIRANGI RAY 

RIHAKA VALLÊY 

140IOZ +I r 174 

L?aeoz 41 3 L72 

L74 0 578 

t72 3? Leg 25 

t72 49 r7l ló 

9 

55 

erTt 

133 tó

COBB POTIER STATION 

ßIIAKA t IIOTUE KA -- rzl-ttrf 

ÎH¡'IROTHERS LIGHT. 1414T1 

1 2070t 

-6- -LïZ 5F-- 

_-IûI--t Þ-etKo-KiÑ-l- ---TtI963--41--6--TTT-56-TI-ö-T4- 

ffi-T4[OoT- 

4I 

TESIERN L oTFÅ xqvr Ej' i 1_4 e_q_1 

4L 

-4-1- 

41 

5 t12 44 149 ?4 COBB DAH L2l6A2 41 6 L72 41 118 9 

6 174 21 69 13 

T---T7T-T-_-LTT_N 

7L742 

41 1ù 112 58 88 e 

T4-17- - -- mlrE_ï rurFR-tr-- 

84 

57 

ó3 

HDTUEKA 131002 4t 1 L73 I 118 1.8 

IZ1eO3 4I e L7? 5e 

141002 4l 10 L74 2 

}.AITARIA 8AY 

ïHAHCA¡|OA 2 1315û4 4L 11 t7? 3t t44 ?5 COLLTNS VALLEY 131503 41 rt r73 14 

rjffiRTFo_T-22aõr--¿i-rz--_IT2-5o-__T3T2o----__FtanÃKEK-_-13200_T-lT-I'-1?'-_r 

TFFIEEY-- ---rrzrol--4Tar-T1a--é----6r--4----TEt-gctr FRo-õRTrr4-F-.-T!2-62ffi 

ffi1¡_qKSI4ZOOr 

BËNE AG LE 

GLENI{AE 

SEAVI trll 

LZ3 ¿> 

L54 24 

l3ó 1.5 

nAI.vALLEy L32501 41 t4 t7a 35 t41 14 THORPÊ L22802 4L 17 112 5L 

6t- 

NELSON t7¿¡.o1 41 L7 .173 18 6e 4 r.lA ITAI VALLÊY L323A2 4L t7 173 21 141 26 

HAVELOCK l327OL 4L 11 173 46 146 24 LIÀ¡KWATÊR 

r32Súl 4l t7 171 52 155 26 

çT-TT--TTÇ-T---T0-g-¡¡ Dltv-E-õ-A-LE 

---LT'EOT-4-I T8 L12 55 7' 6 

CANYASTOT{N t33ó03 4L l8 113 40 127 ZO BATON 

123701 4L 19 172 43 9t I 

-HÃgËLOCI( SUBTJRBAN 

- 13l7OI 

- 

4I ?a L17 46 114 15 oCÉAN 8AY 

143101- 41 2t taL -'6 109 TT- 

KOROHIKO 133eÛ1 41 21 173 58 153 2L HOUTËRE HILLS 13300L 4L 22 I?35787 

HOUTECE NO.4 133OrO 41 22 113 96 10 HCUTERE N0.5 l330ll 4L 22 1?3 5 e? 11 

lrlot TERÉ No.I2 133014 4L 22 t73 5 9Û 11 i'IOUTERF NÛ.14 

noOine nlven r3?:-g!__+]_22---L7-3- !!-- --. e6 -- ó r33t1 2 41221735979 

- - - -- BRIGHTT{ATE-1--- .-. 1331 02 4t ?t t7t I 9l l4 

-taffirELD NoJ r¡+oo+ 4L 24 173 3 e5 ç HANGÂPËKA 

r'roluPtKo -L-?+:99L 1L ?L t246AZ 4l 26 1?2 38 83 7 

L72 4e 18 L-2 _!ta I toa__G-o R_GË_ N 

q, 3_ _ !34qLó 1LZl L73__5 *__l_04__té_ 

HARSHLA[q_9__-_ -.- !41-0-ql--!I 2-1 l-21---9 -89 

T¡BlANs itÄttgy 135501 41 31 L1? 35 105 1-9 ASnqQ{N siltr!lNAt!Ä!uru!34éQL tt Lq 

10 

-]:D- 4r 12? L5 

aLEÑHEtt'l AERoDRoMtr 1358ü1 41 3l t7l 5? 55 I 

- 

_BLEf{HEIr't _.__I-3å_?g¿ - 4L 1r r11 51 5> 3 r2590L 4r ?2 L72 56 108 18 

---iiI}lIPANGtl 

SEYEilOAKS 135802 +L 72 L73 4e 669 GOLDEN DOIINS FoRÉST 125801 41 33 172 5l 774 

FAI Ri{A LL _ 135803 4L-31- ,!73 51 ò5 

- - 9 

t259or 

-lyrrEsFrELD-- - 51,]l- -11_? 

!\ 

13ó701 +r z6 173 45 

UGBROOKE r46LA3 4r ?1 r71- -þf 

136e40 4L 38 1?3 53 

ITAIHOPAI POyIER STN. !1óÞif - 41 4A- -L73-34 - 

Lt5 28 

554 

6_ 

7 

I 

79t 

93 ll 

__L]Þ2Aþ 41 35 -1?3 

56 192 19 

13ó401 4t 31 177 24 73 e 

14ó101 4L 37 L74 9 59 9 

BIRCH HILL 13ó201 41 39 I13 11 96 L4 

sÉD_qoN 14óOO1- 4! EO- -L74 5.- 7t L6 

EAPE,çÂi{e_LËL-L__LIÇl!Ir L-+7 9-t -*-L 1! -L1--+-}1 

THE LËATHAM 

4L 45 r13 L2 106 t1 rnÊ-H-ll-ooNs 13?9ol 4L 45 173 5e - 84 l8 

¡ I lg LÊÃ I I r^r I 

rAI rrr \1-!9Q-? 41 45 t74 5 9e \3 

AOIEA 137802 4L 47 tlt 4c 77 14 I{URCH I SON 128301 41 48 L12 ?A 653 

ÃglE^ 

- LAKE RoTOITI t2asoz 41 48 L72 5L 1? -J_ - ¿U-UIÅE9!- l387ol +L---]2_ L73 46 85 13 


73 13

â 

NUI,IBER 

Lü{G.E 

ON 

NU14EER 

I,IURCHIS=ON L¿o,v¿ t283OZ 4L +L 50 )u t tl? t1 ?O 2.9 ó[ ó1 s5 HANGLES VALLEY L284ù2 4L 50 172 24 

CHAÍ{CET HARD 14glor 4r ¡o - rz¿ 1r 

- -84 

ls -- --Srx-rriiE - iããaó+ il-m-iffi; 

f.f!99I,.lI4TERE VALLEY 13??91 41 54 L73 34 83 15 r,trpoLE HURST 13e4or 41 5e L73 ?7 

xoLEs¡{oRTH 

---ZidZdL 

CHRISTCHURCH I.iWD DI STRICT 

¡IESTPORT AÉRODROI,IE 

¡NANGAHU_A _ _ _ 

II{ANGAHUA LANDIN6 

L22lOL 

It75A2 

I18901 

1 1eeo I 

4L L5 27 

4L 44 fZf aS 784 

_41 51 _ l7l 57 s3 ó 

4L 55 tzt s¡ ror rr 

ERTo}I 

I{É STPORT 

BERL INS 

DUI{FR E ITH 

746 

776 

50? 

16802 41 41 l7l 53 

117óot 4L 45 171 36 8tå 

118001 4l 52 171 50 135 al 

22020t 42 4 t72 15 89 ô 

REEFION 211801 42 7 l7t 52 78 3 _ REEFTON 211802 42 7 l?t 52 8? 11 

LE¡rls PASS 22340L 42 ?3 L72 24 102 e GREyr{ot TH ?L420L 42 27 '1?1 L? 108 t2 

OOBSON 21430t 42 27 171 t8 109 1l GREYT.IOUTH 21424? 42 2S t?l L2 100 6 

w tt5 tl PAROA 2r5ra2 42 31 171 lO 107 t2 

KArrlAÏA 215401 42 32. 171 25 108 9 HAUprRr Z159ol 4? 34 lzt 5ó 99 lO 

ffi 

HOKITIKA SOUTH 20790t 42 +3 170 57 Lag_ ó _ HOKITTKA AERODROilE 2O7eO! +2 43 t7O 5e LOz ó 

LAKE KANIERE 218102 42 48 l7l I 1ó6 2l OTTRA SUB STATION 218501 42 50 l?1 34 183 I 

Ko¡aHrrIRANGr No.2 z raoor Tr r:-t7r z t51 21 ROSS 20e801 42 54 170 49 t4? 15 

HARI HARI 301502 43 I t?0 33 200 27 HARr HARr 30t503 43 9 t?O 33 L75 25 

LO¡|ER llHaTARoA 302301 43 Lz L7o 22 L52 20 wHATARoA 7oz?o3 43 tó L7o zz ztt 2.3 

FRANZ JOSEF 303lol +3 23 1?O 11 2"2 19 FOX GLACIER 3O4OO1 4t 28 1?O t 184 23 

Fox GLACTER 304002 4? 2S 170 L 215 3? I{AHITAHI 3966c,2 43 38 1ó9 3ó 186 28 

3-EmI- 

BILLY CAHPTHAASÏ 399301 4? ,6 169 tB ?33 32 MCPERSON CAI'IPrHAAST 3g93OZ 43 57 169 19 L9O 27 

ffi-tE116T-4:-4;---T6çm_-FAAS. 

M zaóóói 42 I t?3 5e rz¡ ?+ 

NGAIO DOI{NS____ ?392_A?_42__ 4 _L73 57 L27 28 GRANGE ROADTHAPUKU 2t36OL +2 le L73 4L 158 30 

SA¡IYERS DOI{NS 233401 42 27 l?3 29 I3A ?1 KAIKOURA 234701 

HAI{I{ER FOREST 

---2860T- 47-s-t- TtZ m --zã¡Eõi 

COiITIAY FLAT 23ó401 42 39 L?-f 27 101 24 t{A }tKS HOOD ?3ó302 

RIYERSIDE ?2180t 42 43 t72 53 -IF---E----FERNIEÐ 

548 ISLAND HILLS 

sP01sH00D 23730L +2 45 L7t 18 I08 24 

LAKËS STATION 


?2750L 

22720L 

42 25 tÌ,- 42 968 

42 36 1?3 le 

42 3e L73 20 

42 45 172 ,7 

42 46 L72 ló 

r31 2? 

t3,ô' 25

CULVERDEN 

GME_E¡V--- 

2218A? 42 46 r72 61 +a 6 LOWRY HI_ILS STa¡_1s¡¡ 43q!-q!-!L-2L- 1?3 ó 75 L2 

gÊ . evL 

ãisaoi 4T5r 1E Í9- F- iL sÁL-uoRÃL-FoREsT zzï-tol ãis3o-1 Etsr1B i9- - --f 5- it - sÁL-H0RÃL-F0RESí- zzï-to7- 42 52 t r¿ 1> )+ r 

PORÎ ROBINSON 2383a2 4? 5?- L73 18 ?8 13 MASON! FLAT zzes}L 42 54 L72 32 48 ó 

¿2ô3V¿ -¿ )._ La2 !v 

zzç4d1--12--55--T7Z-26---aZ-iT ARTHURS PASS STORE zresvz +z >6 I rr 5r ¿5v ¿5 

?3e_Lgr_ 42_56 _r't! -2 ,- 

171 

T-l-? -ABr!-r-uLLqël-- -z-!22e,t--!41 

t4 183 l? 

-- 

SANDHURST PASS 3207a1 43 1 L72 42 ó0 lt 

--r.t-otu-tt-¡-u 'hEKA --¡-e-ooor--11- T 173 5 79_ r' 

HouHr rüHIrÊ srArIoN 31oeo1 I{A 

-SRT_TÃSIN 

1? 1 -111 ?9 ---FuTErÉTf 

I P ARA 

72A7A2 43 3 L1? 45 548 

---9ll 

3TT-7c'1 47 I 171 4ó f7 I 

cRrfo¡eaunrr FoREST 311702 47 s 171 43 78 I !L'll3¡_Ë q4_L -E__ _ a?LZOL 43 9 tTz 12 7r tI 

GLENÏHTRN È 311401 43 tl 171 21 

nÃ ¡r-FER-n-TVE R -- -- -- 91 L2 

A].IBÊRLEY 

3 21701 43 9 l-tz +3 80 t7 

Tõð-u-Fs¡--- 3?ø7õ67- 1-3 lZ -t72 2q- -- 1s-t2 

-- :-lT4dT- 6-LT-I71|-2 s 7' lo 

CKUKU 322!02 43 14 172 23 67 to 

TEf,FO-SFSIATION 

KTLt{ARNOCK 

- 

GLENALLEN 22960t 42 'e 

l7z 39 51 I 

ciËiñ'-- ttolaz- 43--2-a7T-+5--- -62 -6 

CASTLÉ HILL 3r27AL 43 L4 171 43658 

-FEIK_HIf,t 

_=4ilg--f7T TTT4TT rT--_-TZ-T3------m-0-ur¡rTtRaãssE--------3T3-90T--E-5-TE-TirI- 56 a5s 

RAN6¡ORA 

t23502 47 le 112 34 66 9 I{OODEND ?23602 43 ?A 172 40 73 ló 

L.COLERIDGE HOI{ES TEAD3l350T 43 ?I I71 35 óü7 LAKÊ colÉarocl 713502 43 22 l?l 32 ó1 6 

TÃL-ËTHT¡RPE 

- --3-13-t-07- -45 -Êfln-e 

2A- 171-52 74 l0 wÉlu roresr- - 1z-+7ol +{-24 - 7.72-fr-------6T-T 

¡IAII{AKARIRI BRIDGÊ 3246CIL 43 25 LlZ 79 

ffi õñ- ---TtTTrJ r - -4t ZT 

DARFIÉLD 

!24IO2 4l 29 - -¡¡--Ça- 12 15 UPPER, LAKF TIFRON 314110 47 26 171 11 77 tO 

---?E--e- - --frcV-Fl-¿ID-S-- 

L72 I 6.5 

Ar¡1PORT 3Z+50L 43 29 172 12 51 7 

43 

SI{IRLEY 3256A3 

-Þ-AFÃRIIÃ-TR-rSOñI-FARE - ã25-{OI - -43-tf 

43 3ü L12 40 17 18 

- 

a7-f28 

43 

Èrpffi_¡R-rsoñr-F¡Rm -ã25-{oI --43-tr -a7-f28 - EREhHON 3058Ü1 31 170 5? e2 L2 

iuoSfof e--.. - 5ó- 11 H0'ìE-RATA |.¡ËsT -3f58or 32 171 51 6-3---T 

43 

CHRISTCI{URCH 3256t1 +3 32 L72 V7 54 3 BRûFILEY 

iI5-óoz tzt +r - 

r C 

+3 

iuosrore---- II5-óOZ +z tl l?1 41 75 - r-{RI STCqURCI'{ 325103 3? 172 42 78 14 

1 HoR0RÀTA 

- 31i90i 13 L7l 54 ó5 '9 

43 

HORORATA SUB STATION 315e(i3 43 33 l?t 5e 51 5 WI GRAù{ AE RODc'0i'1E ? 25502 ?3 L72 33 544 

I12 4a 

HIGIJBANK PÛþ¡Ëì S1\¡. 3L57C2 47 35 17I +4 

I,IOUNT PLEASANT 3251A4 43 34 T12 4A 53 543 

B 

172 GOIILEY H:AD LI\;HT. 325801 43 35 L1? 4g 

HOR0TANE 3251A5 43 75 r72 42 71 15 

.Eß-E. EltÊ-L-E-L D-S-r Lt t-it1Ð¡{-(- 3-r-ó7-QL -43 6 T5 18 

? --lU- 4L-_ ó8 I 

ALASKA 

I 

-- 

3L6505 +3 76 -.-L7L_--3_-1- - - EÞ- - e- 

LYTIÊLTON ?261CL 47 ?7 L72 47 84 19 

stRilHAH SEþlloE PLÂNT 3263AL 43 31 L17 19 55 9 

üE-IHV-EN 1!ó6QL 

- 

- -43 38 -r?l--ae - -.- 

7L L2 

-Ë-Esg¿Ol¡tltÀ - --- 3.Ûé901-- 43 39- L79 5-4 tt L? 

3 !6tù_? _ +? 19 _ Ll L 27-- __gt- r I 

r,rouNT Po99E5!!-o¡L-- 3162C11 +3 32 L7-L- ]! -83 18 

ST AVE L ËY 

326401 47 ?9 172 28 54 ? 

cneesloÈ 3lô8ol 4? 3e t'71 4e 86 t7 

L INCOLN 

puRAU 3?6'192---43 39 l7Z 45 L25 30 336001 43 4A 1?3 0 96 ?l 

SPRINGBURN 3ló403 41 +l -- 

LTTTLE A(ALOA 

171 29 

EVAN9ALE -1113-03- 43 83 18 TÊ PIRITA TI{ÊAD 3ró901 43 4t 171 59 62 lO 

42 rf I 20 _8/+,18 tI LYgÂ¡iK_ 5T-AI I8N 3q_?J!1 43 _!3._ rla 84 13 

- Water & soil technical publication no. 20 (1982) 

"4 

\¡

æ 

TATI 

¡rouNT sor.tERS 7L740? 43 43 1?1 24 

THE HERMITAGE,r1- -c-ooK3o?ro ll¡-++- Ito --- ó 

KILLINCHY 3212A2 43 44 t72 L4 

EASTHOODTLE FONS 3Ay 33710L 43 45 173 6 

SOIfERToN 38992 43 46 tll s5 

83 _U______ GRËENPARK__ 3275OL 43 43 L12 3L 453 

zag 15 BUCCL EUGH r t¡tT. SOüE R S 317403 43 44 171 29 ?5 t3 

5\ -l 

TJH I lF RNfìK 

3 1710 t 41 45 t?t tô ,A l, 

lo0 21 BRAC(LEY, T.IAYFIELD tL73O4 43 +6 171 rrl 25 

558 

o \ AI-Ë-IÐUVÂUEIJ E l=L E -B¡ Y3eZ9-q! 

- 43 46 L'tz 19 

56 948 

1?_l _35 _ óé _1_r 

t{ I NCH tYtOR, S 

318803 43 48 171 48 55 I 

172 58 t37 27 LOCHA B ÉR 

318001 41 5g 171 4 74 tO 

171 l5 lI3 ?4 I,IAGNET BAY ___ .128701 43 5l L72 45 65 13 

170 28 544 VA LETTA 3L85A2 43 53 171 75 58 I 

AKAROA 32890L 4' 49 

IrtouNT P EEL 3t5202 43 50 

GÛDLEY PEAKSITEKAPO 3O84OI 4! 52 

AKARoA HÊAD ____ 728eAZ 4? 57 t7z 59 -___ 8e _2r_ ___!{IDEAI_!!5HAßL __ _L,L?403 !3 54 t7r Z' 78 1? 

ASHBURTON 319?01 +3 54 t7L 45 5e j_ __ DEEPBURN 3Oe8Ol 43 56 170 1?O 51_ e8 t5 

ORARI GORGE 319206 +3 58 l7l t2 101 T8 BRAEI{AR 

309201 43 59 170 12 6? 3 

IqJryI- {OHN 30e4or 43 5e r?O 28 +2 4 HrltDs 3te4ot 43 5s 1?l 2ó ó3 7 

171 ro sBrr ffi- ;ôó¿õi ¿í-í_jiffi 

FORD 410601 44 7L ?6 58 6 HORIIELL s 4007a2 44 2 170 43 Ác å 

HIIAST PASS 4eL3A2 44 6 L69 22 t+4 

ffiñ+ç-la- 

9 

LAI4BROO( 4018û1 44 t?O 51 57 4 

I t711e óO 7 

CûLDSTREAT{ No.3 411503 44 9 l7l 33 ãl , 

.LAKE €IHAU_!_I¡rION +etBfJz +4 

s l?l 37 5r t 

LO- Lq 49 724 LAKE PUKAKJ NO.z _- 4OI1O2 44 11 17O B 12? 

TEHGAIIA I 4O27O2 & 13 l7O t+4 51 7 1ËI,IUKA 4l?204 44 15 171 l? 453¿ 

iE-- 

ç9f!=CIEEK'r'lAllARo 403e03 44 l'8 l?0 54 ó8 12 TIIIARU AERoDRot{E 4l31ot 44 lB t?l 14 4? 3 

SEADOIIN 

RIEBOt{tlü)D __ 493801 44 22 169 51 60 + SilITHFIELD 4lt2o2 ¿* 22 171 15 4' 5 

GLENITI RESERVOIR 414104 44 ?4 1.71 ll 51 4 TII{ARU HARBOUR 414202 * 24 171 l5 476 

TIñARU 4t4ZOt 44 25 l?t 15 51 t ADAIR 4r4rol 44 26 fm 

HAKA ITAKA uuhrNs DOIJNS 5lAlluN STATTON r+(xlóol 404óOl +4 44 26 r70 170 40 +9 3 r{ouNT NIt{RoD 4o4got 44 26 170 53 75 12 

oTEXATATA 1062q3 +4 36 1?0 L2 38 3 __IIOANAROA 416101 ¿+4 36 l7t ó 78 l? 

¡rA¡KORA 40ó?01 t4 40 l?o 41 ó6 6644 LAKE I{AITAKI 

}|A¡HATE SADD-LE ¿07t-t- 

40ô401 * 41 t7l) 170 2, 

* 

47 I 

1+ Ií7A 

70 59 -----ã- 7 HArrrrATE 

FORD HILLS 407?01 44 45 

--- nzoói ++ +¿---Îtrt 57 

70 

46 


\o 

ffi ,F----4ezz6z-44-Tr-rETt---18ç--ç---------tîrñÃmr-Eãy-- 

rARA HrLLs,or{ARAr,rA +929-9\ !1 2! !!9 =2- 2-2 ? 

TPFEn-TEG Þo-H-Ed-tÎ-N; 4-ca0õT - 14 5B-- 

i-oçoõ-i 14-58-- Gç--¡ - --61__--- - -oÃEÃ-[u Ãr-tro-oTsHE--_--4fç06T--1T3î 

-¡FTFUFs_To1NT-----,t696ilr'-++-5Ç_-ró8_Zõ---74l4---[ÃÚDER¡TÃ1---_--_'g61 

¡TEODERBURN 5OOOO2 45 1 1?O O 42 ó NASEBY FOR,EST 5OOIO2 4, I t?0 6 44 2 

TúEEñsfirFr s-õiioiffi----tr-i-ffi---Eirini 

G¡BBSTO¡{ 5gggot 4, L68 57 51 7 CROI'IHELL 59O2Ol 45 2 L69 12 39 t 

-mTÃK-ANút---- 5to5õ-1 +'s i " l_¿q-¡r-- - 5l -a - o¡¡r-n:: - E-çreor--€-T-a6r-?F------æ-T 

--a --raE- 45_- - --4T-l - -RAN-Fu-RTf 50rt01 4, I 170 6 30t 

-FTE-TFEER- 

581?õi 

tfAlPIAlA 501102 45 r01709?83 

TË ANAU ÐOHNS 571802 45 ll 1ó7 50 

59130r 45Tf-T-6e-TE 365 -- -_x¡T-æR 

45 

5oró01 45 11 1?0 4l t07 25 -t1ó02 

11 l6e 

GALLOHAY 

59249L 45 13 ló9 79 

28 

HERBERT FOREsT 

IIANORBURN DAlt 

-TROTTEFS CRE'EK 

TE AtìlAU 

45 

5-e25A2- 45 L1 T6E-2A- ---24-¿ w-Ãril¡Àîf 

- - 

- l6zÍdT' -85- r4--f To--E ,32 

W ró915 59 ó 

ËoRyEN HILLS 4eó501 44 a9 1ó9 30 58 I HILFORD SOUND 47ó901 44 4A L67 55 235 16 

T[mm-FosT-EFFr-r-E---4-çzTõrîïEz-:toç:i---6=-7-=E 

TTinRE---- 

-----ZõEE-oI - -44-TE -Fto ¡-o-- 4? -a----TARRAS--- 4e8401 44 ,o lóe 26 ,79 

GLEìIORCHY 488301 44 5l ló8 23 78 15 DUNTROON 408601 44 52 170 4l 19 I 

49930L 44 54 ló9 19 5ó 10 AL-AßSTONE HILL ¿r999ol ¿l+ )ö ló9 55 40+ 

TEX'õTGO_- 

489801 44 51 169 50 49 3 KNOÐS FLAT _____489001 44 ló8 2 e07 

IRROHTOIdN 

'8 t?l 5 56 lO 

Tf,YD- 

KAURUTTHE DASHËR 

-mFFSgCC-usF- 

5T¿-762 --45 I5-- 1-7O 46 -' -9T-21 

30 z 

593601 45 22 169 76 t2 1 GLENDALE STATION 503401 45 22 L70 ?7 óo t3 

5 03 EOZ - -4T -ZT-TZo--49---' -Tt - 11 ffiD-- 

574801 45 ?4 1ô7 53 öO E 

5141$t 45 25 167 44 5t 5 TE ANAUr(A(APO RD 574802 45 

- óî --6 

25 ló? 4S 59 ? 

-p-ÃEFÄII- --5o490T- -45-25 --L-ô,-e -17 - - RoxtuRdi{- Po-WER 

-Sïñ; 

-ss43õ-I--4-52Tl6119----=0-T- 

-EYFF-CR-EF-K- 

-5e546-1 4l3T- L-e,s zl - - 5-t--ó 

G-R 

-ÊÃ1 -rq 

oS 5 -S w-A r'1Þ- - - 5958 0- t - 4-t-3-T--I69-49 ++, 

GARTHIIYL?tlIDDLEt¡IARCH 5û5102 45 al 170 I 385 CFNTREWOOü 505?Ol 45 31 170 4ó 619 

-5-E toT' -41-TT-Tæ-I9-_---- 1{-7- ---Hf LtTõ-Þ'' RorSnRcF-- '--595-405-aÆ- 33 169 24 

ROXEURGH EAST 

FlAflÃru\,^L TIANAPOURI 

' --' ---__- 

575601 4' 34 L67 36 51 5 MID I)OMÉ 

585502 45 34 1ó8 30 

-ëx-Ë-nn-v=rA-R-F;Þ-u¡Err1¡r -EOó-6Õz 11 1r -iz6 T'Ì- --tI - 

6- LÕHÍHËR- 5-ft6401, -15-41- 16{21 42 3 

-DEíp-TTRË¡EI-O;Z-_- 45 4r -I:ÇE 5e --- ]3 

ruNROBIN '.q69Ú2 587101 45 44 168 7 5e 

R f LÞEñ r\Io .I 5 912tL 45 4t I ¿i9 r 2 Lg 

HINDON 1:ARM 5012itL 45 45 17û 12 62 

I{ENDONSIDE 5877Ü1 45 46 158 4+ 41 

9 

7 

êt 

9 

(, 


MUR{AV CRËEK 

T? rl 

3t 

2Ö 

I 

3 

4rc 

5612OL - 45 42-- L6{TT------37--ThATKAIA 

58?8ol 45 44 168 51 57 t2 

pt,rt'w;¡o - 

5o12t2 45 44 170 15 69 14- 

ELAC(t{tLJiìi STATITJN 57871Û 45 +6 16? 4Û ?0 I 

MüA trLAT' 5972ú? 45 46 1ó9 t7 41 3 

5l 

ât

N) 

o 

STATIoN NAr{gmLfï3---ffij 

NUIIE ER 

f.{ONOtlA I 5 7760 1 

IAIAROA HEAD 5077Û1_- 

ST PATRTCKS,DUNEOIN 588503 

tÞ_ 

45 

45 

IULLIYAN__AAH 5_Q,95_o__3 

INVERI{AYITAIERI 5083i1 

41 

45 

47 L(r'| a7 

- 

4't tza 44 . _, 

4e t68 32 

1_9 _L7A _31__ 

51 1?0 22 

-r, ---- 

-NAf--TTrrlo¡¡ 

NUI{B ER 

LAT. S LONG.E 

55 5 L:: ËLAT 50?001 45 47 t7O Z 4L j 

---19 -J. - -B4F-s- -J-!rN-EI-r-ç¡¡,t--._ ._ sea90l__.t.Js Jþ2__4_ 44 6 

46 7 I{HARÊ FLAÎ 5í}84ùa i{ +ç tiO zd -1rr 2r 

?? L6 _SAbI_YËRS 84Y 29góq1 45 !e_ IIO 3ó er 15 

51 ó Rsss cRÊ=K roe¡oi ¿t 5a i70- 30 - 8-Ìi4 

s B¡,rúo,r¡Lr eurnÃu 5alzo:- 45- il - Iio-It-- óo t2 

BEAUIIONT 

5eß402 45 52 foÞ ls 

DUNEDTN BTL. GAR,pENS 5085C2 45 52 t10 3L 61 4 

I{AHINERANGI DAII 59åi9ol 45 53 

_-_ LTNHOPE 

l¿ì9 

__ 5S841O 45 53 L68 ?7 

58 576 

tE:M,t= I{ËTHER 

I4r_ HI LL __ _____51 ee 0 l_ _!5__ 5 4 _ _ f_61 _ 57 

souTH RSRVR.,DUNEÐIN 50 e4g2- -4t 54-- L-lc- i - X? --5 --3!8I[SI-DErQU|!ED-IN -- -- 5-qe1g1- +t-54 L7o 21 

111 Zt r.tussÊL3uR6Hrt-lui,tÊtllN 509504 45 54.1?O 31 3t 

LAITRENCE 5ee60t -1E ss - r¿s +1 si tZ-- 

KAHEKU 589óOt 45 tl tóg 40 4? 6 

5ee2o1 -ã-ffiö-ä--r-ä- 

LTNHUTE __ 5EB4IO 45 53 lóg 2Z 5g 6 

CAPE SAUNDERS LIGHT. 5A8702 45Ñ 

DUNEDIN A IRPORT 

5úe2AL 4' 56 l?O ¡.2- 42 

59eOt 7 16q 

RANKLEBURN ' 

FOREST 599401 45 

EtslE_eu._B_u_sll_ 

HENLEY _ 57_27ar 

5oetot--tt -tC -_iro 58 169 26 

_ qg, 5_9 

to i{ n 

_L67 46 46 5 

Lf LLBURN 

ô70óol 46 0 L67 40 

-ttÃttOEvll-f-E-- 

546 

680801 aeoßor -i* +6 0 n -rô-Zó lo8 4e +ã couof a-nir-r--- ozo¿or-aó__l - 

LOßA. STATION I 

ó8050. ó80501 16? _ 4ó I tó8 33 

n 627 

6û 9 

_ HA 

REABY 

rHOLA 

DOI{NS jggo_a__4é ___Þ 

6&0701 46 __ 

Z 

l_r_?q 63 14 

768 46 39 4 TUAPEKA f.IOUTH ó9Ü5OI 46 2 169 

:ll5pF+icH'ra_L____ g!+!az_!q 

73 

3 Lþ7t3_ 

395 

_2_c_ 8- 

EAST L-oqL_Sc_tlqpL 

GOR,5 6ß0903 46 __ _ __ó8qj_!_o_ 9þ _-4 I óg 

5 

29 

1ó8 

457 

57 t7 t TA IER I f,4OUÎH ó00201 +6 5 170 L2 486 

GoRE -- 

457 

6E tO 

503 

¿sieor- ãe o--ioelð- ---E-T 

__-_681701 46 Ióß_ 45 43 4 

ó91e01 46 7 169 58 4g ? 

ts z 

gtQ!NS'UI-NI-0-N-- 

--_---é,-q!!10-- 4é---e- 

PUYSEGUR POINT LIGHT.óó1601 46 i-_1ó6 --!6s 3?- 27 - 81 4 

HTNTON oarãoã ?¿ -ó---r-oe 20- - -lo -l 

3 orrrihli 

OT AUTAU 681002 -ro +o tót-õ---- 40 2 

P:åIE!=STCCK,T{An{ËRA s.6e¡5gl _19 !o róe 31 34 5 r{rNToN 

IIII9I^ 

-Ð-_Ë_-ffi 

é!¡æl-tå. rI 

ó82810 46 ll -!é-8-2-g-----_{r 

ü¡-ïÂuRA 

1ó8 52 38 -¿ 

3 

þ_ 68280l þ.1gllL _.rô _t_? L6g 52 

cHRYSTALLS eEÁcH -9I?F4óìr-rãa 

ó02101 + -:? 46 +-3- 12 -170 =!_ég -¿ 

Þe__. _ 3? _ E _ c_LrNroN _ 

37' 

þ?¿?ez _1þ- 12 LqeL?-- 4? 6_ 

POURAKINO VALLEY 672elo 46 13 167 55 56 6 

HEOGEHOPE 682501 46 t3 1ó8 a? 4L5 

OlA}IUTI 6BZTOT- 4ó l4 l6s--to 36 

B A LC LUTHA 

44 4_._._PÊBBLY HILLS 

45 7 OREPUK I 

HOKONUI FI}RE ST 

68250? 46 t3 168 35 392 

6e27A2 46 t4 L69 45 --3t 

2 

68l6LZ tú I ó 

6727û2 46 1? 

683701 46 19 168 47 

INCHCLUIHA _i!!_.3 óe38o2 jL6___rB __f_Þ? 50 _ 52 ?.. _- - _E_D_rN-qaL_E 

333 


pAHIA 6?3801 46 Zú t61. 42- 54 5 SLOPËDOI{N -- , 693ZLA 46 20 ló9 LZ 42 4 

rfËx-r-^rDÊR-_6ç4orõ-__=4;-7>-içÇ-ï- -- îi--1- - - _- 

GNNtrrãrï¡r 

- aal4ta- 4621--t6e n ----1î-t 

INVERCARGILL AIRpoRT ôB43cp" 46 25 ré,q 2Cj- 36 2 !l\yËÀc,A3GI!!- ó843Û2 25 168 Z? 7e 3 

ffi---6ñEdr--:4îæ-i;-¡t--Í.T'rr 

--=õ4iEi- 46ffi 

!,NA\,l Y ALLL I 

LÊ A A 

t¡tATAuRA I5LANDS óg4?10 46 z't lóg 45 4û 5 ot{AKA ó94{5û1 46 ?7 169 39 65 13 

-{qr¡¡r 

lluiqEl PgINI_ Lt9tlI: _ 6_?4?91_ 4þ_ CËNTRE ISLANIÌ LIGHT. ó74801 +6 28 ló7 51 45 5 

-ÃI{ÀRUA- 

?7 L69 49 ?)4 

685301 46 3r 

.ã¡¡äii-ilil-r-s---- ¿s5oof +e zz t6e 3 ---66 

168 22 373 

LT 

BUCKINGHAM RESERVE 695ZIO 46 33 16e l? 7C r? 

-oõ-e-fSf ¡Ho -nenf-t8ó4sr +a 

- 

-zs' 

oan,r¡rsre¡lET--isLAND oeçror 46 54 1ó8 I 50 2 

168 25 155 


APPENDIX E 

Compadson of Regional Flood 

Estimation Method with TM61 

comparison because all catchments used here also were used 

in deriving the regional method. 

References 

mates on average by 4t/0, 

Table E'1 comparison of or estimatos with rM61 €stimates ($l and regional flood estimation estimates (efl. 

Region 

Number of 

Catchments 

Return 

Period 

T 

roi/q) 

Mean Std Max Min 

Dev 

(o+/q) 

Mean Std Max Min 

Dev 

Canterbury/ 

Waitaki Basin 17 20t1, 2.11 1.19 6,01 1.10 1.06 0.36 1.A7 0.59 

Westland 

Northland 

2011, 0.76 0.1 5 0.89 0.52 0.96 0.22 1.32 0.68 

512) 0.56 0.18 0.88 0.38 o.94 0.23 1.16 0.60 

Note: (1) Estimates of elo and Ozo from Ogle (1g7gl. 

l2l Esrimates of Oi from Waugh fi 973). 

122 


Appendix F 

Flood frequency analysis for Otago and 

Southland 

F.1 lntroduction 

At the time of developing the flood frequency curves for 

the eight regions covering New Zealand, there were only six 

relatively short flood records available for the 

Otago/Southland region. This region's flood frequency 

curve was therefore treated as provisional and was only extended 

to the 100-year return period; for the other regions 

the curves were drawn up to 200 years. The tentative nature 

of the analysis is best illustrated by the fact that one of the 

records used was for the Pomahaka River at Burkes Ford 

(Station 75232) for the period 1963-1975. The flood peak 

for 1972 of 1088 mtls was omitted because it appeared to 

be an extreme outlier, yet this peak has been exceeded three 

times over the period 1978-1980. 

The number of notably large floods in the area in the 

period 1978-1980, and the availability of substantially more 

data, suggested that reassessment of flood frequencies in 

this area was appropriate. This appendix gives the results 

of the reassessment, which has been completed just in time 

to be published as a supplement to the main study. 

F.2 Data collection 

With assistance of staff of the Otago and Southland Catchment 

Boards, annual maximum flows for stations with at 

least l0 years of reliable flow record were extracted. The 

catchments are listed in Table F.l and their locations are 

indicated in Figure F.l. The flood peak data are given in 

Table F.2. 

Additional historical data were sought. These data took 

two forms. The first was estimates of large floods which 

occurred before recording commenced and which were the 

largest for a known period. For example, the estimated 

p"it of 220 m3/s in tÈe Leith on 19-20 March 192í is the 

largest known in this area since settlement, which is taken 

as dating from 1850. The second form was when the largest 

recorded flood was also the largest known peak in a 

preceding interval. For example, the peak of 505 m',/s 

recorded on the Makarewa River on 15 October 1978 is 

known not to have been exceeded since 1895. 

Sources of historical information are "Hydrology Annuals" 

No. 3 No. 17 published by the Ministry of Works 

(1955-1969), and 

- 

"Floods in New Zealand (1920-1953)" 

published by the Soil Conservaton and Rivers Control 

Council (1957), supplemented by information from catchment 

boa¡ds and some early newspaper reports. As early 

historical estimates are of uncertain accuracy, only data 

considered to be reliable were used. 

Annual maximum l2-hr duration lake inflows calculated 

from records of levels and outflows (Gilbert 1978) for 

Hawea, Wanaka, Wakatipu and Te Anau were used. Local 

inflows to Manapouri were not used because they are 

calculated as Manapouri outflow, minus inflow from Te 

Anau, minus change in lake storage, and since inflow from 

Te Anau is 6690 of Manapouri outflow the residual local 

inflow is subject to large errors. Although the l2-hr maxima 

inflows are less than instantaneous maxima, the 

reasonable assumption that the instantaneous maxima are 

a constant ratio (say 1.2) of the l2-hr maxima suggests 

these data can usefully supplement the maxima recorded on 

rivers for frequency analysis purposes. 

Flow records were also derived for two contributing 

areas in large catchments by subtracting, from downstream 

flows, the upstream flows lagged to allow for time of 

travel, Records of annual maxima were thus derived for the 

Waiau River between Tuatapere and the Mararoa confluence, 

and the Clutha River between Clyde and the 

Shotover and the three lakes. Because these data are derived 

by differencing hydrographs, after making assumptions 

about the travel times of the upstream hydrograph, the errors 

in the estimated peaks are significantly greater than for 

other records. They were therefore not used in deriving the 

regional curves; however, they provide a useful independent 

check on the curves derived from the other data. 

Table F.1 L¡st of catchments. 

Number of 

Stat¡on 

Catchment number 

in Fig. 1 

Name of River and Recording Station 

Year 

Record 

starts 

Catchment 

atea 

(km2l 

1 

2 

3 

4 

5 

6 

7 

I I 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

73501 

74308 

74310 

74314 

74346 

75259 

75232 

77504 

77505 

7A502 

78607 

78625 

78633 

78803 

78906 

75276 

75253 

23 

24 84701 

Water of Le¡th at University Footbridge 

Taieri at Outram 

Taier¡ at Sutton 

Taieri at Patearoa-Paerau Bridge 

Loganburn at Paerau 

Fraser at Old Man Range 

Pomahaka at Burkes Ford 

Mataura at Gore 

Mataura at Parawa 

Waihopai at Kennington 

Oreti at Lumsden 

Otap¡ri at McBridges Bridge 

Makarewa at Freezing Works Bridge 

Middle Creek at Otahuti 

Aparima at Dunrobin 

Lake Wakatipu inflow 

Lake Wanaka inflow 

Lake Hawea inflow 

Lake Te Anau inflow 

Shotover at Bowens Peak 

Manuherikia at Ophir 

1 964 

1 955 

1 961 

1 968 

1 967 

1 969 

1 962 

1 957 

1 956 

1 958 

1 957 

1 963 

1 955 

1 970 

1 963 

1927 

1 930 

1 931 

1 926 

1 968 

197 1 

Clutha tributaries above Clyde, and below 

Shotover and the lake outflows (see McKerchar, 

1981. Table 4.1) 1963 

Waiau tributa¡ies above Tuatapere and below 

Mararoa. {see McKerchar, 1981, Table 4.1} 1969 

Cleddau at M¡lford 1964 

45 

4 705 

3 066 

738 

150 

122 

1 924 

3 465 

766 

152 

1 160 

108 

1 040 

27 

215 

3 133 

2 624 

1 384 

3 124 

1 088 

2 036 

3 839 

2 336 

155 


t23

Table F.2 Flood peak data. 

NEW OTAGO DATA 

NEW SOUTHTAND DATA 

3I TE 73501 

I.EI18 TT UTI9EESÍTY POOIBNIDG? sITE 15232 

POitñtKÀ À1 Do¡t(zs ¡oBD 

crrcHtBtT t8Et, 5Q Kü = 

tollBER oP ÀXtltÀL PEÀKS = 

IEIB PEÀI( IB¡I P¿TK 

CÀrCllAIl IREÀ¡ 5Q Klt = 47A5 

!0;8EF OF IIXûÀL PE¡ñS = 25 

IEI! PETK IEÀE 

45 ¡Àp RBFpREì¡cE = s16q:i63?2s 

17 P¡iFIoD 0P REc, = 196q-e0 

YETR PBTK YEÀR PET T 

1964 4.7 1965 6. t 1966 1,\ 196? 5.2 

1968 r 13 1969 8.5 1911. 39.6 1971 95. 6 

1972 65. I 1973 8.5 1974 51.8 tq?5 ta?, 9 

t976 46.7 1971 28.7 1978 49.4 19?9 23.5 

t9B0 1 30 

lBtf = 41.16 STD. DEv. = 39.9€ coEF. Op sKEs = 1.01Â 

tolBs: 

1. rflE t929 pElK, ESIltttTED tÎ 220 CUiECS, rtS THE LtRcESl 

ST¡CE SETTLEI'EIIT À¡TD TÀKET IS ÎIIE LÀRGÈsT Tll TfE PERIOD 

ts50-1980. 

sIîB 7¡308 

1955 10S5 1957 

'1960 181 ¡961 

1964 37.6 1965 

1968 845 1969 

1972 832 1973 

I 9?6 t 43 1977 

1980 2600 

Pr¡[ 

2009 

12't0 

119 

152 

151 

326 

1ÀI8RI À1 OIITRÀñ 

llÀP REPEREIICE = S163:9337q(¡ 

PERIoD 0P 8Ec. = 1955-F0 

YEÂR PBÀK TEÀR PEÀI( 

1958 425 1959 21Ã 

1962 205 1963 368 

1966 300 1961 19( 

1970 266 t97t 43f 

1914 864 19?5 J34 

1978 1133 1919 r¡Oo 

;!Àt = 593.2 STD. DEg. = 62t¡.5 Copp, Op SÍEc = 1.965 

tolE5: 

1. T_8!'l?qo-g_Err, rRE r868 pE¡t (Bslrt!llED À1 2179 coiEcsl 

rfD ÎE?.1957 PEÀi ¡ERE IIKEI rS ÎIIE 1ÍRN8 L¡RGEST rìI 

TI¡E PIRIOD 1858-1980. 

5I1E 7q3 10 

cllcfliliT À¡Er, sQ K; 3366 

xltllBtg OP ¡¡[0ÀL pEÄis = t8 

I'IR PgTf TEÀR PETK 

1961 06¡t 1962 108 

t966 56.6 1968 3OO 

1971 115 1972 207 

1975 96.2 1976 156 

1979 96-2 1980 800 

TIIERI tÎ S0110tl 

lllP EEPEnEICE - s15¡t:939092 

PeÂIOD oP REc, = t96l-90 

TPÀR PETi t¿ÀR PEÀX 

1963 t30 1e65 66.5 

1969 59.4 r97o 76. ! 

1973 113 1974 311 

1911 67,9 19?8 ¿ü? 

t8¡¡ = 204.0 sTD, DEt. = 196.3 coEp. op siE3 = r.986 

tolEs: 

l. PB¡Ís, irssl¡c FoR 1964 rxD 196?. 

cÀTCHllELT tREA, S0 Klt = 1924 ilP REPEREItCg 5711.221472 

llullBEF oP Àf,tlûÀL PEI(S = tq PEnIoD oF R¡)c. = 1962-S0 

IETR PEÀK fEÀR PETI( IEÀR PETß PI¡f 

1962 1?6 1963 337 1964 96. I 'E¡¡ 1965 3lo 

1966 216 1967 467 t968 516 1969 2¡9 

't 970 2s5 1971 369 1972 t08? 1973 170 

t 97q 206 1975 32A 1916 201 1917 375 

t 978 1217 1979 352 1980 1210 

ÍEltl = 435,2 STD. DEV. = 353.6 COPF. op SiE¡ = 1.?tO 

ltotEs: 

1. Tfir 1978, 1980 ÀXD t972 pEtKS íERE TlFEL tS TEE Î[tBr 

LTRGPST TI THE PERTOD 1920-1980. 

s rlE 17504 tlTl0Sl lT coRt 

c^TcHiEtT rt8l, s0 ¡ü = 

llUllBER OP IUtaUÀL PEÀRs = 

IEIE PRIK 

1 957 1 047 

1962 586 

1966 352 

1970 252 

197r¡ 21O 

1 978 22f5 

TETE PE¡( 

1959 6CS 

1963 tt33 

1e61 656 

19?1 443 

t9?5 51C 

1979 52t) 

3q 65 

23 

766 

25 

llP REtEnutc? st70:013¡t3 

PERIoD oP EEc. = 1957-S0 

tEtR PEtß tzl¡ Pllf 

1960 tt52 1961 35t 

1964 260 1965 292 

1968 1290 t969 62a 

1912 121A 1973 2O1 

1916 453 1971 1300 

1980 1625 

ËEtl¡ = 6c2.3 stD. DEI. = 520.3 coEp. op sf,B¡ = t.59o 

ùtoTEs: 

1. rflE 1978, 19t3 (1700 cu;Ecsl rrD t98o pErxs tB¡E î¡ßE¡ 

ls îfl¡ L^RGESÎ fIf TflE pFRTOD t870-1980, 

srlE 77505 

ctIcHllEN? ttEr, sQ ßÍ = 

llUllEER 0P rXXuÀL PEÀKS = 

PEIX IEIA 

YDT R 

1956 

1950 

t 961¡ 

t 960 

197 2 

1916 

1 980 

PETK 

68 1957 !2\ 

rc,t 1961 92 

117 1965 103 

276 1969 259 

214 1973 1 lC 

165 1977 266 

215 

rrT¡str Àr P¡llt¡ 

ËtP REPEEE¡CE st5t:¡9t058 

PEDIoD 0P REc. = 1956-80 

IEIR PEÀÌ fBTÂ PIT¡ 

t95S rq3 1959 2tt5 

1962 103 1963 55 

1 966 106 1967 292 

19 70 84 197t 2t¡ 

197tt 93 1e75 136 

1978 590 t979 29t 

iEtü = 190.¡ STD. DEV. = "124,0 CoEp. o¡ srEt = 1.638 

SIlE 78501 ¡TIROPÀI TT ¡ETIII6IOI 

SIÍI ?131¡ 1ÀIEtr tÎ PtTEtROI-P¡lt¡u cÀrcflllFl¡T ÀREt, SO till = 152 nlP REFERE¡cr 

NUIBER O? = sl773t3t0¡5 

ÀTI'OÀL PEÀKS = 19 PERIoD 0P REc, - t95B-77 

c¡lcElt¡î rRElr SQ fr 738 iÀP BEPEfiEICI 

tUiBEn OF À¡lott. pEtÍS = St45:675374 

= l3 PEBIoD oP 

IEIR 

nEC. 

PFTK TE¡ R PEÀß 

= 1968-S0 

IETR Pttf( tEtR 

1958 Pttt 

tt.6 1959 26,6 1961 2q.1 1962 

IIIB PETf, 

1953 31.3 

2¡. t 

IEIß PEÀi 

t964 

1t68 PEII 

25.tt 

61.0 '1969 

IEIR PETI 

196 

IBAB 

5 39,1 

196? 1966 26.A 

56,0 19?0 

23. I 1968 t¡1,3 

65. 6 

1972 

30.9 1971 

1969 26.1 1970 25. O 

¡02.r¡ 1913 q6.0 

1971 17.7 7912 55. R 

197¡a 

1976 

55,3 

191 

1975 

3 

68.5 

19.8 1974 31. ó 

39.0 1971 69,9 

19?5 

't 

21.8 t9?6 30.7 

51. 

1980 

978 t 37. 5 

1917 ql.6 

1979 I 

205 

Ëxlt{ = 28.93 SrD, DEc. = 1C.û2 COEP, op S(Et = 0.9960 

iEl¡ = 76.07 SfD. DEt. = 47.67 COEP. oP SrEs = 1.98F 

sITe 7860" OF¡:îI T1 LOËSDEI 

s¡ ÎE 743¡6 LOGIXBoÀX tÎ PtERto 

CÀTCflll¡ll1 àRP^¡ SQ ßñ = 116C FÃp fiEpFRENCE = SrSO:lBr¡g62 

c¡lc8llrT rSEr¡ sQ l(r ùU;BEF = t50 llP REPERBICE 

OP lIilûAL ÞEIKS = 22 PERIOD OF RDC. = 1957-80 

¡0lBB¡ OF ¡lIÛÀL PBIÍS 

= Stqtt:62¡t217 

= t3 PEBIOD 0p nEc, = 1967-79 YEAR PfAK IFÀ8 PEÀK ÍNTR PRÀI( TEÀR PEI 

II¡g ÞE¡Í IE¡8 PE¡R IEAR PEÀX TEÀR 666 1e58 

f 

1957 

334 

ÞIÀt( 

1959 378 1960 271 

t957 5.48 t968 20.7 

't95| 

t969 12.2 19?O 352 1962 352 

22.9 

1963 183 1964 211 

19?r 35,5 1972 50.0 1973 

196 5 

21.7 

-lc 

197¡t 1 1q66 232 

15.6 

tc67 416 1968 352 

t975 26.4 19?6 1s,7 1977 

t969 

20.3 t97B 211 l97C 21C 

58.s 

19'11 t69 1912 139 

7yr9 1 8. 9 

1 975 765 1976 453 '1917 871 1978 1171 

197C 131 1980 I 10c 

lBlf . 24.91 STD. DEt. = trt.92 COEp. oF SßEr = 1.2ge ñE¡tl È 454. I 51r\. DRv. = 29Ê. I coFF. oF s(Ft = t.27tt 

Ìorts : 

1. TBE 1980 pEti oF 365 CUTECS 

NOTES 3 

tÀS OñIÎTED FFOil TltE 

ITTLISTS: I1 9Ts IT BITRETE oOT¡,IER 1. lIIF 

ÀIID T¡tE IYÀrLIEL! 

1C-8 ÀNTJ 198C PEIKS Y¡]FII ÌÀKE¡r ÀS lHf L¡RGEST I¡ 

LpxGTft ot ¡EcoRD ¡rs fùstrFFlcrEilT TO Rltt¡L8 

THE PPFIOD 

REÀLISTIC 

1879-198i. 

TETIIEI¡ PEBIOD 1O BB ISS¡GIIBD 10 Iî. 

^ srtt 7a625 OlTÞIRT ÀT iCBRfDES BRIDGI 

PRÀZEF 

:l::__--- _ t:::: 

IT OLD ItTN R¡IIGF 

c¡tc¡rrir tBEt, s0 [t = 180 ItP AEFEREIICE = S169:|t22516 

c¡fcfitBlT rREr, SQ Kü !ûIBEB 

= llÀP 

ol 

REF¡ll?Eilcr 

¡IlûrL PEÀIS 5143:03't485 

= 1B 

122 

PEAIOD OP REC. = 1963-80 

XUÚBER OP TT¡Of,L PEÀKS = 12 PERIoD 0r 8EC. = 1969-80 r'¡¡ PEIf, TET¡ PEÀK IETS PPÀK fEtS PEIX 

IE¡R PEÀT YEÀK PRTß 1965 31.2 1 

TETR 1963 tt2.3 196¡ 

PEÀÍ 

29.1 

966 

YEIF 

30. 3 

PEI f, 

1969 23.4 1970 1911 t967 

19,3 

52,5 1968 85.5 

11,9 1969 60.0 1970 70.3 

1912 

'19t3 22.3 

1975 1971 43.5 1972 65.8 

16.2 1973 

1976 

25.9 

1 

31. rl t974 tq.2 

974 

12.7 

34.7 

1971 11.9 1919 1915 

1?,0 3q,2 1976 rt3.9 

t978 88. 

1977 90.2 1978 198 

O 

t980 26. 0 

1979' 52.8 1980 r15 

¡E¡i = 26.29 sTD. DEY. = 20,29 COFP, OF SÍF:C = 2,911 tE¡x = 61.3r¡ sÎD. DEÍ. = 41.93 COEP. oF SIEc = 2.28A 

tu 


a

786 33 

!lll::l- 1I-::TÏÏ-i:Î:: 

cltcElExl lRBl, sQ fl = tOlO rrP nBFEREtrcE : s1?7:331130 

¡trlBB¡ oP lllûll. PEIRS = 24 PERIOD OP R¡c. = 195'80 

tEA¡ P¡Àf fSÀB PEÀT tEÀR PETK IETR PBIÍ 

1955 2rl 1957 175 1959 111 1960 216 

1961 156 1962 169 1963 201 1964 90.6 

1965 201 t965 81 1967 156 1968 395 

1969 r78 19t0 170 1911 200 1912 263 

1973 1l¡5 1974 136 19?5 195 1916 2\2 

1977 318 1978 505 1919 287 1980 434 

rr¡l = 223.0 sTD. DEv. = 103.0 coEF' ot sfEl = t'326 

lolBs ¡ 

I. Tf,E 1978 T¡D'1980 PB¡TS CEIE TÀÍET ¡S lNE TUO LÀRGISÍ 

III lEE PE¡IOD 1895.1980. 

srrr 78803 

:I:3ï-::::I-"-ilÏ1I 

cttcErtrl tElr' sQ rl 27.4 ËÀP 8E?BR!¡cr s176:192268 

llttDE¡ or rflÛrl. PE¡[s = 10 PER¡oD o! REc. = 1970-79 

rllr Pltf tE¡B pBl[ IEIB PSTÍ IEI! PEÀT 

1970 3.16 1971 9.51 '1972 13.41 1973 l.?3 

19?¡ 1.55 1975 2.74 t9?6 3.60 1977 5. 1? 

197ø 1.82 1919 9.40 

;Elr = 5.ll STD. DEV. = 

tl.O2 COE!. o! srEÍ = 1.170 

¡PtEttt 

lT D0¡RoBlll 

IEIR PEÀI( IEIR PB¡K rElB PEIÍ ftlB Dltt 

1930 1037 1931 1832 1932 1210 1933 t588 

1934 1 106 1935 15rt0 193ó 1716 1937 llrt 

1 938 952 1939 1080 1940 1293 19t1 17t2 

1942 1889 t9¡t3 19rt3 t944 9¡r8 19t5 t93¡ 

't9q6 2265 19q7 1 160 1948 3227 19¡9 2l7t 

1950 2867 l95t 975 1952 t¡459 t953 t5ó0 

1954 1261 1955 1700 1956 960 1957 :¡11ó 

t958 2022 1959 1255 't960 1 458 t961 1279 

1962 2004 1963 A27 196¡ r 163 1963 1936 

1966 1337 1967 30lr 196S 1854 1969 325a 

t970 1512 197 1 1 t5C 1972 1127 1973 1706 

1970 791,, 1975 2419 1976 t 104 1971 1169 

t9?8 3991 1919 3¡23 

ttEltl = 1829 sTD. DEV, = 841.9 coEt. Ol SiE¡ - 1.316 

IOl9S: 

1. TÍF II'PLOCS TERE DERTgED FÂOË [Àf¿ LEÍIL IID OOT'I.OI 

BECORDS USrilc r l2-800R rrtE rtrEBVlL. 

5ITE 9 I ?O LrÍE FtrEl rttlo¡ 

CÀTcllllELT à88Àr S0 fl = r38q nlP ¡Elgnzlcr = 

ùUtlBER 0F l¡il0ll PEIKS = lt8 PEBIoD 0t nEc. . 

IETE P?TK 

193t 187 

1935 653 

I 93e 606 

19q¡ 599 

t 947 !rt2 

1951 502 

t955 619 

1959 367 

196:t 338 

1967 903 

1971 325 

1915 q6 t 

fETR 

1932 

193 6 

19¡t0 

t 9ll¡ 

19C8 

1952 

t 956 

1960 

196¡r 

1968 

1912 

197 C 

PB¡K 

593 

503 

599 

332 

845 

157 

371 

561¡ 

453 

¡r08 

552 

365 

IE¡ R 

1 933 

19 3? 

l94t 

1945 

1949 

't9 53 

1937 

19 61 

1 965 

1959 

1 973 

1917 

l93l-78 

PEtß rBtt p;lf 

539 193¡t 717 

l¡23 1936 60¡ 

585 l9e2 62t 

540 19¡ó 926 

665 1950 7¡¡ 

605 195¡ 373 

700 1958 556 

$15 1962 839 

ø23 t966 631 

1 r 36 1970 650 

cl?CElBIÎ rlsr, SQ Ír 215 llP rErrBBtc! s159:119827 

rulBlB O? I¡IU¡L Ptrfs = t8 PEEIoD ol ¡Ec. = 1963-80 

162 197¡t {36 

rB¡¡ PEIÍ IET¡ PEIf, IEIB PETf, tEtn Pllf 

t23 19?8 ltl¡ 

1963 15.2 1964 1îs 1965 t43 1966 81 

1967 l7q 1968 131 1969 6 t. 6 t 970 10.2 ËEtù = 596.5 srD. DEv. = 197.5 coEP. oF sßP9 ' 0.7392 

1 971 6 1, 6 1972 8l¡.5 1973 11 1970 68 

t975 135 1976 t03 1977 169 rs76 53q ¡OTES : 

19?9 119 1980 196 

T. TflE IIPLOflS 3ENE DERIYED FßOI LTßE LEVFL IID OTîILO¡ 

NECORDS USTf,G À 12-HO¡IR 1I'IE IIITESYTL. 

rEtI = 126.5 STD. DEt' = 113.7 CO!F. oP SKEI = 2.895 

fotlS ! 

srlE 957C 

LÀr(E îE t¡lt lltlot 

1. tEE '1978 PttÍ CÀS Ttf,E[ tS tllE LlnCEsr rx rtlE PEFToD 

1914-1980. 

CtrCtËEf,T tREl, SO K¡ 3124 ülP BEFEREICE = 

l¡UliBEF OP ¡[iÛll PEÀxs = 5q PERIOD OP REc. = 1926-19 

NEW SOUTH ISLAND WEST COAST 

YEÀR PEIK 

PEÀK 

PEÀf, YEIR P'Tf 

1926 1q20 'EÀF 1921 1737 'EAR 1928 20 r6 1929 1500 

srlB 

9 1 l0 

Llt(E fltrlllP0 IftloS 1930 1500 1931 1285 1932 2511 1933 2604 

193ft 2365 1935 1609 1936 2608 193? 1¡20 

1938 l8lq 1939 260'Ì 1940 3499 194'1 2294 

cÀTCBllFxT ÀREt' sQ KË = 3133 llÀP REPERE¡CE = 

1942 1362 l9rrl 1935 194r¡ 20 rB 1905 2540 

NUiBER OF ¡xNUlL PEÀKS = 53 PEBIoD oF FEC' ' 

1946 3C6l 'l9tt1 221 '' 

t9rr8 3¡a59 19¡9 1948 

1927-79 1950 2167 1951 2671 1952 lt4r¡ 1953 2865 

YEIR PEIK Y¡ÃF PEÀ¡( TDIR PETR f!I¡'B PEIT 195¡1 2942 1955 2C6C 1956 210U 1957 3512 

1927 1¡¡9t 192A 1855 1929 1?9lr 1930 

r 958 31105 1959 2¡t88 1960 2818 1961 1937 

75¡ 

1931 1250 1932 929 

t962 tB80 1963 1166 1 

1933 792 193¡ l26t 

964 1723 1965 227e 

1935 199 1936 736 1937 648 1938 r061 1966 l6rrl 1967 3715 1968 2381 1969 2552 

1919 512 1940 1q90 19¡.1 1635 1942 

1970 226A 1971 2202 1912 2220 r9?3 1495 

10tt6 

1943 939 1944 669 

1974 19¡¡4 lq15 2426 19?6 20 19 

1945 1332 t9¡6 2799 

191't 2009 

1907 1288 l9q8 2118 1949 1866 1950 1463 1978 4839 19fs 4r¡38 

1 95f 1 094 1952 26qA 1953 11r¡5 19511 10?3 

1955 1C26 1956 759 19 57 2933 1958 20r5 ËElN = 2561.8 sÎD. DFv' = ?68. O COEF. OP sKE¡ = 0.9820 

1959 890 1960 1181 t961 1700 1962 It98 

1961 585 1964 t057 '1965 963 1966 t t¡2 l¡0TEs: 

1961 2CUi 1968 1869 1969 2254 1970 88r I. T8E INFI,O9S TE¡T DERI9ED ¡ROII LIÍE LPVgL AIID OOTPLOT 

r9?1 780 1912 1\29 1973 812 197¡ loTt 

RECOFDS ÛSIIIG À 12-IIOUR TIIIE I¡lERVAL. 

1975 2006 1916 1 138 1917 1 469 l97S 2¡60 

1979 26J2 

;Eltl = 1382 sTD. DEY. = 609.2 coBP. oF s(E¡ = 0.88{9 sIrD 75276 

saofoÍE8 tT BosElrs ÞErl 

l¡oTEs - I 

i. rue rt¡Lots IBRE DERTSED FRoË LÀiE rtYEL ¡lD ooTrlo¡ C¡lCErErT tREf,' SQ ß; = lC88 irp ¡EPlBEfcE = s132:589786 

RECOBDS OSII¡G T 12-HOUR TIIE IXIENYTL. 

TUTBER O! llf,tttl, PEIIS = 12 PERIOD oF REC. = 1968-?9 

IETB PEÀK IEIB PETK IETR PETI tEÀR PEÀÍ 

639 

srtB 9150 

LltrE Clllfl I¡FLOI 1968 l¡51 1969 

1970 369 191 1 328 

1972 00r¡ 1973 277 197¡a 528 1915 56c 

1976 r¡? 1 1911 508 1978 c18 1979 tt81 

cllcflüE¡Î ÀnEl, S0 Kll 

I'IP RE?EREf,CE = 

PERIOD OP REC. = 

167.5 COEP. O? SKEi = l.l¡06 

IOIBER O! I¡IIUÀL = 2624 

PEIÍS =50 r93O-?9 rEl¡ = 4C5.C SrD. DEY. r 


125

F.3 Analysis and results 

tatively placed with 

Region on the basis 

the hydrograph for 

to the Taieri River 

Paerau and Loganburn at Paerau (Figure F. l0) 

Southland rivers (Figure F.9). 

- 

than the 

(see section 3.1.6). Plots with similar shape were overlaid to 

form combined plots. 

Flood frequency data thus plotted were found to lie in 

three groups: 

(a) peak lake inflows and Shotover floods; 

(b) Southland floods and the pomahaka floods; 

(c) East Otago floods. 

Group (a) closely resembled the South Island West Coast 

data 

Canterbury data 

(see 

these two groups 

were 

I plots of the data 

they 

Support for the differentiation of the lake inflows and 

Shotover from the other sites studied is also given by the 

hydrographs (Figure F.8). These show that floods are frequent 

and occur at the same time for each catchment. Since 

the floods result from the same storms, it is an argument 

for each catchment having a similar shape in its flo;d frequency 

curve and for grouping them together. Also shown 

in Figure F.8 is the hydrograph for Cieddau at Milford. 

Finally, 

- 

the hydrographs (Figures F.8, F.9 F.lO) show 

that the majority of large floods in the decade l97l-19g0 

o-ccurred in the years 1978-1980. Figures for F.g, F.9, F.l0 

also show the wide extent of the October l97g flood which 

was the largest of the decade for many of the records. 

F.4 Gonclusion 

and the Manuherikia at Ophir (1971-1980) wirh rhe 

regional clrves (Figure F.7) shows the difficulty in determining 

which curve is appropriate. Central Otágo is ten_ 

graphs (Figures F.8, F.9, F.l0) 

because the frequency of minor 

ach region but not across region 

ïable F.3 Co-ordinates fiom regional frequency curves. 

O2.33/O 

o5/o 

olo/o 

ozdo 

o5o/o 

orodo 

ozoo/o 

S.l. West 

Coast 

1.OO 

1.24 

1.45 

1.64 

1.89 

2.O8 

2.27 

Southland 

1.03 

1.46 

1.82 

2.16 

2.61 

2.94 

3.27 

sth 

Canterbury- 

Otago 

0.97 

1.51 

1.99 

2.48 

3.17 

3.73 

4.33 

Acknowledgements 

D. McMillan in compiling the 

Miss K. Vollebregt in anatysing 

owledged. 

References 

Fitzharris, B.B.; Stewart, D; Harrison, W. l9g0: Contribution 

of snowmelt to the October l97g flood of the 

Pomahaka and Fraser Rivers, Otago. Journal o! 

Hydrologlt (NZ) I9(2): 84-93. 

Gilbert, D.J. 1978: Calculating lake inflow. Journal o! 

Hydrologlt (NZ) I 7(I): 3943. 

Ministry of Works: Hydrology Annual. (No. 3, 1955 ... 

No. 17, 1969). Ministry of Works, Wellington. 

t2Á Water & soil technical publication no. 20 (1982)

c o 

E 

anîn 

o 

\' 

f¡l 

U) 

o 

oô 

^' s' r- 

: ô¡ 

f¡¡ 

o _ L \-zi 

,-l"-l'X 

\/'\ 

þ 

-: 

t! 

.E .c, 

o 

F 

.= 

Itoø 

= o6 

at, 

| ; -r'-9-\-/ 

-l¿-ì 

.' 

^,2 

.t ì.---.'{ --- 

t!--/ 

\-' 

-r'---\-,-. 

" --b-.^, 

r\- -ti 

ffi r 

:' =

ét 

êt 

REOUCEO VßFIHTE 

2. 33 5 l0 ?0 50 t00 ?Do 

NETURN 

PEFIOD (TERRSI 

Fþurc F.2 Plot of normalised flood frequency data for lake inflows and Shotover River superimposed on the Wost Coast data given in 

Figure 3.13' (Circled points are lake inflows and Shotover floods with plotting position retuin peiiod greãt€rthan 20 years.l 

o 

o 

REDUCEO 

VNBIHTE I 

?.33 5 ¡0 20 s0 too 20D 

RETUB}'I PEBIOO (YEflRS) 

Fþure F.3 Plot of normal¡sed flood frequency data for the Pomahaka River and the southland R¡vers. 

t?ß 


ct 

ct 

o 

ê 

o 

.25 

ñEDUCEO VRBIFTE 

2.33 5 t0 20 50 

RETUBN PERIOD (YERRSI 

100 200 

Figuo F.4 Plot of normalised flood frequency data for East Otago rivers (Taieri catchment and Leith) superimposed on the South Canterbury 

data given in Figure 3.1 5. (Circled points are Taier¡ catchment and Leith floods with plotting pos¡tion retum period of greater than 20 

years.) 

Qr/Q 

\q 

\þ) 

X 

y'x* 

o 

0 r.011 2.33 5 ]0 20 50 100 200 

RETURN PERIOD 1 (yrS) 

Frgurc F.5 Average points from Figures F,2 (ol, Figure F.3 {x) and Figure F.4 ( +). The fitred curves ars for (a} West Coast, (b) Southland, 

(cl Sor¡th Canteôury-Otago. 


t29

SOLITH 

I 

EA 

l') 

COAST 

soUTH CANTERBURY/oreco 

SOUTHLAND r l00km . 

E$r. F.6 Regions inferod from dots of flood frequency data. 

130 


RETURN PERIOD T (Yrs) 

20 

Figure F.7 Frequency analysis of annual maxima derived for Clutha river tributar¡es above Clyde and below Shotover and the lakes, (x) 

1963-198O, Manuherikia (ol 1971-80, and Waiau Riv6r tr¡butar¡es above Tuatapere and below Mararoa (tr) 1969-1980. Regional frequency 

curves are also shown. 

I 

sHotovtx . uuxtils PK i3/5 

t 

cLE00Êu o Ë¡LFoRo sÛuNo il3/s 

LÊfiE HNKÂÍIPO INFLOH Í3lS 

Figurc F.8 Hydrographs of shotover, cleddau and l¡ke wakatipu inflow, 1 971 - 1 979. 


t3l

0tiftflt a itÉitut5 ü¡. il/5 

tg?t 

t9?¿ 

l9 ?J 

i¡fÊ¡Erâ nI FflEEZtrc lis 88. ff3/5 

¡l 

f 

Flgure F.9 Hydrographs of two stations ¡n ü€ Soúhland region, l97l-l9gO. 

lfflti¡ Hr f(ltHH0H-PHtffHU iJ/5 

I 

l06PxBU8N nr PFESFU ¡3/S 

,å 

P- 

t8{uHE8lÍtF Êt oPttfi t9/5 

t 

lt?r lr?{ tE?! ¡9?6 ¡9?7 t¡76 

Fþure F.1O Hydrographs of three Orago stations, I9Zl-I9gO. 

a, 

\* 1; lr' P. D. llulbe¡¡ CoUu¡at Prlala, Wcllia¡oo, Nd ?Fl.d-lSll 


C0g6flE-6OO/¿V82R

1. 

2. 

I.IATER AND SOIL TECHNICAL PUBLICATIONS 

Liqu'id and waterborne wastes research in New Zealand ($t-OO¡ Salty 

Sampling of surface waters ($1-OO¡ 

M Kingsford, J S Nielsen, A D Pritchard, C D Stevenson 

Davis L977 

I977 

3. l.later quaìity research in New Zealand 1976 ($1-OO) Saìly Davis 

4. Shotover River catchment. Report on sediment sources survey and 

of control , L975 (out of stock) 

5. Late Quaternary sedimentary processes at Ohiwa Harbour, eastern Bay of 

with speciâl reference- to property loss on Ohiwa ($1-OO¡ J G Gibb 

6. Recorded channe'l changes of the Upper [,laipawa River, Ruahine Range, 

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-r. 

7. Effects of domestic wastewater disposal by land irri 

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G N Martin and M J Noonan 

feasibility 

gation on groundwater 

) 

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1978 

P1 enty 

1978 

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application to urban flood design ($1-00) J R tlaugh 

9. Research and Survey annual review 1977 (out of stock) 1978 

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11. The Waikato R'iver: A water resources study ($12-00) 

L2. A review of the habitat requirernents of fish in New Zealand rivers ($3-00) 

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L978 

1978 

L979 

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21.. 

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F.egiona1 flood estímation in New Zealand. M E Beable and 

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l-982 

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1981

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