DISCLAIMER - Waterh2o.water.gov.my/man_hp1/HP4(2018).pdf · Procedure No. 4 (Revised and Updated 2018) are gratefully acknowledged. Special thanks to the Director of Water Resources

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ii

DISCLAIMER

The department or government shall have no liability or responsibility to the user or any other

person or entity with respect to any liability, loss or damage caused by or alleged to be caused,

directly or indirectly, by the adaptation and use of the methods and recommendations of this

publication, including but not limited to, any interruption of service, loss of business or

anticipatory profits or consequential damages resulting from the use of this publication.

The opinions expressed in the Department of Irrigation and Drainage (DID) publications are

those of the authors and do not necessarily reflect those of DID.

Copyright ©2018 by the Department of Irrigation and Drainage (DID) Malaysia Kuala Lumpur,

Malaysia.

Perpustakaan Negara Malaysia Cataloguing-in-Publication Data

MAGNITUDE AND FREQUENCY OF FLOODS IN MALAYSIA

(REVISED AND UPDATED 2018)

ISBN 978-983-9304-43-5

1. Floods--Malaysia.

2. Hydrologic cycle--Malaysia.

3. Hydrogeology--Malaysia.

4. Government publications—Malaysia.

I. Department of Irrigation and Drainage Malaysia.

551.4809595

All rights reserved. Text and figures in this publication are the copyright of the Department of

Irrigation and Drainage Malaysia unless otherwise stated and may not be reproduced without

permission.

iii

PREFACE

A simple and robust procedure to calculate flood discharges is necessary for the design of

water-related infrastructures in ungauged areas. Hydrological Procedure No 4 (HP 4) was

developed for this purpose based on Regional Flood Frequency Analysis (RFFA).

The previous HP 4 was released in 1987. It covers only Peninsular Malaysia. The Method of

Moments (MOM) was used to determine the parameters of a Gumbel Distribution. The

Revised and Updated Hydrological Procedure No 4 (2018) covers Peninsular Malaysia and the

States of Sabah and Sarawak. Furthermore, L-Moments (LM) Method which proven to yield

more robust estimates of parameters was used. In HP 4 (1987), the Mean Annual Flood (MAF)

was derived based on catchment area and rainfall. In this update, slopes were incorporated

in determining the estimated MAF. Isohyet maps showing mean annual rainfall were also

updated based on the recent rainfall data, which was extracted from DID’s hydrological

database.

This procedure provides a simple method to estimate peak floods of various ARIs in ungauged

catchments. The MAF is estimated based on catchment area, mean annual rainfall and

weighted average slope of the catchment. The extreme peak discharges of an ungauged

catchment, corresponding to flood of various degree of severity (ARIs), can be estimated from

the regional flood frequency of the ungauged catchment.

The accuracy of this procedure is highly dependent on the quantity and quality of the data,

spatial distribution of data in regions and statistical analysis. This procedure is useful for

estimating flood peak discharges for ungauged rural areas where the catchment area is larger

than 20 km2. This procedure may not be applicable where the catchment area is smaller than

20km2 or where the river morphology and land use have changed drastically and where major

water resources such as dams and river diversions exist.

RPM Engineers Sdn Bhd (RPM) was commissioned by the Division of Water Resources

Management and Hydrology, the Department of Irrigation and Drainage (DID) Malaysia to

produce Hydrological Procedure No 4: Magnitude and Frequency of Floods in Malaysia

(Revised and Updated 2018) through contract No: JPS/IP/C/H/21/2017.

iv

ACKNOWLEDGEMENT

The Revised and Updated of Hydrological Procedure No. 4 (HP 4) has been prepared through

the cooperative and collaborative efforts between Water Resources Management and

Hydrology Division, the Department of Irrigation and Drainage (DID) Malaysia and RPM

Engineers Sdn Bhd (RPM). The efforts of those involved in preparing the Hydrological

Procedure No. 4 (Revised and Updated 2018) are gratefully acknowledged.

Special thanks to the Director of Water Resources Management and Hydrology Division,

Department and Irrigation Drainage (DID) Malaysia YBhg. Dato' Ir. Nor Hisham bin Mohd.

Ghazali.

This procedure could not have been completed without the guidance and assistance of key

staff members from DID Water Resources Management and Hydrology Division recognized as

follows: Ir. Roslina binti Yusop, Hazalizah binti Hj. Hamzah, Adilah binti Mohamad Anuar, Nor

Hamizah binti Muhamad, Sazali bin Osman and all the engineers and staff members who have

contributed.

The contributions of Technical Committee members are also acknowledged as follows:

Rosly bin Aman, Ezaire bin Md. Eusofe, Ir. Normahyusni binti Mohd Annuar, Tay Siew Voon

and Mohd Rizal bin Abd. Ghani.

The Water Resources Management and Hydrology Division of DID, Ministry of Water, Land

and Natural Resources Malaysia would like to express sincere appreciation to RPM, especially

Ir. Liam We Lin, Badruz Zaman, Shiamala Velaichamy and team members for successfully

preparing and publishing the Hydrological Procedure No. 4 (Revised and Updated 2018).

v

TABLE OF CONTENTS

DISCLAIMER ii

PREFACE iii

ACKNOWLEDGEMENT iv

TABLE OF CONTENTS v

LIST OF APPENDICES vii

LIST OF FIGURES viii

LIST OF TABLES viii

SYMBOLS AND ABBREVIATIONS ix

1 INTRODUCTION 1

1.1 Regional Flood Frequency Analysis 1

1.2 Frequency Distribution 2

2 DEVELOPMENT OF THE PROCEDURE 4

2.1 Data Collection 4

2.2 Derivation of Regional Mean Annual Flood Equations 5

2.3 Regional Flood Frequency Analysis 8

2.3.1 Discordancy Measure 8

2.3.2 Homogeneity Test 9

2.3.3 Regional Frequency Distributions 9

2.3.4 Derivation of Regional Dimensionless Flood Frequency Curve 12

3 APPLICATION OF THE PROCEDURE 15

3.1 Method of Application 15

3.2 Worked Examples 16

4 ACCURACY OF THE PROCEDURE 20

4.1 Comparison with the Observed Data 20

vi

4.2 Comparison with HP 4 (1987) 21

5 LIMITATIONS OF THE PROCEDURE 22

REFERENCES 25

APPENDIX I: CATCHMENT CHARACTERISTICS 27

APPENDIX II: ESTIMATED PEAK FLOODS BASED ON HP 4 (2018) 35

APPENDIX III: MEAN ANNUAL RAINFALL OF PENINSULAR MALAYSIA 41

APPENDIX IV: MEAN ANNUAL FLOOD (MAF) REGIONS OF PENINSULAR MALAYSIA 43

APPENDIX V: FLOOD FREQUENCY (FF) REGIONS OF PENINSULAR MALAYSIA 45

vii

LIST OF APPENDICES

APPENDIX I: CATCHMENT CHARACTERISTICS 27

APPENDIX II: ESTIMATED PEAK FLOODS BASED ON HP 4 (2018) 35

APPENDIX III: MEAN ANNUAL RAINFALL OF PENINSULAR MALAYSIA 41

APPENDIX IV: MEAN ANNUAL FLOOD (MAF) REGIONS OF PENINSULAR MALAYSIA 43

APPENDIX V: FLOOD FREQUENCY (FF) REGIONS OF PENINSULAR MALAYSIA 45

viii

LIST OF FIGURES

Figure 1: Regional Average L-Moments of Peninsular Malaysia 11

Figure 2: Regional Average L-Moments for Sabah and Sarawak 11

Figure 3: Regional Growth Curves of Peninsular Malaysia 13

Figure 4: Regional Growth Curves of Sabah and Sarawak 14

Figure 5: Percentages of PBIAS 20

Figure 6: Percentage of PBIAS between HP 4 (1987) and Updated HP 4 (2018) 21

LIST OF TABLES

Table 1: Parameters of Flood Quantiles Formulas 3

Table 2: Model Performance Rating Based on R2 and PBIAS [ 1 ] 6

Table 3: Coefficients of 𝒂, 𝒃, 𝒄 and 𝒅 7

Table 4: Results of Goodness-of-Fit Test 10

ix

SYMBOLS AND ABBREVIATIONS

Symbols Abbreviations

𝑎 Coefficient to Catchment Area 𝐴 Catchment Area

𝑏 Coefficient to Mean Annual Rainfall ARI Average Recurrence Interval

𝐵4 Bias of L-Kurtosis DID Department of Irrigation and Drainage

𝑐 Coefficient to Weighted Average Slope FF Flood Frequency

𝑑 Coefficient to Independent Variables GEV Generalised Extreme Value Distribution

𝐷𝑖 Discordancy Measure GLO Generalised Logistic Distribution

H Heterogeneity Measure HP4 Hydrological Procedure No. 4

𝐿𝐶𝑉 L-Moment of Variance ID Identity

𝐿𝑠𝑘𝑒𝑤 L-Moment of Skewness Lat Latitude

𝐿𝑘𝑢𝑟 L-Moment of Kurtosis Long Longitude

𝑛 Number of Data Sample LM L-Moments

𝑁 Number of Catchments in the Region 𝑀𝐴𝐹 Mean Annual Flood

Nsim Number of Simulations MAR Mean Annual Rainfall

Q𝑡 Flood Discharge in t-years ARI MOM Method of Moments

𝑄(𝐹) Flood Quantile Obs Observed Data

R2 Coefficient of Determination 𝑃𝐵𝐼𝐴𝑆 Percent Bias

𝑡𝑅 The Regional Average of L-CV 𝑅 Mean Annual Rainfall

𝑢𝑖 L-Moment Ratios RFFA Regional Flood Frequency Analysis

�̅� Regional Average of L-Moment Ratios 𝑆 Weighted Average Slope

𝑉 Weighted Standard Deviation SF Streamflow

𝑥𝑖 Samples of data St Station

𝑥 Mean of data 𝑡 Year ARI

Yical Calculated MAF USGS United States Geological Survey

Yiobs Observed MAF YCD Years of Complete Data

Y̅ Average of the Observed MAF

𝑍𝐷𝑖𝑠𝑡 L-Moment Goodness-of-Fit Test

𝜎4 Standard Deviation of L-Kurtosis

x

1

1 INTRODUCTION

In the planning and design of flood and drainage projects, obtaining an estimate of peak flood

discharge for flood events of various degrees of severity is critical. Not all river basins or

waterways are gauged. Hence, it is the necessary to allow statistical or modelling works to

estimate the flood discharges.

Regional Flood Frequency Analysis (RFFA) is one approach adopted for estimating peak flood

discharges for ungauged areas. The United States Geological Survey (USGS) is the pioneer in

adopting this technique [ 2 ].

DID developed a flood frequency estimation procedure for Peninsular Malaysia in the form of

Hydrological Procedure No 4 (HP 4) in 1974. This procedure allowed DID to estimate the

design peak flood discharges for many projects and is applicable to rural catchments, as most

of the data were taken from stations in rural catchments. It was used in estimating design

floods for many road and highway projects, where it was necessary to size the road culverts.

In contrast, Sabah and Sarawak did not have such a procedure and many must rely on other

techniques for estimating flood discharges. HP 4 was updated in 1987 with updated gauging

data. The procedure again adopted the regional analysis method of Dalrymple and did not

include Sabah and Sarawak.

In the HP 4 (2018), the RFFA procedure was updated and the coverage areas were extended

to Sabah and Sarawak. This procedure describes the use of regional flood frequency analysis

to estimate the design peak floods in Malaysia.

1.1 Regional Flood Frequency Analysis

Regional Flood Frequency Analysis using Index Flood Method was originally developed by

Dalrymple [ 2 ]. Hosking and Wallis [ 8 ] proposed a new statistical parameter estimator method

based on L-moments which was improvement over the method of moments used by

Dalrymple. Hosking and Wallis [ 9 ] also provide a guideline on RFFA based on L-moments. The

RFFA using L-Moments has been applied in many basin areas around the world, such as in

New Zealand[ 17 ], India [ 16 ], South Africa [ 11 ], China [ 10 ], and Turkey [ 18 ].

2

In this study, RFFA using Index Flood Method was adopted. Basically, the method involves

the development of two components:

(i) A set of regional regression equations relating the mean annual peak discharge to

the characteristics of catchment area, mean annual rainfall and weighted average

slopes.

(ii) A set of dimensionless regional frequency curves relating 𝑄𝑇 /𝑀𝐴𝐹 to 𝑇 where

𝑄𝑇 is the peak discharge of 𝑇-years recurrence interval, 𝑀𝐴𝐹 is the mean annual

flood or peak discharge.

1.2 Frequency Distribution

In RFFA, a region needs to be fitted with a single frequency distribution from several sites. In

general, there is no single distribution that applies in a region. The aim therefore is to find a

distribution that can provide accurate quantile estimates for each site.

From the goodness-of-fit test, it was found that Generalised Extreme Value (GEV) and

Generalised Logistic (GLO) are distributions that were accepted for all Flood Frequency (FF)

Regions. The GEV distribution was accepted for FF 1, FF 3, FF 5, FF 6, FF 7 and FF Regions in

Sabah and Sarawak (FF 9, FF 10, FF 11, and FF 12) while GLO distribution was accepted for FF

2, FF 4, and FF 8. The FF Regions are shown in APPENDIX V.

The flood quantile formula for GEV is:

𝑄(𝐹) = 𝑚 − 𝑛 {1 – (−𝑙𝑛 ( 1 –1

𝑇))−𝑘} (1)

And the flood quantile formula for GLO is:

𝑄(𝐹) = 𝑚 + 𝑛{1 – (𝑇 – 1)−𝑘} (2)

Where the parameters of 𝑚, 𝑛, and 𝑘 are shown in Table 1.

3

Table 1: Parameters of Flood Quantiles Formulas

FF Region

Q(F) Parameters

m n k

1 0.8106 17.8368 0.0190

2 0.9338 -1.9444 -0.1422

3 0.7550 -1.8408 -0.1709

4 0.8714 -1.1923 -0.2470

5 0.5859 -2.0624 -0.2309

6 0.7473 8.7577 0.0549

7 0.7855 20.6237 0.0186

8 0.9420 -1.6144 -0.1460

9 0.8404 -3.8677 -0.0718

10 0.9135 1.5252 0.1209

11 0.8522 1.5253 0.2667

12 0.8414 1.9958 0.1913

The peak flood discharges can be estimated by multiplying flood quantiles with the mean

annual floods as the following formula:

𝑄𝑇 = 𝑄(𝐹) 𝑥 𝑀𝐴𝐹 (3)

Where:

𝑄𝑇 : Peak flood discharge for specified ARI (m3/s)

T : Average Recurrence Interval (years)

Q(F) : Flood quantiles or dimensionless growth curves

MAF : Mean annual floods (m3/s)

4

2 DEVELOPMENT OF THE PROCEDURE

The method used in developing this procedure is summarised below:

(a) Data Collection (streamflow, rainfall, catchment area and river slopes).

(b) Data Screening.

(c) Development of predictions of mean annual floods using multiple linear regression.

(d) Identification of homogeneous regions.

(e) Selection of the regional frequency distributions.

(f) Development of regional flood frequency curve.

2.1 Data Collection

The important hydrological data (i.e. annual maximum flow and rainfall) was collected from

DID Ampang Database and DID states of Sabah and Sarawak. The initial data screening was

carried out with the following criteria:

i. Minimum 10 years record.

ii. Missing data are discarded from the data set.

iii. Any major water-infrastructures inside catchment area are also discarded from the

data sets.

iv. Reasonably good quality and reliable data: doubtful data (outlier or repeated

constants data values) is removed from the data set.

A total of 85 streamflow data varies from 10 to 38 years records were used for the analysis.

60 streamflow stations were selected in Peninsular Malaysia, 14 streamflow stations in

Sabah and 11 streamflow in Sarawak. For rainfall data, 597 rainfall stations were selected

for the analysis which consists of 330 rainfall stations in Peninsular Malaysia, 29 rainfall

stations in Sabah and 238 rainfall stations Sarawak.

The catchment areas’ data were collected from DID data base. If unavailable, catchment

delineation based on Shuttle Radar Topography Mission (SRTM) Elevation data, river

networks, topomaps and river basin was carried out.

5

The river slopes were calculated using Weighted Average Slope (S) method. Firstly, the river

gradient was divided into several segments which represent high slope, intermediate slope

and main stem. The number of segments was defined based on visual observation of the

gradient condition from the SRTM data. All data used in the analysis are shown in APPENDIX

I.

2.2 Derivation of Regional Mean Annual Flood Equations

The magnitude of Mean Annual Flood (MAF) is affected by both the physiographical,

meteorological and catchment characteristics of the basin. Catchment area mean annual

catchment rainfall, mean channel slope, mean channel length and drainage pattern are some

of the easily defined characteristics that could affect the MAF.

In this procedure, catchment area, mean annual rainfall and river slopes were selected for

deriving the MAF equations.

The relationship between catchment characteristics and MAF is shown in Equation (4):

𝑀𝐴𝐹 = 𝑑 𝐴𝑎 𝑅𝑏 𝑆𝑐 (4)

Where :

MAF : Mean Annual Flood (m3/s)

A : Catchment Area (km2)

R : Mean Annual Rainfall (m)

S : Weighted Average Slope (m/km)

a, b, c, and d are parameters of catchment characteristics

The MAF equation is reduced to a multiple linear regression by transforming Equation (4) into

its logarithmic form:

Log 𝑀𝐴𝐹 = Log 𝑑 + 𝑎 Log 𝐴 + 𝑏 Log 𝑅 + 𝑐 Log 𝑆 (5)

To evaluate the accuracy of the regression equations, model evaluation statistics based on R2

and PBIAS were used. The formula of R2 and PBIAS are as follows:

6

R2 = 1 −∑ (Yi

obs−Yical)

2ni=1

∑ (Yiobs−Y̅)

2ni=1

(6)

Where :

R2 : Coefficient of determination

Yiobs : Observed mean annual floods (m3/s)

Yical : Calculated mean annual floods (m3/s)

Y̅ : Average of observed mean annual floods (m3/s)

𝑃𝐵𝐼𝐴𝑆 = [∑ (𝑌𝑖

𝑜𝑏𝑠−𝑌𝑖𝑐𝑎𝑙)∗100𝑛

𝑖=1

∑ (𝑌𝑖𝑜𝑏𝑠)𝑛

𝑖=𝑛

] (7)

Where:

𝑃𝐵𝐼𝐴𝑆 : Percent Bias (%)

Yiobs : Observed mean annual floods (m3/s)

Yical : Calculated mean annual floods (m3/s)

The criteria of model performance rating are based on Table 2 below:

Table 2: Model Performance Rating Based on R2 and PBIAS [ 1 ]

Objective Function Value Range Performance Classification

R2

0.7 < R2 < 1

0.6 < R2 < 0.7

0.5 < R2 < 0.6

R2 < 0.5

Very Good

Good

Satisfactory

Unsatisfactory

PBIAS

PBIAS < ±10

±10 ≤ PBIAS < 15

± 15 ≤ PBIAS < ± 25

PBIAS > 25

Very Good

Good

Satisfactory

Unsatisfactory

The criteria above were applied in this study. The regression analysis results were accepted if

the values of R2 above 0.6 and |𝑃𝐵𝐼𝐴𝑆| lower than ±25%.

7

The MAF regions was initially established using the MAF Regions in HP 4 (1987). Adjustment

of the initial MAF regions was carried out using the following steps:

• Move a site or a few sites from one region to another region

• Subdivide the region

• Merge the region with the other region or redefine a new region

• If not possible, delete a site or a few sites from data sets

• Obtain more data and redefine regions if possible

The processes were continued until the values of R2 and PBIAS were satisfied.

Finally, 9 regions were formed based on the selected criteria above. 6 MAF Regions located

in Peninsular Malaysia, 1 MAF Region in Sarawak and 2 MAF Regions in Sabah. The catchment

characteristic constants derived for each region are listed in Table 3.

Table 3: Coefficients of 𝒂, 𝒃, 𝒄 and 𝒅

Region Parameter

a b c d

MAF 1 0.6263 0.0000 0.0000 3.48

MAF 2 0.5281 0.0000 0.2260 2.28

MAF 3 0.4718 3.1500 0.0916 0.36

MAF 4 0.6344 1.6276 0.3144 0.71

MAF 5 0.8151 2.2226 0.0000 0.19

MAF 6 1.0021 1.0805 0.3061 0.20

MAF 7 0.5020 1.2815 0.0000 9.10

MAF 8 1.1523 0.0000 1.1413 0.02

MAF 9 0.8910 4.5177 0.4675 0.002

8

2.3 Regional Flood Frequency Analysis

Regional flood frequency analysis was carried out as Hosking and Wallis proposed[ 9 ]. The peak

floods of a specific event in an ungauged area are calculated from a fitted probability

distribution in a homogeneous region. The homogeneous regions were formed using L-

moment measure i.e. Discordancy Measures, Homogeneity test and Zdist test, as described in

the following Sections (2.3.1, 2.3.2 and 2.3.3).

2.3.1 Discordancy Measure

A discordancy measure was used to identify outliers in the data set. It was based on L-moment

ratios (𝑢𝑖). The discordancy measure formula is the following:

𝐷𝑖 =1

3𝑁(𝑢𝑖 − �̅�)𝑇𝐴−1(𝑢𝑖 − �̅�) (8)

Where:

𝐷𝑖 : Discordancy measure for a catchment 𝑖

𝑁 : Number of catchments in the region

𝑢𝑖 : A vector containing LCV, L-skew, and L-kur

�̅� : Regional average of 𝑢𝑖

𝐴 is defined as:

𝐴 = ∑(𝑢𝑖 − �̅�)(𝑢𝑖 − �̅�)𝑇

𝑁

𝑖=1

(9)

The site 𝑖 is considered as discordant if 𝐷𝑖 ≥ 3.

For the discordant sites, the detailed analysis of data sets was carried out to clarify the causes

of discordancy and further to decide whether the data must be removed or remained in the

data sets.

9

2.3.2 Homogeneity Test

The aim of homogeneity test is to assess whether the sites can be treated as a homogeneous

region or not. The homogeneity test compares the site variation in sample L-moments within

a homogeneous region.

The homogeneity measure is the following:

𝐻 =(𝑉−𝜇𝑣)

𝜎𝑣 (10)

𝑉 is the weighted standard deviation of the sample LCVs. The formula is the following:

𝑉 = {∑ 𝑛𝑖(𝐿𝐶𝑉

(𝑖)−𝐿𝐶𝑉𝑅)

2𝑁𝑖=1

∑ 𝑛𝑖𝑁𝑖=1 }

}

1

2

(11)

𝐿𝐶𝑉𝑅 is the regional average of simulated 𝐿𝐶𝑉 in a homogeneous region with the formula as

follows:

𝐿𝐶𝑉𝑅 =

∑ 𝑛𝑖 𝐿𝐶𝑉(𝑖)𝑁

1

∑ 𝑛𝑖𝑁𝑖=1

(12)

The mean (𝜇𝑣) and standard deviation (𝜎𝑣) of the region were obtained from a repeated

simulation using a best-fitted kappa distribution.

The region is considered as homogeneous if 𝐻 less than 2.

2.3.3 Regional Frequency Distributions

Hosking and Wallis [ 9 ] propose a goodness-of-fit measure based on L-moment ratios (𝑍𝐷𝑖𝑠𝑡).

The idea was based on the difference between L-kurtosis of the proposed distribution (𝐿kur𝐷𝑖𝑠𝑡)

and the regional average (𝐿kur𝑅 ) and then compared it with the standard deviation of the L-

kurtosis in a region. If the comparison is relatively small, then the proposed distribution was

accepted.

The goodness-of-fit measure based on L-moments is the following:

𝑍𝐷𝑖𝑠𝑡 =(𝐿𝑘𝑢𝑟

𝐷𝑖𝑠𝑡−𝐿𝑘𝑢𝑟𝑅 +𝐵4)

𝜎4 (13)

10

𝐵4 is the bias of L-kurtosis which calculated using the following formula:

𝐵4 =∑ (𝐿𝑘𝑢𝑟

𝐷𝑖𝑠𝑡−𝐿𝑘𝑢𝑟𝑅 )

𝑁𝑠𝑖𝑚𝑚=1

𝑁𝑠𝑖𝑚 (14)

A repeated simulation using Kappa Distribution was carried out to obtain the simulated

standard deviation of L-kurtosis (𝜎4).

The formula of L-kurtosis (𝜎4) is as follows:

𝜎4 = [(𝑁𝑠𝑖𝑚 − 1)−1 {∑ (𝐿𝑘𝑢𝑟𝐷𝑖𝑠𝑡 − 𝐿𝑘𝑢𝑟

𝑅 )2

−𝑁𝑠𝑖𝑚𝑚=1 𝑁𝑠𝑖𝑚𝐵4

2}]

1

2 (15)

The best fit distribution is accepted when |𝑍𝐷𝑖𝑠𝑡| score is lower than 1.64.

Table 4 below shows the accepted distributions in the FF Regions of Malaysia.

Table 4: Results of Goodness-of-Fit Test

Region Dist Regional Average

Ztest L-skew L-kur

1 GEV 0.176 0.146 -0.05

2 GLO 0.16 0.208 -1.26

3 GEV 0.202 0.104 1.28

4 GLO 0.258 0.222 -0.45

5 GEV 0.328 0.204 0.35

6 GEV 0.227 0.147 -0.15

7 GEV 0.119 0.098 0.6

8 GLO 0.117 0.157 0.46

9 GEV 0.2712 0.1416 0.19

10 GEV 0.1038 0.0876 1.09

11 GEV 0.142 0.1851 -0.27

12 GEV 0.1866 0.1073 0.81

Figure 1 and Figure 2 show the regional average L-moments for Peninsular Malaysia and

States of Sabah and Sarawak respectively.

11

Figure 1: Regional Average L-Moments of Peninsular Malaysia

Figure 2: Regional Average L-Moments for Sabah and Sarawak

1

2

3

4

5

6

7

8

9

0.0

0.1

0.2

0.3

0.0 0.1 0.2 0.3 0.4

L-k

urt

osis

L-skewness

FF Region EXPGUM GEVGLO PE3LP3 LNOGPA

10

11

12

13

0.0

0.1

0.2

0.3

0.0 0.1 0.2 0.3 0.4

L-ku

rto

sis

L-skewness

FF Region EXP

GUM GEV

GLO PE3

LP3 LNO

GPA

12

GLO and GEV are the most acceptable distributions in Peninsular Malaysia, while for Sabah

and Sarawak GEV is the most acceptable.

2.3.4 Derivation of Regional Dimensionless Flood Frequency Curve

Regional dimensionless curves were derived from flood quantile estimates based on Equation

(1) for GEV and Equation (2) for GLO using parameters in

. The regional growth curves for Peninsular Malaysia and the states of Sabah and Sarawak are

shown in Figure 3 and Figure 4.

13

Figure 3: Regional Growth Curves of Peninsular Malaysia

5 20 1000.5

1.0

1.5

2.0

2.5

3.0

3.5

2 10 50

QT/

MA

F

Recurrance Interval, T (years)

FF1

FF2

FF3

FF4

FF5

FF6

FF7

FF8

14

Figure 4: Regional Growth Curves of Sabah and Sarawak

5 20 1000.5

1.0

1.5

2.0

2.5

2 10 50

QT/

MA

F

Recurrance Interval, T (years)

FF9

FF10

FF11

FF12

15

3 APPLICATION OF THE PROCEDURE

In the development of this procedure many constraints were set by the nature of the

hydrological data used in deriving the regional flood frequency curves and the MAF equations.

Therefore, in the application of this procedure, the catchment of interest should also satisfy

the following criteria:

(i) The catchment must not be significantly regulated (by reservoir, diversion, etc).

(ii) The catchment must not be influenced by tidal effects.

(iii) The catchment must be relatively an undeveloped area.

(iv) The catchment area must be larger than 20km2.

3.1 Method of Application

The method of application of this procedure involves the following steps:

Step 1 Determine the catchment area (A) in kilometre squares.

Step 2 Estimate the mean annual rainfall (R) in metres.

i. The mean annual rainfall can be estimated from available rainfall records of DID

rainfall stations within or near the catchment.

ii. If rainfall records are not available, R can be estimated from Mean Annual

Rainfall Maps as shown in APPENDIX III.

Note: The unit for R used in the MAF regression analysis is in metres.

Step 3 Determine the MAF region of the catchment from MAF maps as shown in APPENDIX

IV.

Step 4 Compute the MAF from the appropriate regional using Equation (4).

Step 5 Determine the FF Region of the catchment from FF maps as shown in APPENDIX V.

Step 6 Obtain the dimensionless ordinates 𝑄𝑇/𝑀𝐴𝐹 from the regional flood frequency

curves for specified ARIs (refer to Figure 3 for Peninsular Malaysia and Figure 4 for

Sabah and Sarawak) or calculate using Equation (1) or Equation (2).

16

Step 7 Determine 𝑄𝑇 for the various ARIs by multiplying the 𝑄𝑇/𝑀𝐴𝐹 factor with the MAF

obtained in Step 4.

3.2 Worked Examples

Problem 1:

Determine the 20-year and 100-year of peak discharges for an ungauged site in Sg Batang Kali,

located at Latitude: 3.452818° and Longitude: 101.672704°, with a catchment area of 88 km2.

The weighted slope of this area is 2 m/km.

Solution:

Reference Calculation Output

Step 1: Determine the catchment area (A)

88 km2

APPENDIX III

Step 2: Estimate the mean annual rainfall (R)

R = 2600 mm

2.6 m

APPENDIX IV

Step 3: Determine the MAF Region

MAF 3

Step 4: Compute the MAF

A = 88 km2

R = 2.6 (m)

S = 2 m/km

a, b, c and d = Parameters of variables

Table 3

Region Parameter

a b c d

3 0.4718 3.1500 0.0916 0.36

Equation (4)

MAF = 0.36 x (880.4718) x (2.63.1500) x (20.0916)

MAF =

64.85 m3/s

APPENDIX V

Step 5: Determine the FF Region

FF 3

17


Step 6: Calculate the flood quantile

Where the parameters of m, n and k are:

Region Q(F) Parameters

m n k

3 0.7550 -1.8408 -0.1709

Equation (1)

For T = 20 years

Q(F) = 0.7550 – (–1.8408) [1 – (– ln (1 −1

20))0.1709]

Q(F) = 1.49

Equation (3) Q20 = Q(F) x MAF

Q20 = 1.49 x 64.33

Q20 =

96.48 m3/s

Equation (1)

For T = 100 years

Q(F) = 0.7550 – (–1.8408) [1 – (– ln (1 −1

100))0.1709]

= 1.76


= 1.76 x 64.33

Q100 =

113.95 m3/s

18

Problem 2:

Determine the 2-year and 10-year design discharge for an ungauged site on Sg. Sadong

located at Lat. 1.15972°, Long. 110.56667° with a catchment area of 953 km2. The weighted

slope is 5.24 m/km.

Solution:


Step 1: Determine the catchment area (A)

953 km2

APPENDIX III

Step 2: Estimate the mean annual rainfall (R)

R = 3467 mm

3.467 m

APPENDIX IV

Step 3: Determine the MAF Region

MAF 9

Step 4: Compute the MAF

A = 953 km2

R = 3.467 m

S = 5.24 m/km

a, b, c and d = Parameters of variables

Table 3

Region Parameter

a b c d

9 0.8910 4.5177 0.4675 0.0017

Equation (4)

MAF = 0.0017 x (9530.8910) x (3.4674.5177) x (5.240.4675)

MAF =

457.57 m3/s

APPENDIX V

Step 5: Determine the FF Region

FF 9

19


Step 6: Calculate the flood quantile

Where the parameters of m, n and k are:

Region Q(F) Parameters

m n k

9 0.8404 -3.8677 -0.0718

Equation (1)

For T = 2 years

Q(F) = 0.8404 – (–3.8677) [1 – (– ln (1 −1

2))0.0718]

Q(F) = 0.94


Q2 = 0.94 x 457.57

Q2 =

430.51 m3/s

Equation (1)

For T = 10 years

Q(F) = 0.8404 – (–3.8677) [1 – (– ln (1 −1

10))0.0718]

= 1.42


= 1.42 x 538.32

Q10 =

648.58 m3/s

20

4 ACCURACY OF THE PROCEDURE

4.1 Comparison with the Observed Data

To measure the accuracy of HP 4 (2018) procedure, comparison between estimated floods

using the Updated HP 4 (2018) procedure with the observed floods for each streamflow

stations were carried out. The error was presented in percentages of PBIAS for the selected

ARIs. The estimated peak floods were calculated based on the developed MAF formulas and

flood frequency of each FF region. The observed peak floods were calculated from the

streamflow data that best-fitted to the GEV and GLO distributions. The results of PBIAS for

each FF region are shown in Figure 5 below.

Figure 5: Percentages of PBIAS

In general, the estimated peak floods using HP 4 (2018) are satisfied. Three regions which

provide high PBIAS error are Region FF 11, FF 10 and FF 5. Therefore, caution must be taken

for those regions by comparing the estimated peak floods using HP 4 (2018) with other

methods of calculation.

-100

-50

0

50

100

2 5 10 20 50 100

PB

IAS

(% E

rro

r)

Recurrence Interval (years ARI)

FF1 FF2 FF3 FF4

FF5 FF6 FF7 FF8

FF9 FF10 FF11 FF12

21

4.2 Comparison with HP 4 (1987)

A comparison of the estimated peak floods using HP 4 (1987) and HP 4 (2018) was also carried

out. The comparison was based on the available data provided in HP 4 (1987). Figure 6 below

shows the comparison of HP (2018) and HP (1987) in percentage of PBIAS.

Figure 6: Percentage of PBIAS between HP 4 (1987) and Updated HP 4 (2018)

HP 4 (2018) has provided less PBIAS errors compared with HP 4 (1987). The average absolute

PBIAS of HP 4 (2018) and HP 4 (1987) are 3.6% and 35.90% respectively.

-26

.82

-23

.10

-22

.18

-22

.52

-24

.22

96

.56

-3.2

1

-0.1

0

1.7

4

3.4

9

6.0

7

6.8

8

-60

-30

0

30

60

90

120

2 5 10 20 50 100

PB

IAS

(%)

Reccurence Interval (ARI)

HP 4 (1987) HP 4 (2018)

22

5 LIMITATIONS OF THE PROCEDURE

The following are the limitations of the HP 4 (2018) procedure:

• Sample Size - In this study 55 streamflow stations were used in Peninsular Malaysia.

24 streamflow stations were used in the states of Sabah and Sarawak. There is

difficulty in relating the observed Mean Annual Floods (MAF) with the catchment

characteristics (catchment area, MAR and slope) because of limited number of

streamflow stations and reliable sources of data.

• Catchment Size – This study used the available data for catchment sizes ranging from

20 km2 to 25,000 km2. Applying this procedure to the catchment outside the size range

will likely give less accurate peak flood estimates, particularly for catchment smaller

than 20 km2.

• Data Accuracy – The streamflow data was derived from rating curves. In the case of

peak water levels beyond the range of stage-discharge rating curves, the data may be

inaccurate. The RFFA mainly relies on the extreme high flow records for analysis.

• Catchment Characteristics – In RFFA it is assumed that regions that are contiguous

and have similar catchment characteristics (aside from catchment area and slope) can

be identified. The stations used in this procedure predominantly consist of rural

catchments. Therefore, this procedure should not be applied to catchments with more

than 15% developed area. It is not advisable to apply this procedure to catchments

that have major flow diversions or man-made flood detention storages. This is

because these factors will alter the natural flow characteristics of the catchment.

• Homogeneous Region – In RFFA it is assumed that the same frequency distribution

can be applied to a homogeneous FF Region. The homogeneity test for Region FF3,

FF9 and FF10 were found to be greater than 3 though they were classified as FF

regions. It is not possible to guarantee all regions will have a H statistic less than 3.

This is a part of natural phenomena which has been found in many RFFA studies,

including Hosking and Wallis [ 9 ].

23

• Flood Estimates - Regions FF 5, FF 10 and FF 12 were found to produce less accurate

flood estimates particularly for the extreme 100-yr ARI flood.

HP 4 provides a convenient method of estimating floods in ungauged catchments. Estimates

of floods are based on historical data of nearby stations in the same region. The use of data

from several stations in a way extend records and any error in a particular observation in a

station is averaged out by data from other stations.

It is not a rainfall-runoff model where it is assumed that a certain ARI flood is caused by the

same ARI rainfall. The approach in estimating peak discharge using rainfall-runoff modelling

sometimes also maximises peak discharge by also selecting the maximum peak discharge

from peak discharges simulated using rainstorm of the same ARI and of various storm

durations. This could be the reason why peak flood discharges estimated based on rainfall-

runoff simulations tend to be higher than peak flood discharges estimated using frequency

analysis of observed peak discharge data.

25

REFERENCES

[ 1 ] Ayele, G.T., Teshale, E.Z., Yu, B., Rutherfurd, I.D. and Jeong, J., 2017. Streamflow and

sediment yield prediction for watershed prioritization in the Upper Blue Nile River

Basin, Ethiopia. Water, 9(10), p.782.

[ 2 ] Dalrymple, T., 1960. Flood-frequency Analysis, manual of hydrology: Part 3(No.

1543-A). USGPO.

[ 3 ] Draper, N.R. and Smith, H., 2014. Applied regression analysis (Vol. 326). John Wiley

& Sons.

[ 4 ] Dubreuil, P. and Vuillaume, G., 1975. Influence du milieu physico-climatique sur

l'écoulement de petits bassins intertropicaux. Publication-AISH, (117), pp.205-215.

[ 5 ] Dubreuil, P.L., 1986. Review of relationships between geophysical factors and

hydrological characteristics in the tropics. Journal of Hydrology, 87(3-4), pp.201-222.

[ 6 ] Farquharson, F.A.K., Meigh, J.R. and SutcliFF e, J.V., 1992. Regional flood frequency

analysis in arid and semi-arid areas. Journal of Hydrology, 138(3-4), pp.487-501.

[ 7 ] Hosking, J.R.M. and Wallis, J.R., 1988. The effect of intersite dependence on regional

flood frequency analysis. Water Resources Research, 24(4), pp.588-600.

[ 8 ] Hosking, J.R.M. and Wallis, J.R., 1993. Some statistics useful in regional frequency

analysis. Water resources research, 29(2), pp.271-281.

[ 9 ] Hosking, J.R.M. and Wallis, J.R., 2005. Regional frequency analysis: an approach

based on L-moments. Cambridge University Press.

[ 10 ] Jingyi, Z. and Hall, M.J., 2004. Regional flood frequency analysis for the Gan-Ming

River basin in China. Journal of hydrology, 296(1-4), pp.98-117.

[ 11 ] Kjeldsen, T.R., Smithers, J.C. and Schulze, R.E., 2002. Regional flood frequency

analysis in the KwaZulu-Natal province, South Africa, using the index-flood

method. Journal of hydrology, 255(1-4), pp.194-211.

26

[ 12 ] Lim, Y.H. and Lye, L.M., 2003. Regional flood estimation for ungauged basins in

Sarawak, Malaysia. Hydrological sciences journal, 48(1), pp.79-94.

[ 13 ] Mohd Baki, A., Yusof, M., Asmani, D., Atan, I., Halim, M. and Farina, N., 2015.

Regional flow frequency analysis on Peninsular Malaysia using L-moments. Jurnal

Intelek, 9(1), pp.63-68.

[ 14 ] N. Vivekanandan (2015) Flood frequency analysis using method of moments and L-

moments of probability distributions, Cogent Engineering.

[ 15 ] Nash, J.E. and Shaw, B.L., 1966. Flood frequency as a function of catchment

characteristics. In River Flood Hydrology (pp. 115-136). Thomas Telford Publishing.

[ 16 ] Ouarda, T.B.M.J., Bâ, K.M., Diaz-Delgado, C., Cârsteanu, A., Chokmani, K., Gingras, H.,

Quentin, E., Trujillo, E. and Bobée, B., 2008. Intercomparison of regional flood

frequency estimation methods at ungauged sites for a Mexican case study. Journal

of Hydrology, 348(1), pp.40-58.

[ 17 ] Pearson, C.P., 1991. New Zealand regional flood frequency analysis using L-

moments. Journal of Hydrology (New Zealand), pp.53-64.

[ 18 ] Saf, B., 2009. Regional flood frequency analysis using L-moments for the West

Mediterranean region of Turkey. Water Resources Management, 23(3), pp.531-551.

[ 19 ] Te Chow, V., 1988. Applied hydrology. Tata McGraw-Hill Education.

[ 20 ] Theil, H. and Chung, C.F., 1988. Information-theoretic measures of fit for univariate

and multivariate linear regressions. The American Statistician, 42(4), pp.249-252.

27

APPENDIX I: CATCHMENT CHARACTERISTICS

Old ID New ID Station Name MAFObs (m3/s)

Number of

Record (Year)

Catchment Area (km2)

MAR (mm)

Specific Discharge

(m3/s/km2)

Weighted Slope

(m/km) Latitude Longitude

5606410 0050301SF Sg. Muda di Jam. Syed Omar Kedah

664.24 27 3,330 2231 0.2 1.62 5.60972 100.62639

5206432 0090141SF Sg. Kerian di Selama Perak 205.05 19 629 2366 0.3 17.45 5.22917 100.68889

5505412 0050051SF Sg. Muda di Ldg. Victoria Pulau Pinang

611.35 44 4,010 2241 0.2 1.70 5.53194 100.57222

5506416 0050061SF Sg. Sedim di Merbau Pulas Pulau Pinang

115.43 11 440 2294 0.3 18.50 5.56667 100.63889

6503401 0010291SF Sg. Arau di Ldg. Tebu FeIda Perlis

23.90 17 21 1981 1.2 6.56 6.50278 100.35139

6602402 0010041SF Sg. Pelarit di Kaki Bkt. Perlis 46.48 12 54 2055 0.9 21.94 6.61250 100.20694

6602403 0010341SF Sg. Jarum di Kg. Masjid Perlis 47.53 12 64 1976 0.7 8.05 6.62500 100.26028

3813414 0190191SF Sg. Trolak di Trolak Perak 63.33 24 66 2636 1.0 27.08 3.89167 101.37917

3814415 0190181WL Sg. Bil di Tg. Malim-Slim Perak 39.39 15 41 2685 1.0 130.82 3.82500 101.48889

3911457 0180451WL Sg. Sungkai di Jln. Ansor-Kampar Perak

60.53 19 479 2450 0.1 15.87 3.98889 101.12500

4011451 0180441SF Sg. Bidor di Bt. JIn. Anson Perak 94.23 19 373 2388 0.3 14.48 4.00000 101.13194

4012401 0180861SF Sg. Bidor di Bidor Malayan Tin Bhd. Perak

132.13 17 210 2460 0.6 34.60 4.07500 101.24444

4012452 0180431SF Sg. Bidor di Bt. Jln. Anson Perak 76.06 18 339 2436 0.2 25.49 4.02917 101.23333

28

APPENDIX I: CATCHMENT CHARACTERISTICS (Cont.)


Number of

Record (Year)


MAR (mm)

Specific Discharge

(m3/s/km2)

Weighted Slope


4111455 0180261SF Sg. Batang Padang di Tg. Keramat Perak

90.69 31 445 2316 0.2 17.53 4.13472 101.14722

4212467 0180641SF Sg. Chenderiang di Bt. JIn. Tapah Perak

48.30 23 119 2231 0.4 9.11 4.23194 101.21944

4410461 0180111SF Sg. Kinta di Bt. Gajah Perak 258.56 20 1,054 2341 0.2 25.59 4.46806 101.04722

4610466 0180131SF Sg. Pari di JIn. Silibin, Ipoh Perak

112.55 38 245 2369 0.5 12.20 4.60556 101.06667

4611463 0180291SF Sg. Kinta di Tg. Rambutan Perak 125.78 31 246 2327 0.5 40.03 4.66944 101.15833

4907422 0100011SF Sg. Kurau di Bt. JIn. Taiping Perak

26.15 25 80 3431 0.3 35.09 4.97778 100.78056

5007421 0100041SF Sg. Kurau di Pondok Tg. Perak 106.09 26 337 2573 0.3 15.85 5.01250 100.73194

5007423 0100051SF Sg. Ara di Bt. Jin. Taiping Perak 74.55 24 140 2518 0.5 22.49 5.03333 100.79028

5106433 0090031SF Sg. Ijok di Titi Ijok Perak 61.94 37 216 2672 0.3 8.60 5.14028 100.69722

3814416 0190321SF Sg. Slim di Slim River Perak 87.84 34 455 2624 0.2 17.89 3.82639 101.41111

2920432 0550391SF Sg. Triang di Kg. Chenor Negeri Sembilan

63.23 31 228 1890 0.3 21.30 2.94861 102.08889

3022431 0550381SF Sg. Triang di Juntai Negeri Sembilan

71.90 31 904 1961 0.1 11.24 3.07500 102.21806

2816441 0240341SF Sg. Langat di Dengkil Selangor 299.90 36 1,240 2509 0.2 18.50 2.99278 101.78694

29



Number of

Record (Year)


MAR (mm)

Specific Discharge

(m3/s/km2)

Weighted Slope


2918401 0240511SF Sg. Semenyih di Sg. Rinching Selangor

67.30 20 225 2309 0.3 4.48 2.91528 101.82361

3118445 0240441SF Sg. Lui di Kg. Lui Selangor 34.03 24 68 2471 0.5 24.34 3.17361 101.87222

3615412 0190131SF Sg. Bernam di Tg. Malim Selangor

126.75 40 186 2710 0.7 45.65 3.68528 101.52333

3813411 0190161SF Sg. Bernam di Jam. SKC Selangor

218.21 45 1,090 2670 0.2 16.70 3.80750 101.36944

3116434 0230391SF Sg. Bt. Di Sentul W. P. Kuala Lumpur

225.58 20 145 2634 1.6 16.65 3.17639 101.68750

1737451 0430121SF Sg. Johor di Rantau Panjang Johor

258.30 31 1,130 2150 0.2 0.92 1.78056 103.74583

1836402 0430271SF Sg. Sayong di Jam. Johor Tenggara Johor

616.16 14 624 2116 1.0 1.00 1.80417 103.66944

1836403 0430321SF Sg. Pengeli di Felda Inas Johor 60.38 11 143 2140 0.4 4.77 1.82083 103.62083

2235401 0500281SF Sg. Kahang di Bt. Jin. Kluang Johor

382.42 22 587 2197 0.7 5.95 2.25139 103.58750

2237471 0500141SF Sg. Lenggor di Bt. Kluang/Mersing Johor

180.81 19 207 2377 0.9 6.50 2.25833 103.73611

2528414 0320191SF Sg. Segamat di Segamat Johor 282.68 21 658 1875 0.4 4.77 2.50694 102.81806

2224432 0310061SF Sg. Kesang di Chin Chin Melaka 22.12 35 161 1675 0.1 2.85 2.29028 102.49306

30



Number of

Record (Year)


MAR (mm)

Specific Discharge

(m3/s/km2)

Weighted Slope


2322413 0290131SF Sg. Melaka di Pantai Belimbing Melaka

69.61 42 350 1708 0.2 2.68 2.34306 102.25278

2322415 0290141SF Sg.Durian Tunggal di Bt. Air Resam Melaka

23.06 15 73 1710 0.3 4.19 2.32361 102.29306

2519421 0270081SF Sg. Linggi di Sua Betong Negeri Sembilan

135.30 32 523 1914 0.3 9.30 2.68111 101.92750

2520423 0270091SF Sg. Pedas di Kg. Pilin Negeri Sembilan

32.37 27 111 1810 0.3 17.71 2.51667 102.05833

2524416 0320371SF Sg. Gemencheh di Gedok Negeri Sembilan

40.50 27 114 1642 0.4 4.11 2.55139 102.42222

2525415 0320331WL Sg. Gemencheh di JIn. Gemas-Rompin Negeri Sembilan

181.52 26 453 1623 0.4 4.10 2.56556 102.44667

2722413 0320341SF Sg. Muar di K. Pilah Negeri Sembilan

278.43 29 370 1706 0.8 11.82 2.74861 102.24861

2723401 0320551SF Sg. Kepis di Jam. Kayu Lama Negeri Sembilan

43.64 17 21 1654 2.1 6.15 2.70556 102.35556

3424411 0550941SF Sg. Pahang di Temerloh Pahang 4,275.20 28 19,000 2364 0.2 2.38 3.44444 102.42917

3519426 0551041SF Sg. Bentong di Jam. K. Marong Pahang

136.32 19 241 2495 0.6 44.29 3.51250 101.91528

3527410 0551191SF Sg. Pahang di Lubok Paku Pahang

3,798.12 19 25,600 2065 0.1 1.53 3.51250 102.75833

31



Number of

Record (Year)

Catchment Area

(km2)

MAR (mm)

Specific Discharge

(m3/s/km2)

Weighted Slope


3629403 0551181SF Sg. Lepar di Jam. Gelugor Pahang

252.44 21 560 2362 0.5 4.36 3.69722 102.97222

4019462 0551021SF Sg. Lipis di Benta Pahang 372.02 27 1,670 2364 0.2 10.38 4.01806 101.96528

5721442 0730231SF Sg. Kelantan di Jam. Guillemard Kelantan

8,307.12 28 11,900 2571 0.7 2.22 5.76250 102.15000

6019411 0740021SF Sg. Golok di Rantau Panjang Kelantan

462.77 34 761 3138 0.6 1.18 6.02297 101.97600

4131453 0600101SF Sg. Cherul di Ban Ho Terengganu

812.94 25 505 3098 1.6 2.47 4.13333 103.17500

4232401 0600011SF Sg. Kemaman di Jam. Air Putih Terengganu

608.32 15 381 3201 1.6 6.17 4.27083 103.19861

4232452 0600111SF Sg. Kemaman di Rantau Panjang Terengganu

690.81 19 626 3185 1.1 5.62 4.28056 103.26250

4332401 0600021SF Sg. Tebak di Jam. Tebak Terengganu

111.41 12 134 3179 0.8 9.46 4.37778 103.26250

4832441 0630091SF Sg. Dungun di Jam. Jerangau Terengganu

1,672.98 29 1,480 3691 1.1 2.24 4.84306 103.20417

4930401 0670011SF Sg. Berang di Menerong Terengganu

401.06 18 140 3964 2.9 29.84 4.93889 103.06250

5130432 0670061SF Sg. Terengganu di Kg. Tanggol Terengganu

2,706.18 30 3,340 3846 0.8 1.37 5.13750 103.04583

32



Number of

Record (Year)

Catchment Area

(km2)

MAR (mm)

Specific Discharge

(m3/s/km2)

Weighted Slope


4955403 1490031WL Sg. Mengalong di Sindumin Sabah

624.72 26 522 3322 1.2 12.18 4.99444 115.57778

4959401 1460101WL Sg. Padas di Kemabong 1,793.96 24 3,185 3256 0.6 8.41 4.91778 115.92000

5074401 1040031WL Sg. Kuamut di Ulu Kuamut 2,379.10 26 2,950 2384 0.8 3.92 5.08194 117.44167

5261402 1460121WL Sg. Sook di Biah 241.24 25 1684 2704 0.1 2.90 5.25694 116.14028

5275401 1040091WL Sg. Kinabatangan di Pagar Sabah

1,601.92 21 9,430 2606 0.2 1.62 5.22639 117.50278

5373401 1040171WL Sg. Milian di Tangkulap 1,234.74 17 5,730 2,617 0.2 2.05 5.30417 117.31806

5375401 1040071WL Sg. Kinabatangan di Balat 1,888.89 15 10,800 2534 0.2 1.20 5.30972 117.59722

5760401 1400021WL Sg. Papar di Kaiduan Sabah 578.51 12 365 3085 1.6 35.06 5.76944 116.09167

5760402 1400041WL Sg. Papar di Kogopon Sabah 1,011.74 21 546 3041 1.9 21.46 5.70833 116.03611

5872401 1160051WL Sg. Labuk di Porog Sabah 1,957.73 26 3,185 2895 0.6 6.28 5.85417 117.22778

6073402 1160031WL Sg. Tungud di Basai Sabah 869.89 22 700 2919 1.2 6.67 6.05361 117.31639

6264401 1340021WL Sg. Kadamaian di Tamu Darat Sabah

967.01 29 388 3058 2.5 27.61 6.26389 116.45278

6468402 1280011WL Sg. Bongan di Timbang Bt. Sabah

631.98 13 570 2955 1.1 33.24 6.44778 116.81167

6670401 1260011WL Sg. Bengkoka di Kobon Sabah 1,400.71 12 700 2932 2.0 10.87 6.62500 117.04167

33



Number of

Record (Year)


MAR (mm)

Specific Discharge

(m3/s/km2)

Weighted Slope


1301427 1810061WL Sg. Sarawak Kanan di Pk. Buan Bidi

269.57 39 215 4059 1.2 5.44 1.39861 110.11278

1302428 1810141WL Sg. Sarawak Kiri di Kg. Git 500.21 36 442 3885 1.1 0.93 1.35556 110.26389

1304439 1800021WL Bt. Gong Sarawak 16.63 29 64 3839 0.3 2.09 1.34611 110.44028

1004438 1790041WL Sg. Kayan di Krusen 440.07 39 456 3484 1.1 7.87 1.06972 110.49778

1005447 1790051WL Sg. Kedup di New Meringgu 78.29 37 342 3420 0.2 4.48 1.05000 110.55278

1105401 1790201WL Sg. Sadong di Serian 340.35 44 953 3467 0.4 5.24 1.15972 110.56667

1415401 1750021WL Lubau Sarawak 724.42 35 321 3402 2.3 5.60 1.49722 111.58889

1813401 1740031WL Sebatan Sarawak 11.81 29 35 3276 0.3 5.03 1.80417 111.33333

1826401 1730431WL Sg. Katibas di Ng Mukeh 513.76 35 2,257 3540 0.2 3.35 1.84722 112.62917

2130405 1730061WL Sg. Rajang di Ng Benin 4,802.23 34 21,043 4043 0.2 0.97 2.16528 113.06944

2421401 1710011WL Stapang Sarawak 312.08 26 869 3428 0.4 3.50 2.40000 112.13472

34

35

APPENDIX II: ESTIMATED PEAK FLOODS BASED ON HP 4 (2018)

Old ID New ID Station Name MAFCal (m3/s)

Peak FloodCal (m3/s) in Year ARI

2 5 10 20 50 100

5606410 0050301SF Sg. Muda di Jam. Syed Omar Kedah 559.93 523.67 742.60 890.17 1033.71 1222.45 1366.09

5206432 0090141SF Sg. Kerian di Selama Perak 130.98 122.31 177.80 215.72 254.74 310.56 357.15

5505412 0050051SF Sg. Muda di Ldg. Victoria Pulau Pinang 629.04 588.31 834.26 1000.04 1161.3 1373.33 1534.70

5506416 0050061SF Sg. Sedim di Merbau Pulas Pulau Pinang 157.62 147.41 209.04 250.58 290.99 344.12 384.55

6503401 0010291SF Sg. Arau di Ldg. Tebu FeIda Perlis 23.45 21.93 31.10 37.28 43.29 51.20 57.21

6602402 0010041SF Sg. Pelarit di Kaki Bkt. Perlis 42.37 39.63 56.19 67.36 78.22 92.50 103.37

6602403 0010341SF Sg. Jarum di Kg. Masjid Perlis 47.12 44.07 62.49 74.91 86.99 102.87 114.96

3813414 0190191SF Sg. Trolak di Trolak Perak 75.07 65.07 87.93 100.80 111.69 123.93 131.91

3814415 0190181WL Sg. Bil di Tg. Malim-Slim Perak 48.83 42.32 57.19 65.56 72.65 80.61 85.80

3911457 0180451WL Sg. Sungkai di Jln. Ansor-Kampar Perak 111.02 96.23 130.03 149.07 165.17 183.28 195.08

4011451 0180441SF Sg. Bidor di Bt. JIn. Anson Perak 95.29 82.59 111.61 127.95 141.77 157.31 167.44

4012401 0180861SF Sg. Bidor di Bidor Malayan Tin Bhd. Perak

85.66 74.25 100.33 115.02 127.44 141.41 150.52

4012452 0180431SF Sg. Bidor di Bt. Jln. Anson Perak 102.95 89.23 120.58 138.23 153.16 169.96 180.90

4111455 0180261SF Sg. Batang Padang di Tg. Keramat Perak 109.22 94.67 127.92 146.65 162.49 180.31 191.92

4212467 0180641SF Sg. Chenderiang di Bt. JIn. Tapah Perak 46.94 40.69 54.98 63.03 69.84 77.49 82.48

4410461 0180111SF Sg. Kinta di Bt. Gajah Perak 187.58 162.59 219.70 251.87 279.07 309.67 329.61

4610466 0180131SF Sg. Pari di JIn. Silibin, Ipoh Perak 73.42 63.64 85.99 98.58 109.23 121.21 129.01

36

APPENDIX II: ESTIMATED PEAK FLOODS USING HP 4 (2018) (Cont.)



2 5 10 20 50 100

4611463 0180291SF Sg. Kinta di Tg. Rambutan Perak 96.25 83.43 112.73 129.24 143.20 158.90 169.13

4907422 0100011SF Sg. Kurau di Bt. JIn. Taiping Perak 51.62 48.20 70.07 85.01 100.39 122.39 140.76

5007421 0100041SF Sg. Kurau di Pondok Tg. Perak 92.18 86.08 125.13 151.81 179.28 218.57 251.35

5007423 0100051SF Sg. Ara di Bt. Jln. Taiping Perak 62.74 58.59 85.17 103.33 122.02 148.76 171.08

5106433 0090031SF Sg. Ijok di Titi Ijok Perak 63.48 59.28 86.17 104.55 123.46 150.52 173.09

3814416 0190321SF Sg. Slim di Slim River Perak 177.14 153.54 207.47 237.85 263.54 292.43 311.26

2920432 0550391SF Sg. Triang di Kg. Chenor Negeri Sembilan

46.22 34.82 54.98 65.71 74.39 83.69 89.45

3022431 0550381SF Sg. Triang di Juntai Negeri Sembilan 214.06 198.34 293.04 356.85 418.90 500.46 562.51

2816441 0240341SF Sg. Langat di Dengkil Selangor 247.61 215.77 336.32 428.53 531.49 692.57 839.03

2918401 0240511SF Sg. Semenyih di Sg. Rinching Selangor 74.82 65.20 101.63 129.49 160.60 209.27 253.53

3118445 0240441SF Sg. Lui di Kg. Lui Selangor 61.50 53.59 83.53 106.44 132.01 172.02 208.39

3615412 0190131SF Sg. Bernam di Tg. Malim Selangor 140.09 121.43 164.08 188.10 208.42 231.27 246.16

3813411 0190161SF Sg. Bernam di Jam. SKC Selangor 280.77 243.36 328.85 376.99 417.72 463.51 493.36

3116434 0230391SF Sg. Bt. di Sentul W. P. Kuala Lumpur 103.83 90.48 141.03 179.69 222.87 290.41 351.83

1737451 0430121SF Sg. Johor di Rantau Panjang Johor 208.65 157.17 248.21 296.63 335.83 377.78 403.80

1836402 0430271SF Sg. Sayong di Jam. Johor Tenggara Johor

143.19 107.86 170.34 203.57 230.47 259.26 277.12

37




2 5 10 20 50 100

1836403 0430321SF Sg. Pengeli di Felda Inas Johor 93.60 70.5 111.35 133.07 150.65 169.47 181.15

2235401 0500281SF Sg. Kahang di Bt. JIn. Kluang Johor 256.53 193.23 305.17 364.70 412.89 464.47 496.47

2237471 0500141SF Sg. Lenggor di Bt. Kluang/Mersing Johor 154.78 116.59 184.13 220.05 249.12 280.24 299.55

2528414 0320191SF Sg. Segamat di Segamat Johor 198.79 149.74 236.48 282.62 319.96 359.93 384.72

2224432 0310061SF Sg. Kesang di Chin Chin Melaka 57.61 50.20 78.25 99.7 123.66 161.14 195.21

2322413 0290131SF Sg. Melaka di Pantai Belimbing Melaka 95.46 83.18 129.66 165.21 204.90 267.00 323.47

2322415 0290141SF Sg.Durian Tunggal di Bt. Air Resam Melaka

40.72 35.48 55.31 70.47 87.41 113.89 137.98

2519421 0270081SF Sg. Linggi di Sua Betong Negeri Sembilan

292.11 254.54 396.76 505.54 627.01 817.04 989.82

2520423 0270091SF Sg. Pedas di Kg. Pilin Negeri Sembilan 91.67 79.88 124.51 158.65 196.77 256.40 310.63

2524416 0320371SF Sg. Gemencheh di Gedok Negeri Sembilan

50.27 37.87 59.80 71.47 80.91 91.02 97.29

2525415 0320331WL Sg. Gemencheh di JIn. Gemas-Rompin Negeri Sembilan

118.26 89.08 140.68 168.13 190.34 214.12 228.87

2722413 0320341SF Sg. Muar di K. Pilah Negeri Sembilan 157.37 118.54 187.21 223.73 253.29 284.93 304.56

2723401 0320551SF Sg. Kepis di Jam. Kayu Lama Negeri Sembilan

19.74 14.87 23.48 28.06 31.77 35.74 38.20

3424411 0550941SF Sg. Pahang di Temerloh Pahang 3881.44 3596.45 5313.61 6470.61 7595.70 9074.58 10199.70

3519426 0551041SF Sg. Bentong di Jam. K. Marong Pahang 124.46 115.32 170.38 207.48 243.56 290.98 327.06

38




2 5 10 20 50 100

3527410 0551191SF Sg. Pahang di Lubok Paku Pahang 3664.45 3390.73 5492.98 6958.60 8422.34 10404.96 11958.57

3629403 0551181SF Sg. Lepar di Jam. Gelugor Pahang 219.08 202.72 328.40 416.02 503.53 622.06 714.95

4019462 0551021SF Sg. Lipis di Benta Pahang 534.83 495.56 732.17 891.60 1046.62 1250.40 1405.43

5721442 0730231SF Sg. Kelantan di Jam. Guillemard Kelantan

8604.06 8105.02 11221.15 13358.69 15565.35 18732.53 21383.86

6019411 0740021SF Sg. Golok di Rantau Panjang Kelantan 559.16 526.73 729.24 868.15 1011.56 1217.39 1389.69

4131453 0600101SF Sg. Cherul di Ban Ho Terengganu 458.41 424.17 687.15 870.50 1053.61 1301.62 1495.98

4232401 0600011SF Sg. Kemaman di Jam. Air Putih Terengganu

473.89 438.49 710.36 899.89 1089.18 1345.58 1546.49

4232452 0600111SF Sg. Kemaman di Rantau Panjang Terengganu

753.38 697.11 1129.31 1430.63 1731.56 2139.17 2458.58

4332401 0600021SF Sg. Tebak di Jam. Tebak Terengganu 188.14 174.09 282.02 357.27 432.42 534.21 613.98

4832441 0630091SF Sg. Dungun di Jam. Jerangau Terengganu

1579.04 1487.46 2059.33 2451.62 2856.6 3437.84 3924.42

4930401 0670011SF Sg. Berang di Menerong Terengganu 354.66 334.09 462.54 550.65 641.61 772.16 881.44

5130432 0670061SF Sg. Terengganu di Kg. Tanggol Terengganu

3210.43 3024.23 4186.94 4984.52 5807.90 6989.66 7978.95

4955403 1490031WL Sg. Mengalong di Sindumin Sabah 518.86 523.44 831.45 1093.06 1398.32 1891.30 2349.89

4959401 1460101WL Sg. Padas di Kemabong 2793.90 2755.78 4203.95 5350.82 6616.95 8537.31 10218.17

5074401 1040031WL Sg. Kuamut di Ulu Kuamut 1070.29 1055.69 1610.45 2049.80 2534.83 3270.48 3914.39

39




2 5 10 20 50 100

5261402 1460121WL Sg. Sook di Biah 443.21 437.16 666.89 848.83 1049.68 1354.32 1620.96

5275401 1040091WL Sg. Kinabatangan di Pagar Sabah 1489.56 1469.24 2241.32 2852.77 3527.81 4551.64 5447.79

5373401 1040171WL Sg. Milian di Tangkulap 1097.58 1082.60 1651.52 2102.06 2599.46 3353.87 4014.20

5375401 1040071WL Sg. Kinabatangan di Balat 1236.49 1219.62 1860.53 2368.10 2928.45 3778.34 4522.23

5760401 1400021WL Sg. Papar di Kaiduan Sabah 745.58 752.16 1194.76 1570.68 2009.32 2717.71 3376.69

5760402 1400041WL Sg. Papar di Kogopon Sabah 1203.03 1213.65 1927.80 2534.37 3242.14 4385.16 5448.45

5872401 1160051WL Sg. Labuk di Porog Sabah 2038.94 2011.12 3067.97 3904.93 4828.93 6230.38 7457.05

6073402 1160031WL Sg. Tungud di Basai Sabah 432.33 592.90 681.58 755.49 837.21 889.58 432.33

6264401 1340021WL Sg. Kadamaian di Tamu Darat Sabah 760.19 766.90 1218.17 1601.46 2048.70 2770.97 3442.86

6468402 1280011WL Sg. Bongan di Timbang Bt. Sabah 882.49 890.28 1414.15 1859.11 2378.29 3216.76 3996.74

6670401 1260011WL Sg. Bengkoka di Kobon Sabah 968.62 955.40 1457.47 1855.08 2294.04 2959.81 3542.55

1301427 1810061WL Sg. Sarawak Kanan di Pk. Buan Bidi 83.89 82.75 126.23 160.66 198.68 256.34 306.81

1302428 1810141WL Sg. Sarawak Kiri di Kg. Git 171.98 161.81 212.45 243.77 272.28 307.06 331.63

1304439 1800021WL Bt. Gong Sarawak 42.53 40.01 52.54 60.28 67.33 75.93 82.01

1004438 1790041WL Sg. Kayan di Krusen 265.68 249.97 328.19 376.59 420.63 474.35 512.32

1005447 1790051WL Sg. Kedup di New Meringgu 160.44 150.95 198.19 227.42 254.01 286.45 309.38

1105401 1790201WL Sg. Sadong di Serian 457.57 430.51 565.23 648.58 724.43 816.95 882.34

40



Peak FloodCal (m3/s)

2 5 10 20 50 100

1415401 1750021WL Lubau Sarawak 164.34 161.48 199.96 228.50 258.41 301.21 336.60

1813401 1740031WL Sebatan Sarawak 18.30 17.98 22.27 25.44 28.78 33.54 37.48

1826401 1730431WL Sg. Katibas di Ng Mukeh 863.31 848.29 1050.43 1200.34 1357.50 1582.34 1768.22

2130405 1730061WL Sg. Rajang di Ng Benin 6562.35 6448.19 7984.74 9184.74 9124.27 12027.95 13440.92

2421401 1710011WL Stapang Sarawak 331.61 325.84 403.49 461.07 521.44 607.80 678.20

41

APPENDIX III: MEAN ANNUAL RAINFALL OF PENINSULAR MALAYSIA

42

APPENDIX III: MEAN ANNUAL RAINFALL OF SABAH AND SARAWAK

43

APPENDIX IV: MEAN ANNUAL FLOOD (MAF) REGIONS OF PENINSULAR MALAYSIA

44

APPENDIX IV: MEAN ANNUAL FLOOD (MAF) REGIONS OF SABAH AND SARAWAK

45

APPENDIX V: FLOOD FREQUENCY (FF) REGIONS OF PENINSULAR MALAYSIA

46

APPENDIX V: FLOOD FREQUENCY (FF) REGIONS OF SABAH AND SARAWAK

13

Documents

DISCLAIMER - Waterh2o.water.gov.my/man_hp1/HP4(2018).pdf · Procedure No. 4 (Revised and Updated 2018) are gratefully acknowledged. Special thanks to the Director of Water Resources