i 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.
ii 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.
iii 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).
iv 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
v 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
vi 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
vii 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 풂, 풃, 풄 and 풅 7
Table 4: Results of Goodness-of-Fit Test 10
viii SYMBOLS AND ABBREVIATIONS
Symbols Abbreviations 푎 Coefficient to Catchment Area 퐴 Catchment Area 푏 Coefficient to Mean Annual Rainfall ARI Average Recurrence Interval
퐵4 Bias of L-Kurtosis DID Department of Irrigation and Drainage 푐 Coefficient to Weighted Average Slope FF Flood Frequency 푑 Coefficient to Independent Variables GEV Generalised Extreme Value Distribution
퐷푖 Discordancy Measure GLO Generalised Logistic Distribution H Heterogeneity Measure HP4 Hydrological Procedure No. 4
퐿퐶푉 L-Moment of Variance ID Identity
퐿푠푘푒푤 L-Moment of Skewness Lat Latitude
퐿푘푢푟 L-Moment of Kurtosis Long Longitude 푛 Number of Data Sample LM L-Moments 푁 Number of Catchments in the Region 푀퐴퐹 Mean Annual Flood
Nsim Number of Simulations MAR Mean Annual Rainfall
Q푡 Flood Discharge in t-years ARI MOM Method of Moments 푄(퐹) Flood Quantile Obs Observed Data R2 Coefficient of Determination 푃퐵퐼퐴푆 Percent Bias 푡푅 The Regional Average of L-CV 푅 Mean Annual Rainfall
푢푖 L-Moment Ratios RFFA Regional Flood Frequency Analysis 푢̅ Regional Average of L-Moment Ratios 푆 Weighted Average Slope 푉 Weighted Standard Deviation SF Streamflow
푥푖 Samples of data St Station 푥 Mean of data 푡 Year ARI cal Yi Calculated MAF USGS United States Geological Survey obs Yi Observed MAF YCD Years of Complete Data Y̅ Average of the Observed MAF 푍퐷푖푠푡 L-Moment Goodness-of-Fit Test
휎4 Standard Deviation of L-Kurtosis
ix x 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 ].
1 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 푄푇 /푀퐴퐹 to 푇 where
푄푇 is the peak discharge of 푇-years recurrence interval, 푀퐴퐹 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:
1 푄(퐹) = 푚 − 푛 {1 – (−푙푛 ( 1 – ))−푘} (1) 푇
And the flood quantile formula for GLO is: 푄(퐹) = 푚 + 푛{1 – (푇 – 1)−푘} (2)
Where the parameters of 푚, 푛, and 푘 are shown in Table 1.
2 Table 1: Parameters of Flood Quantiles Formulas
FF Q(F) Parameters Region 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:
(3) 푄푇 = 푄(퐹) 푥 푀퐴퐹
Where:
3 푄푇 : Peak flood discharge for specified ARI (m /s) T : Average Recurrence Interval (years) Q(F) : Flood quantiles or dimensionless growth curves MAF : Mean annual floods (m3/s)
3 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.
4 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):
푀퐴퐹 = 푑 퐴푎 푅푏 푆푐 (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 푀퐴퐹 = Log 푑 + 푎 Log 퐴 + 푏 Log 푅 + 푐 Log 푆 (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:
5 2 ∑n (Yobs−Ycal) 2 i=1 i i R = 1 − 2 (6) n obs ̅ ∑i=1(Yi −Y) Where :
R2 : Coefficient of determination
obs 3 Yi : Observed mean annual floods (m /s)
cal 3 Yi : Calculated mean annual floods (m /s) Y̅ : Average of observed mean annual floods (m3/s)
푛 표푏푠 푐푎푙 ∑푖=1(푌푖 −푌푖 )∗100 푃퐵퐼퐴푆 = [ 푛 표푏푠 ] (7) ∑푖=푛(푌푖 ) Where:
푃퐵퐼퐴푆 : Percent Bias (%)
obs 3 Yi : Observed mean annual floods (m /s)
cal 3 Yi : Calculated mean annual floods (m /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
0.7 < R2 < 1 Very Good
2 Good R2 0.6 < R < 0.7 0.5 < R2 < 0.6 Satisfactory R2 < 0.5 Unsatisfactory
PBIAS < ±10 Very Good Good PBIAS ±10 ≤ PBIAS < 15 ± 15 ≤ PBIAS < ± 25 Satisfactory PBIAS > 25 Unsatisfactory
The criteria above were applied in this study. The regression analysis results were accepted if the values of R2 above 0.6 and |푃퐵퐼퐴푆| lower than ±25%.
6 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 풂, 풃, 풄 and 풅
Parameter Region 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
7 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 (푢푖). The discordancy measure formula is the following:
1 퐷 = 푁(푢 − 푢̅)푇퐴−1(푢 − 푢̅) (8) 푖 3 푖 푖
Where:
퐷푖 : Discordancy measure for a catchment 푖 푁 : Number of catchments in the region
푢푖 : A vector containing LCV, L-skew, and L-kur
푢̅ : Regional average of 푢푖 퐴 is defined as:
푁 푇 (9) 퐴 = ∑(푢푖 − 푢̅)(푢푖 − 푢̅) 푖=1
The site 푖 is considered as discordant if 퐷푖 ≥ 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.
8 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:
(푉−휇 ) 퐻 = 푣 (10) 휎푣
푉 is the weighted standard deviation of the sample LCVs. The formula is the following:
1 2 푁 (푖) 푅 2 ∑푖=1 푛푖(퐿퐶푉 −퐿퐶푉 ) (11) 푉 = { 푁 } ∑푖=1 푛푖}
푅 퐿퐶푉 is the regional average of simulated 퐿퐶푉 in a homogeneous region with the formula as follows:
푁 (푖) 푅 ∑1 푛푖 퐿퐶푉 퐿퐶푉 = 푁 (12) ∑푖=1 푛푖
The mean (휇푣) and standard deviation (휎푣) of the region were obtained from a repeated simulation using a best-fitted kappa distribution.
The region is considered as homogeneous if 퐻 less than 2.
2.3.3 Regional Frequency Distributions
Hosking and Wallis [ 9 ] propose a goodness-of-fit measure based on L-moment ratios (푍퐷푖푠푡). 퐷푖푠푡 The idea was based on the difference between L-kurtosis of the proposed distribution (퐿kur ) 푅 and the regional average (퐿kur) 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:
퐷푖푠푡 푅 (퐿 −퐿 +퐵4) 푍퐷푖푠푡 = 푘푢푟 푘푢푟 (13) 휎4
9 퐵4 is the bias of L-kurtosis which calculated using the following formula:
푁푠푖푚 퐷푖푠푡 푅 ∑푚=1 (퐿푘푢푟 −퐿푘푢푟) 퐵4 = (14) 푁푠푖푚
A repeated simulation using Kappa Distribution was carried out to obtain the simulated standard deviation of L-kurtosis (휎4).
The formula of L-kurtosis (휎4) is as follows: 1 2 −1 푁푠푖푚 퐷푖푠푡 푅 2 2 (15) 휎4 = [(푁푠푖푚 − 1) {∑푚=1(퐿푘푢푟 − 퐿푘푢푟) − 푁푠푖푚퐵4 }]
The best fit distribution is accepted when |푍퐷푖푠푡| 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
Regional Average Region Dist 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.
10 0.3
5 2
0.2 4
7
9 1
kurtosis
- L 6 3 0.1 8 FF Region EXP GUM GEV GLO PE3 LP3 LNO GPA 0.0 0.0 0.1 0.2 0.3 0.4 L-skewness
Figure 1: Regional Average L-Moments of Peninsular Malaysia
0.3
0.2 12
kurtosis 10
- L 11 0.1 13 FF Region EXP GUM GEV GLO PE3 LP3 LNO GPA 0.0 0.0 0.1 0.2 0.3 0.4 L-skewness
Figure 2: Regional Average L-Moments for Sabah and Sarawak
11 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.
12 3.5 FF1
FF2 3.0 FF3
FF4 2.5 FF5
FF6 2.0
FF7 QT/MAF FF8 1.5
1.0
0.5 2 5 10 20 50 100 Recurrance Interval, T (years)
Figure 3: Regional Growth Curves of Peninsular Malaysia
13 2.5
FF9
FF10
FF11 2.0 FF12
1.5 QT/MAF
1.0
0.5 2 5 10 20 50 100
Recurrance Interval, T (years)
Figure 4: Regional Growth Curves of Sabah and Sarawak
14 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 푄푇/푀퐴퐹 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).
15 Step 7 Determine 푄푇 for the various ARIs by multiplying the 푄푇/푀퐴퐹 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 Parameter Region 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
16 Reference Calculation Output Step 6: Calculate the flood quantile Where the parameters of m, n and k are:
Q(F) Parameters Region m n k
3 0.7550 -1.8408 -0.1709
For T = 20 years 1 Equation (1) Q(F) = 0.7550 – (–1.8408) [1 – (– ln (1 − ))0.1709] 20 Q(F) = 1.49
Equation (3) Q20 = Q(F) x MAF
Q20 = 1.49 x 64.33
3 Q20 = 96.48 m /s
For T = 100 years 1 Equation (1) Q(F) = 0.7550 – (–1.8408) [1 – (– ln (1 − ))0.1709] 100 = 1.76
Equation (3) Q100 = Q(F) x MAF = 1.76 x 64.33
3 Q100 = 113.95 m /s
17 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: Reference Calculation Output 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
Parameter Table 3 Region 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
18 Reference Calculation Output Step 6: Calculate the flood quantile Where the parameters of m, n and k are:
Q(F) Parameters Region m n k
9 0.8404 -3.8677 -0.0718
For T = 2 years 1 Equation (1) Q(F) = 0.8404 – (–3.8677) [1 – (– ln (1 − ))0.0718] 2 Q(F) = 0.94
Equation (3) Q2 = Q(F) x MAF
Q2 = 0.94 x 457.57
3 Q2 = 430.51 m /s
For T = 10 years 1 Equation (1) Q(F) = 0.8404 – (–3.8677) [1 – (– ln (1 − ))0.0718] 10 = 1.42
Equation (3) Q10 = Q(F) x MAF = 1.42 x 538.32
3 Q10 = 648.58 m /s
19 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.
100 FF1 FF2 FF3 FF4 FF5 FF6 FF7 FF8 FF9 FF10 FF11 FF12 50
0 PBIAS (% Error) PBIAS (%
-50
-100 2 5 10 20 50 100 Recurrence Interval (years ARI) 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.
20 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.
120 96.56 90
60
30
PBIAS (%) PBIAS
6.88
6.07
3.49 1.74
0
0.10
3.21 -
-30 -
22.18
22.52
23.10
24.22
-
-
-
26.82 - -60 - 2 5 10 20 50 100 Reccurence Interval (ARI)
HP 4 (1987) HP 4 (2018)
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.
21 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 ].
22 • 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.
23
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26 APPENDIX I: CATCHMENT CHARACTERISTICS Number Catchment Specific Weighted MAFObs of MAR Old ID New ID Station Name Area Discharge Slope Latitude Longitude (m3/s) Record (mm) (km2) (m3/s/km2) (m/km) (Year) Sg. Muda di Jam. Syed Omar 5606410 0050301SF 664.24 27 3,330 2231 0.2 1.62 5.60972 100.62639 Kedah 5206432 0090141SF Sg. Kerian di Selama Perak 205.05 19 629 2366 0.3 17.45 5.22917 100.68889 Sg. Muda di Ldg. Victoria Pulau 5505412 0050051SF 611.35 44 4,010 2241 0.2 1.70 5.53194 100.57222 Pinang Sg. Sedim di Merbau Pulas 5506416 0050061SF 115.43 11 440 2294 0.3 18.50 5.56667 100.63889 Pulau Pinang Sg. Arau di Ldg. Tebu FeIda 6503401 0010291SF 23.90 17 21 1981 1.2 6.56 6.50278 100.35139 Perlis 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 Sg. Sungkai di Jln. Ansor- 3911457 0180451WL 60.53 19 479 2450 0.1 15.87 3.98889 101.12500 Kampar Perak 4011451 0180441SF Sg. Bidor di Bt. JIn. Anson Perak 94.23 19 373 2388 0.3 14.48 4.00000 101.13194 Sg. Bidor di Bidor Malayan Tin 4012401 0180861SF 132.13 17 210 2460 0.6 34.60 4.07500 101.24444 Bhd. Perak 4012452 0180431SF Sg. Bidor di Bt. Jln. Anson Perak 76.06 18 339 2436 0.2 25.49 4.02917 101.23333
27 APPENDIX I: CATCHMENT CHARACTERISTICS (Cont.)
Number Catchment Specific Weighted MAFObs of MAR Old ID New ID Station Name Area Discharge Slope Latitude Longitude (m3/s) Record (mm) (km2) (m3/s/km2) (m/km) (Year) Sg. Batang Padang di Tg. 4111455 0180261SF 90.69 31 445 2316 0.2 17.53 4.13472 101.14722 Keramat Perak Sg. Chenderiang di Bt. JIn. 4212467 0180641SF 48.30 23 119 2231 0.4 9.11 4.23194 101.21944 Tapah Perak 4410461 0180111SF Sg. Kinta di Bt. Gajah Perak 258.56 20 1,054 2341 0.2 25.59 4.46806 101.04722 Sg. Pari di JIn. Silibin, Ipoh 4610466 0180131SF 112.55 38 245 2369 0.5 12.20 4.60556 101.06667 Perak 4611463 0180291SF Sg. Kinta di Tg. Rambutan Perak 125.78 31 246 2327 0.5 40.03 4.66944 101.15833 Sg. Kurau di Bt. JIn. Taiping 4907422 0100011SF 26.15 25 80 3431 0.3 35.09 4.97778 100.78056 Perak 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 Sg. Triang di Kg. Chenor Negeri 2920432 0550391SF 63.23 31 228 1890 0.3 21.30 2.94861 102.08889 Sembilan Sg. Triang di Juntai Negeri 3022431 0550381SF 71.90 31 904 1961 0.1 11.24 3.07500 102.21806 Sembilan 2816441 0240341SF Sg. Langat di Dengkil Selangor 299.90 36 1,240 2509 0.2 18.50 2.99278 101.78694
28 APPENDIX I: CATCHMENT CHARACTERISTICS (Cont.)
Number Catchment Specific Weighted MAFObs of MAR Old ID New ID Station Name Area Discharge Slope Latitude Longitude (m3/s) Record (mm) (km2) (m3/s/km2) (m/km) (Year) Sg. Semenyih di Sg. Rinching 2918401 0240511SF 67.30 20 225 2309 0.3 4.48 2.91528 101.82361 Selangor 3118445 0240441SF Sg. Lui di Kg. Lui Selangor 34.03 24 68 2471 0.5 24.34 3.17361 101.87222 Sg. Bernam di Tg. Malim 3615412 0190131SF 126.75 40 186 2710 0.7 45.65 3.68528 101.52333 Selangor Sg. Bernam di Jam. SKC 3813411 0190161SF 218.21 45 1,090 2670 0.2 16.70 3.80750 101.36944 Selangor Sg. Bt. Di Sentul W. P. Kuala 3116434 0230391SF 225.58 20 145 2634 1.6 16.65 3.17639 101.68750 Lumpur Sg. Johor di Rantau Panjang 1737451 0430121SF 258.30 31 1,130 2150 0.2 0.92 1.78056 103.74583 Johor Sg. Sayong di Jam. Johor 1836402 0430271SF 616.16 14 624 2116 1.0 1.00 1.80417 103.66944 Tenggara Johor 1836403 0430321SF Sg. Pengeli di Felda Inas Johor 60.38 11 143 2140 0.4 4.77 1.82083 103.62083 Sg. Kahang di Bt. Jin. Kluang 2235401 0500281SF 382.42 22 587 2197 0.7 5.95 2.25139 103.58750 Johor Sg. Lenggor di Bt. 2237471 0500141SF 180.81 19 207 2377 0.9 6.50 2.25833 103.73611 Kluang/Mersing Johor 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
29 APPENDIX I: CATCHMENT CHARACTERISTICS (Cont.)
Number Catchment Specific Weighted MAFObs of MAR Old ID New ID Station Name Area Discharge Slope Latitude Longitude (m3/s) Record (mm) (km2) (m3/s/km2) (m/km) (Year) Sg. Melaka di Pantai Belimbing 2322413 0290131SF 69.61 42 350 1708 0.2 2.68 2.34306 102.25278 Melaka Sg.Durian Tunggal di Bt. Air 2322415 0290141SF 23.06 15 73 1710 0.3 4.19 2.32361 102.29306 Resam Melaka Sg. Linggi di Sua Betong Negeri 2519421 0270081SF 135.30 32 523 1914 0.3 9.30 2.68111 101.92750 Sembilan Sg. Pedas di Kg. Pilin Negeri 2520423 0270091SF 32.37 27 111 1810 0.3 17.71 2.51667 102.05833 Sembilan Sg. Gemencheh di Gedok 2524416 0320371SF 40.50 27 114 1642 0.4 4.11 2.55139 102.42222 Negeri Sembilan Sg. Gemencheh di JIn. Gemas- 2525415 0320331WL 181.52 26 453 1623 0.4 4.10 2.56556 102.44667 Rompin Negeri Sembilan Sg. Muar di K. Pilah Negeri 2722413 0320341SF 278.43 29 370 1706 0.8 11.82 2.74861 102.24861 Sembilan Sg. Kepis di Jam. Kayu Lama 2723401 0320551SF 43.64 17 21 1654 2.1 6.15 2.70556 102.35556 Negeri Sembilan 3424411 0550941SF Sg. Pahang di Temerloh Pahang 4,275.20 28 19,000 2364 0.2 2.38 3.44444 102.42917 Sg. Bentong di Jam. K. Marong 3519426 0551041SF 136.32 19 241 2495 0.6 44.29 3.51250 101.91528 Pahang Sg. Pahang di Lubok Paku 3527410 0551191SF 3,798.12 19 25,600 2065 0.1 1.53 3.51250 102.75833 Pahang
30 APPENDIX I: CATCHMENT CHARACTERISTICS (Cont.)
Number Catchment Specific Weighted MAFObs of MAR Old ID New ID Station Name Area Discharge Slope Latitude Longitude (m3/s) Record (mm) (km2) (m3/s/km2) (m/km) (Year) Sg. Lepar di Jam. Gelugor 3629403 0551181SF 252.44 21 560 2362 0.5 4.36 3.69722 102.97222 Pahang 4019462 0551021SF Sg. Lipis di Benta Pahang 372.02 27 1,670 2364 0.2 10.38 4.01806 101.96528 Sg. Kelantan di Jam. Guillemard 5721442 0730231SF 8,307.12 28 11,900 2571 0.7 2.22 5.76250 102.15000 Kelantan Sg. Golok di Rantau Panjang 6019411 0740021SF 462.77 34 761 3138 0.6 1.18 6.02297 101.97600 Kelantan Sg. Cherul di Ban Ho 4131453 0600101SF 812.94 25 505 3098 1.6 2.47 4.13333 103.17500 Terengganu Sg. Kemaman di Jam. Air Putih 4232401 0600011SF 608.32 15 381 3201 1.6 6.17 4.27083 103.19861 Terengganu Sg. Kemaman di Rantau 4232452 0600111SF 690.81 19 626 3185 1.1 5.62 4.28056 103.26250 Panjang Terengganu Sg. Tebak di Jam. Tebak 4332401 0600021SF 111.41 12 134 3179 0.8 9.46 4.37778 103.26250 Terengganu Sg. Dungun di Jam. Jerangau 4832441 0630091SF 1,672.98 29 1,480 3691 1.1 2.24 4.84306 103.20417 Terengganu Sg. Berang di Menerong 4930401 0670011SF 401.06 18 140 3964 2.9 29.84 4.93889 103.06250 Terengganu Sg. Terengganu di Kg. Tanggol 5130432 0670061SF 2,706.18 30 3,340 3846 0.8 1.37 5.13750 103.04583 Terengganu
31 APPENDIX I: CATCHMENT CHARACTERISTICS (Cont.)
Number Catchment Specific Weighted MAFObs of MAR Old ID New ID Station Name Area Discharge Slope Latitude Longitude (m3/s) Record (mm) (km2) (m3/s/km2) (m/km) (Year) Sg. Mengalong di Sindumin 4955403 1490031WL 624.72 26 522 3322 1.2 12.18 4.99444 115.57778 Sabah 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 Sg. Kinabatangan di Pagar 5275401 1040091WL 1,601.92 21 9,430 2606 0.2 1.62 5.22639 117.50278 Sabah 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 Sg. Kadamaian di Tamu Darat 6264401 1340021WL 967.01 29 388 3058 2.5 27.61 6.26389 116.45278 Sabah Sg. Bongan di Timbang Bt. 6468402 1280011WL 631.98 13 570 2955 1.1 33.24 6.44778 116.81167 Sabah 6670401 1260011WL Sg. Bengkoka di Kobon Sabah 1,400.71 12 700 2932 2.0 10.87 6.62500 117.04167
32 APPENDIX I: CATCHMENT CHARACTERISTICS (Cont.)
Number Catchment Specific Weighted MAFObs of MAR Old ID New ID Station Name Area Discharge Slope Latitude Longitude (m3/s) Record (mm) (km2) (m3/s/km2) (m/km) (Year) Sg. Sarawak Kanan di Pk. Buan 1301427 1810061WL 269.57 39 215 4059 1.2 5.44 1.39861 110.11278 Bidi 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
33 34 APPENDIX II: ESTIMATED PEAK FLOODS BASED ON HP 4 (2018)
3 MAFCal Peak FloodCal (m /s) in Year ARI Old ID New ID Station Name (m3/s) 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 Sg. Bidor di Bidor Malayan Tin Bhd. 4012401 0180861SF 85.66 74.25 100.33 115.02 127.44 141.41 150.52 Perak 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
35 APPENDIX II: ESTIMATED PEAK FLOODS USING HP 4 (2018) (Cont.)
3 MAFCal Peak FloodCal (m /s) in Year ARI Old ID New ID Station Name (m3/s) 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 Sg. Triang di Kg. Chenor Negeri 2920432 0550391SF 46.22 34.82 54.98 65.71 74.39 83.69 89.45 Sembilan 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 Sg. Sayong di Jam. Johor Tenggara 1836402 0430271SF 143.19 107.86 170.34 203.57 230.47 259.26 277.12 Johor
36 APPENDIX II: ESTIMATED PEAK FLOODS USING HP 4 (2018) (Cont.)
3 MAFCal Peak FloodCal (m /s) in Year ARI Old ID New ID Station Name (m3/s) 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 Sg.Durian Tunggal di Bt. Air Resam 2322415 0290141SF 40.72 35.48 55.31 70.47 87.41 113.89 137.98 Melaka Sg. Linggi di Sua Betong Negeri 2519421 0270081SF 292.11 254.54 396.76 505.54 627.01 817.04 989.82 Sembilan 2520423 0270091SF Sg. Pedas di Kg. Pilin Negeri Sembilan 91.67 79.88 124.51 158.65 196.77 256.40 310.63 Sg. Gemencheh di Gedok Negeri 2524416 0320371SF 50.27 37.87 59.80 71.47 80.91 91.02 97.29 Sembilan Sg. Gemencheh di JIn. Gemas-Rompin 2525415 0320331WL 118.26 89.08 140.68 168.13 190.34 214.12 228.87 Negeri Sembilan 2722413 0320341SF Sg. Muar di K. Pilah Negeri Sembilan 157.37 118.54 187.21 223.73 253.29 284.93 304.56 Sg. Kepis di Jam. Kayu Lama Negeri 2723401 0320551SF 19.74 14.87 23.48 28.06 31.77 35.74 38.20 Sembilan 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
37 APPENDIX II: ESTIMATED PEAK FLOODS USING HP 4 (2018) (Cont.)
3 MAFCal Peak FloodCal (m /s) in Year ARI Old ID New ID Station Name (m3/s) 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 Sg. Kelantan di Jam. Guillemard 5721442 0730231SF 8604.06 8105.02 11221.15 13358.69 15565.35 18732.53 21383.86 Kelantan 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 Sg. Kemaman di Jam. Air Putih 4232401 0600011SF 473.89 438.49 710.36 899.89 1089.18 1345.58 1546.49 Terengganu Sg. Kemaman di Rantau Panjang 4232452 0600111SF 753.38 697.11 1129.31 1430.63 1731.56 2139.17 2458.58 Terengganu 4332401 0600021SF Sg. Tebak di Jam. Tebak Terengganu 188.14 174.09 282.02 357.27 432.42 534.21 613.98 Sg. Dungun di Jam. Jerangau 4832441 0630091SF 1579.04 1487.46 2059.33 2451.62 2856.6 3437.84 3924.42 Terengganu 4930401 0670011SF Sg. Berang di Menerong Terengganu 354.66 334.09 462.54 550.65 641.61 772.16 881.44 Sg. Terengganu di Kg. Tanggol 5130432 0670061SF 3210.43 3024.23 4186.94 4984.52 5807.90 6989.66 7978.95 Terengganu 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
38 APPENDIX II: ESTIMATED PEAK FLOODS USING HP 4 (2018) (Cont.)
3 Peak FloodCal (m /s) in Year ARI MAFCal Old ID New ID Station Name (m3/s) 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
39 APPENDIX II: ESTIMATED PEAK FLOODS USING HP 4 (2018) (Cont.)
3 Peak FloodCal (m /s) MAFCal Old ID New ID Station Name (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
40
APPENDIX III: MEAN ANNUAL RAINFALL OF PENINSULAR MALAYSIA
41
APPENDIX III: MEAN ANNUAL RAINFALL OF SABAH AND SARAWAK 42
APPENDIX IV: MEAN ANNUAL FLOOD (MAF) REGIONS OF PENINSULAR MALAYSIA
43
APPENDIX IV: MEAN ANNUAL FLOOD (MAF) REGIONS OF SABAH AND SARAWAK 44
APPENDIX V: FLOOD FREQUENCY (FF) REGIONS OF PENINSULAR MALAYSIA
45
APPENDIX V: FLOOD FREQUENCY (FF) REGIONS OF SABAH AND SARAWAK 46
13