Regional Statistical Models for the Estimation of Flood Peak Values at Ungauged Catchments: Peninsular Malaysia

Regional Statistical Models for the Estimation of Flood Peak Values at Ungauged Catchments: Peninsular Malaysia

Multivariate regional statistical models were developed to estimate flood peak values of various return periods in the Peninsular Malaysia. Annual maximum flood peak data was collected, screened and analysed to identify the river gauging stations potential to produce identical flood frequency curves...

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Main Authors: Al-Mamun, Abdullah, Hashim, Alias, Amir, Zalin
Format: Article
Language:English
Published: American Society of Civil Engineers 2012
Subjects:
TA170 Environmental engineering
Online Access:http://irep.iium.edu.my/6272/
http://irep.iium.edu.my/6272/
http://irep.iium.edu.my/6272/
http://irep.iium.edu.my/6272/1/Regional_statistical_model_PM_%282%29.pdf
id iium-6272
recordtype eprints
spelling iium-62722013-03-06T00:02:45Z http://irep.iium.edu.my/6272/ Regional Statistical Models for the Estimation of Flood Peak Values at Ungauged Catchments: Peninsular Malaysia Al-Mamun, Abdullah Hashim, Alias Amir, Zalin TA170 Environmental engineering Multivariate regional statistical models were developed to estimate flood peak values of various return periods in the Peninsular Malaysia. Annual maximum flood peak data was collected, screened and analysed to identify the river gauging stations potential to produce identical flood frequency curves. The Peninsula was divided into ten (10) flood regions. The mean annual flood (MAF) for each region was considered as the function of catchment area (A) and mean annual rainfall (MAR). The regional equations exhibited good coefficient of determination (R2). Except for the west of Johor Baru State (Region F6) which showed R2 value of 0.874, other regions had values higher than 0.90. The regions located along the east coast of the Peninsula exhibited better coefficients of determination compared to those for the west coast, due to the influence of the north‐east monsoon along the east coast. Mean index errors (MIE) with respect to the actual MAF of each flood region are provided for the users to rationalise the design flood peak values to minimise the uncertainty in the predictions. Flood frequency values for the lower, mean and upper limits were proposed to reduce the effect of outliers and uncertainty in prediction of flood peak values. Knowing the catchment area and MAR of the regions, the design flood peaks of various frequencies can be estimated by the users for the rural ungauged catchments in the Peninsula. American Society of Civil Engineers 2012-04 Article PeerReviewed application/pdf en http://irep.iium.edu.my/6272/1/Regional_statistical_model_PM_%282%29.pdf Al-Mamun, Abdullah and Hashim, Alias and Amir, Zalin (2012) Regional Statistical Models for the Estimation of Flood Peak Values at Ungauged Catchments: Peninsular Malaysia. Journal of Hydrologic Engineering, 17 (4). ISSN 1084-0699 (P) ; 1943-5584 (O) (In Press) http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29HE.1943-5584.0000464 doi:10.1061/(ASCE)HE.1943-5584.0000464
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic TA170 Environmental engineering
spellingShingle TA170 Environmental engineering
Al-Mamun, Abdullah
Hashim, Alias
Amir, Zalin
Regional Statistical Models for the Estimation of Flood Peak Values at Ungauged Catchments: Peninsular Malaysia
description Multivariate regional statistical models were developed to estimate flood peak values of various return periods in the Peninsular Malaysia. Annual maximum flood peak data was collected, screened and analysed to identify the river gauging stations potential to produce identical flood frequency curves. The Peninsula was divided into ten (10) flood regions. The mean annual flood (MAF) for each region was considered as the function of catchment area (A) and mean annual rainfall (MAR). The regional equations exhibited good coefficient of determination (R2). Except for the west of Johor Baru State (Region F6) which showed R2 value of 0.874, other regions had values higher than 0.90. The regions located along the east coast of the Peninsula exhibited better coefficients of determination compared to those for the west coast, due to the influence of the north‐east monsoon along the east coast. Mean index errors (MIE) with respect to the actual MAF of each flood region are provided for the users to rationalise the design flood peak values to minimise the uncertainty in the predictions. Flood frequency values for the lower, mean and upper limits were proposed to reduce the effect of outliers and uncertainty in prediction of flood peak values. Knowing the catchment area and MAR of the regions, the design flood peaks of various frequencies can be estimated by the users for the rural ungauged catchments in the Peninsula.
format Article
author Al-Mamun, Abdullah
Hashim, Alias
Amir, Zalin
author_facet Al-Mamun, Abdullah
Hashim, Alias
Amir, Zalin
author_sort Al-Mamun, Abdullah
title Regional Statistical Models for the Estimation of Flood Peak Values at Ungauged Catchments: Peninsular Malaysia
title_short Regional Statistical Models for the Estimation of Flood Peak Values at Ungauged Catchments: Peninsular Malaysia
title_full Regional Statistical Models for the Estimation of Flood Peak Values at Ungauged Catchments: Peninsular Malaysia
title_fullStr Regional Statistical Models for the Estimation of Flood Peak Values at Ungauged Catchments: Peninsular Malaysia
title_full_unstemmed Regional Statistical Models for the Estimation of Flood Peak Values at Ungauged Catchments: Peninsular Malaysia
title_sort regional statistical models for the estimation of flood peak values at ungauged catchments: peninsular malaysia
publisher American Society of Civil Engineers
publishDate 2012
url http://irep.iium.edu.my/6272/
http://irep.iium.edu.my/6272/
http://irep.iium.edu.my/6272/
http://irep.iium.edu.my/6272/1/Regional_statistical_model_PM_%282%29.pdf
first_indexed 2023-09-18T20:15:09Z
last_indexed 2023-09-18T20:15:09Z
_version_ 1777407738044743680

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