Nowadays, a risk-based flood mitigation concept has received more attention rather than the conventional flood control approach in reducing the impacts of flooding. With the intention to assist in the management of flood risk, flood modeling is useful in providing information on the flood extent and flood characteristics. This paper presents the application of HEC-RAS model to the development of floodplain maps for an urban area in Segamat town in Malaysia. The analysis used Interferometric Synthetic Aperture Radar (IFSAR) as the main modeling input data. Five distribution models, namely Generalized Pareto, Generalized Extreme Value, Log-Pearson 3, Log-Normal (3P) and Weibull (3P) were tested in flood frequency analysis to calculate extreme flows with different return periods. Using Kolmogorov-Smirnov (KS) test, the Generalized Pareto was found to be the best distribution for the Segamat River. The peak floods from frequency analysis for selected return periods were input into the HEC-RAS model to find the expected corresponding flood levels. Results obtained from HEC-RAS model were used in ArcGIS to prepare floodplain maps for different return periods. The results indicated that most of the inundated areas in the simulated 100 year return period were also affected by 2011 historical floods. For 100 years flood simulation, the inundated area was almost 5 times larger than the simulated 10 years' flood.
In recent years, flood risk map has been widely accepted as a tool for flood mitigation. The risk of flooding is normally illustrated in terms of its hazard (flood inundation maps), while vulnerability emphasizes the consequences of flooding. In developing countries, literatures on flood vulnerability assessment are limited, especially on flood damage. This paper attempts to establish a flood damage and risk assessment framework for Segamat town in Johor, Malaysia. A combination of flood hazard (flood characteristics), exposure (value of exposed elements), and vulnerability (flood damage function curve) were used for estimating the flood damage. The flood depth and areal extent were obtained from flood modeling and mapping using HEC-HMS/RAS and Arc GIS, respectively. Expected annual damage (EAD) for residential areas (50,112 units) and commercial areas (9,318 premises) were RM12.59 million and RM2.96 million, respectively. The flood hazard map shows that Bandar Seberang area (46,184 properties) was the most affected by the 2011 flood. The flood damage map illustrates similar patterns, with Bandar Seberang suffering the highest damage. The damage distribution maps are useful for reducing future flood damage by identifying properties with high flood risk.
Flood damage assessment is important in flood risk management for the assessment of flood vulnerability, development of flood risk map and flood management financial appraisal. In Malaysia, there is a lack of studies on flood damages estimation. In addition, the needed data for the assessment of flood damages is scarce. This review identified the approaches and problems in flood damage assessment. For Malaysia, the combination of four elements namely; flood characteristics (flood depth and flood duration), characteristic of exposed elements, value of exposed element and flood damage function curve are recommended. The scarcity of data for developing flood damage curve could partly be overcome by applying synthetic method to generate additional data from the existing flood damage data.
Nowadays, a risk-based flood mitigation concept has received more attention rather than the conventional flood control approach in reducing the impacts of flooding. With the intention to assist in the management of flood risk, flood modeling is useful in providing information on the flood extent and flood characteristics. This paper presents the application of HEC-RAS model to the development of floodplain maps for an urban area in Segamat town in Malaysia. The analysis used Interferometric Synthetic Aperture Radar (IFSAR) as the main modeling input data. Five distribution models, namely Generalized Pareto, Generalized Extreme Value, Log-Pearson 3, Log-Normal (3P) and Weibull (3P) were tested in flood frequency analysis to calculate extreme flows with different return periods. Using Kolmogorov-Smirnov (KS) test, the Generalized Pareto was found to be the best distribution for the Segamat River. The peak floods from frequency analysis for selected return periods were input into the HEC-RAS model to find the expected corresponding flood levels. Results obtained from HEC-RAS model were used in ArcGIS to prepare floodplain maps for different return periods. The results indicated that most of the inundated areas in the simulated 100 year return period were also affected by 2011 historical floods. For 100 years flood simulation, the inundated area was almost 5 times larger than the simulated 10 years' flood.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.