Evaluation of Flood Risk Map Development through GIS-Based Multi-Criteria Decision Analysis in Maran District, Pahang-Malaysia

Many places in Malaysia suffer from annual floods that sometimes affect the environment, properties, and infrastructures. In this contribution, we attempt to provide a flood information system through the development of a flood risk map. The study was conducted in Maran district from 2017 to 2021 wi...

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书目详细资料
发表在:International Journal of Geoinformatics
主要作者: 2-s2.0-85177172670
格式: 文件
语言:English
出版: Association for Geoinformation Technology 2023
在线阅读:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177172670&doi=10.52939%2fijg.v19i9.2873&partnerID=40&md5=408146939ba9e0e967f1a55c9f6962b1
实物特征
总结:Many places in Malaysia suffer from annual floods that sometimes affect the environment, properties, and infrastructures. In this contribution, we attempt to provide a flood information system through the development of a flood risk map. The study was conducted in Maran district from 2017 to 2021 with the available data of Digital Elevation Model (DEM), land use map, topographic map, rainfall intensity, and soil type. The Geographic Information System (GIS) was integrated with the Multi-Criteria Decision Analysis (MCDA) to analyze the potential flood risk area. The distribution of rainfall intensity in the study area is developed using the Inverse Distance Weighted (IDW) interpolation method. The Analytic Hierarchy Process (AHP) is used to determine the weight value of flood hazard criteria. In our study area, there are some natural factors that determine flood risk, such as land use criteria (41.55%), terrain slope (28.95%), rainfall intensity (16.93%), and soil type (12.58%). The value of the consistency ratio is less than 10%, showing that the assessment for each criterion is consistent. It was found that the study area is likely to be at risk of flooding because it has a low slope, has clayey soils, has little vegetation, and is subject to heavy rainfall. © Geoinformatics International.
ISSN:16866576
DOI:10.52939/ijg.v19i9.2873