Quantitative and semi-quantitative methods in flood hazard/susceptibility mapping: a review

被引:24
|
作者
Mudashiru R.B. [1 ,2 ]
Sabtu N. [1 ]
Abustan I. [1 ]
机构
[1] School of Civil Engineering, Universiti Sains Malaysia, Engineering Campus, Nibong Tebal, 14300, Pulau Pinang
[2] Department of Civil Engineering, Federal Polytechnic Offa, Offa
关键词
Climate disaster risk reduction; Flood hazard mapping; Flood susceptibility mapping; Machine learning; Multi-criteria decision-making; Statistical method;
D O I
10.1007/s12517-021-07263-4
中图分类号
学科分类号
摘要
Flood mitigation and risk management is a very challenging task that requires accurate identification of flood hazard/susceptible regions for adequate planning and management. Accurate determination of locations that are prone to flood hazards needs the application and adaptation of techniques that will provide flood hazard/susceptibility maps with minimal uncertainty. Previous literature reviews on flood hazard analysis have focused on the flood hazard mapping methods such as hydrodynamic, conceptual, and multi-criteria decision-making (MCDM). Thus, this current study thoroughly reviews studies that applied MCDM, statistical, and machine learning (ML) methods in the identification of flood hazard/susceptible regions. The paper presents information about these methods, their integration in flood studies, strengths, limitations, uncertainty, and recent developments. Conclusively, the paper provided observations and recommendations to enhance the existing information for relevant knowledge in future studies. This will assist stakeholders and key policymakers in making good decisions for flood analysis for a sustainable climate disaster risk reduction management. © 2021, Saudi Society for Geosciences.
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