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

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.