Methods Used in Flood Susceptibility Mapping

Abstract

In recent years, flood susceptibility mapping has an important place among the studies carried out to take precautions against floods and mitigate the damages and possible negative effects caused by floods. In this context, flood susceptibility analysis, especially on a regional scale, has been the subject of research by many researchers. In this study, the methods used in flood susceptibility mapping were investigated. 155 studies on flood susceptibility published between 2014 and 2022 were evaluated. In general, the methods used in the determination and evaluation of flood susceptibility are multi-criteria decision making (MCDM) methods, physically based hydrological models, statistical methods and various soft computing methods. Although the use rate of traditional statistical methods and multi-criteria decision making methods is already high among researchers, the methods used in flood susceptibility analysis have evolved over the years from traditional human judgments to statistical methods based on big data and machine learning methods. In the reviewed studies, it has been observed that machine learning, fuzzy logic, metaheuristic optimization algorithms and heuristic search algorithms, which are soft computing methods, have been widely used in the flood susceptibility mapping in recent years.