Comparison of statistical and MCDM approaches for flood susceptibility mapping in northern Iran

Abstract

• This study is a comparison assessment between statistical and MCDM approach in FHSM in Mohammad Abad catchment, Iran. • The results show that MCDM model have better prediction accuracy than statistical models. • The results show that slope, distance of rivers and geology are the most influential factors in flood formation, respectively. • Evaluations show that increasing Ground Flood Points will have impact on the results of statistical models. Accurate mapping of flood risk areas is the basis for providing basic information on flood hazard reduction strategies and facilitates the relocation process. This study compared statistical approaches and multi-criteria-decision-making (MCDM) in flood hazard susceptibility mapping (FHSM). The performance of two statistical methods, the Evidential Belief Function (EBF) and Weight of Evidence (WOE), was compared with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) as an MCDM technique. Mohammad-Abad catchment, known as one of the flood susceptible areas in northern Iran, was selected as a case study. A 100-year flood event with a peak flow of 85 m 3 /s, known as the most severe flood in the study catchment during the last 20 years (2000–2020), is considered a basis for selected modelling and evaluation. The accuracy and efficiency of the adopted methods were evaluated using the area under the receiver operating characteristic (AUROC) curve, seed cell surface index, and frequency ratio. Flood inventory maps (including 56 flooded points) and flood-related conditioning factors in the study area were prepared to establish FHSM. Elevation, slope, aspect, plan curvature, topographic wetness index (TWI), stream power index (SPI), distance from the river, drainage density, NDVI, geology, soil type, and land use/land cover were used as flood-related conditional factors. The results of the MCDM method showed that the slope of the catchment is the most important factor in flood formation (with a relative weight of 0.25). By examining the validity of the methods, TOPSIS showed the highest efficiency (AUC = 0.8423), followed by WofE (AUC = 0.7686) and EBF methods (AUC = 0.6251). Based on the frequency ratio and values ​​of seed cell surface index, the MCDM approach shows better performance than statistical methods.