A comparative assessment of multi-criteria decision analysis for flood susceptibility modelling

Abstract

The purpose of this study is to develop a reliable model for identification of flood susceptible areas. Three multi-criteria decision-making techniques, namely Analytical Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Attributive Border Approximation Area Comparison (MABAC) methods combined with weight of evidence (WOE) were used in Babolroud Watershed, Iran. First, 50 flood locations were identified, of which 35 (70%) locations were selected randomly for modelling, and 15 (30%) locations were used for validation. Using GIS with eight conditioning factors including rainfall, distance from rivers, slope, soil, geology, elevation, drainage density and land use, the flood susceptibility maps were prepared. Area under receiver operating characteristic curve (AUROC) for test data of AHP-WOE, TOPSIS-WOE-AHP and MABAC-WOE-AHP methods were 72.8%, 90.5% and 81.6%, respectively, which indicate the reasonable accuracy of models. High accuracy of the proposed new model (MABAC) clarifies its applicability for preventive measures.