علی آذره

Floods are among the most frequently occurring natural disasters and the costliest in terms of human life and ecosystem disturbance. Identifying areas susceptible to flooding is important for developing appropriate watershed management policies. As such, the goal of the present study was to develop an integrated framework for flood susceptibility assessment in data-scarce regions, using data from the Haraz watershed in Iran. Flood-influencing indices best suited to the identification of areas particularly prone to flooding were selected. The decision-making trial and evaluation laboratory (DEMATEL) approach was used to investigate the interdependence among criteria and to develop a network structure representative of the problem. The relative importance of different flood-influencing factors was determined using the analytical network process (ANP). A flood susceptibility map was produced using weights obtained through the ANP and fuzzy-value function (FVF) and validated using 72 available flood locations where flooding occurred between 2006 and 2018. After validating the results, fuzzy theory served to better delineate the flood susceptibility scores among the region’s sub-watersheds. Incorporating the DEMATEL-ANP approach with FVF yielded an accuracy of 89.1%, as was assessed through the area under the curve (AUC) of a receiver operating characteristics (ROC) curve. The results indicated that the strongest flood-influencing (occurrence/nonoccurrence) factors were elevation, land use, soil texture, and frequency of heavy rainstorms. The fuzzy theory showed sub-watershed C1 to be highly susceptible to flooding, and thus, most in need of flood management.