Spatial prediction of flood-susceptible areas using frequency ratio and maximum entropy models

Abstract

Modelling the flood in watersheds and reducing the damages caused by this natural disaster is one of the primary objectives of watershed management. This study aims to investigate the application of the frequency ratio and maximum entropy models for flood susceptibility mapping in the Madarsoo watershed, Golestan Province, Iran. Based on the maximum entropy and frequency ratio methods as well as analysis of the relationship between the flood events belonging to training group and the factors affecting on the risk of flooding, the weight of classes of each factor was determined in a GIS environment. Finally, prediction map of flooding potential was validated using receiver operating characteristic (ROC) curve method. ROC curve estimated the area under the curve for frequency ratio and the maximum entropy models as 74.3% and 92.6%, respectively, indicating that the maximum entropy model led to better results for evaluating flooding potential in the study area.