Adaptive flood zoning in Cheshmekile watershed, Tenkabon

Floods are one of the most important natural hazards that often affect millions of people around the world annually with huge impacts. In recent years, due to the occurrence of frequent floods in the watershed of Cheshmekile River and the subsequent damage caused by floods, the need to pay attention to the zoning of the flood risk in the investigated basin is becoming more apparent. Among the different methods for preparing flood zoning maps, statistical methods are more important due to their simplicity and acceptable accuracy. The aim of this research is to compare the reliability of Shannon entropy models, frequency ratio and witness weight in the context of flood zoning in Cheshmekile watershed. In this research, the criteria of slope, elevation classes, soil type, topographic humidity index, distance from the river, geology, land use, watercourse density, NDVI and rainfall have been used. The probability of flood occurrence has been calculated for each class of each parameter. The calculated weights for each class were applied in the ARC GIS software in the relevant layers and flood zoning maps of the area were obtained. The final maps resulting from the implementation of these three models in the region were divided into 3 low risks, medium and high-risk classes. And finally, the reliability of each model was evaluated using the system performance characteristic curve (ROC). The results have shown that frequency ratio (FR), weight of evidence (WOE) and Shannon entropy (SE) techniques have the highest accuracy in predicting the occurrence of floods.