Flood Hydrograph Estimation based on Various Components of Rainfall Using Adaptive Neuro-Fuzzy Inference System in Kasilian Watershed

Flood hydrographs preparation and estimation are considered a comprehensive information for managers and planners. While, it is not simply possible preparing it for all watersheds. Therfore, suitable flood hydrograph estimation and modeling seems to be necessary using available rainfall data. The study area is located in Kasilian representative watershed in Mazandaran province comprising 66.75km2 in area. For the accomplished present study, 15 characteristics of hyetograph as independent variables and 8 characteristics of hydrograph as dependent variables were considered for 60 storms from 1975 to 2009. For estimation flood hydrograph, aadaptive neuro-fuzzy inference system with two methods i.e., grid partitioning and subtractive clustering was used. Variance inflation factor (VIF) was used to select the input variables. The ANFIS results showed that subtractive clustering was found to be superior to grid partitioning.