Suspended Sediment Simulation Using ANN Based MLP and MLR Technique for Narmada River in Hoshangabad Station M.P

Rainfall runoff sediment modelling is good one of the most important topics in water resources planning development and management on sustainable basis. The Multilayer Perceptron MLP and Multiple linear regression MLR . This study was undertaken to develop and evaluate the applicability of the MLP and MLR models by way of training and testing of developed models during monsoon period June to September for Narmada River in Hoshngabad station. Daily data of rainfall-runoff and suspended sediment were used in the study for monsoon season. The daily data were splite into two set a training data set 2006 to 2010 and testing data in 2011 to 2012 for Narmada River. The Neurosolution 5.0 software and Microsoft excel were used in analysis and the performance evaluation indices for developed models. respectively .The best input combination of rainfall, runoff and suspended sediment were identify using the input output combination for simulation of suspended sediment. 10 best models for sediment were selected out of 31 models. The predicted suspended sediment using MLP and MLR models were found to be the performing models for Narmada River but MLP model the predicted suspended sediment best performing models for Narmada River. It was clearly evident MLR models fit very poorly for the dataset under study. The current day’s suspended sediment can be simulated using the data of rainfall and runoff of previous one day MLP-5.