Rainfall-Runoff Modelling: Conventional regression and Artificial Neural Networks approach

Transformation of occurred rainfall into runoff generated within a catchment is a complex natural phenomenon that passes through various inter-related processes and influenced by many topographic, geographic, geologic and sociologic factors. To develop a model that can reliably imbibe the complex Rainfall-Runoff interaction, two different approaches namely, conventional regression and Artificial Neural Networks (ANN) have been attempted for Rajsamand Catchment located in the Banas River Basin of Rajasthan. The monthly weighted rainfall of the catchment and inflow received during the monsoon period in the Rajsamand Dam for last twenty years were used for the study. The weighted rainfall and corresponding runoff for the months July, August, September and the monsoon period were considered as inputs and outputs respectively for the model. The performance compared using three different statistical metrics reveal that, the Rainfall-Runoff Model based on ANN approach offer better prediction accuracy than the conventional regression model.