Estimation of Runoff Under Changed Climatic Scenario of a Meso Scale River by Neural Network Based Gridded Model Approach

Abstract

Climate change is linked with change in precipitation, evapotranspiration, and other climatological parameters, and therefore the runoff of a river basin will be affected. The Gomati River basin is the largest in Tripura. The increased settlement in the Gomati River basin and climate change may threaten the natural flow patterns that enable its diversity. This study assesses the impact of climate change on total flow from a catchment in northeast India (the Gomati River catchment). For this assessment, the Group Method of Data Handling (GMDH) model was used to simulate the rainfall–runoff relationship in the catchment with respect to the observed data during 2008–2009. The statistically downscaled outputs of the Hadley Centre Global Environment Model version 2 (HadGEM2-ES) general circulation model scenario was used to assess the impacts of climate change on the Gomati River basin. Future projections were developed for the 2030s, 2040s, and 2050s. The results of this study may contribute to the development of adaptive strategies and future policies for the sustainable management of water resources in northeast Tripura.