Sensitivity of Different Satellites Gridded data over Brahmaputra Basin by using Soil and Water Assessment Tool (SWAT)

Abstract:

More than half a billion people of India, China, Nepal, Bangladesh and Bhutan are directly or indirectly dependent on the water resources of the Brahmaputrariver. With climatic and anthropogenic change of this basin region is becoming a cause of concern for future water management and sharing with transboundary riparian nations. To address such issues, robust watershed runoff modeling of the basin is essential. Soil and Water Assessment Tool (SWAT) is a widely used semi-distributed watershed model that is capable of analyzing surface runoff, stream flow, water yield,sediment and nutrienttransport in a large river basin such as Brahmaputra, but the performance of runoff the model depends on the accuracy of input precipitation datasets. But for a transboundary basin like Brahmaputra, precipitation gauge data from upstream areas is either not available or not accessible to the scientific communities.Satellite rainfall products are very effective where radar datasets are absent and conventional rain gauges are sparse. However, the sensitivity of the SWAT model to different satellite data products as well as hydrologic parameters for the Brahmaputra Basin are largely unknown. Thus in this study, a comparative analysis with different satellite data product has been made to assess the runoff using SWAT model. Here, data from three sources: TRMM, APHRDOTIE and GPCP were used as input precipitation satellite data set and ERA-Interim was used as input temperature dataset from 1998 to 2009. The main methods used in modeling the hydrologic processes in SWAT were curve number method for runoff estimating, Penman-Monteith method for PET and Muskingum method for channel routing. Our preliminary results have revealed thatthe TRMM data product is more accurate than APHRODITE and GPCP for runoff analysis. The coefficient of determination (R²) and Nash-Sutcliffe efficiencies for both calibration and validation period from TRMM data are 0.83 and 0.72, respectively.