Modelling of Water Resources in the Brahmaputra River Basin

Abstract

In some parts of the world, network density of local hydro-meteorological station data is lacking. A solution to this is to use satellite or reanalysis data. In the present study, different interpolation techniques are applied to estimate precipitation and temperature using local observed data and compared with global reanalysis WFDEI forcing data in the Brahmaputra River Basin. The different forcing datasets were used to drive the global-scale hydrological PCR-GLOBWB model to estimate discharge on a roughly 10×10 km spatial and daily temporal resolution. Discharge model results were compared with observed records from the Bahadurabad gauging station. Results show that the interpolated in-situ temperature forcing data is generally warmer than the WFDEI forcing dataset. The interpolated in-situ precipitation forcing data consists of generally higher quantities than the WFDEI forcing dataset, especially during the monsoon period. Discharge is underestimated considerably using the WFDEI forcing dataset. Using the interpolated in-situ forcing data, the model overestimates the discharge slightly. Several dataset combinations and data modifications were applied. The run with interpolated in-situ precipitation forcing data in the upper part of the basin and WFDEI precipitation forcing data applied in the lower part of the basin, while using the interpolated local temperature forcing data, produced the best result. This study concludes that the WFDEI forcing dataset is useful and can provide reasonable estimates in combination with local hydro-meteorological information.