Hydrologic model forcing over the Himalaya

Abstract

In the Himalayas –the mountain range in Asia, there is a high demand for hydro-meteorological datasets for the water resource management. Hydro-meteorological observations is minimal because of the adverse geographical conditions and this represent a problem. Remote sensing and climate models offer a global perspective on many atmospheric climatic variables. However, low spatial resolution and inability to measure some atmospheric properties, such as Aerosol Optical Depth (AOD) over the brighter surface limits their ability to reflect the effects on hydrologic systems. During this PhD study, the candidate and team developed an empirical based model to estimate the AOD for the region. The model helps to understand aerosol and its impacts on the Himalayan hydrology. Similarly, we evaluated a regional climate model and reanalysed datasets for hydrological simulations. We fond the highest-fidelity of discharge simulation when using observation combined Watch Forcing Dataset ERA Interim (WFDEI) datasets. Our results show the successful application of global forcing datasets over the Himalayas. Finally, we demonstrated that catchment discretization has a significant impact on hydrologic simulation results. Triangular Irregular Network (TIN) based catchment discretization gives the highest model performance. Hence the selection of models with an appropriate complexity and accurate forcing data are the most required to achieve reliable hydrologic simulation over the entire Himalayan region