Application of hydrological model to simulate streamflow contribution on water balance in Himalaya river basin, Nepal

Abstract

Hydrological models are widely used and often regarded as reliable tools for accurately estimating various components of the water balance. In a remote Himalayan catchment, such as Tamakoshi basin, where limited hydrometric dataset is available, such models often provide essential insights that are crucial to water researchers and planners. In this regard, we employed the semi-distributed HBV-light (version 4.0.0.25) hydrological model for glacierized Tamakoshi river basin and attempted to quantify various water balance components. For our model tests, using the daily streamflow records, we selected two distinct periods, i.e., 2004–2008 as a calibration period whilst 2011–2012 for model validation. Based on our findings, the model was able to reasonably predict the streamflow (validation efficiency: Nash-Sutcliffe Efficiency of 0.82 and percent bias −21%). At our site, HBV-light model predicted that the change in streamflow was mostly governed by monsoonal rain (62%) followed by baseflow (20%), glacier melt (13%) and snowmelt (5%). As expected, the streamflow peaked during the month of August where monsoon-induced rain and melting of glaciers significantly contributed to river flow. As a result, monsoon period showcased largest fluctuation in water storage while negligible change was observed during post-monsoon season. Nonetheless, our findings revealed that the baseflow contribution to streamflow was maximum during the month of October and lowest during February. Our findings indicated that the water balance of the Tamakoshi basin is largely influenced by monsoonal rain during June–September window as well as baseflow and glacier melt during the dry season. Runoff components contribution to streamflow was increasing but water storage changes was decreasing in recent decade (2011–2020). We believe our findings are crucial for future initiatives involving water resources, water-induced disaster management, and studies of climate change may benefit from the findings of this study, especially in a region with limited hydrometric data availability.