<p>The hydro-meteorological observations in the Hindu Kush Himalayan region are hampered by difficult accessibility to the terrain, which in turn has drastically reduced the number of stations for hydro-meteorological observations. This study evaluates bias correction sensitivity of ERA5 Land (ERA5L) on runoff simulation in data scarce Himalayan region of Langtang catchment. The calibration and validation of the Integrated Catchment Hydrological Model (ICHYMOD) against observed data yielded Nash-Sutcliffe Efficiency (NSE) values of 0.72 and 0.84, and Root mean square error (RMSE) values of 2.79 and 2.50 m³/s, respectively. The Water balance analysis yields glacier melt contributions of 13.2% and snowmelt contributions of 29.4%, which is consistent with previous work. Additionally, fractional snow cover area validation using Moderate Resolution Image Spectroradiometer (MODIS) data yielded an NSE of 0.73 and RMSE of 0.05. Performance assessment was carried out by testing four different combinations ERA5L data. Simulations based on uncorrected precipitation and temperature fail to accurately represent catchment flow dynamics which represents the necessity of the bias correction. Results showed that correcting the temperature only led to notable improvement of runoff simulations with NSE = 0.73 and RMSE = 2.89 m³/s, which was slightly better than the results produced by correction of both temperature and precipitation (NSE = 0.7, RMSE = 3.02 m³/s). This suggests that temperature correction for ERA5L is more sensitive to hydrological modeling accuracy in snow-fed Himalayan regions. This study helps the transferability of bias correction factor for ERA5L to other data scarce Himalayan catchments to enhance regional hydrological modeling.</p>