In the past century, water demand increased extensively due to the rapid growth of the human population. Ground observations can reveal hydrological dynamics but are expensive in the long term. Alternatively, hydrological models could be utilized for assessing streamflow with historical observations as the control point. Despite the advancements in hydrological modeling systems, watershed modeling over mountainous regions with complex terrain remains challenging. This study utilized the multi-physical Weather Research and Forecasting Hydrological enhancement model (WRF-Hydro), fully distributed over the Amu River Basin (ARB) in Afghanistan. The calibration process focused on land surface model (LSM) physics options and hydrological parameters within the model. The findings emphasize the importance of LSM for accurate simulation of snowmelt–runoff processes over mountainous regions. Correlation coefficient (R), coefficient of determination (R2), Nash-Sutcliff efficiency (NSE), and Kling-Gupta efficiency (KGE) were adopted for accuracy assessment over five discharge observation stations at a daily time scale; overall performance results were as follows: R was 0.85–0.42, R2 was 0.73–0.17, NSE was 0.52 to −8.64, and KGE was 0.74 to −0.56. The findings of the current study can support snowmelt process simulation within the WRF-Hydro model.
Citation: Wahidullah Hussainzada, Han Soo Lee. Impact of land surface model schemes in snow-dominated arid and semiarid watersheds using the WRF-hydro modeling systems[J]. AIMS Geosciences, 2024, 10(2): 312-332. doi: 10.3934/geosci.2024018
In the past century, water demand increased extensively due to the rapid growth of the human population. Ground observations can reveal hydrological dynamics but are expensive in the long term. Alternatively, hydrological models could be utilized for assessing streamflow with historical observations as the control point. Despite the advancements in hydrological modeling systems, watershed modeling over mountainous regions with complex terrain remains challenging. This study utilized the multi-physical Weather Research and Forecasting Hydrological enhancement model (WRF-Hydro), fully distributed over the Amu River Basin (ARB) in Afghanistan. The calibration process focused on land surface model (LSM) physics options and hydrological parameters within the model. The findings emphasize the importance of LSM for accurate simulation of snowmelt–runoff processes over mountainous regions. Correlation coefficient (R), coefficient of determination (R2), Nash-Sutcliff efficiency (NSE), and Kling-Gupta efficiency (KGE) were adopted for accuracy assessment over five discharge observation stations at a daily time scale; overall performance results were as follows: R was 0.85–0.42, R2 was 0.73–0.17, NSE was 0.52 to −8.64, and KGE was 0.74 to −0.56. The findings of the current study can support snowmelt process simulation within the WRF-Hydro model.
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Wahidullah Hussainzada, Han Soo Lee. Impact of land surface model schemes in snow-dominated arid and semiarid watersheds using the WRF-hydro modeling systems[J]. AIMS Geosciences, 2024, 10(2): 312-332. doi: 10.3934/geosci.2024018
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