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Research Article | Open Access

Impact of land surface model schemes in snow-dominated arid and semiarid watersheds using the WRF-hydro modeling systems

Wahidullah Hussainzada1Han Soo Lee1,2,3( )
Transdisciplinary Science and Engineering Program, Graduate School of Advanced Science and Engineering, Hiroshima University, Japan
Center for the Planetary Health and Innovation Science (PHIS), The IDEC Institute, Hiroshima University, Japan
Graduate School of Innovation and Practice for Smart Society, Hiroshima University, Japan
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Abstract

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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AIMS Geosciences
Pages 312-332

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Cite this article:
Hussainzada W, Lee HS. Impact of land surface model schemes in snow-dominated arid and semiarid watersheds using the WRF-hydro modeling systems. AIMS Geosciences, 2024, 10(2): 312-332. https://doi.org/10.3934/geosci.2024018

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Received: 28 February 2024
Revised: 29 April 2024
Accepted: 06 May 2024
Published: 13 May 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)