Open Access
Open access
AIMS Geosciences, volume 10, issue 2, pages 312-332

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

Wahidullah Hussainzada 1
Han Soo Lee 1, 2, 3
2
 
Center for the Planetary Health and Innovation Science (PHIS), The IDEC Institute, Hiroshima University, Japan
3
 
Graduate School of Innovation and Practice for Smart Society, Hiroshima University, Japan
Publication typeJournal Article
Publication date2024-05-13
Journal: AIMS Geosciences
SJR
CiteScore
Impact factor0.9
ISSN24712132
Abstract
<abstract> <p>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 (R<sup>2</sup>), 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, R<sup>2</sup> 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.</p> </abstract>
Found 

Top-30

Journals

1
1

Publishers

1
1
  • We do not take into account publications without a DOI.
  • Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
  • Statistics recalculated weekly.

Are you a researcher?

Create a profile to get free access to personal recommendations for colleagues and new articles.
Share
Cite this
GOST | RIS | BibTex | MLA
Found error?