Applicability analysis of hydrological models for different types of watersheds in the eastern section of the agro-pastoral transitional zone in northern China
Received date: 2024-10-31
Revised date: 2024-11-27
Online published: 2025-06-11
Water resources form the foundation for maintaining ecosystem balance and ensuring human life and economic development. Simulating hydrological processes in arid and semi-arid ecosystems promotes the effective utilization of local water resources. This paper analyzed the applicability of two models—the Distributed Hydrology Soil Vegetation Model (DHSVM) and the Soil and Water Assessment Tool (SWAT)—in different types of watersheds in semi-arid regions by performing: Sensitivity analysis and parameter calibration. simulation of monthly runoff for the upper reaches of the Xar Moron River and the Laoha River during the growing seasons of 2011-2012 and 2017-2019. The upper reaches of the Xar Moron River are dominated by grasslands, while those of the Laoha River are dominated by forestland and farmland. The results show that DHSVM exhibits 7 primary sensitive parameters in the Xar Moron River and 6 in the Laoha River, whereas SWAT identifies 11 and 12 sensitive parameters, respectively. Following parameter calibration, in the upper reaches of the Xar Moron River the Nash-Sutcliffe efficiency coefficient for DHSVM is 0.70 during calibration and 0.11 during validation, while for SWAT it is 0.43 and 0.04, respectively. In the upper reaches of the Laoha River, the Nash-Sutcliffe efficiency coefficients for DHSVM are 0.56 and 0.70 during the two periods, compared with 0.86 and 0.54 for SWAT. The findings indicate that both models are applicable for simulating hydrological processes in the study area, with DHSVM more accurately simulating overall runoff and SWAT more accurately simulating peak monthly runoff.
ZHANG Yajing , HAO Ruifang . Applicability analysis of hydrological models for different types of watersheds in the eastern section of the agro-pastoral transitional zone in northern China[J]. Arid Zone Research, 2025 , 42(6) : 1021 -1031 . DOI: 10.13866/j.azr.2025.06.06
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