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Ecohydrological response to multi-model land use change at watershed scale

Wenxian Guo, Long Yu, Lintong Huang, Ning He, Wenxiong Chen, Fengtian Hong, Bing Wang, Hongxiang Wang

2023Journal of Hydrology Regional Studies17 citationsDOIOpen Access PDF

Abstract

The Min River basin, China. In order to investigate the ecohydrological response under historical and future land use changes, we simulated daily runoff sequences under different land use scenarios by coupling the PLUS model with the Physical Hydrological Model and quantitatively assessed the ecohydrological impacts of different land use changes in the watershed by combining the IHA method. The Min River Basin is dominated by grassland, woodland and, cultivated land which account for 94 % of the total. During the period 2000–2020, the area of cultivated land decreased by 4.47 % overall, and construction land increased by 78.68 % overall. Compared to the base year of 2010, the multi-year average monthly runoff increased under different land use scenarios. The high flow indicators (1 daymax, 7 daymax, and 30 daymax) had the largest increasing trend under the natural development scenario in 2030, 54 m3/s, 33 m3/s, and 24 m3/s, respectively, whereas their increase decreased under the ecological protection scenario in 2030; the low flow indicators (1 daymin, 7 daymin, and 30 daymin) decreased less in the 2030 eco-protection scenario than in the natural development scenario, where they decreased by − 5 m3/s, − 9 m3/s, and − 11 m3/s, respectively. The results of the study contribute to a deeper understanding of the response of watershed hydrological processes to land-use change.

Topics & Concepts

Environmental scienceWatershedSurface runoffLand use, land-use change and forestryLand useWoodlandHydrology (agriculture)EcohydrologyGrasslandLand managementDrainage basinWater resource managementGeographyEcosystemEcologyGeologyBiologyMachine learningGeotechnical engineeringCartographyComputer scienceHydrology and Watershed Management StudiesFlood Risk Assessment and ManagementHydrological Forecasting Using AI
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