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• W4384828152 abstract "SWAT+ is a revised version of the SWAT model that has the capability to route flow across landscape units in the catchment, which is expected to improve the spatial representation of processes in watersheds. We applied the SWAT+ model in the Uruguay River Basin, an international river basin in South America with a total surface area of 370,000 km2, in order to (1) assess the water balance components, (2) represent their spatial distribution, and (3) examine their changes over time. The catchment was divided into uplands and floodplains and a decision table rule was developed based on streamflow data. The SPOTPY Python library was linked to SWAT+ and used as a tool to perform sensitivity analyses and calibration. The model represented the fluctuations of discharge well, although there was a general tendency to underestimate peak flows. Blue (precipitation and runoff) and green (evapotranspiration and soil water content) hydrological components were spatially plotted. Overall, SWAT+ simulated a realistic spatial distribution of the water cycle components. A seasonal Mann–Kendall test suggests a positive increasing trend in the average temperature (p-value = 0.007; Sen’s slope = 0.09), the soil water content (p-value = 0.02; Sen’s slope = 1.29), and evapotranspiration (p-value: 0.03; Sen’s slope = 1.97), indicating that the ecosystem experienced a changing climate during the simulation period. The findings presented in this study are of significant value for the impacts of sustainable management and the evaluation of climate change on water resources in the Uruguay River Basin." @default.
• W4384828152 created "2023-07-21" @default.
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• W4384828152 date "2023-07-18" @default.
• W4384828152 modified "2023-10-14" @default.
• W4384828152 title "Representation of Hydrological Components under a Changing Climate—A Case Study of the Uruguay River Basin Using the New Version of the Soil and Water Assessment Tool Model (SWAT+)" @default.
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• W4384828152 doi "https://doi.org/10.3390/w15142604" @default.
• W4384828152 hasPublicationYear "2023" @default.
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