The Spatio-Temporal Impact of Land Use Changes on Runoff in the Yiluo River Basin Based on the SWAT and PLUS Model

As a major tributary of the Yellow River, the Yiluo River holds vital importance for regional water resource management and ecological sustainability. In this study, the SWAT (version 2012) and PLUS models were used in combination to simulate the hydrological responses of the basin and to analyze how land use changes have influenced runoff dynamics over time. During the calibration and validation periods, the Nash–Sutcliffe efficiency coefficient (NS) and coefficient of determination (R2) for the SWAT model both exceeded 0.8, while the Kappa coefficient for the PLUS model indicated an overall accuracy of 0.91, confirming the applicability of both models to the Yiluo River Basin. However, despite strong annual performance, potential monthly or seasonal simulation uncertainties should be acknowledged and warrant further analysis. From 2000 to 2020, the areas of forest land, water, urban land, and unused land in the Yiluo River Basin increased by 795.15 km2, 29.33 km2, 573.67 km2, and 0.25 km2, respectively, while cultivated land and grassland decreased by 814.50 km2 and 583.89 km2. The spatial distribution of the annual average runoff depth generally exhibited a pattern of “higher in the upstream and lower in the downstream”. An increase in the forestland and grassland areas was found to suppress runoff generation, whereas the expansion of urban land promoted runoff production. Implementing water-sensitive land use strategies—such as expanding forest cover and conserving grasslands—is crucial for reducing the negative hydrological impacts of urban land expansion. Such measures can improve runoff regulation, enhance groundwater recharge, and support the sustainable management of water resources within the basin. Assuming climate conditions remain constant, land use in the Yiluo River Basin in 2025 and 2030 is expected to remain dominated by cultivated land and forestland. Under this scenario, the annual average runoff is projected to increase by 0.42% and 0.51% compared to in 2020, respectively.