In regions with arid and semi-arid climates, water consumption for agricultural irrigation is much higher than that used for urban and industrial purposes. Intensive irrigation plays a vital role in influencing the interaction between groundwater and surface water. Understanding the impact of irrigation on the local hydrological cycle is of great significance for maintaining regional food production and -security. In order to study the impact of irrigation on the regional hydrological cycle, the present study employed the SWAT-MODFLOW coupled model to analyze the Weigan River Basin from 2002 to 2016. In the modeling process, detailed agricultural management measures were considered, including the zoning of crop types, amount of irrigation water for different crops, irrigation methods, and different sources of irrigation water. Before coupling, each model was set, calibrated, and validated separately. After coupling, the irrigation pumps and drainage units were mapped with the SWAT automatic irrigation and subbasins. Calibration and validation studies showed that the SWAT-MODFLOW coupled model could simulate the river flow and groundwater levels in the Weigan River Basin well. The model simulation results showed that the sources of water in the soil included groundwater irrigation (1147.5 mm) and surface water irrigation (68.4 mm), as well as precipitation and snowmelt recharge (97.62 mm). The groundwater balance was influenced by the river leakage (75.6 mm), lateral inflow from surrounding areas (3.6 mm), unsaturated zone infiltration (197.7 mm), and irrigation pumping (1275 mm). When compared with the scenario without irrigation, the surface runoff, groundwater infiltration, soil moisture content, and evapotranspiration increased by 7.9%, 3.2%, 4.1%, and 2.3%, respectively. Irrigation activities increased the soil moisture content and permeability, resulting in more groundwater recharge and evaporation, as well as a higher surface runoff. This model provides guidance for evaluating drought irrigation systems in future sustainable water resource management.

This study employs the Driving Force–Pressure–State–Response (DPSR) framework to establish an evaluation index system for the water resource carrying capacity (WRCC) in the Cele–Yutian Oasis (China). Utilizing the TOPSIS and obstacle degree models, we analyze the trends in the WRCC and its main hindrance factors in the Cele–Yutian Oasis from 2005 to 2020. Additionally, we employ the Markov model to investigate the dynamic changes in the land use types. The findings reveal that the most unfavorable WRCC status occurred in 2007, with a Grade IV rating (a mild overload). By 2020, the WRCC improved to a Grade III rating (critical), indicating a positive trajectory. However, persistent challenges for water resources remain, with a prolonged critical state. Over the past 15 years, the grassland area has decreased by 15.18%, and the forest area has decreased by 50%. The dynamic degree of grassland, forests, and water bodies is negative, signifying shifts to other land types, with water bodies undergoing the most significant change at −10.16%. Based on the outcomes of these two models, we propose regionally tailored measures to support sustainable development. These research results provide a scientific foundation for optimal water resource allocation and sustainable development in the Cele–Yutian Oasis Economic Belt.