Enhancing water balance simulations in SWAT for paddy-dominated catchments through refined soil moisture dynamics

Agricultural water management, especially irrigation regimes such as Alternate Wetting and Drying (AWD) in rice cultivation, holds significant implications for regional water balances. However, the Soil and Water Assessment Tool (SWAT) model, widely used for agricultural water management, has notable limitations in accurately simulating AWD irrigation practices due to improper description of soil moisture dynamics. In this study, a soil moisture module that dynamically simulates surface ponding and soil water redistribution is introduced to SWAT to address the limitation. The calculation of evapotranspiration (ET) and percolation under unsaturated conditions is improved. A controlling irrigation scheme based on soil moisture content and field water depth is introduced to manage the irrigation and drainage operations. Subsequently, the improved SWAT-Paddy Water (SWAT-PW) model is evaluated in the Yangshudang (YSD) basin, where 55.70 % of the area is rice and AWD irrigation is widely promoted, in the Zhanghe Irrigation District, China. The improvements in the Nash-Sutcliffe efficiency coefficient(NSE) and relative error coefficient(RE) demonstrate that SWAT-PW shows promise for improving predictions of water balance components and runoff compared with the original SWAT model and existing SWAT-MD model, which are critical for optimizing irrigation scheduling and reducing water waste in paddy fields. Scenario analysis (1999–2019) demonstrated the recommended AWD3, using alternate wetting and drying irrigation with optimized maximum ponding depth, could reduce total irrigation volumes by 16.92 % compared to local continuous flooding (CF1), providing evidence-based support for adopting AWD in water-scarce areas. While the results are demonstrated in the YSD basin, SWAT-PW’s modular design enables its application to global paddy-dominated catchments with similar irrigation practices, provided local soil, crop, and climate data are available. While the accuracy of ET depends on region-specific crop coefficients, future integration with remote sensing data could enhance its scalability. Therefore, through the soil moisture dynamics module, this study advances hydrological modeling for water-saving irrigation, offering policymakers a tool to balance agricultural productivity and water sustainability in rice systems.