Abstract: Against the backdrop of global climate change, the increasing frequency of extreme precipitation events has significantly heightened the risks of tailings dam failures and associated pollutant leakage, posing a serious threat to the water environment security of river basins. The current technical guidelines for environmental risk assessment of tailings ponds in China (HJ 740—2015) mainly employ the Analytic Hierarchy Process (AHP) for qualitative and semi-quantitative evaluation. This approach suffers from notable drawbacks, including strong subjectivity, an inability to precisely quantify the spatiotemporal distribution of risks, and a failure to capture risk evolution under extreme hydrological scenarios. To address these limitations, this study takes the tailings pond-concentrated area in Dexing City, Jiangxi Province as the research object. A two-dimensional unsteady hydrodynamic model is constructed, in which the runoff generation and infiltration module of SWMM is deeply coupled with the PCSWMM 2D overland flow module. This integration enables a full-process physical simulation of "precipitation—infiltration—surface runoff—two-dimensional overland flooding," offering a novel pathway for hydrological-hydrodynamic modeling in regions lacking pipe network data. By incorporating extreme rainfall scenarios with different return periods (20-year, 50-year, and 100-year events), the study systematically conducts quantitative assessments of inundation risks and pollutant dispersion risks. Furthermore, a systematic comparison with the results derived from the conventional AHP method reveals that the traditional approach may systematically underestimate risks under extreme hydrological conditions, thereby underscoring the necessity of physically based hydrodynamic models for accurate risk identification. The modeling results indicate that as the rainfall return period increases from a 20-year to a 100-year event, the proportion of high inundation risk areas rises from 9.27% to 11.52%. Taking zinc as the characteristic pollutant, the proportion of high environmental risk areas increases from 8.47% to 9.42%, demonstrating a clear expansion of the risk footprint with intensifying extreme precipitation. This research can provide scientific support for precise environmental risk management and the development of emergency prevention and response systems in tailings pond-concentrated areas.