Abstract: The dynamic evolution of lake aquatic environments directly affects ecological security and the sustainable development of regional economies. To address the limitations of traditional forecasting methods—such as insufficient consideration of complex hydrodynamic processes in water bodies,low prediction accuracy,and inadequacy in supporting practical management—this study developed and operationally deployed a short-term forecasting and early warning system for the water environment of Erhai Lake,which integrates a coupled mechanistic model with a data assimilation module. This system not only focuses on short-term prediction and early warning technologies for lake water environments,but also emphasizes its deep integration and application in the practical management of Erhai Lake. Unlike conventional approaches that rely solely on historical data for static validation,this system has undergone continuous “dynamic validation” over multiple years. The forecasting model has been running operationally within real management workflows,continuously being tested against observed data and incorporating decision-making feedback,thereby forming a complete cycle of forecasting,application, and re-validation. The system not only provides early warnings of water quality deterioration,but also directly supports key management tasks,including cause analysis,operational scheduling,and algal bloom control. The results from over five years of operational application indicate that the system achieves high accuracy in 7-day forecasts of total nitrogen（TN）,total phosphorus（TP）,ammonia nitrogen（NH₃-N）,and chlorophyll-a（Chl-a）,with the relative errors between the observed and forecasted values of all indicators within 30%. The forecast products have been deeply embedded into routine management,effectively supporting emergency response for cyanobacterial-bloom prevention and control,as well as water-resource optimization and scheduling decisions. This has effectively shifted Erhai Lake governance from a passive,response-driven mode to a proactive,early-warning-oriented mode,offering a replicable and extensible technical paradigm for the refined management of lakes in China.