<p>The role of aquatic vegetation restoration in mitigating lake eutrophication is well-recognized, yet the underlying nutrient dynamics-vegetation response relationship remains poorly quantified, hindering a mechanistic understanding of grass-algae regime shifts. To address this, the Wetland Eco-dynamic Model for Submerged Plants (WET) was developed to mechanistically simulate ecological processes within the water–sediment-plant continuum by coupling hydrodynamics, nutrient cycling, and plant growth modules. Applied to Lake Taihu (2005–2019), the model effectively simulated submerged plant responses to hydrological and physicochemical parameters, with simulated vegetation cover validation achieving an R² of 0.68. A multi-scale analysis further identified a significant positive correlation between N:P ratios and aquatic vegetation cover. The model was subsequently employed to simulate vegetation dynamics under 121 distinct nutrient regulation scenarios, revealing that aquatic vegetation cover exerts a stronger influence on total phosphorus than on total nitrogen, a relationship characterized by steady-state nonlinearity. The findings demonstrate that under stable meteorological, hydrological, and pollution load conditions, managing aquatic vegetation is an effective eutrophication mitigation strategy for large, shallow lakes. Specifically for the phosphorus-limited Lake Taihu, simulations indicate that increasing vegetation coverage to 27.7% would shift its trophic status from eutrophic to oligotrophic-mesotrophic. By systematically quantifying these nonlinear responses, this study provides operational thresholds and a scientific basis for lake ecological management, overcoming a key limitation of traditional qualitative descriptions.</p>