The combined effects of climate change and human activities have increased hydrological process complexity and uncertainty, posing ever greater challenges to traditional water resource management. To simultaneously address water quantity, water quality, and aquatic ecosystem objectives under meteorological uncertainty, this study proposes a mixed time-scale, multi-dimensional collaborative dynamic operational framework for integrated water resource management. In this framework, a watershed hydrology model is coupled with a zero-dimensional hydrodynamic model at the annual scale to derive a robust year-round water level control strategy. At the monthly scale, an integrated watershed hydrology−water quality model is coupled with a three-dimensional hydrodynamic−water quality−ecology model to achieve multi-objective optimization of inflow and outflow operations. Using zero-dimensional surrogate models and parallel computing, 500,000 scenario simulations can be completed in 48 h, far outperforming traditional 3D models that would require over 1 year of computation. An empirical application in China’s Erhai Lake watershed demonstrates that the framework can raise year-end water levels by 0.2−0.5 m and reduce the risk of falling below the statutory minimum water level by over 20%, effectively coordinating water supply, flood control, water quality, and aquatic ecosystem objectives. Overall, the framework exhibits strong adaptability and generality, offering a deterministic and replicable technical pathway for refined regional water resource management under meteorological uncertainty, with the potential for application to other lakes and watersheds worldwide.
Ren et al. (Wed,) studied this question.