A decision-making method for water resource regulation that considers the multi-objective time-varying competition relationship is proposed, given the dynamic time-varying characteristics of the mutual feedback relationship and its strength as the main targets in the water resources scheduling cycle. With a focus on different dispatching periods, a time-varying multi-objective model of annual generation, annual ecology, period ecology is constructed. Dynamic decision weights are built using a method that combines entropy weight and FAHP, and then selects the dynamic preference scheme from the frontier cluster by weighted TOPSIS based on the weights. In this study the lower reaches of the Jinsha River are used as an example. The spatiotemporal variation relationship of the multi-objective is analyzed, the entire year is divided into three operation periods, and the Pareto frontier cluster is solved with a time-varying process. The results show that power generation is competitive with ecology on an annual scale. However, the relationship varies slightly in each period, being weakly cooperative in the flood period, not significant in the storage period, and competitive in the routine period. The decision method of focusing on the key period, considering time-varying demands and dynamic preferences, can obtain better annual power generation and ecological protection benefits than the traditional unified annual regulation method, and can improve the degree of guarantee of ecological demand in key areas during critical periods. Focusing on ecological protection during the routine period can achieve the best balance between power generation and ecological protection.

以相互反馈关系的动态时变特征及其强度作为水资源调度周期中的主要目标，提出了一种考虑多目标时变竞争关系的水资源调控决策方法。针对不同调度时段，构建了年发电量、年生态、周期生态的时变多目标模型。采用熵权和FAHP相结合的方法构建动态决策权重，然后根据权重通过加权TOPSIS从前沿聚类中选择动态偏好方案。本研究以金沙江下游为例。分析多目标的时空变化关系，全年分为三个运算期，帕累托边界聚类采用时变过程求解。结果表明，发电在年度规模上与生态竞争。但各时期的关系略有不同，汛期合作弱，蓄水期不显着，常规期竞争。以关键时期为重点，考虑时变需求和动态偏好的决策方法，比传统的统一年度调控方法可以获得更好的年发电量和生态保护效益，提高重点区域生态需求的保障程度在关键时期。