Qi LuoYuxuan LuoYanlai ZhouDi ZhuFi-John ChangChong-Yu Xu2025-05-132025-05-132025-03-20https://www.scopus.com/record/display.uri?eid=2-s2.0-105001167483&origin=resultslisthttps://scholars.lib.ntu.edu.tw/handle/123456789/729264Article number: 2770Optimizing the joint drawdown operation of mega reservoirs presents a significant opportunity to enhance the comprehensive benefits among hydropower output, water release, and carbon emission reduction. However, achieving the complementary drawdown operation of mega reservoirs while considering reservoir carbon emissions poses a notable challenge. In this context, this study introduces an innovative multi-objective optimization framework tailored for the joint drawdown operation of mega reservoirs. Firstly, a multi-objective optimization model, leveraging an intelligent evolutionary algorithm, is developed to minimize reservoir carbon emissions (Objective 1), maximize hydropower output (Objective 2), and maximize water release (Objective 3). Subsequently, a multi-criteria decision-making approach to search for the optimal scheme is employed. The proposed framework is applied to seven mega reservoirs within the Hanjiang River basin, China. The results show that the framework is effective in promoting comprehensive benefits, improving hydropower production by 8.3%, reservoir carbon emission reduction by 5.6%, and water release by 6.2% from the optimal solution under wet scenarios, compared to standard operation policies. This study not only provides a fresh perspective on the multi-objective drawdown operation of mega reservoirs but also offers valuable support to stakeholders and decision-makers in formulating viable strategic recommendations that take potential carbon emissions and advantages into account.truecarbon emissionHanjiang Riverintelligent evolutionary algorithmmulti-objective optimizationreservoir drawdown operation[SDGs]SDG6[SDGs]SDG13[SDGs]SDG14journal article10.3390/su170627702-s2.0-105001167483