Reservoir operation optimization approach accounting for methane emission mitigation and water quality improvement targets

• This study incorporates CH 4 mitigation as a reservoir operation optimization objective. • The coupled cycling of hydrodynamic, water quality, and CH 4 processes is considered. • Optimized operation realizes CH 4 emission mitigation, particularly during dry periods. • CH 4 mitigation exhibits synergy with water quality improvement and power generation. Mitigating reservoir methane (CH 4 ) emissions is critical for the sustainable development of water conservancy and hydropower projects. Reservoir operations influence hydrodynamic and biogeochemical processes by regulating water storage and discharge, which significantly impact reservoir carbon (C) cycling and ensuing CH 4 emissions. However, existing operation optimization approaches have rarely considered CH 4 emission mitigation, and the relationships among CH 4 emission, water quality, and socioeconomic objectives remain unclear. This study proposes a multi-objective optimization approach for reservoir operations accounting for CH 4 mitigation, water quality, and socioeconomic objectives (i.e., water supply and hydropower generation) while exploring the relationships among these targets. A reservoir hydrodynamic-biogeochemical model is used to simulate CH 4 emissions and water quality under multiple reservoir operation scenarios. Machine learning (ML) models are trained to predict CH 4 emissions and water quality responses to reservoir operations, and these models are then incorporated into an operation optimization model. Using China’s second largest reservoir (Danjiangkou Reservoir) as a case, results show that maintaining higher water levels mitigates CH 4 emissions and improves water quality. Under the optimized operation scheme, multi-year averaged annual CH 4 emission decreases by 12.2%, chlorophyll a (Chl- a ) exceeding degree declines by 13.4%, hydropower generation increases by 3%, while water supply volume is slightly reduced by 0.4%. Pareto optimal solutions reveal a synergistic relationship between CH 4 mitigation and both water quality improvements and hydropower generation, while showing a tradeoff with water supply. This study provides a cleaner strategy for sustaining reservoir services and moving towards watershed C neutrality.

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Publication Details

Journal
Journal of Hydrology
Published
2025-03-22
DOI
https://doi.org/10.1016/j.jhydrol.2025.133129
Citations
6
Primary Topic
Water resources management and optimization
Type
article
Field-Weighted Citation Impact
6.87

Funders

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article

Reservoir operation optimization approach accounting for methane emission mitigation and water quality improvement targets

Yanpeng Cai, Kaiheng Chen, Zhihao Xu, Zhifeng Yang et al.
6 citations
Journal of Hydrology
Water resources management and optimization
6.87
article

Reservoir operation optimization approach accounting for methane emission mitigation and water quality improvement targets

Yanpeng Cai, Kaiheng Chen, Zhihao Xu, Zhifeng Yang, Yulei Xie, Chunyuan Xu
article en
6 citations

Abstract

• This study incorporates CH 4 mitigation as a reservoir operation optimization objective. • The coupled cycling of hydrodynamic, water quality, and CH 4 processes is considered. • Optimized operation realizes CH 4 emission mitigation, particularly during dry periods. • CH 4 mitigation exhibits synergy with water quality improvement and power generation. Mitigating reservoir methane (CH 4 ) emissions is critical for the sustainable development of water conservancy and hydropower projects. Reservoir operations influence hydrodynamic and biogeochemical processes by regulating water storage and discharge, which significantly impact reservoir carbon (C) cycling and ensuing CH 4 emissions. However, existing operation optimization approaches have rarely considered CH 4 emission mitigation, and the relationships among CH 4 emission, water quality, and socioeconomic objectives remain unclear. This study proposes a multi-objective optimization approach for reservoir operations accounting for CH 4 mitigation, water quality, and socioeconomic objectives (i.e., water supply and hydropower generation) while exploring the relationships among these targets. A reservoir hydrodynamic-biogeochemical model is used to simulate CH 4 emissions and water quality under multiple reservoir operation scenarios. Machine learning (ML) models are trained to predict CH 4 emissions and water quality responses to reservoir operations, and these models are then incorporated into an operation optimization model. Using China’s second largest reservoir (Danjiangkou Reservoir) as a case, results show that maintaining higher water levels mitigates CH 4 emissions and improves water quality. Under the optimized operation scheme, multi-year averaged annual CH 4 emission decreases by 12.2%, chlorophyll a (Chl- a ) exceeding degree declines by 13.4%, hydropower generation increases by 3%, while water supply volume is slightly reduced by 0.4%. Pareto optimal solutions reveal a synergistic relationship between CH 4 mitigation and both water quality improvements and hydropower generation, while showing a tradeoff with water supply. This study provides a cleaner strategy for sustaining reservoir services and moving towards watershed C neutrality.

Journal of HydrologyVol. 659
Guangdong University of Technology (CN), Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (CN)
National Natural Science Foundation of China
Clean water and sanitation
Openalex Percentile: Top 3%
Water resources management and optimization
6.87
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