Sun et al. (2026) Synergistic optimization of the Han-to-Wei project under dry conditions via the MOEA/D-PFE: a case study of the Huangjinxia reservoir

Identification

• Journal: Scientific Reports
• Year: 2026
• Date: 2026-09-10
• Authors: Xiaomei Sun, Boyu Zhang, Yichu Lu, Kekuo Yuan, Xinyi Zhang, Wencai Hui
• DOI: 10.1038/s41598-026-70770-5

Research Groups

• Department of Hydrology, Wuhan University
• Institute of Water Resources and Hydropower Research, Chinese Academy of Sciences
• School of Engineering, University of California, Los Angeles (UCLA)

Short Summary

This study investigates the synergistic operation dilemma of water supply and power generation under a 75% dry-year hydrological scenario for the Han-to-Wei River Diversion Project. The Multi-objective Evolutionary Algorithm based on Decomposition with Pareto Front Estimation (MOEA/D-PFE) is employed to address solution clustering caused by strong nonlinear operational constraints.

Objective

• Investigate the synergistic operation dilemma of water supply and power generation under a 75% dry-year hydrological scenario for the Han-to-Wei River Diversion Project.
• Develop an optimized operation scheme that balances competing objectives of water diversion, power generation, and flood control.

Study Configuration

• Spatial Scale: Regional scale (Hanjiang River Basin)
• Temporal Scale: Monthly time step

Methodology and Data

• Models used: MOEA/D-PFE algorithm with a reservoir operation model
• Data sources: Historical inflow series, evaporation data, and mandatory diversion quotas from the design specifications of the Han-to-Wei project.

Main Results

• The Pareto front analysis reveals a clear trade-off between water diversion and power generation under dry conditions.
• The MOEA/D-PFE algorithm achieves better solution uniformity and reduces the SP by 57.2% compared to the NSGA-II and standard MOEA/D.
• The optimized operation schemes demonstrate the practical rationality of raising reservoir water levels to compensate for generation head and prioritizing water supply during dry periods.

Contributions

• This study pioneers the integration of the MOEA/D-PFE framework to resolve complex flow-head-output nonlinearities of the Huangjinxia Reservoir under a 75% dry-year scenario.
• The algorithmic superiority is systematically validated using the hypervolume (HV) indicator, spacing (SP) metric, and Wilcoxon rank-sum tests.

Funding

• National Natural Science Foundation of China (Grant No. 51979015)
• Chinese Academy of Sciences Key Research Program (Grant No. ZDRW-ZS-2019-1-3)
• University of California, Los Angeles (UCLA) Research Grant

Citation

@article{Sun2026Synergistic,
  author = {Sun, Xiaomei and Zhang, Boyu and Lu, Yichu and Yuan, Kekuo and Zhang, Xinyi and Hui, Wencai},
  title = {Synergistic optimization of the Han-to-Wei project under dry conditions via the MOEA/D-PFE: a case study of the Huangjinxia reservoir},
  journal = {Scientific Reports},
  year = {2026},
  doi = {10.1038/s41598-026-70770-5},
  url = {https://doi.org/10.1038/s41598-026-70770-5}
}