Evidence map›Paper›PMID 40825810›Full record

ArticleScientific reports2025

Optimize multi-objective transformation rules of water-sediment regulation for cascade reservoirs in the Lower Yellow River of China.

Kunhui Hong, Aixing Ma, Wei Zhang, Mingxiong Cao

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
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2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. A Review of Reservoir Operation Optimisations: from Traditional Models to Metaheuristic Algorithms.Archives of computational methods in engineering : state of the art reviews · 2022
    Review
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Kunhui HongCollege of Harbour, Coastal and Offshore Engineering, Hohai University, Nanjing, 210098, China.
Aixing MaNanjing Hydraulic Research Institute, Nanjing, 210029, China. axma@nhri.cn.
Wei ZhangCollege of Harbour, Coastal and Offshore Engineering, Hohai University, Nanjing, 210098, China.
Mingxiong CaoNanjing Hydraulic Research Institute, Nanjing, 210029, China.

Funding

the National Key Research and Development Funds 2021YFC3200403.
6 · The paper itself

Abstract

The Yellow River is characterized by water scarcity and high sediment load, leading to significant sedimentation issues in reservoirs. This severely restricts normal operation and contributes to frequent flooding, making it one of the most challenging problems in the Yellow River management. This study focuses on the operation of the Sanmenxia and Xiaolangdi cascade reservoirs, developing a multi-objective model (hydropower generation and sediment transport) and two single-objective models (hydropower generation only and sediment transport only). An innovative method (ESS-NSGA-II) is proposed, combining Efficient Search Space (ESS) with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to optimize cascade reservoirs operation. We analyzed the impact and transformation rules of multiple objectives under various optimization schemes. The results indicate a non-linear competitive relationship between the hydropower generation and sediment transport. An extreme case indicates an increase of 0.49 billion kWh in hydropower generation (4.08% increase) leads to greatly reduce the amount of sediment transport (96.25% decrease), while still meeting both water supply and flood control. The findings also indicate that Xiaolangdi reservoir plays a dominant role in the operation of the two reservoirs. The impact of different schemes is mainly reflected in the variation in Xiaolangdi's discharge, with the sediment transport maximization scheme offering greater flood control potential. Furthermore, the efficiency of sediment transport is closely related to hydropower generation: when hydropower is below 12.28 billion kWh, the conversion efficiency from hydropower generation to sediment transport increases significantly. This research reveals the transformation rules between multi-objectives in cascade reservoir operation, providing a scientific basis for water and sediment regulation in the Yellow River Basin and offering valuable insights into prolonging reservoir lifespans.

Indexed as

Efficient search space-non-dominated sorting genetic algorithm II (ESS- NSGA-II)Multi-objective optimizationThe lower yellow riverTransformation rulesWater-sediment regulation

Identifiers

PMID40825810
PMCPMC12361479

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.