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Optimal reservoir operation using multi-objective evolutionary algorithms for potential estuarine eutrophication

Yang Yu1, Peifang Wang1, Chao Wang1

  • 1College of Environment, Hohai University, Nanjing 210098, China; Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, Hohai University, Nanjing 210098, China.

Journal of Environmental Management
|July 10, 2018
PubMed
Summary
This summary is machine-generated.

Integrated reservoir operation and in-estuary nutrient control effectively manage estuarine eutrophication and harmful algae blooms. This approach optimizes water resources, improving ecological health and ensuring water security.

Keywords:
Eutrophication potentialEvolutionary algorithmsICEP indicatorMulti-objective reservoir operationNutrient controlling

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Area of Science:

  • Environmental Science
  • Water Resource Management
  • Ecological Modeling

Background:

  • Estuarine waters face eutrophication and harmful algae blooms due to increased nutrient loads and altered ratios.
  • Toxin-producing non-siliceous algae proliferation is a major consequence of these changes.
  • Effective control strategies are needed to mitigate these ecological impacts.

Purpose of the Study:

  • To propose a multi-objective reservoir operation model for estuarine eutrophication control on a 10-day timescale.
  • To minimize the indicator of estuarine eutrophication potential (ICEP) while considering hydropower generation and water requirements.
  • To evaluate the effectiveness of different multi-objective evolutionary algorithms (MOEAs) in optimizing reservoir operations.

Main Methods:

  • Development of a multi-objective reservoir operation model incorporating ecological and socio-economic objectives.
  • Application of three modern multi-objective evolutionary algorithms (MOEAs) to solve the model.
  • Case study using the Three Gorges Reservoir and its impact on the Yangtze Estuary, with performance evaluation of MOEAs.

Main Results:

  • The multi-objective evolutionary algorithm based on decomposition with differential evolution operator (MOEA/D-DE) demonstrated superior performance.
  • Combined in-estuary total phosphorus (TP) concentration control and optimal reservoir operation proved more effective than hydrological management alone.
  • Optimized operation significantly increased the ecological satiety rate for estuarine drinking water sources across different year types.

Conclusions:

  • Integrated management combining reservoir optimization and TP control is crucial for mitigating estuarine eutrophication and non-siliceous algae blooms.
  • The proposed approach enhances water security for drinking water sources without negatively impacting economic and social interests.
  • This integrated strategy offers valuable guidance for water managers to achieve stable trophic control in estuarine ecosystems.