Multi-objective optimization of quantitative-qualitative operation of water resources systems with approach of supplying environmental demands of Shadegan Wetland

2021 ◽  
Vol 292 ◽  
pp. 112769
Author(s):  
Zahra Goorani ◽  
Saeid Shabanlou
Keyword(s):  
Water Resources ◽  
Multi Objective Optimization ◽  
Water Resources Systems ◽  
Multi Objective ◽  
Environmental Demands ◽  
Shadegan Wetland

The Multi-Objective Optimization Allocation Model of Water Resources in Xiaokai River Irrigation Area

2015 ◽  
Vol 1092-1093 ◽  
pp. 1289-1294
Author(s):  
Xin Wang ◽  
Jing Xu ◽  
Ke Kong ◽  
Lei Yan ◽  
Fang Wu
Keyword(s):  
Water Resources ◽  
Optimization Model ◽  
Supply And Demand ◽  
Reference Value ◽  
Multi Objective Optimization ◽  
Allocation Model ◽  
Irrigation Area ◽  
Multi Objective ◽  
Groundwater Environment ◽  
Sequence Method

For the three big problems of water resources supply and demand contradiction, protection of groundwater environment and sediment over long distances in Xiaokai river irrigation area, the model of water utilization benefit maximization, groundwater level optimal control and the goal of sediment transport effect optimization model are established, and coupled into a multi-objective optimization model. The model is solved by using The delaminating sequence method, obtained the rational allocation plan of water resources in water years, and analyzing the rationality of the plan. The results show that, the scheme comprehensively considers the economic and environmental issues and has great reference value to promote sustainable development of irrigation area.

scholarly journals Sustainable Water Resources Management in an Arid Area Using a Coupled Optimization-Simulation Modeling

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 885 ◽  
Author(s):  
Siamak Farrokhzadeh ◽  
Seyed Hashemi Monfared ◽  
Gholamreza Azizyan ◽  
Ali Sardar Shahraki ◽  
Maurits Ertsen ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Water Resources ◽  
Environmental Data ◽  
Multi Objective Optimization ◽  
Wetland Ecosystems ◽  
Multi Objective ◽  
Sustainable Water Resources Management ◽  
Trade Offs ◽  
Conflicting Demands ◽  
Conflicting Objectives

Severe water scarcity in recent years has magnified the economic, social, and environmental significance of water stress globally, making optimal planning in water resources necessary for sustainable socio-economic development. One of the regions that is most affected by this is the Sistan region and its Hamoun wetland, located in south-east Iran. Water policies are essential to sustain current basin ecosystem services, maintaining a balance between conflicting demands from agriculture and the protection of wetland ecosystems. In the present study, a multi-objective optimization model is linked with the Water Evaluation and Planning (WEAP) software to optimize water allocation decisions over multiple years. We formulate and parameterize a multi-objective optimization problem where the net economic benefit from agriculture and the supply of environmental requirements were maximized, to analyze the trade-off between different stakeholders. This problem is modeled and solved for the study area with detailed agricultural, socio-economic, and environmental data for 30 years and quantification of ecosystem services. By plotting Pareto sets, we investigate the trade-offs between the two conflicting objectives and evaluate a possible compromise. The results are analyzed by comparing purely economic versus multi-objective scenarios on the Pareto front. Finally, the disadvantages and advantages of these scenarios are also qualitatively described to help the decision process for water resources managers.

scholarly journals Application and comparison of NSGA-II and MOPSO in multi-objective optimization of water resources systems

2018 ◽  
Vol 66 (3) ◽  
pp. 323-329 ◽  
Author(s):  
Ali Hojjati ◽  
Mohsen Monadi ◽  
Alireza Faridhosseini ◽  
Mirali Mohammadi
Keyword(s):  
Water Resources ◽  
Flood Control ◽  
Optimization Methods ◽  
Optimal Operation ◽  
Nsga Ii ◽  
Water Resources Systems ◽  
Multi Objective ◽  
Trade Offs ◽  
Reservoir Systems ◽  
Alternative Solutions

Abstract Optimal operation of reservoir systems is the most important issue in water resources management. It presents a large variety of multi-objective problems that require powerful optimization tools in order to fully characterize the existing trade-offs. Many optimization methods have been applied based on mathematical programming and evolutionary computation (especially heuristic methods) with various degrees of success more recently. This paper presents an implementation and comparison of multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II) for the optimal operation of two reservoirs constructed on Ozan River catchment in order to maximize income from power generation and flood control capacity using MATLAB software. The alternative solutions were based on Pareto dominance. The results demonstrated superior capacity of the NSGA-II to optimize the operation of the reservoir system, and it provides better coverage of the true Pareto front than MOPSO.

scholarly journals Multi-Objective Optimization for Reservoir Operation Considering Water Diversion and Power Generation Objectives

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1540 ◽  
Author(s):  
Xiaomei Sun ◽  
Jungang Luo ◽  
Jiancang Xie
Keyword(s):  
Power Generation ◽  
Water Resources ◽  
Reservoir Operation ◽  
Weight Vector ◽  
Water Shortage ◽  
Water Diversion ◽  
Volume Index ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Adaptive Weight

Due to the uneven distribution of water resources in time and space, the problem of water shortage has become increasingly serious in some areas. To optimize use of water resources, it is urgent to establish multi-objective models and apply effective optimization algorithms to guide reservoir management. This study proposed a model of multi-objective optimization for reservoir operation (MORO) with the objectives of maximizing water diversion and power generation. The multi-objective evolutionary algorithm based on decomposition with adaptive weight vector adjustment (MOEA/D-AWA) was applied to solve the MORO problem. In addition, the performance of the MOEA/D-AWA was compared with two other algorithms based on the hyper-volume index. Huangjinxia reservoir, which is located in Shaanxi, China, was selected as the case study. The results show that: (1) the proposed model is effective and reasonable in theory; (2) the optimization results obtained by MOEA/D-AWA demonstrate this algorithm can be applied to the MORO problem, providing a set of evenly distributed non-dominated solutions; and (3) water diversion and power generation are indeed contradictory objectives. The MORO strategy can be used to efficiently utilize water resources, improve the comprehensive benefits of reservoirs, and provide decision support for actual reservoir operation.

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