Chance-Constrained Dynamic Programming for Multiple Water Resources Allocation Management Associated with Risk-Aversion Analysis: A Case Study of Beijing, China

Water shortage and water pollution have become major problems hindering socio-economic development. Due to the scarcity of water resources, the conflict between water supply and demand is becoming more and more prominent, especially in urban areas. In order to ensure the safety of urban water supply...

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Bibliographic Details
Published in:Water (Basel) 2017-08, Vol.9 (8), p.596
Main Authors: Li, Wei, Jiao, Kuo, Bao, Zhe, Xie, Yulei, Zhen, Jiliang, Huang, Guohe, Fu, Lingbo
Format: Article
Language:English
Subjects:
Aquatic resources
Aversion
Canada
Case studies
China
cities
Decision making
Dynamic programming
Economic development
Feasibility
Feasibility studies
financial economics
Forecasts and trends
Frameworks
Management
planning
Reservoirs
Resource allocation
Risk allocation
Risk analysis
Risk aversion
Risk management
socioeconomic development
Storage reservoirs
supply balance
uncertainty
Urban areas
Water
Water allocation
Water pollution
Water resources
Water scarcity
Water shortages
Water supply
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Summary:Water shortage and water pollution have become major problems hindering socio-economic development. Due to the scarcity of water resources, the conflict between water supply and demand is becoming more and more prominent, especially in urban areas. In order to ensure the safety of urban water supply, many cities have begun to build reservoirs. However, few previous studies have focused on the optimal allocation of water resources considering storage reservoirs. In this study, a multi-water resources and multiple users chance-constrained dynamic programming (MMCDP) model has been developed for water resources allocation in Beijing, China, which introduces reservoir and chance-constrained programming into the dynamic programming decision-making framework. The proposed model can distribute water to different departments according to their respective demands in different periods. Specifically, under the objective of maximal benefits, the water allocation planning and the amount of water stored in a reservoir for each season under different feasibility degrees (violating constraints or available water resources situations) can be obtained. At the same time, the model can be helpful for decision-makers to identify the uncertainty of water-allocation schemes and make a desired compromise between the satisfaction degree of the economic benefits and the feasibility degree of constraints.
ISSN:2073-4441
2073-4441
DOI:10.3390/w9080596