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Multi-objective game-theory models for conflict analysis in reservoir watershed management
1Department of Environmental Engineering, Kun Shan University, Tainan City 71003, Taiwan. cslee@mail.ksu.edu.tw
Chemosphere
|January 31, 2012
Summary
A new multi-objective game-theory model (MOGM) effectively balances economic development and environmental protection in watershed management. This approach simplifies complex decisions for reservoir management, unlike traditional methods.
Area of Science:
- Environmental Science
- Game Theory
- Water Resource Management
Background:
- Reservoir watershed management requires balancing competing economic and environmental interests.
- Traditional decision-making methods can be complex and produce numerous alternatives, hindering practical application.
- Strategic interactions between land use, economic development, and water quality protection are critical.
Purpose of the Study:
- To develop a multi-objective game-theory model (MOGM) for integrated reservoir watershed management.
- To provide a decision-support tool that balances economic and environmental objectives.
- To compare the MOGM approach with conventional multi-objective methods.
Main Methods:
- Utilized game theory to model strategic interactions between economic development and environmental protection.
- Employed Geographic Information System (GIS) for land use area calculation and illustration.
- Applied the MOGM methodology to a case study in the Tseng-wen reservoir, Taiwan.
Main Results:
- The MOGM successfully balanced economic and environmental concerns in watershed management.
- Results from the MOGM were easily interpretable for decision-makers.
- The MOGM proved more effective than conventional multi-objective methods in simplifying the decision process.
Conclusions:
- The developed MOGM offers an innovative and advantageous approach to reservoir watershed management.
- The model provides a clear and practical tool for balancing economic development and environmental protection.
- MOGM enhances decision-making efficiency and clarity in complex environmental management scenarios.
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