期刊
SCIENCE OF THE TOTAL ENVIRONMENT
卷 751, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.scitotenv.2020.141759
关键词
Hydrological ecosystem services; Urmia Lake Basin; Game theory; Hierarchical decision making; Water management scenarios
资金
- Urmia Lake Restoration Program
- Iran National Science Foundation (INSF) [98014423]
This paper presents a new methodology for evaluating water resources management scenarios, considering various aspects of hydrological ecosystem services. The temporal variations in supplied water and agricultural drought management policies are assessed, along with ecological conditions as a criterion. A game theory-based hierarchical evidential reasoning technique is used for prioritizing and selecting the best water resources management scenario.
This paper introduces a new methodology for evaluating water resources management scenarios considering different aspects of their hydrological ecosystem services. The temporal variations of supplied water to different demands are assessed as provisioning hydrological ecosystem services. Then, three agricultural drought management policies have been defined for each water supply-demand alternative to reduce the irrigation water and cultivated area of the agricultural demand nodes during droughts. In addition to the net primary productivity criterion (NPP) and economic profit, the ecological condition of the system has been evaluated as an ecosystem services-based criterion. To prioritize and select the best water resources management (WRM) scenario(s), a game theory-based hierarchical evidential reasoning (ER) technique with multiple decision-makers has been used. The proposed methodology has been applied to the Urmia Lake basin, which is the largest saline lake in the Middle East. The grade-based values of the criteria have been used to compare the WRM scenarios. The results show that a scenario that includes supplying 100% of the lake's water demand has the highest priority. This scenario also suggests reducing the cultivated area of dominant crops and using deficit irrigation practices. (C) 2020 Elsevier B.V. All rights reserved.
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