Managing conflicts and equitability in hierarchical decision making for water resources planning under fuzzy uncertainty: A case study of Yellow River, China
Study area: The Yellow River, China Study focus: The Yellow River as the second longest river of China is of vital importance to maintain regional water security. With the influence of climate change and intense human activities, there will be an increasing severe water shortage which would bring ch...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/31eb32d39f9c4e7ab9b2de665e689db1 |
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| Sumario: | Study area: The Yellow River, China Study focus: The Yellow River as the second longest river of China is of vital importance to maintain regional water security. With the influence of climate change and intense human activities, there will be an increasing severe water shortage which would bring challenges to regional water resources management. In this study, an interactive fuzzy bi-level water resources management (FuzzyBiWRM) model with a hierarchical structure, has been proposed for water resources planning to satisfy the conflicting requirements of decision makers and quantify the trade-offs in a top-down decision-making process. New hydrological insights: The results show that there would be conflicts of water allocations among riparian provinces in the Yellow River region due to the increasing severe water shortage. The allocated water for all riparian provinces will decrease, especially for provinces with high water consumption. Accordingly, the proportional structure of water use by sectors in a province will also change. The proportion of water used for agriculture will decrease firstly. Although the FuzzyBiWRM model can generate fairer water resources allocation schemes, the water demands of the provinces with powerful economy would be firstly met to ensure maximum economic benefits. Shandong province would not face too much financial losses, but Shaanxi and Shanxi would suffer the most economic damages with more than 20%, followed by Henan with an economic loss of 11%. |
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