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Spatial Distribution of Water Risk Based on Atlas Compilation in the Shaanxi Section of the Qinling Mountains, China
Global climate change and rapid socio-economic development have increased the uncertainty in water resource systems and the complexity of water risk issues. Analyzing water risk and its spatial distribution is integral to the attainment of Sustainable Development Goal (SDG) 6, as this contributes to effective water resource partition management. In this paper, a compiling method of risk atlas with multiple layers is proposed, and the water risk system is divided into five sub-systems including the risk of resource, management, engineering, quality, and disaster. The information used for the risk atlas is calculated by a risk evaluation model based on a Pressure–State–Response (PSR) framework, hierarchical cluster, and set pair analysis (SPA). Risks in the Qinling Mountains of Shaanxi (as a case study) are evaluated and visualized. The results show that grades IV and V of engineering, disaster, and resource risk exceed 40%, indicating that they require prior control. The quality and management risks are not major, but there is still room for improvement. Overall, the risk atlas can effectively and objectively reflect the spatial distribution of water risk and provide a basis for the layout of water risk control measures.
Spatial Distribution of Water Risk Based on Atlas Compilation in the Shaanxi Section of the Qinling Mountains, China
Global climate change and rapid socio-economic development have increased the uncertainty in water resource systems and the complexity of water risk issues. Analyzing water risk and its spatial distribution is integral to the attainment of Sustainable Development Goal (SDG) 6, as this contributes to effective water resource partition management. In this paper, a compiling method of risk atlas with multiple layers is proposed, and the water risk system is divided into five sub-systems including the risk of resource, management, engineering, quality, and disaster. The information used for the risk atlas is calculated by a risk evaluation model based on a Pressure–State–Response (PSR) framework, hierarchical cluster, and set pair analysis (SPA). Risks in the Qinling Mountains of Shaanxi (as a case study) are evaluated and visualized. The results show that grades IV and V of engineering, disaster, and resource risk exceed 40%, indicating that they require prior control. The quality and management risks are not major, but there is still room for improvement. Overall, the risk atlas can effectively and objectively reflect the spatial distribution of water risk and provide a basis for the layout of water risk control measures.
Spatial Distribution of Water Risk Based on Atlas Compilation in the Shaanxi Section of the Qinling Mountains, China
Xinyue Ke (author) / Ni Wang (author) / Long Yu (author) / Zihan Guo (author) / Tianming He (author)
2023
Article (Journal)
Electronic Resource
Unknown
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