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Risk Assessment of Water Resources and Energy Security Based on the Cloud Model: A Case Study of China in 2020
With the rapid development of economy and society, China’s demand for water resources and energy is increasing, and the supply situation is becoming increasingly severe. The correlation and binding characteristics between the two have become increasingly prominent, which will become bottlenecks in sustainable economic and social development in the future. In this paper, the Liang–Kleeman method was used to screen the risk factors of water resources and energy security, and then four major risk factors were selected. Based on the cloud model, the water resource and energy security risk assessment models were constructed combined with the predicted values using GM (1,1) and Pearson III curve methods, and the water resource and energy security risks of 30 provinces (cities) in 2020 were quantitatively assessed. The risk assessment results showed that the risk level zoning of water resource shortage with different guarantee rates in most regions has undergone little change, but the spatial distribution was quite different, showing the characteristics of “low in the South and high in the North”. When the guarantee rate changed from P = 25% to P = 95%, the risk level of water shortage in Sichuan, Jiangxi, Hunan, Hainan, Jilin, Ningxia and Nei Monggol significantly increased, and the spatial distribution of energy security risk and water resource shortage risk was obviously inconsistent.
Risk Assessment of Water Resources and Energy Security Based on the Cloud Model: A Case Study of China in 2020
With the rapid development of economy and society, China’s demand for water resources and energy is increasing, and the supply situation is becoming increasingly severe. The correlation and binding characteristics between the two have become increasingly prominent, which will become bottlenecks in sustainable economic and social development in the future. In this paper, the Liang–Kleeman method was used to screen the risk factors of water resources and energy security, and then four major risk factors were selected. Based on the cloud model, the water resource and energy security risk assessment models were constructed combined with the predicted values using GM (1,1) and Pearson III curve methods, and the water resource and energy security risks of 30 provinces (cities) in 2020 were quantitatively assessed. The risk assessment results showed that the risk level zoning of water resource shortage with different guarantee rates in most regions has undergone little change, but the spatial distribution was quite different, showing the characteristics of “low in the South and high in the North”. When the guarantee rate changed from P = 25% to P = 95%, the risk level of water shortage in Sichuan, Jiangxi, Hunan, Hainan, Jilin, Ningxia and Nei Monggol significantly increased, and the spatial distribution of energy security risk and water resource shortage risk was obviously inconsistent.
Risk Assessment of Water Resources and Energy Security Based on the Cloud Model: A Case Study of China in 2020
Yafeng Yang (Autor:in) / Hongrui Wang (Autor:in) / Yuanyuan Zhang (Autor:in) / Cheng Wang (Autor:in)
2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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