Spatial-Temporal Evolution Pattern and Future Scenario Analysis of Water Resources Carrying Capacity of Ningbo City

Author(s):  
Yanjuan Wu ◽  
Zhiming Feng ◽  
Yanzhao Yang
Author(s):  
Zhenghua Deng ◽  
Liqi Dai ◽  
Bing Deng ◽  
Xiaoyong Tian

Abstract A three-dimensional rating index system for water resources system–water environment system–socioeconomic system is constructed based on data from Hunan Dongting Lake Eco-environment Monitoring Center, Hunan Provincial Water Resources Bulletin, and Hunan Statistical Yearbook. The water resources carrying capacity (WRCC) of Dongting Lake Basin from 2009 to 2018 is evaluated by the TOPSIS model combined with analytic hierarchy process (AHP) and entropy weight, and then the temporal evolution and spatial distribution characteristics of the WRCC of the Dongting Lake Basin are analyzed. The results show that: (1) The WRCC in the Dongting Lake Basin decreases from a good level to a reasonable level during the period. Among them, the WRCC of the Ouchi River, Hudu River, and Songzi River Basins decreases significantly. (2) There are obvious spatial differences in the WRCC of the Dongting Lake Basin in 2018, the WRCC order is Lishui River, West Dongting Lake, Zijiang River, South Dongting Lake, Yuanshui River, Xiangjiang River, East Dongting Lake, Songzi River, Hudu River, Ouchi River, with scores of 0.586, 0.526, 0.472, 0.448, 0.416, 0.397, 0.393, 0.313, 0.306, and 0.304, respectively. Finally, some policy recommendations for improving the WRCC of the Dongting Lake Basin are proposed.


2015 ◽  
Vol 1092-1093 ◽  
pp. 1202-1208
Author(s):  
Ming Xia Jing

This paper predicted HuangShui River carrying capacity level of environmental resources at the end of the "twelfth five-year" period and even longer, based on the economic and social development in the base year 2011 data, to provide reference for the development of various government related department reference.


2018 ◽  
Vol 06 (04) ◽  
pp. 1850023 ◽  
Author(s):  
Xifeng WANG

Most of the existing studies on regional water resources efficiency only consider the total regional water use while ignoring the regional endowment. Therefore, it is essential to introduce the water resources carrying capacity into the study. Given that data envelopment analysis (DEA) cannot compare the time series of a single decision-making unit, we employ the DEA-window analysis to study China’s water resources efficiency during 2005–2012 with the regional carrying capacity being considered, and analyze the spatiotemporal evolution. The study shows that such efficiency has increased from 0.71 in 2005 to 0.79 in 2012. High water resources efficiency is observed in Liaoning, Tibet, Yunnan, Beijing, Tianjin, Shanghai, Jiangsu, Zhejiang, Guangdong and Sichuan, where the output levels and utilization ratios of water resources are positively correlated. Low water resources efficiency is observed in Henan, Shaanxi, Gansu, Ningxia and Xinjiang which feature high-level utilization and low carrying capacity of water resources. As for regional water resources efficiency, eastern and southern coastal regions rank first, followed by Northeast China and northern coastal regions, southwest and northwest regions of China and lastly the middle reaches of the Yellow and Yangtze Rivers. Therefore, policy-makers should not only accord the regional development with carrying capacity, but also enhance cross-regional industrial cooperation for coordinated development.


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