Comprehensive evaluation on water resource carrying capacity in karst areas using cloud model with combination weighting method: a case study of Guiyang, southwest China

2020 ◽  
Vol 27 (29) ◽  
pp. 37057-37073 ◽  
Author(s):  
Tao Peng ◽  
Hongwei Deng
Keyword(s):  
Water Resource ◽  
Carrying Capacity ◽  
Southwest China ◽  
Comprehensive Evaluation ◽  
Cloud Model ◽  
Weighting Method ◽  
Karst Areas ◽  
Water Resource Carrying Capacity ◽  
Combination Weighting Method

Assessment of water resource carrying capacity in karst area of Southwest China

2015 ◽  
Vol 75 (1) ◽  
Author(s):  
Qiyong Yang ◽  
Fawang Zhang ◽  
Zhongcheng Jiang ◽  
Daoxian Yuan ◽  
Yongjun Jiang
Keyword(s):  
Water Resource ◽  
Carrying Capacity ◽  
Southwest China ◽  
Karst Area ◽  
Water Resource Carrying Capacity

scholarly journals A Comprehensive Evaluation Model of Regional Water Resource Carrying Capacity: Model Development and a Case Study in Baoding, China

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2637 ◽  
Author(s):  
Siyu Mou ◽  
Jingjing Yan ◽  
Jinghua Sha ◽  
Shen Deng ◽  
Zhenxing Gao ◽  
...  
Keyword(s):  
Water Resource ◽  
Carrying Capacity ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Large Population ◽  
Model Development ◽  
Evaluation Framework ◽  
Influential Factor ◽  
Water Resource Carrying Capacity ◽  
Response Feedback

Scientific water resource carrying capacity (WRCC) evaluations are necessary for providing guidance for the sustainable utilization of water resources. Based on the driving-pressure-state-impact-response feedback loop, this paper selects 21 indicators under five dimensions to construct a regional WRCC comprehensive evaluation framework. The projection pursuit clustering (PPC) method is implemented with the matter-element extension (MEE) model to overcome the limitations of subjective deviation and indicator attribute incompatibility in traditional comprehensive assessment methods affecting the accuracy of evaluations. The application of the integrated evaluation model is demonstrated in Baoding city in the Jing-Jin-Ji area from 2010 to 2017. The results indicate that the economic water consumption intensity is the most influential factor that impacts the WRCC change in Baoding, and the pressure subsystem and response subsystem are dominant in the entire system. The WRCC in Baoding significantly improved between 2010 and 2017 from a grade V extremely unsafe state to a grade III critical state. Natural water shortages and large population scales are the main negative factors during this period; however, the existing measures are still insufficient to achieve an optimal WRCC status. Considering the future population and industry inflow, additional actions must be proposed to maintain and promote harmonious conditions.

scholarly journals Spatio-temporal evolution and influencing factors of water resource carrying capacity in Shiyang River Basin: based on the geographical detector method

2020 ◽  
Vol 20 (4) ◽  
pp. 1409-1424
Author(s):  
Liang-jie Yang ◽  
Xiao-rong Yang ◽  
Wei Wei ◽  
Jing-hu Pan
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Water Resource ◽  
Carrying Capacity ◽  
Population Distribution ◽  
Comprehensive Evaluation ◽  
Shiyang River Basin ◽  
Geographical Detector ◽  
Two Factors ◽  
Water Resource Carrying Capacity

Abstract In this article, the comprehensive evaluation of water resource carrying capacity (for short WRCC) in Shiyang River Basin is the objective. Based on the comprehensive evaluation model of regional WRCC, the spatial and temporal change characteristics of the WRCC in Shiyang River Basin in 2007, 2011 and 2016 have been analyzed. Moreover, the influence elements of water resource carrying capacity in Shiyang River Basin are detected by the geographical detector. The results show that: (1) In terms of the spatial dimension, water resources in Shiyang River Basin are not in accordance with the distribution of social and economic development and population distribution, presenting a prominent contradiction between supply and demand of water resources; (2) in terms of the temporal dimension, the pressure on water resources in Shiyang River Basin has gradually increased, and the area of overload, light overload and serious overload has been augmented; (3) the geographical detector indicates that the influences of the water resources system and coordinating system factors are declining, and the influences of the social economy system and ecological factor are obviously increasing. The influences of the interaction with any two factors are stronger than that of a single factor, and the synergistic influences of two factors are aggravated.

scholarly journals Study on the Water Resource Carrying Capacity in the Middle Reaches of the Heihe River Based on Water Resource Allocation

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1203 ◽  
Author(s):  
Ruining Jia ◽  
Xiaohui Jiang ◽  
Xingxing Shang ◽  
Chen Wei
Keyword(s):  
Resource Allocation ◽  
Water Resource ◽  
Carrying Capacity ◽  
Industrial Structure ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Heihe River ◽  
Water Resource Allocation ◽  
Water Resource Carrying Capacity

The study of water resource carrying capacity (WRCC) is significant for rational water resource utilization and promotion of the coordinated development of a regional economy, society, and ecology, especially in arid regions. In this paper, using different scenarios, a fuzzy comprehensive evaluation model based on water resource allocation is constructed to obtain the WRCC in the middle reaches of the Heihe River. The results show that the current development of water resources has a certain scale, and the carrying capacity is relatively low. Compared with the current water resource scheme, various scenario schemes have higher evaluation indexes. Among the schemes, scheme 7 is the optimal plan for the recent planning year, and scheme 13 is the best for the long-term planning year. Based on a subsystems analysis, the social subsystem has the highest score, which is followed by the economic subsystem, water resource subsystem, and ecological subsystem, and the evaluation index of the economic subsystem shows the largest increase. The main factors affecting the WRCC are the water-saving level and crop irrigation quota. Therefore, the WRCC should be improved by raising the level of agricultural water use, restricting the irrigation area, and adjusting the local industrial structure.

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