Prediction of water resource carrying capacity by the analytic hierarchy process-fuzzy discrimination method in a mining area

Chi, Mingbo; Zhang, Dongsheng; Fan, Gangwei; Zhang, Wei; Liu, Honglin

doi:10.1016/j.ecolind.2018.09.021

Cited by 56 publications

(31 citation statements)

References 35 publications

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“…The focus of the evaluation is to quantify the carrying capacity of a specific region [27]. Predictive research usually sets different development scenarios for the HWRS, and then predicts the WRCC of each scenario [28]. The research on regulation refers to planning, such as water environment protection planning and water resources development planning, and then the target of WRCC is set.…”

Section: Literature Reviewmentioning

confidence: 99%

A Three-Stage Hybrid Model for Space-Time Analysis of Water Resources Carrying Capacity: A Case Study of Jilin Province, China

Liu

Yang

et al. 2020

Water

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Water shortage, water pollution, shrinking water area and water mobility are the main contents of the water resources crisis, which are widespread in the social and economic development of Jilin Province. In this paper, a three-stage hybrid model integrating evaluation, prediction and regulation is constructed by combining the load-balance method and the system dynamics method. Using this model, the current states of water resources carrying capacity (WRCC) in 2017 and the trend of water demand/available from 2018 to 2030 were obtained. Using the orthogonal test method, the optimal combination program of agricultural and industrial water efficiency regulation and water resources allocation was selected. The results show that the pressure of the human–water resources system in Changchun, Liaoyuan and Baicheng is greater than the support, and the other six cities are not overloaded. The water demand in Jilin Province and its nine cities will increase from 2018 to 2030, if the current socio-economic development pattern is maintained. Therefore, we change the water quantity carrying capacity index by controlling agriculture, industrial water efficiency and trans-regional water transfer. Compared with 2015, among the optimal program obtained, the change range of the water use per 10,000 RMB of agricultural output is (−5%, 25%), and the water use per 10,000 RMB of industrial added value is (−45%, −35%), and the maximum water transfer is 1.5 billion m3 per year in 2030. This study analyzes the development pattern of WRCC in the process of water conservancy modernization in Jilin Province and provides reference for other provinces to make the similar plan.

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Section: Literature Reviewmentioning

confidence: 99%

A Three-Stage Hybrid Model for Space-Time Analysis of Water Resources Carrying Capacity: A Case Study of Jilin Province, China

Liu

Yang

et al. 2020

Water

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“…The evaluation methods of resources and environmental carrying capacity (RECC) mainly include the ecological footprint method [33,34], energy analysis [35], system dynamics [36] and the comprehensive evaluation method [37,38]. Ecological footprint is a resource supply-demand balance method, which is more applicable at the global level [39].…”

Section: Introductionmentioning

confidence: 99%

Resources and Environmental Pressure, Carrying Capacity, And Governance: A Case Study of Yangtze River Economic Belt

et al. 2020

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The analysis of the relationship between regional resources and environment and human activities plays an important role in sustainable regional development. This study proposes the pressure-capacity-governance (PCG) model, an analytic framework for the assessment of the resources and environmental pressure (REP), carrying capacity (RECC) and governance (REG) levels over a large watershed scale, with the Yangtze River Economic Belt (YREB) as the study area. A limiting factor analysis is used to recognize the limiting factors of the regional RECC. The coupling analysis of resources and environmental pressure-capacity-governance identifies the regional potential and utilization direction. The research results are as follows. (1) The REP, RECC and REG levels of the YREB exhibit spatial differences. The REPs of the upper reaches are lower than those of the lower reaches, which does not match the RECC but matches the REG levels.(2) The proportions of unused land, water resources, and atmospheric environmental quality are the main limiting factors of the regional RECC. (3) The PCG analysis framework is used as the basis to divide the YREB into several subareas to analyse the resources and environmental potential carrying capacity and utilization direction of different types of region. This research may provide decision-making references for regional sustainable development at the large watershed scale.

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“…In order to quantitatively reflect WECC, the evaluation grades, v 1 , v 2 and v 3 , were scored between 0 and 1: a 1 = 0.95, a 2 = 0.5, a 3 = 0.05. The higher score indicates that water environment protection is more effective [26].…”

Section: Fuzzy Comprehensive Evaluationmentioning

confidence: 99%

“…At present, the main challenge facing WECC evaluation is the fuzziness and uncertainty of carrying capacity and the complicated relationships between indicators and WECC [26]. The aforementioned three methods cannot efficiently handle the uncertainty and ambiguity of the evaluation process.…”

Section: Introductionmentioning

confidence: 99%

Temporal Variation of Water Environment Carrying Capacity in a Highly Urbanized Region of China

Xiao

et al. 2020

Water

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China has experienced an unparalleled urbanization process in recent decades, which has dramatically changed the water environment. Quantification of the water environment carrying capacity (WECC) is crucial given its importance to sustainable development. Existing studies have typically focused on the overall WECC system and lacked analysis of its internal features. In this study, the concepts, calculations, and classifications of the WECC were further developed. Using Nanjing, China, as a case study, we developed a hierarchical evaluation indicator system including three system layers (social, environmental and economic subsystems). We applied the entropy weight and fuzzy comprehensive evaluation method to evaluate the temporal variation tendency of WECC, and explored the deep-seated problems stemming from urbanization. The results indicated that WECC in Nanjing was 0.3045–0.5302 during 2006–2017, thus approaching a moderate grade with a relatively slow growth rate. Social, environmental, and economic subsystems increased by 29.3%, 83.1%, and 97.2%, respectively. Overall, Nanjing had a solid foundation regarding its economic subsystem, but its social and environmental subsystems were under pressure. Factors such as slow population growth as well as reduced energy and water use intensity improved WECC, whereas factors such as increased population density and excessive water consumption blocked WECC. Practical suggestions were proposed to resolve the primary problems of the WECC under urbanization. This holistic approach is urgently needed to achieve water environmental sustainability, both for Nanjing and for other emerging cities.

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Prediction of water resource carrying capacity by the analytic hierarchy process-fuzzy discrimination method in a mining area

Cited by 56 publications

References 35 publications

A Three-Stage Hybrid Model for Space-Time Analysis of Water Resources Carrying Capacity: A Case Study of Jilin Province, China

A Three-Stage Hybrid Model for Space-Time Analysis of Water Resources Carrying Capacity: A Case Study of Jilin Province, China

Resources and Environmental Pressure, Carrying Capacity, And Governance: A Case Study of Yangtze River Economic Belt

Temporal Variation of Water Environment Carrying Capacity in a Highly Urbanized Region of China

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