Distributed hierarchical evaluation and carrying capacity models for water resources based on optimal water cycle theory

Zhang, Shanghong; Xiang, Mengshi; Yang, Jiawei; Fan, Weiwei; Yi, Yang

doi:10.1016/j.ecolind.2019.01.048

Cited by 33 publications

(10 citation statements)

References 28 publications

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“…Furthermore, Kazakis et al [154] used the AHP method for research of potential groundwater systems in Kashmir Valley, northwestern-Himalayas. Also, Kazakis et al [155] used a distributed hierarchical analysis to evaluate the water cycle status in Beijing, China; therefore, the states of the water cycle are essential for modeling the potential water for sustainable progress.…”

Section: Analytical Hierarchical Process (Ahp) Methodsmentioning

confidence: 99%

Modification of the Water Quality Index (WQI) Process for Simple Calculation Using the Multi-Criteria Decision-Making (MCDM) Method: A Review

Akhtar

Ishak

Ahmad

et al. 2021

Water

149

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Human activities continue to affect our water quality; it remains a major problem worldwide (particularly concerning freshwater and human consumption). A critical water quality index (WQI) method has been used to determine the overall water quality status of surface water and groundwater systems globally since the 1960s. WQI follows four steps: parameter selection, sub-indices, establishing weights, and final index aggregation, which are addressed in this review. However, the WQI method is a prolonged process and applied to specific water quality parameters, i.e., water consumption (particular area and time) and other purposes. Therefore, this review discusses the WQI method in simple steps, for water quality assessment, based on two multi-criteria decision-making (MCDM) methods: (1) analytical hierarchical process (AHP); and (2) measuring attractiveness by a categorically based evaluation technique (MACBETH). MCDM methods can facilitate easy calculations, with less effort and great accuracy. Moreover, the uncertainty and eclipsing problems are also discussed—a challenge at every step of WQI development, particularly for parameter selection and establishing weights. This review will help provide water management authorities with useful knowledge pertaining to water usage or modification of existing indicators globally, and contribute to future WQI planning and studies for drinking, irrigation, domestic, and industrial purposes.

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Section: Analytical Hierarchical Process (Ahp) Methodsmentioning

confidence: 99%

Modification of the Water Quality Index (WQI) Process for Simple Calculation Using the Multi-Criteria Decision-Making (MCDM) Method: A Review

Akhtar

Ishak

Ahmad

et al. 2021

Water

149

View full text Add to dashboard Cite

show abstract

“…There are many factors that affect the carrying capacity of water resources. Water resources factors include the quantity and quality of water sources, the development and utilization of water resources, and the self-purification capacity of water bodies [8,29]. Economic factors include the level of economic development, productivity, and economic structure [18,30].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Agricultural Water Resources Carrying Capacity and Its Influencing Factors: A Case Study of Townships in the Arid Region of Northwest China

et al. 2022

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The water resources carrying capacity (WRCC) strongly determines the agricultural development in arid areas. Evaluation of WRCC is important in balancing the availability of water resources with society’s economic and environmental demands. Given the demand for sustainable utilization of agricultural water resources, we combine the water stress index and comprehensive index of WRCC and use multi-source data to evaluate agricultural WRCC and its influencing factors at the township scale. It makes up for the deficiencies of current research, such as the existence of single-index evaluation systems, limited calibration data, and a lack of a sub-watershed (i.e., township) scale. By applying multi-source data, this study expands the spatial scale of WRCC assessment and establishes a multidimensional evaluation framework for the water resources in dryland agriculture. The results indicate water stress index ranges from 0.52 to 1.67, and the comprehensive index of WRCC ranges from 0.25 to 0.70, which are significantly different in different types of irrigation areas and townships. Water quantity and water management are key factors influencing WRCC, the water ecosystem is an area requiring improvement, and the water environment is not a current constraint. Different irrigation areas and different types of townships should implement targeted measures to improve WRCC.

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“…: action direction iv: forced action : feedback direction v: enhanced feedback i: intrinsic motivation vi: relieved feedback ii: act directly vii: optimal feedback iii: act again viii: weakening or encouraging feedback Based on previous research [9,16,22,[25][26][27][28][29][30][31][32][33][34][35], this paper establishes an evaluation index system by combining a theoretical analysis and frequency statistics. Indicators frequently used in the relevant literature are included under the DPSIR framework.…”

Section: Evaluation Indicator System Constructionmentioning

confidence: 99%

“…Indicators frequently used in the relevant literature are included under the DPSIR framework. After deleting some indicators that cannot meet the requirements of generality and practicality, we selected 17 common evaluation indicators as shown in Table 1 Based on previous research [9,16,22,[25][26][27][28][29][30][31][32][33][34][35], this paper establishes an evaluation index system by combining a theoretical analysis and frequency statistics. Indicators frequently used in the relevant literature are included under the DPSIR framework.…”

Section: Evaluation Indicator System Constructionmentioning

confidence: 99%

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

Mou

Yan

Sha

et al. 2020

Water

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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.

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Distributed hierarchical evaluation and carrying capacity models for water resources based on optimal water cycle theory

Cited by 33 publications

References 28 publications

Modification of the Water Quality Index (WQI) Process for Simple Calculation Using the Multi-Criteria Decision-Making (MCDM) Method: A Review

Modification of the Water Quality Index (WQI) Process for Simple Calculation Using the Multi-Criteria Decision-Making (MCDM) Method: A Review

Evaluation of Agricultural Water Resources Carrying Capacity and Its Influencing Factors: A Case Study of Townships in the Arid Region of Northwest China

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

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