Evaluation Of Water Resources Carrying Capacity Research Articles

Study on Spatial-Temporal Differentiation of Water Resources Carrying Capacity Evaluation in Liaoning Province

Study on Spatial-Temporal Differentiation of Water Resources Carrying Capacity Evaluation in Liaoning Province

Effect of Weight of Water Resources Carrying Capacity Evaluation Index on Its Evaluation Results in Xinjiang, China

To analyze the effect of the weight of water resources carrying capacity evaluation index on its evaluation results, taking Xinjiang, China, as an example, this paper selects nine evaluation indicators related to the water resources system, social and economic development system, and ecosystem. The analytic hierarchy process (AHP), the coefficient of variation method, the geometric average method, and Murphy’s averaging method are used to calculate the weight of evaluation indexes. Subsequently, the fuzzy comprehensive evaluation model is used to evaluate the water resources carrying capacity of Xinjiang from 2011 to 2015. The results show that Murphy’s averaging method improves the shortcomings of single subjective or objective weight values and rankings that are inconsistent with the actual situation. The water resources carrying capacity of the study area was in a weak overload state for all years except 2014, and the water resources carrying capacity showed a downward trend year by year. According to the actual situation of precipitation change, Murphy’s averaging method is more reasonable in terms of index assignment and evaluation results. This method is more suitable for the water resources carrying capacity evaluation in Xinjiang.

Assessment of the Water Resources Carrying Capacity in the Great Dunhuang Region

Water resources carrying capacity (WRCC) is an important index for assessing the coordinated development relationship between population and water resources. The quantitative evaluation of WRCC can provide an important basis for water resource regulation and sustainable economic and social development. Based on the statistical data of cities and counties in the Great Dunhuang Region (GDR), and taking counties as the basic units, this study quantitatively analyzed the WRCC and carrying status of the GDR under different water inflow conditions and policy constraints from 2010 to 2017. The study revealed three main trends. (1) From 2010 to 2017, the WRCC of the GDR increased year by year, from 343700, 315900 and 291100 people to 458700, 415400 and 375600 people in normal, dry and extremely dry years, respectively. (2) Under policy constraints, the WRCC of the GDR increased year by year from 309400 people in 2010 to 412400 people in 2017. Based on future estimates, the WRCC of the GDR are expected to be 326600 people in 2020 and 341200 people in 2030. (3) From 2010 to 2017, the water resources carrying index of the GDR was decreasing, and it decreased from 1.05, 1.14 and 1.24 to 0.80, 0.88 and 0.97 in normal, dry and extremely dry years, respectively. The carrying status changed from critical overload to balanced. Although the WRCC and the carrying status of the GDR had significantly improved by 2017, the overall upper limit of the carrying capacity is not high. Therefore, efforts should be made to improve the utilization efficiency of water resources in order to maintain the sustainable utilization of water resources in the GDR.

Evaluation of water resources carrying capacity in ecologically fragile mining areas under the influence of underground reservoirs in coal mines

The coal mine underground reservoir (CMUR) technology effectively solves the problem of “rich coal, poor water and weak ecology” in the mining areas of northwest China. This technology not only makes full use of underground space formed by coal mining, but also protects regional water resources. Water resources carrying capacity (WRCC) is an important indicator for characterizing the sustainable development of regional water resources and ecosystem. With the concept and technical core of " conductivity, storage and use" of CMUR as the entry point, this paper defines the concept of WRCC in the mining area. Based on the fuzzy comprehensive discrimination method, Focusing on stability and sustainability of the ecosystem in the mining area and fully considering geological factors, mining factors, water resource factors, this study constructs an evaluation system for the WRCC of the mining area under the influence of the coal mine underground reservoir based on fuzzy comprehensive discriminant method. Moreover, the evaluation criteria are formulated, and the membership functions and weights of 16 impact factors are derived. The transformation characteristics of WRCC with and without underground reservoir in Shendong mining area from 2009 to 2021 are evaluated CMUR, and the results show that CMUR improves the WRCC of the mining area, and supports the benign development of the regional ecosystem. The results of this study are of reference value and academic significance for the evaluation of WRCC in mining areas and the protection of water resources in ecologically fragile mining areas.

Evaluating water resources carrying capacity: The empirical analysis of Hubei Province, China 2008–2020

Scientific evaluation of water resources carrying capacity (WRCC) is the basis for implementing water resources conservation measures. Hubei Province, with the longest runoff mileage of the Yangtze River, the reservoir area of the Three Gorges Project and the core water source area of the South-to-North Water Diversion Middle Line Project, bears great responsibility for ecology conservation in China. How to evaluate WRCC in Hubei Province has become significant. This study created a WRCC evaluation method based on information entropy method, principal component analysis and Spearman’s rank correlation coefficient to assess the WRCC in Hubei Province from 2008 to 2020. The available indicators were collected and summarized from the aspects of economy, population, resources and environment. By three-dimensionally displaying different indicators’ eigenvalues of principal component analysis, the major indicators can be screened. Subsequently, information entropy method was applied to estimate WRCC in Hubei Province and Spearman’s rank correlation was examined between WRCC and relevant factors. The results indicated that the WRCC in Hubei Province had been unstable in the range of 0.065 to 0.088 with the annual growth rate of 0.096%. It had a few peaks in year 2010, 2012, 2014, 2015 and 2016 while it decreased dramatically in year 2009, 2011, 2013, 2018 and 2020. Specifically, agricultural water use is more influential than industrial water use. The annual decline at 1.865% in agricultural water use is much smaller than the annual decline at 10.471% in industrial water use. Economically developed areas in the province have higher WRCC while economically backward areas have weaker WRCC.

Evaluation of spatial variation of water resources carrying capacity using optimal method: a case study of Fujian, China.

Studying regional water resources carrying capacity (WRCC) is an important guarantee for realizing regional sustainable development. Previous evaluation of WRCC mainly focused on the construction of the index system and the optimization of multiattribute decision analysis methods (MDAMs). The selection of the weighting assignment method (WAM) is a key link in the evaluation of WRCC, but different WAMs may bring different results, which brings challenges to the actual WRCC evaluation. Therefore, this paper proposes a WAM selection framework, under which WRCC evaluation index system is firstly constructed. Secondly, from the four objective WAMs, the most suitable WAM is identified and selected to evaluate WRCC in Fujian Province in terms of the reliability and stability of the evaluation results. In addition, the main factors affecting regional WRCC are discussed using the obstacle degree model. The results show that (1) under the same evaluation index system, the CRITIC method was the suitable method with more reliability and stability than the coefficient of variation method, the entropy method, and the equal weight method. (2) The higher water resources carrying capacity (level I) is mainly located in the west of the study area, and the lower one (level V) is located in the east coast. (3) The superimposition effects ecological water use rate, water production modulus, acreage water consumption of farmland irrigation, per capita water resources, and COD emissions hindering the level of regional WRCC. The framework proposed in this study can provide methodological options for quantitative evaluation of WRCC. The results of this paper provide favorable support for decision makers to carry out rational planning of resources.

The optimal allocation and the evaluation of water resources carrying capacity in Shendong mining area

Coal mining has consumed a large amount of water resources in China, and the entire industrial chain of coal production has a larger consumption of water resources than the past especially in Shendong mining area. The water resources carrying capacity determines the scale of coal industry development. The previous research had been conducted at the national, provincial and municipal levels, but there were few studies on the water resources carrying capacity of coal mining areas. The Shendong mining area is located in the coal-rich and water-scarce western region, where precipitation is low and evaporation is high. As a water-scarce area, the development of Shendong mining area is inseparable from the support of coal resources and the rational use of water resources. Therefore, firstly, taking the Shendong mining area as the research object, this paper set high, medium and low scenarios according to the development goals of Shendong mining area, Shenhua Group and the plans of China. The gray forecast model was used to predict the water demand of the economic-social-ecological system of the mining area from 2020 to 2030 under different scenarios. Secondly, a multi-objective optimization model was established with the objective function to optimize the water resources allocation in Shendong mining area. Thirdly, based on the forecast and optimization results, a water resources carrying capacity evaluation model was constructed to evaluate the water resources carrying capacity of the Shendong mining area. Finally, based on the results, the suggestions for rational development and the utilization of water resources in the Shendong mining area were proposed.

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

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.

Research on water resources carrying capacity evaluation based on innovative RCC method

Scientific assessment of water resources carrying capacity (WRCC) is the basis for implementing water resources protection measures. To make the evaluation more objective and reasonable, this study created a WRCC evaluation method based on R-clustering-variance coefficient method coupled with cloud model (RCC) for the state study of WRCC in a specific region. The study collected and summarized the available indicators through the review of existing studies to build a database of extensively selected indicators, and also combined with the characteristics of the study area to construct the initial indicators database. Then the indicators were categorized into 12 factor layers under the concept of water resources carrying subjects and objects, and the R clustering-variance coefficient method was introduced to screen the indicators to construct a concise and effective evaluation index system. Finally, combined with the cloud model to identify the comprehensive state of WRCC, the quantitative expression of WRCC was realized. Taking Henan Province of China as the research area, a total of 81 available indicators were collected, and an evaluation index system composed of 30 indicators was constructed after screening. During the evaluation years of 2005–2017, the WRCC level in Henan Province gradually raised from level IV (overload) to level II (weakly bearable), and the results of the study were stable and consistent with the changing trend of existing studies. The study can provide new ideas for the evaluation indicators selection and quantitative evaluation of water resources carrying capacity or other carrying capacity for a specific county, city, or provincial study area.

Comprehensive evaluation on water resources carrying capacity based on improved AGA-AHP method

The combined weight method (CWM) for comprehensive water resources carrying capacity evaluation is proposed in this paper to evaluate the regional water resources carrying capacity. Firstly, the accelerating genetic algorithm based on analytic hierarchy process (AGA-AHP) method is improved to optimize the expert evaluation matrix and determine the subjective weight, in which entropy weight method is used to determine objective weight, and the combined weight formula is put forward to get the combined weight of evaluation index. Secondly, the certainty degree is calculated by using the multi-dimensional normal cloud model. The obstacle factors of evaluation index are diagnosed. Finally, taking Henan Province as an example, the regional water resources carrying capacity is evaluated by using CWM method. The comparison between single cloud model, AHP-TOPSIS and CWM is made. It is proved that CWM method takes the fuzziness and randomness into account in the evaluation process, and the efficient and intuitive results can be obtained through evaluation. The obstacle degree and the time changing pattern of the index can be clearly diagnosed, which can provide a new idea for the evaluation method of water resources carrying capacity.

Dynamic simulation and comprehensive evaluation of the water resources carrying capacity in Guangzhou city, China

The quantity and quality of water resources are of vital importance to the sustainable development of the social economy. Accordingly, research on the water resources carrying capacity (WRCC) has received wide attention from scholars. The WRCC system comprises multiple complex and nonlinear interactions related to society, economy, water resources and the water environment. A full understanding of its internal mechanism is conducive to the further improvement of the regional WRCC. In this study, the system dynamics (SD) model is applied to establish the dynamic feedback system of the WRCC. The quantitative and qualitative evaluation of WRCC is conducted by coupling the analytic hierarchy process (AHP), entropy weight method and multiobjective linear weighting function. Furthermore, the coupling coordination degree model is introduced to rate the coordination of the WRCC system. Five typical scenarios designed for distinct purposes are simulated by the constructed SD model in Guangzhou from 2021 to 2030. The results indicate that the rapid economic development scenario performs worst in terms of WRCC (0.39 in 2030) and coupling coordination degree (0.28 in 2030), the water environment protection scenario and water conservation scenario are considerably effective for improving WRCC and promoting its coordinated development, and the comprehensive scenario performs best in both aspects. Pearson correlation analysis shows that there is a strong positive correlation between WRCC and coupling coordination degree, with a correlation coefficient of 0.91. Thus, to further enhance WRCC, we must attach great importance to regional coordinated development. In view of the problems existing in Guangzhou, several feasible suggestions are put forward for improving water use efficiency, reducing pollutant emissions and developing high-tech industries. This research can provide a scientific reference for promoting regional sustainable development.

Evaluation method of regional water resources carrying capacity based on semipartial connection number and dynamic subtraction set pair potential

为准确和客观地评价区域水资源承载力，从水资源承载力评价样本与评价等级标准这一集对的复杂系统结构角度，应用集对分析半偏联系数和减法集对势方法，构造了定量反映和刻画集对联系数系统结构中联系数分量间微观运动的迁移率矩阵，提出了一种联系数分量值的修正方法，同时基于减法集对势和三角模糊数方法动态确定了差异度系数，构建了区域水资源承载力定量评价方法. 该方法在安徽省淮北市的应用结果表明：2011—2019年水资源承载力介于2~3级之间，承载力较差，系统态势总体上由偏反势向均势过渡，逐渐向好发展；在判别系统态势发展方面，基于普通减法集对势的联系数值由2011年的-0.279变化到2018年的-0.037，再到2019年的-0.218，基于半偏减法集对势的联系数值由2011年的-0.267变化到2018年的-0.035，再到2019年的的-0.207，说明两种方法均适用，但在确定评价等级值方面，评价效果后者更优，相对误差在1 % 以内，这与半偏减法集对势的物理解释意义更为深刻有关. 联系数系统结构中联系数分量间的微观运动结果表明，原联系数中最大分量的值会减小，其他两个分量的变化情况与该分量本身的大小、半偏联系数表示的增量与原联系分量的比例、被迁移的原联系分量的大小有关. 基于半偏联系数和动态减法集对势法可实现联系数的修正更新和差异度系数的动态确定，方法物理解释性强、评价结果准确可靠，为从系统结构成因机理角度准确判别水资源复杂系统所处状态及总体发展趋势提供了新的有效途径.;In order to accurately and objectively evaluate the level of regional water resources carrying capacity (WRCC), from the perspective of WRCC evaluation samples and evaluation level standards, set pair analysis semipartial connection number (SCN) and subtraction set pair potential (SSP) method were applied in this study. A mobility matrix which quantitatively reflects and describes the micro movement between the connection number components (CNCs) in the connection number system structure was constructed, along with a correction method on CNC values. Meanwhile, the difference coefficient was dynamically determined based on SSP and triangular fuzzy number method, and the quantitative evaluation method of regional WRCC was constructed. The application of this method in Huaibei City, Anhui Province showed that WRCC in 2011-2019 was between level 2-3, and the carrying capacity was relatively poor. The overall system situation transited from partial inverse potential to equilibrium potential, and gradually developed for the better. In judging the development of system situation, the connection number value based on SSP changed from -0.279 in 2011 to -0.037 in 2018 and then to -0.218 in 2019, and connection number value based on SSP changed from -0.267 in 2011 to -0.035 in 2018 and then to -0.207 in 2019. Results indicated that both methods were applicable, with the latter one better in determining the evaluation grade value and relative error < 1 %, which was related to the more profound physical interpretation of the semipartial SSP. The micro motion results between the CNCs in the structure of the connection number system showed that the value of the largest component in the original connection coefficient will decrease, and the changes of the other two components are related to the size of the component itself, the proportion of the increment represented by the SCN to the original CNCs, and the size of the migrated original CNCs. Based on the SCN and dynamic SSP method, the correction and updating of connection number and the dynamic determination of difference coefficient can be realized. The method has strong physical interpretation and accurate and reliable evaluation results, which provides a new and effective way to accurately distinguish the state and overall development trend of complex water resources system from the perspective of system structure and genetic mechanism.

Ecological balance model of effective utilization of agricultural water resources based on fractional differential equations

Abstract Water is a key factor that controls the evolution of the ecosystem and restricts social and economic development. The rational allocation of water resources is the basis for the basin's sustainable use of water resources. The article uses fractional differential equations to discuss the increasingly prominent contradictions between supply and demand of agricultural water resources, serious pollution and overexploitation, the decline in groundwater level and water quality, low agricultural water efficiency, and serious waste from the perspective of sustainable development. Second, the article classifies the index system of the water resources carrying capacity evaluation model. Finally, model the resource balance of water supply and water demand in the irrigation area. The study found that the water quantity analysis and determination of the irrigation area will have important guiding significance for implementing the irrigation area's continued construction and water-saving transformation. The allocation and utilization of water resources in farmland irrigation areas will tend to be rationalized. This will greatly improve the water-saving efficiency of irrigation districts.

Uncertain Analysis of Fuzzy Evaluation Model for Water Resources Carrying Capacity: A Case Study in Zanhuang County, North China Plain

The scientific and accurate evaluation of water resources carrying capacity has good social, environmental and resource benefits. Reasonable selection of evaluation parameters is the key step to realize efficient and sustainable development of water resources. Taking Zanhuang County in the North China Plain as the research area, this study selected fuzzy comprehensive evaluation models with different weights in the established evaluation index framework to explore the sources of uncertainty affecting the evaluation results of water resources carrying capacity. By using the sensitivity analysis method of index weight, the index with the biggest influence factor on the evaluation result is selected to reduce the uncertainty problems such as index redundancy and small correlation degree. The results show that the correlation and reliable of comprehensive evaluation value obtained by different weight methods is different. The evaluation result obtained by using the analytic hierarchy process is more relevant than the entropy weight method, and it is more consistent with the actual load-bearing situation. The study of sensitivity index shows that water area index is the biggest factor affecting the change of evaluation results, and water resources subsystem and socio-economic subsystem play a dominant role in the whole evaluation framework. The results show that strengthening the data quality control of index assignment and weight method is helpful to reduce the error of water resources carrying capacity evaluation. It can also provide scientific basis for the improvement of fuzzy evaluation model.

Comprehensive analysis of water carrying capacity based on wireless sensor network and image texture of feature extraction

This article takes the complex uncertainty in the carrying process of water resources system as the research object. Firstly, the water resources carrying capacity system is divided into three sub-systems: bearing support capacity, bearing pressure and bearing regulation capacity. System analysis methods based on wireless sensor network and image texture of feature extraction for correlation analysis, gray correlation analysis, and multi-dimensional conditional cloud algorithm are introduced into the field of water resources carrying capacity evaluation research. Moreover, combine it with the subtraction set opposition, the effect partial bias connection number, and the risk matrix. Finally, three types of models for water resource carrying capacity evaluation and trend analysis were constructed. The evaluation results of water resources carrying capacity are consistent with the actual process, and the overall development trend is gradually improving. The application results of the evaluation model of water resource carrying capacity are established. The calculation results of the image texture feature of extraction model are similar to the overall change trend of the model before the improvement. The trend of change is more obvious. It can not only describe the water resource carrying level as a whole, but also characterize the reliability of the calculation results and the bearing risk caused by the uncertainty of the water resource carrying system. The water resources carrying capacity evaluation and trend analysis of calculation results are reasonable and feasible. The research results can provide a reasonable and effective decision-making basis for the systematic analysis of the bearing boundary issues between regional complex water resources systems and human water activities, and then propose adaptive risk prevention and control strategies for water resources carrying capacity.

Assessment of regional-scale water resources carrying capacity based on fuzzy multiple attribute decision-making and scenario simulation

This study associates the fuzzy multi-attribute decision making (FMADM) and the analytic hierarchy process (AHP) to assess the water resources carrying capacity and to tackle uncertain problems of multiple subsystems during its evaluation. For this purpose, the water resources carrying capacity evaluation index system is proposed, and the AHP-FMADM is used to evaluate the water resources carrying capacity of 15 areas in Xinjiang Uygur Autonomous Region from 2004 to 2017. Several scenarios with different weight-allocation modes are also conducted to study the influence of decision-makers’ preferences on target level. Results show that the water resources carrying capacity of all areas have been gradually improved. Overall, the economic and social indexes present an oscillation pattern with a rising, falling, and rising trend simultaneously in the study period from 2004 to 2017. The water resource utilization index varies with the amount of precipitation and reaches its peak in 2010. The ecological environment index depicts a diminishing overall trend initially before reaching a turning point in 2014. Increasing the water resources utilization and controlling rapid population growth can improve the water resources carrying capacity. The AHP-FMADM can help decision-makers to determine management plans based on their preferences, and the results of the study may contribute towards improving water resources carrying capacity.

Research on Evaluation System and Threshold Value of Water Resources Carrying Capacity Based on Principal Component Analysis

The traditional water resources carrying capacity evaluation system obtained by the fuzzy comprehensive evaluation method has strong subjectivity in factor selection and threshold calculation, and the factor analysis is relatively one-sided. Therefore, water resources carrying capacity evaluation system based on principal component analysis is established and its threshold is studied. First, the main influencing factors of water resources carrying capacity, including water resources endowment, society, ecology, and other resources are analyzed. Then, the water resources carrying capacity evaluation system is established by selecting the relevant indicators in the evaluation system, comprehensively considering the selection principles, and selecting the index with the highest score as the main component. Finally, different methods are used to calculate the threshold value of the evaluation index. So far, the establishment of the evaluation system of water resources carrying capacity based on principal component analysis and the calculation of the threshold value is completed. The results of the case analysis show that the established water resources carrying capacity evaluation system are more scientific and effective than the traditional system.

Research on the County Water Resources Carrying Capacity in the New Period

With the rapid economic and social development, human disturbances to the ecosystem have become more and more intense. However, the scale of regional economic and social development, supported by regional water resources, has boundaries. The central government and local governments of all levels have clearly proposed to carry out water resources carrying capacity evaluation and early warning. From the perspective of the actual management of the county water administrative department, with the administrative divisions within the county as the basic unit, the principle of index selection and index grading standards determination is proposed, and an index system including the four major levels of society, economy, water resources, and ecology is constructed. Then, combined with the functions of various government departments, the basic framework of a universal water resources carrying capacity early warning mechanism, including three major processes: carrying capacity evaluation and update, early warning information release, and implementation of differentiated control measures, is proposed.

Assessment on water resources carrying capacity in karst areas by using an innovative DPESBRM concept model and cloud model

The shortage of water resources in karst areas is mainly caused by the development of karst landforms, poor availability of water resources and the difficulty of utilization. To reasonably evaluate water resources carrying capacity (WRCC) of karst areas, based on characteristics of urban water resources utilization in karst areas, this study put forward DPESBRM (Driver-Pressure-Engineering water shortage-State-Ecological basis-Response-Management) concept model the first time to build an urban evaluation index system of WRCC in karst areas. Based on this index system and in allusion to uncertainties that exist during the evaluation process, a cloud model is used to represent index weights and perform comprehensive evaluation calculations, which fully considers the randomness and ambiguity of evaluation objects. WRCC from 2009 to 2018 were evaluated and were classified as five grades (Serious overload – Overload – Critical – Weak carrying capacity – Strong carrying capacity). Results proved that WRCC had improved year after year, gradually changing from a serious overload state in 2009 to a strong carrying capacity state in 2018. 2009 and 2016 were classified as I grade (serious overload). 2010 and 2011 were classified as II grade (overload). 2012, 2013 and 2015 were classified as IV grade (weak bearing capacity). 2014, 2017 and 2018 were classified as V grade (strong bearing capacity). Cloud model assessment results are compared with that of TOPSIS method, and assessment results are basically unanimous. It shows that the established WRCC evaluation method based on cloud model in this study is reasonable and feasible. Population density, urbanization rate and per capital water consumption are important driving factors affecting WRCC. Hence, strengthening the construction of water conservancy facilities, optimizing the water consumption structure, improving the efficiency of industrial water use, reducing per capital water consumption, and narrowing urban water supply and demand gap are important measures to ensure WRCC.

Variable precondition S-type cloud algorithm: Theory and application on water resources carrying capacity assessment

The purpose of water resources carrying capacity (WRCC) research is to meet the sustainable utilization of water resources and realize its sustainable development strategy. Scientifically evaluating the carrying capacity of regional water resources is extremely important. In this study, a variable precondition S-type cloud algorithm (VPSCA) is developed for assessment of regional WRCC based on social economic subsystem, water resources subsystem, ecological and environmental subsystem including thirteen indicators, which can overcome the shortcoming that the existing evaluation methods rarely consider fuzziness, randomness, and dynamic variability of parameters at the same time. First, forward S-type cloud generator algorithm (FSCGA) is developed based on segmented S-type membership function. On this basis, precondition S-type cloud generator algorithm (PSCGA) is proposed. Moreover, the VPSCA is developed by embedding PSCGA into variable fuzzy evaluation (VFE) method. Taking Beijing as a typical research area, this paper analyzes and forecasts the comprehensive benefits of water supply of the Middle Route of South-to-North Water Diversion Project (SWDP) in 2030 using VPSCA. The results show that SWDP can increase the carrying capacity of local water resources by 3.80%. In addition, feasibility and validity of VPSCA are further verified by comparison with other existing methods. This study aims to provide some suitable theoretical and practical implications of the evaluation of WRCC.