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In order to better allocate water resources and maintain sustainable development, we selected Jining City as a specific research area and used the coefficient of variation entropy weight GM (1,1) research method to systematically evaluate the water resource carrying capacity. The results showed that the water resource carrying capacity system in the Jining area exhibited and will exhibit obvious economic ecological characteristics during the two periods of 2016-2021 and 2022-2026. From 2016 to 2021, the ecological environment water consumption rate, agricultural value-added water consumption per 10000 yuan, and industrial value-added water consumption per 10 000 yuan had become strong influencing factors. From 2022 to 2026, the weight of per capita GDP and per capita domestic water consumption would increase, becoming strong influencing factors along with the top three. [ABSTRACT FROM AUTHOR]

In order to evaluate regional water resource carrying capacity, the subtraction set pair analysis is adopted to calculate the connection number, and an evaluation model of the regional water resource carrying capacity based on quadratic subtraction set pair potential is established. The model is applied to assess the water resource carrying capacity of 16 cities in Anhui province, China, 2015. The results show that the water resource carrying capacity was sever throughout the province in 2015. Specifically, the carrying capacity in southern part of Anhui province was better than that in the northern part. The main factor of water resource carrying status varied in different cities. [ABSTRACT FROM AUTHOR]

[Display omitted] • The water resource carrying capacity in Qinling Mountain from 2000 to 2021 was evaluated. • The WRCC in the Qinling Mountain in the past 20 years can be divided into four phases. • 2009 is considered a turning point in the driving factors affecting the WRCC. • The driving factors affecting the WRCC shifted from extensive economy to urbanization expansion. Water resource carrying capacity (WRCC) is crucial to regional development and sustainable growth. The Qinling Mountain (QLM) is an important area for water source protection and conservation of the Yangtze River and the Yellow River. Therefore, it is vital to investigate the WRCC in the QLM region to preserve the ecosystem. This study established a driving force-pressure-state-impact response (DPSIR) model and coupled it with the ideal solution similarity ranking technique (TOPSIS) to evaluate the WRCC of the QLM, the driving factors affecting the WRCC of the QLM were identified by establishing a obstacle degree (OD) model. The results indicated that the WRCC in the QLM region exhibited an overall upward trend in the period, with four phases identified: the initial growth phase, rapid development phase, stable rising phase, and steady fluctuation phase. Since the promulgation of the relevant ecological protection policy in 2007, industrial development in the southern Qinling Mountains has been restricted, and the rapid recovery of the ecological environment has made the change trend of WRCC in the southern QLM is 8.23 % faster than that in the northern. Moreover, all subsystems demonstrated a declining trend through the obstacle degree model, with the impact subsystem displaying the most significant reduction, ranging from 65.3 to 3.8. This suggested that ecological protection measures achieved notable results. Reassigning the weighted calculations based on the obstacle degree model, the factors affecting WRCC exhibited significant temporal differences. The development of an extensive economy characterized by high energy consumption, high pollution, high cost, and low efficiency was the primary constraint from 2000 to 2009, while the expansion of urbanization became the main obstacle from 2010 to 2021. This study provides new insights into the spatiotemporal changes in WRCC in the QLM region, revealing the mechanisms driving regional WRCC, and also provides a reference for the evaluation of WRCC in other regions. [ABSTRACT FROM AUTHOR]

[Display omitted] • The carrying capacity of water resources in Gansu Province is evaluated comprehensively. • The combination weights of different indicators were determined through the application of game theory. • The TOPSIS evaluation model improved by using grey relational analysis was applied to calculate the WRCC of Gansu Province. • The water-carrying capacity of 14 cities and prefectures in Gansu Province has been progressively increasing over the years. • The future water resource carrying capacity has been forecasted using the ARIMA model. The water resource carrying capacity, as a pivotal component of the overall regional natural resource carrying capacity, plays a fundamental role in determining the feasibility of achieving harmonious coexistence among population, economy, and environment in regions with limited water resources. It holds paramount significance for regional development."Based on the theoretical framework of the four subsystems, namely water resources, society, economy, and ecology, this article employs the entropy weight method and CRITIC method to calculate individual weights. The combined weights are then determined using game theory. Subsequently, an improved TOPSIS model based on grey relational analysis is applied to comprehensively evaluate the water resources carrying capacity in Gansu Province from 2009 to 2022. The main obstacles impacting water resources carrying capacity are diagnosed using an obstacle degree model. Finally, a time series model is utilized to predict future trends in water resources carrying capacity from 2023 to 2030. The findings suggest that (1)over the study period, Gansu Province exhibited an upward trend in its overall water resource carrying capacity, with a value of 0.55 (weakly bearable) in 2022, representing a significant 20% increase compared to the baseline year of 2009. (2) In terms of regional changes, before 2015, the water resources carrying capacity of Wuwei, Linxia, Dingxi, and other places were in a weakly bearable carrying range [ 0.5,0.6), while other cities and prefectures were in a critical carrying state [ 0.4,0.5). After 2015, the carrying state of most cities and prefectures has improved, especially in Jiuquan, Jiayuguan, Wuwei, and other places, which may be related to the local government's efforts to increase water resources management and water-saving measures. (3) The key factors influencing the carrying capacity of water resources in Gansu Province include ecological water consumption, industrial wastewater emissions of chemical oxygen demand (COD), urban sewage treatment capacity, effective irrigation area in agricultural land, overall water consumption rate, and per capita daily water consumption in urban areas. To promote sustainable utilization of water resources, it is crucial to strengthen the management and regulation of these major hindering factors. (4) The future carrying capacity of water resources in various cities and states is expected to witness significant improvement. By 2030, it is anticipated that the carrying capacity of all provinces within Gansu Province will reach a bearable state [0.6,1], thereby progressing towards an overall green and sustainable trajectory. [ABSTRACT FROM AUTHOR]

• Incorporating the concept of ecological civilization into the risk assessment model of WRCC. • Apply the correlation matrix to construct the weighted gray TOPSIS model. • Improved entropy weighting method can reduce the oscillation of the weighting method due to the data small fluctuation. • Optimize the calculation of the traditional TOPSIS method in terms of weight and proximity distance. • Assessing WRCC from multiple perspectives of temporal evolution, spatial characterization, and impact subsystems. The issue of global water shortage is a serious concern. The scientific evaluation of water resource carrying capacity (WRCC) serves as the foundation for implementing measures to protect water resources. In addition, most of the studies are based on the analysis and research of regional WRCC from the aspects of water quantity and water quality. There are few studies on the four aspects of water resources endowment conditions, society, economy and ecological environment, which is difficult to scientifically and accurately reflect the analysis and evaluation of regional WRCC by the four systems. Therefore, it is necessary to conduct a deeper discussion and Analysis on this topic. This study presents a WRCC index system and corresponding ranking criteria based on 20 influencing factors from four aspects: water resources endowment (WRE), economy, society, and ecological environment. In addition, by combining the improved entropy weighting method (EWM) with gray correlation analysis, the weighted gray technique for order preference by similarity to an ideal solution (TOPSIS) model is proposed for analyzing and assessing WRCC risk. Finally, the WRCC of the study area from 2012 to 2021 is comprehensively evaluated in the central plains region of China (CPROC) as an example. The results show that the comprehensive evaluation obtained a multi-year average value of 0.2935, and the water resources shortage in the CPROC is generally in grade III status. The comprehensive average value of Beijing is 0.345, and the comprehensive average value of Henan is 0.397. The overall degree of water resources shortage is in the state of grade V shortage, Shaanxi is in the state of grade IV shortage, and the degree of water resources in Tianjin and Shanxi is relatively good. This study provides corresponding scientific basis and methodological guidance for the sustainable utilization of water resources and healthy socio-economic performance in the CPROC. [ABSTRACT FROM AUTHOR]

Water resources is one of the most essential natural resources throughout the world. Development of the early warning methods of water resources carrying capacity, by revealing the interaction mechanism between the water resources, the social economy and the ecological environment, can aid in the effective evaluation and warning of the sudden and abnormal state of the water resources carrying capacity, and is the key part of the early-warning on the carrying capacity of water resources. For this reason, the main methods of early warning of water resources carrying capacity has been summarized into four aspects:diagnosis, prediction, evaluation and regulation, and the main points for future research on water resources bearing capacity early warning have been put forward based on its concepts and mechanisms:① to further refine the concept of water resources carrying capacity warning system; ② to establish the indicator system of water resources carrying capacity; ③ to lucubrate the holistic study of water resources carrying capacity; ④ to realize the dynamic warning of water carrying capacity; ⑤ to enhance the study of the adjustment measure of water carrying capacity. [ABSTRACT FROM AUTHOR]

• An evaluation system was constructed more in line with the water resource carrying capacity in the eastern region of the Heilongjiang Province. • The improved TOPSIS model adopts a new method of assigning weights. • It avoids the deviation caused by subjective factors in the traditional analytic hierarchy process. • It avoids the emergence of extreme weights using the anti-entropy weighting method. Assessments and analyses of the water resource carrying capacity provide practical guidance for regional water resource planning and water resource management. The water resource carrying capacity index system and the corresponding level criteria are constructed from the perspective of the carrying capacity subsystem. Additionally, a water resource carrying capacity model is constructed using the improved TOPSIS method. Finally, a comprehensive evaluation and analysis of the water resource carrying capacity in the study area from 2009 to 2018 is conducted, with the eastern part of Heilongjiang as a case study. The results show that the combination of the improved AHP and the anti-entropy weighting method can avoid the bias caused by subjective factors in the traditional AHP and the bias caused by the randomness of data in the entropy weighting method, yielding accurate estimates of the water resource carrying capacity. A new method of assigning weights in TOPSIS models is developed. In addition, the water resource carrying capacity of the studied cities is generally in state III (Moderate) in the eastern region of Heilongjiang, and the multiyear average value obtained from the comprehensive evaluation is 0.4581. The Qitaihe and Hegang areas have higher water resource carrying capacities than other areas. Overall, water resource and societal factors have an obvious influence on the water resource carrying capacity in the eastern region of Heilongjiang, and these factors vary in different areas. The water supply modulus and proportion of water used for agricultural irrigation have the greatest effects on the water resource carrying capacity in the study area. [ABSTRACT FROM AUTHOR]

As a new development form for evaluating the regional water resources carrying capacity, forewarning regional water resources of their carrying capacities is an important adjustment and control measure for regional water security management. Up to now, most research on this issue have been qualitative analyses, with a lack of quantitative research. For this reason, an index system for forewarning regional water resources of their carrying capacities and grade standards, has been established in Anhui Province, China, in this paper. Subjective weights of forewarning indices can be calculated using a fuzzy analytic hierarchy process, based on an accelerating genetic algorithm, while objective weights of forewarning indices can be calculated by using a projection pursuit method, based on an accelerating genetic algorithm. These two kinds of weights can be combined into combination weights of forewarning indices, by using the minimum relative information entropy principle. Furthermore, a forewarning model of regional water resources carrying capacity, based on entropy combination weight, is put forward. The model can fully integrate subjective and objective information in the process of forewarning. The results show that the calculation results of the model are reasonable and the method has high adaptability. Therefore, this model is worth studying and popularizing. [ABSTRACT FROM AUTHOR]

By inherent mechanism study of water resource system, an evaluation index system based on DPSIRM model is established which takes the influences including resource, ecology, environment, economy and society into consideration. The paper gives the clear definition of each subsystem, which reflects the scientific relationship between each factor within the system. On that basis, coupling SA-PP model is established, and the parameters of projection pursuit are optimized by simulated annealing. The model is used to evaluate the water resource carrying capacity of Yunnan Province from 2003 to 2012, and the projection eigenvalues are analyzed. The study shows that, from 2003 to 2012, the water resources carrying capacity of Yunnan Province was increasing steadily. Under the current situation of economic and social development, water resource carrying capacity can carry the social economic development. Before 2006, the resource carrying capacity had an increasingly enlarged tendency, showing great potential of growth. After 2006, the fluctuation of water resources carrying capacity increased. The growth of water resource carrying capacity was close to zero in 2009 and 2011. The best projection direction reflects the impact degree of each index on water resource carrying capacity, the greater the value, the greater the impact of the corresponding evaluation index on the water resources carrying capacity. The main indexes affecting the water resource carrying capacity are the domestic sewage emissions, the “three wastes” control investment, per capital GDP, the water consumption per unit GDP and the forest coverage. The pressure subsystem accounts for 26.15% of water resource carrying capacity, being the most important factor. This model is practical, which can provide scientific basis for the planning and management of regional water resource. [ABSTRACT FROM AUTHOR]

• Evaluate sustainable development of water resources by Water resources carrying capacity (WRCC). • From starting points of WRCC's internal theory and divides mainstream evaluation methods into three types. • Among logistic, topsis and five-element subtraction set pair potential, the last has higher accuracy. • Results consistent with Beijing's WRCC and reflect indicator status to a certain extent. Water supply is one of the most critical factors for food security in many parts of the world, and the balance of water supply and demand ensures the sustainability of water resources. The water resources carrying capacity (WRCC) can effectively evaluate the state of sustainable development of water resources. Taking Beijing, which is severely lacking in water resources, as an example, the five-element subtraction set pair potential, logistic, and Technique for Order Preference by Similarity to Ideal Solution evaluation models (TOPSIS) were comprehensively compared and assessed to identify a more suitable method for water resource assessment. The results indicate that Beijing's WRCC score substantially improved from 2010 to 2018. The overall WRCC of Beijing has improved from the perspective of the carrying subject subsystem, and this has been particularly evident since 2014. The change of quantity and quality index in the quantity-quality-water bodies-flow index layer was the main reason for the increase in Beijing's WRCC. The South-to-North Water Transfer Project had a major impact on the changes in the quantity and quality index layers, which was reflected most distinctly in the measures of per capita water resources and Chemical Oxygen Demand (COD) emissions per 10,000 yuan. From the perspective of carrying object, Beijing's carrying capacity has improved significantly since 2013. In terms of utilization and social development, water consumption per 10,000 yuan of GDP and the proportion of tertiary industry are important factors affecting WRCC. Of the evaluation results of the three models, the results of the five-element subtraction set pairing evaluation model exhibited the highest accuracy. The results may also reflect the indicator status to a certain extent, and the results were more consistent with Beijing's WRCC. This study accurately identified the advantages and disadvantages of various indicators of WRCC by comparing different models and provided a reference for the formulation of Beijing's regulation measures for the sustainable development of water resources and food security. [ABSTRACT FROM AUTHOR]

Given China's rapid urbanization process, the study of water resource carrying capacity (WRCC) has important theoretical and practical significance for urban sustainable development. In this paper, a "human–water–city" (HWC) framework was proposed that offers a comprehensive consideration of the development of human society, water quality and quantity, and the progress of urban construction. Based on this framework, we established an HWC evaluation indicator system and constructed the WRCC-HWC approach, to assess, compare, and forecast the WRCC. Taking Wuhan, China, as an example, principal component analysis (PCA) was adopted to evaluate the current (2009–2019) and future (2020–2030) WRCC-HWC. Specifically, global climate models (GCMs) and a grey model, GM (1,1), were used to forecast the value of the future index system. The results show that the WRCC-HWC in Wuhan gradually increased from −3.04 to 3.23 during 2009–2019, being mainly affected by the income of urban residents, per capita GDP, reuse ratio of water used by industry, built-up area, and the output value of new and high-tech industry. With a rapid growth rate from 2011 to 2016, the WRCC-HWC reached the Grade I (excellent) state in 2016. In addition, the forecast results show that, with the exceptions of precipitation and good air quality rate, all HWC indicators show upward trends from 2020 to 2030 in Wuhan. In particular, the per capita disposable income of urban residents (N 1), per capita GDP (N 2), and the output value of new and high-tech industry (N 11) have faster growth rates, with relative growth rates from 2020 to 2030 exceeding 100%. Correspondingly, the WRCC-HWC from 2020 to 2030 were predicted to grow steadily each year, with a higher absolute growth rate starting in 2025. This study supports a comprehensive understanding of the current and future situation for WRCC-HWC in Wuhan and can provide a reference for the formulation of scientific and sustainable development strategies. [Display omitted] • A novel HWC framework was proposed to evaluate WRCC-HWC, with a stride from the "poor" to "excellent" stage during 2009–2019. • The mainly influencing factors of the regional WRCC-HWC were identified as the human welfare and reuse ratio of water. • The development trend of the future WRCC-HWC was predicted to be steady growth from 2020 to 2030. [ABSTRACT FROM AUTHOR]

• The water resources carrying capacity in Changchun is studied. • Used an system dynamics model to establish five mutually restricted subsystems. • Combined the improved fuzzy comprehensive evaluation with system dynamics model. • Simulates the dynamic trends of water resources carrying capacity under six scenarios. Water resource carrying capacity describes the relationship between different systems such as the socio-economic, water environment, and water resources systems. Recent studies tend to focus on the qualitative description of water resource carrying capacity, with a lack of quantitative research on the topic. This study proposes an improved water resource carrying capacity assessment method based on combining the improved fuzzy comprehensive evaluation and the system dynamics model, enabling the quantitative and qualitative measurement of water resource carrying capacity. This method can dynamically compute the water resource carrying capacity under different social development scenarios through the feedback regulation and system simulation of social economy–water resources and the water environment interactions. A comprehensive assessment of trends from six scenarios between 2018 and 2025 was conducted, based on scenarios designed for different purposes. The results indicate that if the current development model is adopted, the water resource carrying capacity will continue to decline and remain at a low level of "normal carrying" (0.431 in 2025). However, the water resource carrying capacity in Changchun may improve by changing the production mode of the national economy and adjusting the proportion of the economy. Rationally allocating water resources and strengthening water ecological protections can significantly increase the water resource carrying capacity and maintain it at "positive carrying", while maintaining steady economic and social growth. [ABSTRACT FROM AUTHOR]

Water resource is the crucial strategy resource for sustaining development, and is also a fundamental basis resource for building ecological environment, especially in karst areas of southwest China. In this study, the DPESBR conceptual model was first proposed and used to conduct sustainability evaluation on regional water resources in Guiyang. Based on the DPESBR model, 42 indicators were chosed and empowered by adopting combination weight. Results showed that the pressure on local water resources increased with soaring of total population and proportion of domestic water used by urban and rural residents. Countermeasures and options adopted by the local population had reduced the amount of agricultural irrigation water consumption and industrial water use ratio during the production course of regional agriculture and industry, but the increased water use scale had brought about a growth in resource depletion. Moreover, the sustained development of water resource system in the area was on the decline because of joint impacts of water contamination and use. Humanity could achieve the sustaining utilization of water resources in the region and the sustained progress of compound system by making adjustments on medium and short time bucket factors such as cultural heritages, value concepts, economical framework and technical makeup. [ABSTRACT FROM AUTHOR]

Water resource carrying capacity modelling is a fundamental task to explore the interaction mechanism between socio-economic development and water resource carrying system. To reasonably quantify regional water resource carrying capacity, firstly, the water resource carrying system was divided into pressure, support and regulation forces subsystems, then the multi-dimensional precondition cloud algorithm was introduced to quantify the belonging degree of single evaluation index, and the comprehensive belonging degree of each sample was further obtained through risk matrix and index weight, and finally the multi-dimensional precondition cloud and risk matrix coupling model (PCRM) was established to recognize carrying grade and reveal carrying mechanism. The application results of PCRM model indicated that water resource carrying capacity in Anhui province, China presented a slightly improving trend in both provincial and city scales during 2005 to 2015. Meanwhile, evaluation result of PCRM model was more approaching to the average characteristic value of different approaches, which indicated that PCRM coupling model is effectively to explore properties of indexes and subsystems of water resource carrying system, and could be further applied in other system evaluation and regulation research fields in the future. Unlabelled Image • Cloud model and risk matrix were used to assess water resources carrying capacity. • Water resources carrying system can be described by 3 subsystems and 11 indices. • Water resources carrying capacity in Anhui province presented slight improving trend. • Result of Cloud model is more beneficial to recognize water resources carrying grade. [ABSTRACT FROM AUTHOR]