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Most existing evaluation frameworks for water resource carrying capacity (WRCC) neglect the interdependencies between subsystems. To fill this gap, we introduce a dynamic qualitative comparative analysis (QCA) model to evaluate WRCC and apply it to a vital economic development corridor, the Yangtze River Economic Belt (YREB). Ecological, social, and economic subsystems are defined as condition subsystems, while the water resource subsystem is defined as the outcome subsystem. The entropy weight method is used to calculate and calibrate the comprehensive score of each subsystem. By analyzing the necessity of a single condition subsystem and the sufficiency of condition subsystem configuration via a dynamic QCA, we qualitatively analyze the impact extent and pathways of the ecological, social, and economic subsystems on the water resource subsystem within the WRCC framework. The results reveal generally stable water resource levels despite regional variances, thereby pinpointing the influence pathways, including ecological–social and ecological–economic configurations. The 2011–2015 period saw poor stability, which subsequently improved until 2019 before declining in 2020 in the YREB. The middle-reach urban cluster showed the highest stability, which was less impacted by condition subsystems. These findings could enable provinces and municipalities to tailor policies and enhance subsystem levels for better water resource management. [ABSTRACT FROM AUTHOR]

The Hunjiang River, a vital water system in northeastern China, has suffered severe ecological damage due to overexploitation. This study analyzes the basin's environmental conditions from 2016 to 2020, identifies key restoration factors, and examines practical restoration projects. Investigating five major pollutants (permanganate index, chemical oxygen demand (COD), biochemical oxygen demand, ammonia nitrogen, total phosphorus) in eight sections, the study finds the Xicun section most polluted, mainly from Baishan City's industrial and domestic discharges. The ammonia nitrogen concentration at the Zian section also shows deterioration. Using a DPSIR (Driving forces, Pressures, State, Impacts, Responses) framework, the study elucidates the relationship between environmental and socio-economic issues. Results indicate that population changes, industrial development, and water resource management have complex ecological impacts. Evaluating the urban water resource carrying capacity with the entropy weight method and correlation coefficient weighting method, the study finds that increasing forest coverage, improving wastewater treatment efficiency, and reducing COD emissions are crucial. Quantitative assessment of integrated protection and restoration projects involving mountains, rivers, forests, farmlands, lakes, and grasslands demonstrates their positive impact. This research reveals the interplay between the ecological environment and social factors, proposes practical restoration measures, and clarifies project effects, providing reliable decision-making schemes for policymakers. [ABSTRACT FROM AUTHOR]

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]

The Han River Ecological Economic Belt (HREEB) has a substantial amount of water resources; however, its distribution is uneven, and issues such as seasonal and engineering water shortages are prevalent. This necessitates a thorough assessment of the current water resource situation and trends in water resource carrying capacity (WRCC) to provide scientific support for the rational allocation of water resources. This study employed the RAGA-PP model to establish a WRCC evaluation index system composed of four subsystems: water resources, economy, society, and the ecological environment. The WRCC of the 17 major cities in the HREEB was evaluated from 2008 to 2022. The differentiation method was introduced to compare the reliability of the RAGA-PP model with three evaluation methods: the entropy weight TOPSIS method, the rank sum ratio method, and the principal component analysis method. In addition, an obstacle degree model was introduced to analyze the factors influencing WRCC enhancement. The results indicated the following. (1) In the differentiation test of the four models, the RAGA-PP model was found to have the highest differentiation value, and the results showed that it was more reliable in the WRCC evaluation of HREEB. (2) WRCC in the HREEB underwent significant changes between 2008 and 2022. (3) The WRCC in Shiyan and Wuhan, which are located in the eastern part of the HREEB, were high in Hubei, low in four cities in Henan, and satisfactory in three cities in Shaanxi. (4) The carrying capacity of the subsystems of the cities in the HREEB exhibited fluctuating changes with obvious internal variations. (5) The problems in the WRCC guideline layer were consistent across all cities in the HREEB, with limited per capita water resources being the primary issue in the indicator layer. Assessing WRCC is essential for achieving sustainable water resource use and high-quality regional development. [ABSTRACT FROM AUTHOR]

Water resource carrying capacity is indispensable for sustainable development, acting as a crucial determinant for harmonizing ecological preservation with socio-economic development. This study centers on Hubei Province, which is an important water conservation area in the Yangtze River Basin and is one of the core water source areas for the South-to-North Water Diversion Project, and evaluates the water resource carrying capacity of the three major urban agglomerations in Hubei Province from 2005 to 2020 based on the four dimensions of water resources, economics, society, and ecology, using the entropy weighting method and the TOPSIS model to construct an evaluation index system. We then employ the kernel density estimation method, ArcGIS visualization, and the Dagum Gini coefficient method to perform a comprehensive analysis of spatial and temporal differences, dynamic evolution, and contribution sources. The results show that (1) the water resource carrying capacity of Hubei Province as a whole increased from a severe overload to overload level during the study period. The water resource carrying capacity of the three major urban agglomerations shows a regional distribution pattern where the Yi-Jing-Jing-En agglomeration's capacity surpasses that of the Wuhan urban agglomeration, which is bigger than Xiang-Shi-Sui-Shen urban agglomeration. A lower ecological water use rate primarily constrains the enhancement of the carrying capacity of water resources in Hubei Province. (2) The kernel density estimation reveals an increase in the overall water resource carrying capacity across Hubei Province's three major urban agglomerations during the study period, alongside a pronounced trend towards polarization. (3) While the overall Gini coefficient, indicating an imbalance in water resource carrying capacity in Hubei Province, remains high, it demonstrates a declining trend, suggesting a growing disparity in water resource carrying capacity across the province's three major urban agglomerations. Hubei Province's water resource carrying capacity faces challenges of an overall imbalance and localized vulnerability. Strategies should aim to enhance synergy, address these deficiencies directly, and devise targeted measures tailored to the distinct features of various urban clusters. [ABSTRACT FROM AUTHOR]

Assessment and analysis of water resource carrying capacity (WRCC) can provide practical guidance for regional water resources planning and management. Taking Anhui Province as an example, an evaluation indicator system is established from five aspects: water resource, society, economy, eco-environment and disaster, entropy weighting method and CRITIC method is combined to calculate the comprehensive weight of indicators. The GRA-TOPSIS model is adopted to evaluate regional WRCC, and the obstacle diagnosis model is used to identify the main factors limiting the improvement of WRCC. Additionally, this study analyzes the spatio-temporal changes of water resource, water resource use efficiency and population, and also examines whether the frequent drought disasters in Anhui Province pose a significant threat to the WRCC. The results show that: (1) The overall WRCC in Anhui Province shows a fluctuating upward trend, with a widening disparity among cities, particularly in southern Anhui Province. (2) Per capita water resources, surface water resources, groundwater resources, urbanization rate, per capita GDP, ecological water consumption and forest coverage rate are the main obstacles for the indicator layer, water resource is the main obstacle for the subsystem layer. (3) The spatio-temporal distribution of water resources in Anhui province is uneven, but the utilization efficiency of water resources is increasing year by year, and drought disasters impact the WRCC in Anhui Province but do not pose a significant threat. This study can provide scientific reference for the development and transformation mode of different regions in Anhui Province and realize the “five-in-one” sustainable development. [ABSTRACT FROM AUTHOR]

Copyright of Pearl River is the property of Pearl River Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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.

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.

Water scarcity has significantly hampered China's economic, social, and environmental development. Ensuring sustainable water utilization is crucial given the mounting water stress accompanying continuous economic growth. A quantitative water resource forewarning model was constructed using the vector autoregressive (VAR) model. By analyzing the key indicators related to water systems and GDP data from 2001 to 2022, the VAR model revealed the long-term dynamic correlation between water consumption and economic growth using generalized impulse response, co-integration, and predictive variance decomposition analyses. The results revealed the presence of a long-term equilibrium between water consumption and economic growth, with a stable co-integration relationship and an optimal lag period of one year. The positive impact of water consumption on economic development increased during the 2001–2022 period, indicating a rising dependence of GDP on water resources. Water usage rose with economic development, while the water resource carrying capacity remained high and continued to grow. Based on the generalized impulse response, co-integration, and predictive variance decomposition analyses, this study predicted water-use-related indicators, providing vital early warnings for China's water environment carrying capacity from 2023 to 2050. This enabled informed decision-making and fostered sustainable water management practices for the future. [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]

Most existing evaluation frameworks for water resource carrying capacity (WRCC) neglect the interdependencies between subsystems. To fill this gap, we introduce a dynamic qualitative comparative analysis (QCA) model to evaluate WRCC and apply it to a vital economic development corridor, the Yangtze River Economic Belt (YREB). Ecological, social, and economic subsystems are defined as condition subsystems, while the water resource subsystem is defined as the outcome subsystem. The entropy weight method is used to calculate and calibrate the comprehensive score of each subsystem. By analyzing the necessity of a single condition subsystem and the sufficiency of condition subsystem configuration via a dynamic QCA, we qualitatively analyze the impact extent and pathways of the ecological, social, and economic subsystems on the water resource subsystem within the WRCC framework. The results reveal generally stable water resource levels despite regional variances, thereby pinpointing the influence pathways, including ecological–social and ecological–economic configurations. The 2011–2015 period saw poor stability, which subsequently improved until 2019 before declining in 2020 in the YREB. The middle-reach urban cluster showed the highest stability, which was less impacted by condition subsystems. These findings could enable provinces and municipalities to tailor policies and enhance subsystem levels for better water resource management.

The Han River Ecological Economic Belt (HREEB) has a substantial amount of water resources; however, its distribution is uneven, and issues such as seasonal and engineering water shortages are prevalent. This necessitates a thorough assessment of the current water resource situation and trends in water resource carrying capacity (WRCC) to provide scientific support for the rational allocation of water resources. This study employed the RAGA-PP model to establish a WRCC evaluation index system composed of four subsystems: water resources, economy, society, and the ecological environment. The WRCC of the 17 major cities in the HREEB was evaluated from 2008 to 2022. The differentiation method was introduced to compare the reliability of the RAGA-PP model with three evaluation methods: the entropy weight TOPSIS method, the rank sum ratio method, and the principal component analysis method. In addition, an obstacle degree model was introduced to analyze the factors influencing WRCC enhancement. The results indicated the following. (1) In the differentiation test of the four models, the RAGA-PP model was found to have the highest differentiation value, and the results showed that it was more reliable in the WRCC evaluation of HREEB. (2) WRCC in the HREEB underwent significant changes between 2008 and 2022. (3) The WRCC in Shiyan and Wuhan, which are located in the eastern part of the HREEB, were high in Hubei, low in four cities in Henan, and satisfactory in three cities in Shaanxi. (4) The carrying capacity of the subsystems of the cities in the HREEB exhibited fluctuating changes with obvious internal variations. (5) The problems in the WRCC guideline layer were consistent across all cities in the HREEB, with limited per capita water resources being the primary issue in the indicator layer. Assessing WRCC is essential for achieving sustainable water resource use and high-quality regional development.

The water resource carrying capacity (WRCC) system comprises multiple complex and non-linear interactions related to society, economy, water resources, and the water environment. A comprehensive comprehension of its internal mechanisms is essential for the continual enhancement of the regional WRCC. This study concentrates on the temporal and spatial variability of the WRCC to investigate a method for dynamic successive assessment. Firstly, the pressure–state–response (PSR) framework is used to develop a systematic and causal indicator system. Then, the variable fuzzy pattern recognition (VFPR) model and an analytic hierarchy process—entropy (AHP-E) model are combined to successively and dynamically assess WRCC. The proposed method is applied to the dynamic successive assessment of WRCC in Hebei Province, and it is obtained that the poor water resource carrying capacity in Hebei Province is mainly due to the basic attribute of the decision on the water resource shortage, but Hebei Province actively adopts a variety of measures to save water and pressurize mining, which has made the province's water resource carrying capacity tend to become better gradually. Simultaneously, a system dynamics model (SD) for water resource carrying capacity was established based on an analysis of the model structure. Moreover, three scenarios were designed, including existing continuation, high-efficiency water saving, and cross-regional water transfer. Subsequently, each scenario is further categorized into high- and low-speed economic development and population growth schemes. Afterward, simulations and predictions were conducted for a total of six schemes spanning from 2023 to 2030. The results indicate that if the current development model is adopted, the water resource carrying capacity will continue to maintain low levels. It was concluded that the high-speed development of the economy and population, the efficient water conservation, and the interbasin transfer scenario (scenario 2 with high speed) are the best choices for the sustainable development of water resources and social economy in Hebei. [ABSTRACT FROM AUTHOR]

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.

As the increasing population and rapid urbanization, the pressure on water resources has increased and water environment problems have become more serious. Traditional water resource management methods can no longer meet current and future needs, and new models need to be found. The gray water purification and reuse is an effective water-saving measure. Therefore, based on the regional water consumption and ash water pollution, the assessment model of water resource carrying capacity in this area is established. Then, it improves the elimination rate of gray water, increases the return flow of gray water resources, and thereby increases the carrying capacity of water resources. Finally, performance testing and simulation application analysis are carried out on the model. The results denote that the maximum error in the calculation of population carrying capacity of the model is 2%, with a fitness of about 99%. The stability of different environmental data testing is close to 100%, and the running time of data in D and F is about 30 and 10 min, respectively. And it is predicted that by 2040, when the gray water treatment rate in a certain region reaches 0.93 or above, the predetermined water resource carrying capacity of the region can be achieved. Based on the above data, it demonstrates high accuracy and adaptability, and can efficiently calculate the regional population resource carrying capacity. It has certain reference significance for further promoting the scientific and standardized management of gray water resources. [ABSTRACT FROM AUTHOR]

This study employs the Driving Force–Pressure–State–Response (DPSR) framework to establish an evaluation index system for the water resource carrying capacity (WRCC) in the Cele–Yutian Oasis (China). Utilizing the TOPSIS and obstacle degree models, we analyze the trends in the WRCC and its main hindrance factors in the Cele–Yutian Oasis from 2005 to 2020. Additionally, we employ the Markov model to investigate the dynamic changes in the land use types. The findings reveal that the most unfavorable WRCC status occurred in 2007, with a Grade IV rating (a mild overload). By 2020, the WRCC improved to a Grade III rating (critical), indicating a positive trajectory. However, persistent challenges for water resources remain, with a prolonged critical state. Over the past 15 years, the grassland area has decreased by 15.18%, and the forest area has decreased by 50%. The dynamic degree of grassland, forests, and water bodies is negative, signifying shifts to other land types, with water bodies undergoing the most significant change at −10.16%. Based on the outcomes of these two models, we propose regionally tailored measures to support sustainable development. These research results provide a scientific foundation for optimal water resource allocation and sustainable development in the Cele–Yutian Oasis Economic Belt. [ABSTRACT FROM AUTHOR]

This study conducted a comprehensive analysis of the spatial and temporal variations of water resource carrying capacity (WRCC) and its influencing factors in the significant Yellow River Basin in China. Combining the composite weighting TOPSIS method with geographic detector analysis, the water resource carrying capacity index for nine provinces within the Yellow River Basin was evaluated from 2005 to 2021. The results reveal a continuous upward trend in water resource carrying capacity in the Yellow River Basin, with significant improvements attributed to increased investment in scientific research, enhanced water use efficiency, proactive water resource management, and environmental protection measures. The study also identified differences in water resource carrying capacity among provinces, highlighting the significant impact of factors such as economic development, population density, industrial wastewater discharge, and precipitation. The findings underscore the importance of balancing economic growth with environmental protection. Specifically, Inner Mongolia and Ningxia provinces showed remarkable progress, while Qinghai and Sichuan provinces exhibited slower growth, primarily due to geographical location and industrial development status. Based on these findings, it is recommended that research investment be strengthened, economic structures be optimized, water resource management be improved, and environmental protection measures be enhanced. [ABSTRACT FROM AUTHOR]

[Objective] The water resource carrying capacity of Yulin City, Shaanxi Province, was studied in order to provide a scientific reference for the development and utilization of water resources and regional coordinated development. [Methods] An evaluation system was constructed from the perspective of water-economy-society-ecology. Analytic hierarchy process, entropy, and TOPSIS methods were used to evaluate the carrying capacity of water resources in Yulin City. Coupled coordination degree and obstacle degree models were introduced to analyze the regional coordinated development level and the main obstacles to carrying capacity. Evolution analysis and prediction of carrying capacity were conducted based on development planning. [Results] The water resource carrying capacity indices of all districts and counties in Yulin City were at medium and weak levels, while the development of Yuyang District, Shenmu County, and Dingbian County were not coordinated. High population density and high agricultural water consumption were the main obstacles to increasing carrying capacity in Yuyang District. Ecological environment water demand was the main obstacle factor in Shenmu County. Weak water resources background, low availability, and soil erosion were the main obstacles limiting the carrying capacity of eastern counties. The overall regional water resource carrying capacity in 2020 has increased since 2016. Under future economic and social development and the implementation of water diversion projects, the water resource carrying capacity indices of Yuyang District, Shenmu County, Fugu County, and Hengshan County are expected to increase, while the water resource carrying capacity indices of other districts and counties are expected to weaken because of economic and social development and other factors. [Conclusion] Water resource carrying capacity and regional coordinated development in Yulin City are somewhat fragile and unbalanced. Therefore, it is necessary to further adjust the water use structure, optimize the allocation of water resources, and make coordinated plans to protect the water-food-safety-ecological resources.

Water scarcity has significantly hampered China’s economic, social, and environmental development. Ensuring sustainable water utilization is crucial given the mounting water stress accompanying continuous economic growth. A quantitative water resource forewarning model was constructed using the vector autoregressive (VAR) model. By analyzing the key indicators related to water systems and GDP data from 2001 to 2022, the VAR model revealed the long-term dynamic correlation between water consumption and economic growth using generalized impulse response, co-integration, and predictive variance decomposition analyses. The results revealed the presence of a long-term equilibrium between water consumption and economic growth, with a stable co-integration relationship and an optimal lag period of one year. The positive impact of water consumption on economic development increased during the 2001–2022 period, indicating a rising dependence of GDP on water resources. Water usage rose with economic development, while the water resource carrying capacity remained high and continued to grow. Based on the generalized impulse response, co-integration, and predictive variance decomposition analyses, this study predicted water-use-related indicators, providing vital early warnings for China’s water environment carrying capacity from 2023 to 2050. This enabled informed decision-making and fostered sustainable water management practices for the future.

The breadth and range of water activities in China have expanded along with the social economy's and population's ongoing expansion. In this environment, people are attach importance to water resources. The target area for this study is Anhui Province. To conduct a detailed analysis of the water resource carrying capacity of the region and use its evaluation results to promote the development of the regional economy, this research first explained the relevant connotation of water resources. After that, a methodology for assessing the carrying capacity of water resources that uses Logistic Grey Correlation Analysis was constructed. This study will use the constructed model to assess the water resource carrying capacity of various regions in Anhui Province in the recent past. The carrying capacity of water resources was dynamically evaluated, and the findings indicate the correlation analysis model can clearly display the situation of water resource carrying capacity in various regions of Anhui Province. Furthermore, by utilizing digital transformation technology, the government can achieve a better performance in predicting and allocating carrying capacity of water. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of Soil & Water Conservation is the property of Bulletin of Soil & Water Conservation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The middle reaches of Yangtze River Basin (MYRB) are rich in water resources, with a large number of rivers and lakes. However, in recent years, water resources from this basin are no longer sufficient to support the region's rapid economic development. This study established a model to evaluate the water resource carrying capacity incorporating water resources, population, and socio-economic data. The characteristic values of water resource carrying capacity were calculated using the variable fuzzy evaluation method in MYRB from 2005 to 2020. Although both population and GDP in the MYRB showed an increasing trend between 2005 and 2020, the water supply capacity increased and then decreased. The weights of each index for evaluating the water resource carrying capacity of perennial botanical gardens were as follows: degree of water resource development (0.311) > total water resources (0.24) > population density (0.156) > GDP per capita (0.097) > water resources per capita (0.077) > water supply per capita (0.064) > water resources per unit area (0.055). Furthermore, the water resource carrying capacity in the MYRB showed an increasing trend from 2005 to 2020. In 2020, the carrying capacity of water resources in Changsha, Jingmen, Xiangtan, Hengyang, Wuhan, Xiaogan, Nanyang, and Xiangyang was attributed an evaluation grade of level 3, which indicates that the development and utilization of water resources in these areas were at their saturation point. [ABSTRACT FROM AUTHOR]

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.

The water resource carrying capacity (WRCC) system comprises multiple complex and non-linear interactions related to society, economy, water resources, and the water environment. A comprehensive comprehension of its internal mechanisms is essential for the continual enhancement of the regional WRCC. This study concentrates on the temporal and spatial variability of the WRCC to investigate a method for dynamic successive assessment. Firstly, the pressure–state–response (PSR) framework is used to develop a systematic and causal indicator system. Then, the variable fuzzy pattern recognition (VFPR) model and an analytic hierarchy process—entropy (AHP-E) model are combined to successively and dynamically assess WRCC. The proposed method is applied to the dynamic successive assessment of WRCC in Hebei Province, and it is obtained that the poor water resource carrying capacity in Hebei Province is mainly due to the basic attribute of the decision on the water resource shortage, but Hebei Province actively adopts a variety of measures to save water and pressurize mining, which has made the province’s water resource carrying capacity tend to become better gradually. Simultaneously, a system dynamics model (SD) for water resource carrying capacity was established based on an analysis of the model structure. Moreover, three scenarios were designed, including existing continuation, high-efficiency water saving, and cross-regional water transfer. Subsequently, each scenario is further categorized into high- and low-speed economic development and population growth schemes. Afterward, simulations and predictions were conducted for a total of six schemes spanning from 2023 to 2030. The results indicate that if the current development model is adopted, the water resource carrying capacity will continue to maintain low levels. It was concluded that the high-speed development of the economy and population, the efficient water conservation, and the interbasin transfer scenario (scenario 2 with high speed) are the best choices for the sustainable development of water resources and social economy in Hebei.

The Yellow River basin (YRB) plays an important role in China's economic and social growth. Based on different dimensions, we adopted the radial basis function (RBF) neural network model and the obstacle degree model to examine the water resource carrying capacity (WRCC) of the YRB. From 2005 to 2020, the WRCC of the entire YRB, as well as the upstream and midstream regions, improved, but the WRCC of the downstream region remained poor, revealing spatial differences. The overall improvement in the WRCC of the Yellow River's nine provinces is good, but the WRCC of Inner Mongolia and Henan is poor, suggesting regional differences. From the standpoint of obstacle factors, the development and usage rate of surface water resources are the main challenges. In 2020, the obstacle degree of the YRB reached 87.4871%. The irrigated area rate in Gansu was the primary obstacle factor, and the obstacle degree reached 73.0238%. Qinghai's industrial aspects mostly hindered the improvement of its WRCC, with an obstacle degree of 31.36%. The results provide a theoretical reference for the high-quality development of the YRB. [ABSTRACT FROM AUTHOR]

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. [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]

This study employs the Driving Force–Pressure–State–Response (DPSR) framework to establish an evaluation index system for the water resource carrying capacity (WRCC) in the Cele–Yutian Oasis (China). Utilizing the TOPSIS and obstacle degree models, we analyze the trends in the WRCC and its main hindrance factors in the Cele–Yutian Oasis from 2005 to 2020. Additionally, we employ the Markov model to investigate the dynamic changes in the land use types. The findings reveal that the most unfavorable WRCC status occurred in 2007, with a Grade IV rating (a mild overload). By 2020, the WRCC improved to a Grade III rating (critical), indicating a positive trajectory. However, persistent challenges for water resources remain, with a prolonged critical state. Over the past 15 years, the grassland area has decreased by 15.18%, and the forest area has decreased by 50%. The dynamic degree of grassland, forests, and water bodies is negative, signifying shifts to other land types, with water bodies undergoing the most significant change at −10.16%. Based on the outcomes of these two models, we propose regionally tailored measures to support sustainable development. These research results provide a scientific foundation for optimal water resource allocation and sustainable development in the Cele–Yutian Oasis Economic Belt.

Global climate change and human activities are increasingly affecting the regional water resource carrying capacity (WRCC). For sustainable development, an important social challenge is understanding the carrying level of regional water resources. In this study, to assess the WRCC status, we used a fuzzy comprehensive evaluation model and combined the natural and social attributes of WRCC. Moreover, from the three dimensions of support force subsystem, pressure force subsystem (PFS), and regulation force subsystem (RFS), 12 evaluation indicators were selected. Furthermore, using the fuzzy comprehensive theory and natural and social comprehensive indicators, we constructed a WRCC-level evaluation model and used it to evaluate the carrying level of two typical cities in China, Shijiazhuang and Langfang, for the 2006–2015 period. The results demonstrate that the regional water-carrying status of each of these cities is slightly above that of WRCC and that carrying levels show an interannual increasing trend. Note that, in both cities, the primary reason for the low regional WRCC is water shortage, while PFS improvement, supported by an interannual PFS increasing trend during the same time period, is the primary reason for carrying-level improvement for both cities in the past 10 years. For the RFS dimension, evaluation scores were in the range of 2.14–2.98 for Shijiazhuang and 2.12–2.79 for Langfang. Furthermore, the evaluation model and the indicator system demonstrated complementary functionality; thus, our results have an important academic value, particularly with reference to evaluating the WRCC. HIGHLIGHTS This paper is a good initiative to provide a methodology to evaluate the water resource carrying capacity.; For the regional management of water resources, our study provides both the theoretical basis and data support.;

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.

Water resource carrying capacity (WRCC) is an important index for measuring the relations between water resource systems and socio-economic-environmental development. In view of the difficulty in describing the complex and nonlinear relationships between the WRCC and indicators using traditional methods, this study introduces deep learning theory and proposes a novel deep neural network named WRCC-Net for WRCC assessment. Unlike typical network structures, we constructed a hierarchical structure that can indicate the index system in WRCC evaluation. Furthermore, we utilized a residual learning technique to increase the network depth for fitting the complex relationship between the WRCC state and indicators. The proposed deep learning method was applied to solve the real-world WRCC problem by taking the Yunnan province (Southwest China) as the case area. The WRCC was assessed from the following five dimensions: the water resources, social, economic, ecological environment, and coordination subsystems. Performance evaluation shows the advantages of the proposed WRCC-Net over the typical deep feed-forward network and shallow methods. Therefore, the proposed method provides a new way of evaluating the WRCC state and has potential for WRCC research. Overall, the WRCC evaluation using the WRCC-Net shows that the state of the WRCC in Yunnan constantly decreased from 2008 to 2018. These central-eastern areas in the Yunnan province, such as Kunming, Qujing, and Yuxi, are under an unfavorable capacity state. Measures, such as improving water resources management and increasing water utilization efficiency, should be considered in water resource planning in Yunnan province for the sustainable development of water resources. [ABSTRACT FROM AUTHOR]

The water resource carrying capacity (WRCC) is a carrying capacity of natural resources. It affects the application and expansion of the carrying capacity of water resources. This subject involves various elements, such as water resources, the ecological environment system, humans and their economic and social systems, and a wider range of biological groups and their survival needs. Based on the objective recognition of the complex relationship between the water resource system, ecological environment system, and economic and social system, the support scale of water resources and the ecological environment for economic and social development is studied. Current research on the carrying capacity of water resources has mostly shifted from the previously limited support capacity of water resources to include factors such as the population, economy, and ecology, establishing the internal relationships between the economics, water resources, and ecological environment. This reflects the comprehensive carrying capacity of the entire region (or river basin) of water resources and the ecological environment system on an overall economic and social scale. Based on the conceptual connotation of the WRCC and the actual problems facing water resources in Henan Province, the paper uses a system dynamics method to develop information feedback between the four subsystems of Henan Province: economic, population, water resource, and water environment subsystems. The index system of the WRCC in Henan Province is also determined. The weight of each index is comprehensively determined by a combination weighting method of the analytic hierarchy process and an entropy weight method, and then a fuzzy comprehensive evaluation method is used to evaluate the WRCC of Henan Province under four different development models. The validation period of the model is 2010–2020, and the forecast period is 2021–2030. The results indicate that during the period 2021–2030, the WRCC of Henan Province showed a slight upward trend overall under the four models, but the increase rates were different under the different models. Among the four models, the comprehensive model's benefit was the best, which not only maintained the healthy and stable development of the economy and society but also improved the pressure on the water resources and the quality of the water environment. [ABSTRACT FROM AUTHOR]

The water resource carrying capacity (WRCC) in river basin changes dynamically under climate change, economic development, and technological advancement. Climate change affects hydrological processes and spatial/temporal distribution of water resources; while economic development and technological advancement can also affect the balance of water resources systems. Under climate change, economic development, and technological advancement, it is of great significance to explore the dynamic behavior of WRCC in river basins. This will help to alleviate water resources security issues and build a sustainable water resources system. This study was carried out to evaluate the dynamic WRCC using the “climate, economics, and technology-control objective inversion model”, which used total water consumption, water-use efficiency, and restrained total pollutant control in the water functional area as boundary conditions. This study was conducted on the Keriya River Basin, a sub-catchment located in southern margin of the Taklimakan Desert. The WRCC in the Keriya River Basin in 2015 was calculated, and the trends in the short term (2020), middle term (2030), and long term (2050) were predicted. The results revealed that climate change factors have a positive effect on WRCC in the Keriya River Basin, which leads to an increase in total water resources. Economic and technological development exhibits an overall positive effect, while increasing in water consumption and sewage discharge exhibit a negative effect.

• 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 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.

Water shortage and water pollution have become the key factors restricting the sustainable development of animal husbandry in China. In this study, the water footprint model was used to analyze the water resource carrying capacity and water environment bearing pressure of animal husbandry in 31 provinces of China from 2001 to 2019. The findings indicate that: (1) The development of animal husbandry has exacerbated the regional water deficiency problem. Shandong, Henan, Hebei, and Liaoning have become the most serious water deficit areas of animal husbandry in China. The decreasing water resource carrying capacity indicates that water resources are difficult in supporting the growth of animal husbandry; (2) the change of animal feeding structures has led to the decrease of gray water footprint and the alleviation of the water environment bearing pressure; however, the water environment of animal husbandry in northern China and the northwest is still overburdened, which poses a major challenge to the control of agricultural non-point source pollution; (3) furthermore, according to the spatial and temporal characteristics of the water resource carrying capacity and water environment bearing pressure, the main livestock-producing areas in the north are facing a profound “water-livestock” contradiction and showing an increasing trend. The research results will help decision-makers to adjust the development mode of animal husbandry, optimize resource allocation, and promote the sustainable development of resource-saving and environment-friendly animal husbandry.

China is facing great challenges to balance its natural water resource use and eco-environment protection, especially in the north semi-arid region with large water consumption due to the rapid economic growth. This highlights the urgency to use water resource carrying capacity (WRCC) as a measure to maintain the sustainable development of the human and natural water system. Here, we used a coupled model based on the system dynamics and cellular automaton models to assess the WRCC under the critical value of water resource withdrawal ratio (40%) and its sustainability in the Yongding River watershed in Beijing-Tianjin-Hebei region, where the water use highly depends on river flow and nonrenewable groundwater resources. The analytical results showed that the current regional WRCC is severely overloaded due to strong human activities. The predicted results based on four scenarios, i.e., existing development, water saving, industrial restructuring, and integrated development schemes, showed that although the improvement of water saving and water use efficiency has mitigated the regional water shortage, evidenced by the increased WRCC, the water shortage would continue due to the increased water demand. Under the integrated development scenario, it will need at least additional 7.1 × 108 m3 water per year (Beijing: 2.5 × 108 m3, Tianjin: 0.8 × 108 m3, Hebei: 3.8 × 108 m3) via the water transfer project to maintain the sustainability in the next decades. Our research provides recommendations for reasonable water utilization and supplementation under the severe water crisis. [ABSTRACT FROM AUTHOR]

Water resource carrying capacity (WRCC) is of great importance to assess the maximum capacity of water resource and scientifically evaluate for sustainable development of economic. This study proposes a chicken swarm optimization-projection pursuit evaluation (CSO-PPE) model, to assess the WRCC of Shaanxi province of China for the period of 2007–2016. The effectiveness of CSO was firstly demonstrated using four typical functions. Then, the CSO-PPM model is used to assess WRCC, and the results were compared with other three algorithms including the particle swarm optimization (PSO), firefly algorithm (FA), and seeker optimization algorithm (SOA). An evaluation index system was established based on the drivers-pressure-state-impact-response-management (DPSIRM) model. The results showed that the WRCC has gradually increased from 2007 to 2016. In addition, the southern and northern regions of Shaanxi province had higher water resource carrying capacity with respect to that of Guanzhong region of Shaanxi province. Additionally, the results also indicated that this evaluation method is feasible for assessing WRCC in Shaanxi province of China, which provide a scientific basis for assessing regional WRCC in other places. [ABSTRACT FROM AUTHOR]

With the rapid economic development in the past decades, industrialization and urbanization in China has also rapidly developed and will continue in the next decades. However, the regional water shortage has posed great challenges for the sustainable development of big cities especially in north China. Here, we used the water ecological footprint model combined with the system dynamic model to assess the water resource carrying capacity and its sustainability in Zhangjiakou City, a typical water shortage city in north China. The calculated results showed that irrigation was the largest water consumer in Zhangjiakou. There existed a clear gap between water supply and water consumption in this city and such a gap is demonstrated by the high water resource pressure index. Our predicted results based on the water resource ecological footprint and the system dynamic model showed that although the improving water use efficiency has relieved the regional water shortage pressure, the efficiency gained would be to a large degree offset by increased water demands due to the increasing economic development. The annual average water shortage in Zhangjiakou in 2007–2050 would be up to 8.53 × 108 m3, nearly half of the total local average annual water resource. To deal with the severe water shortage over the next three decades, great attention should be paid to scientific water resource managements and water pollution control. This research provides a long-term view of water resource pressure and provides recommendations for a sustainable water use under the rapid regional socioeconomic development. [ABSTRACT FROM AUTHOR]

In view of the large spatial difference in water resources, the water shortage and deterioration of water quality in the Chang-Ji Economic Circle located in northeast China, the water resource carrying capacity (WRCC) from the perspective of time and space is evaluated. We combine the gray correlation analysis and multiple linear regression models to quantitatively predict water supply and demand in different planning years, which provide the basis for quantitative analysis of the WRCC. The selection of research indicators also considers the interaction of social economy, water resources, and water environment. Combined with the fuzzy comprehensive evaluation method, the gray correlation analysis and multiple linear regression models to quantitatively and qualitatively evaluate the WRCC under different social development plans. The developmental trends were obtained from 2017 to 2030 using four plans designed for distinct purposes. It can be seen that the utilization of water resource is unreasonable now and maintains a poor level under a business-as-usual Plan I. Plan II and Plan III show that resource-based water shortage is the most critical issue in this region, and poor water quality cannot be ignored either. Compared with Plan I, the average index of WRCC in Plan IV increased by 51.8% and over 84% of the regions maintain a good level. Strengthening sewage treatment and properly using transit water resources are more conducive to the rapid development of Chang-Ji Economic Circle.

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.

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]

Currently, climate change is regarded as one of the most important global environmental problems in the world. Future climate change may further exacerbate the contradiction between supply and demand of water resources in China, and affect water resources carrying capacity. This paper, based on the summary of the water resources carrying capacity researches, systematically expounds the concept and connotation of water resources dynamic carrying capacity, and puts forward its calculation theoretical frames and PSO-COIM method (namely the Prediction-Simulation-Optimization-Based Control Object Inversion Model). By constructing the ARIMAX dynamic regression forecasting model of the meteorological factors such as temperature, precipitation and runoff, the paper, taking Tarim River Basin, which is the largest continental river in China, as a typical example, analyses and calculates its water resources dynamic carrying capacity in future different level years under the three kinds of climate situation: RCP8.5, RCP4.5 and RCP2.6. The results of the calculation can clearly reflect the carrying scale of water resources under different climate situations, also determine its carrying levels in the future predicted economic and social development situation, as well as provide the basis for the sustainable development of Tarim River Basin. [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]