Regional Water Resources Carrying Capacity Research Articles

Coupling coordination and driving mechanisms of water resources carrying capacity under the dynamic interaction of the water-social-economic-ecological environment system

The water resources carrying capacity (WRCC) is a complex and comprehensive system that is jointly influenced by water resources, society, the economy and the ecological environment. Previous WRCC studies have primarily focused on estimating the overall level of regional WRCC. Few studies have explored the interactions among the various elements in the WRCC system and their influence on the WRCC evolution. Therefore, the purpose of this paper is, on the one hand, to explore the dynamic interactive relationships within the WRCC system from the perspectives of water resources, society, the economy and the ecological environment using a coupling coordination degree model and a panel vector autoregressive (PVAR) model, and on the other hand, to determine the evolutionary driving mechanism of the WRCC using the geographically and temporally weighted regression (GTWR) model to improve the regional WRCC. Taking 21 cities in Guangdong Province as an example, the results show that (1) the coupling coordination degree among the four WRCC subsystems in Guangdong Province shows an overall upward trend from 2009 to 2020, and the coordination between water resources utilization and other subsystems needs to be further strengthened. (2) The economic subsystem is the core of the WRCC system with reinforcing effects on both water resources and social subsystems but significant inhibitory effects on the ecological environment subsystem. Notably, the development of the ecological environment plays a crucial role in promoting social and economic development. (3) From 2009 to 2020, the development of the WRCC in Guangdong Province is initially driven by social and economic development, followed by economic development and ecological environmental protection, and then mainly by ecological environmental protection, which gradually becomes the primary driving force. This study provides a new entry point for studying the regional WRCC and formulating targeted measures for enhancing the regional WRCC.

Quantitative Diagnosis of Water Resources Carrying Capacity Obstacle Factors Based on Connection Number and TOPSIS in Huaibei Plain

To further quantitatively assess the water resources carrying capacity (WRCC) system and analyze and identify the regional water resources carrying state and the physical mechanism of the state change, WRCC and obstacle factor diagnosis were carried out. In this paper, we proposed the mobility matrix to determine the connection number components, considered the dynamic attributes of the difference degree coefficient, and calculated it using the semi-partial subtraction set pair potential and triangular fuzzy number, so as to construct the quantitative diagnosis method of regional WRCC obstacle factors based on the connection number and TOPSIS. The results applied to six cities in the Huaibei Plain showed that the WRCC fluctuated around grade 2 and was in a poor state, which was mainly due to the insufficient support force; the water resources carrying state of the six cities gradually improved from 2011 to 2018, but the state became worse in 2019, which was related to the low precipitation in that year, the reduction in water resources, and the high degree of water resource utilization. The WRCC of Fuyang and Huainan was worse than that of the other four cities; over the 9 years, the average grades of Fuyang and Huainan were 2.26 and 2.43, while those of Huainan, Bozhou, Suzhou, and Bengbu were 2.19, 2.12, 2.05, and 2.05, respectively. The key obstacles limiting the improvement in the WRCC of the Huaibei Plain were per capita water resources, annual water production modulus, per capita water supply, vegetation coverage ratio, utilization ratio of water resources, water consumption per 104 yuan value-added by industry, and population density. In time, the key obstacle factors in neighboring years generally tended to have similarity, and conversely appeared as a difference; in space, neighboring regions showed similarity and conversely presented as a difference. The results of this study can offer technical support and a decision-making basis for water resources management in the Huaibei Plain. The method constructed in this paper is extremely interpretive, easy to calculate, highly sensitive, and reliable in application results, which opens up a new perspective for the rational determination of the connection number and the difference degree coefficient and provides a new intelligent way to determine the state of a complex set pair system and its causal mechanism analysis and diagnosis of obstacle factors.

Analysis of Spatial and Temporal Evolution of Regional Water Resources Carrying Capacity and Influencing Factors—Anhui Province as an Example

The study of water resources carrying capacity is a crucial aspect of water resources ecological security research. To account for the interplay between regional natural conditions and economic and social factors, a natural–economic–social–environmental evaluation index system is established within the framework of water resources. The comprehensive index of water resources carrying capacity in Anhui Province is then calculated using the entropy weight method and CRITIC model. Spatial kernel density and Dagum analysis are employed to analyze the results. The findings indicate that (1) the overall water resources carrying capacity of Anhui Province has exhibited an upward trend from 2003 to 2021, with the overall index of water resources carrying capacity increasing from 0.34 to 0.49. (2) The presence of water resources carrying capacity polarization in Anhui Province is evident, although this trend has been diminishing in recent years. (3) The Gini coefficient of water resources carrying capacity in Anhui Province first increases and then decreases, with the Gini coefficient between groups being more pronounced than the Gini coefficient within groups. (4) Geospatial factors play a significant role in shaping the future spatial distribution of water resources carrying capacity in Anhui Province. Additionally, the interaction of water resources carrying capacity among neighboring areas contributes to the reduction of differences between water resources carrying capacity in different regions in the future.

Spatiotemporal heterogeneity and driving mechanisms of water resources carrying capacity for sustainable development of Guangdong Province in China

Sustainable water resources utilization is of great significance for sustainable socioeconomic development. Water resources carrying capacity (WRCC), as an important measurement, plays a vital role in guiding regional water resources management and sustainable utilization. Existing studies on WRCC are abundant, but in-depth studies on the multidimensional evolution of WRCC and its driving mechanism are still lacking. Therefore, taking Guangdong (GD) Province as a case, this study is aimed to propose a systematical WRCC research framework and attempts to explore the spatiotemporal heterogeneity of regional WRCC and reveal its evolutionary driving mechanisms. First, a simplified and effective WRCC index system is constructed through the correlation and contribution rate analysis to remove redundant information. Then, a coupled model consisting of an improved technique for order preference by similarity to ideal solution (TOPSIS) and grey relational analysis model is proposed to accurately evaluate WRCC. Last, the geographically and temporally weighted regression (GTWR) and geographical detector models are introduced to perform the driving analysis of WRCC. Results show that (1) from 2009 to 2020, the WRCCs of GD Province and its 21 cities all show an upward trend with the order of the WRCCs from high to low being northern GD, Pearl River Delta (PRD), eastern GD and western GD. (2) The main driving forces of WRCC in GD gradually shift from social and economic development to economic and ecological development. (3) Municipal sewage treatment rate, proportion of the tertiary industry and GDP per capita are the key driving factors of the GD WRCC. This study provides a new perspective for regional WRCC improvement and is greatly helpful to make differentiated management measures.

Comprehensive evaluation on water resources carrying capacity based on water-economy-ecology concept framework and EFAST-cloud model: A case study of Henan Province, China

Water is the basic need for human survival and the development of economy and ecology. Water resources carrying capacity (WRCC) modelling is a fundamental task to explore the interaction mechanism between economy-ecology development and water resources carrying system. To reasonably quantify the regional WRCC, an evaluation method based on Water-economy-ecology (WEE) concept framework and EFAST-Cloud model is proposed in this study, and Henan Province of China is selected as a typical study area. It can both identify the inter-feeding relationships between sub-systems and evaluate the proportion of each grade in detail by reflecting the randomness and fuzziness of the evaluation. A total of 15 indicators including water system, economy system, and ecology system are constructed. The study analyzes the sensitivity of indicators by using Simlab software and then calculates the weight of indicators by using EFAST method. Compared with other traditional methods, EFAST algorithm is a special method for model sensitivity analysis, which can fully consider the coupling effect between indicators. According to the statistical data of 2010, 2015, and 2020, the WRCC at the watershed scale and municipal scale in Henan Province are evaluated through the EFAST-Cloud model. At the watershed scale, the ecology system criterion layer performs best over the multiple years, the Huaihe and Yangtze River basin have better WRCC at the target layer. At the municipal scale, Xuchang, Luohe, and Zhumadian have better WRCC, Puyang, Zhoukou, and Jiaozuo are slightly worse. The results show that WRCC of the study area has shown an overall improvement, but there is still much space for its development. Therefore, targeted recommendations are made for the water, economy, and ecology system respectively. The conclusion of this paper can provide a reference for the government in making water resources management policies.

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

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

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

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

Spatial Equilibrium Evaluation of Regional Water Resources Carrying Capacity Based on Dynamic Weight Method and Dagum Gini Coefficient

With the rapid economic development and the acceleration of urbanization, the pressure on the water resources system is becoming intense. As an important indicator of water resources security and sustainable development, the water resources carrying capacity has become a hot issue. To overcome the limitation of commonly used methods for weight determination and to evaluate the regional water resources carrying capacity reasonably, the index weight determined by the Analytic Hierarchy Process method was revised by the subtraction set pair potential to calculate the dynamic index weight. Then, the dynamic weight was combined with the set pair analysis method to evaluate the regional water resources carrying capacity dynamically. In addition, the Dagum Gini coefficient and its decomposition method were used to analyze the overall difference of water resources carrying capacity in the whole region and the differences within and between subregions considering the lack of quantitative research in spatial equilibrium. Finally, a case study was carried out in Anhui Province, China. The results showed that from 2011 to 2018, most of the water resources carrying capacity for 16 cities in Anhui Province were in a critical state, with the strongest in the south of Anhui Province and the weakest in the north. The overall spatial difference of carrying capacity in Anhui Province showed an increasing trend from 2011 to 2018. Furthermore, the slightest difference within the subregion was in the north of Anhui Province, while the largest was in the south. The most significant difference between the subregions was between the south and the north of Anhui Province. The primary source of carrying capacity spatial difference in Anhui Province was from the difference between subregions. The results of the case study suggested that the method proposed in this paper are conducive to the early find of possible disadvantages of spatial equilibrium and can effectively identify the main source of regional spatial difference in water resources carrying capacity, which means that the method can be widely applied to similar issues.

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

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

Dynamic evaluation of regional water resources carrying capacity based on set pair analysis and partial connection number

Abstract In order to quantitatively evaluate and analyze regional water resources carrying capacity (WRCC) and to describe the micro motion between connection number components, a more applicable evaluation model was sought. Firstly, an evaluation index system and grade standards for a regional WRCC were constructed. Then, a method for determining the connection number was proposed, which considered the micro motion between the connection number components in the system structure. Finally, an evaluation model based on set pair analysis (SPA) and partial connection number (PCN) that used subtraction set pair potential (SPP) to identify vulnerability factors was built, and identification results were compared with the total partial connection number (TPCN). The model was applied to Huaibei City, Anhui Province, China. The results showed that: the WRCC grade value was between 2 and 3 which was poor; the support and regulation subsystem grade value was between 2 and 3, and the pressure subsystem grade value was between 1 and 2. SPP identified that the support force and regulation force subsystem were the vulnerable subsystems. Eight indexes, including water resources per capita, rate of ecological water consumption and density of population, were the main indicators causing the poor WRCC, which were in good agreement with the local measured data. In addition, the SPP and TPCN were compared to further verify rationality of the connection number determination method and reliability of the identification results. The model established in this paper has strong applicability and can also be used for the dynamic evaluation of other resources, including the environment and ecological carrying capacity. The results in this study provide a scientific basis for water resources management and decision-making.

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

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

Early Warning Method for Regional Water Resources Carrying Capacity Based on the Logical Curve and Aggregate Warning Index.

The sustainable utilization of water resources is a significant factor in the development of the national economy and society. Regional water resources carrying capacity (RWRCC) is an appropriate method for evaluating the balance in such utilization. In this paper, we combined time difference correlation analysis and set pair analysis firstly to identify the early warning sign index (EWSI) for RWRCC, and warning limits were determined using a logical curve. Analytic hierarchy process based on the accelerating genetic algorithm (AGA-AHP) method was used to improve the KLR model by determining weights objectively. We took advantage of the new improved model to build the aggregate warning index (AWI). Then, according to the corresponding relationship between EWSI and AWI, the early warning system for regional water resources carrying capacity (EWS-RWRCC) was established, and a case study was carried out in Anhui Province. The results showed there are eight effective EWSI obtained through the early warning analysis process of RWRCC in Anhui Province, among which the repetitive use rate of industrial water and average daily coefficient have a greater impact on AWI. Basically, the EWS-RWRCC can describe RWRCC changes in Anhui Province. From 2006 to 2014, more than half the signal lights in Anhui Province were yellow and orange, which indicated a poor state. It has been proved that the constraints of population, GDP growth and water supply capacity on the utilization of water resources in the future will be further tightened, which should be considered for future monitoring and early warning. The early warning method we used here can be widely applied into other fields; the results will enhance monitoring capacity and scientifically guide regional water resources management.

Application of Projection Pursuit Model to Water Resources Carrying Capacity Assessment in Longitudinal Ridge-gorge Region of Yunnan

Water resources carrying capacity (WRCC) assessment is an effective way to evaluate the coordinated development of water resources, economic society and ecological environment, thus, it is significant to study WRCC to realize the harmony among water resources, economy and society in region. In this paper, an index system for evaluating WRCC was constructed from the perspective of water quantity and water quality. Moreover, the projection pursuit technique was applied to evaluate WRCC. Based on the grade division standard of WRCC, the projection function which could reflect the variability of the WRCC was constructed, and genetic algorithm was introduced to optimize the function and seek the optimum projection vector, while the projection pursuit model to evaluation of WRCC was built by the data of the vector. WRCC of the 80 counties in Longitudinal Ridge-gorge Region of Yunnan was evaluated by this model, and the results which accord with the fact were gained. The result showed that WRCC is dynamic with evaluation index value was presented as the logistic curve. The WRCC in research region was good overall, but that in three counties and four counties was already in overload and nearly overload, respectively. Potential of WRCC in mid and western of research region was higher than the other area. The evaluation results were given with continuous real number, which could reveal the temporal-spatial change characteristics of WRCC accurately. Evaluation model of WRCC based on projection pursuit model was practical and feasible for dynamic evaluation of regional WRCC.

Study on Water Resources Efficiency with the Regional Water Resources Carrying Capacity into Consideration

Most of the existing studies on regional water resources efficiency only consider the total regional water use while ignoring the regional endowment. Therefore, it is essential to introduce the water resources carrying capacity into the study. Given that data envelopment analysis (DEA) cannot compare the time series of a single decision-making unit, we employ the DEA-window analysis to study China’s water resources efficiency during 2005–2012 with the regional carrying capacity being considered, and analyze the spatiotemporal evolution. The study shows that such efficiency has increased from 0.71 in 2005 to 0.79 in 2012. High water resources efficiency is observed in Liaoning, Tibet, Yunnan, Beijing, Tianjin, Shanghai, Jiangsu, Zhejiang, Guangdong and Sichuan, where the output levels and utilization ratios of water resources are positively correlated. Low water resources efficiency is observed in Henan, Shaanxi, Gansu, Ningxia and Xinjiang which feature high-level utilization and low carrying capacity of water resources. As for regional water resources efficiency, eastern and southern coastal regions rank first, followed by Northeast China and northern coastal regions, southwest and northwest regions of China and lastly the middle reaches of the Yellow and Yangtze Rivers. Therefore, policy-makers should not only accord the regional development with carrying capacity, but also enhance cross-regional industrial cooperation for coordinated development.

Comprehensive evaluation and scenario simulation for the water resources carrying capacity in Xi'an city, China

The quantity and quality of water resources are of great importance in maintaining urban socio-economic development. Accordingly, substantial research has been conducted on the concept of the water resources carrying capacity (WRCC). In this study, analytic hierarchy process (AHP) and system dynamics (SD) models were combined to construct a multi-criteria evaluation system of the WRCC and a socio-economic/water resources SD model for Xi'an. The developmental trends of the society, economy, water supply/demand, and wastewater discharge were obtained from 2015 to 2020 using five scenarios designed for distinct purposes; these scenarios and trends were comprehensively evaluated using a combination of qualitative and quantitative analyses. The results indicated that the WRCC (0.32 in 2020) in Xi'an will shift from a normal to a poor state if the current social development pattern is maintained; therefore, we conclude that the socio-economic development of Xi'an is unsustainable. However, under a comprehensive scheme, the WRCC index (0.64 in 2020) will increase by 48% compared with the WRCC index under a business-as-usual scenario. Further, some practical suggestions, including the promotion of industrial reforms and the improvement of water-use efficiency and recycling policies, were provided for improving the regional WRCC.

Forewarning Model of Regional Water Resources Carrying Capacity Based on Combination Weights and Entropy Principles

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.

Evaluation and Prediction of Regional Water Resources Carrying Capacity: A Case Study of Shandong Province

Growing pressure on the world’s water resources is having major impacts on us. In this paper, we discuss on water resources carrying capacity. We have a case study of Shandong Province which is one of the most arid regions in China. Considering the dynamics of water supply and demand, we combine the Falkenmark indicator and the binary dynamics model to establish an evaluation model of regional water resources carrying capacity. According to the result of our model, Shandong Province is heavily exploited. The per capita water resources in Shandong province were less than 300 m3 in the past ten years. The increasing destruction and increasing waste make the situation even worse. Then ARIMA model and BP neural network is combined to propose a prediction model. We use it to predict the supply and demand of water resources in Shandong Province in the next 15 years

Application of Fuzzy Pattern Recognition Model on the Regional Water Resources Carrying Capacity Evaluation

This article analyses the connotations of water resources carrying capacity and its evaluation method, Selecting 9 main factors as the evaluation indexes, combined with fuzzy pattern recognition model and apply this model to comprehensive evaluation of water resources in Erdos. The results show that current exploitation and utilization of water resources in this region has reached a considerable size, under the current economic and technical conditions, the bearing capacity of water resources in this region has been relatively small, water resources supply-demand contradiction is so urgent.

Evaluation of Regional Water Resources Carrying Capacity in Yan'an Based on Principal Component Analysis

Yan'an is the center of political, economic, cultural and military in Shanbei, and is also a city of water resources extremely shortage. This paper by using the principal component analysis to select 13 indicators and establish the indicators system, two main ingredients reflect Yan'an WRCC, thus evaluate Yan'an WRCC in 2006 - 2011 timing data. Results show that: rate of urbanization, ecological and environmental water use rate, per capita GDP, rate of water resources development and utilization and sewage treatment rate are the main factors affecting Yan'an WRCC; 2006-2011 Yan'an in the temporal distribution of WRCC overall downward trend, the development and utilization of water resources potential in Yan'an weaker. Finally put forward reasonable suggestions aim at future sustainable development and utilization of water resources in Yan'an.

Analysis and Assessment of the Regional Water Resources Carrying Capacity Model

Analysis and Assessment of the Regional Water Resources Carrying Capacity Model