Degree Of Water Pollution Research Articles

Flower-like boron-doped zinc single-atom nanozymes for colorimetric sensing and smartphone-assisted detection of Cr(VI)

With the development of electronics, electroplating, printing, and dyeing industries, environmental pollution caused by hexavalent chromium (Cr(VI)) has become increasingly prominent. Skin contact with Cr (VI) can cause allergies or genetic defects, and inhalation can cause cancer, which is a lasting danger to the environment and the human body. Developing effective strategies to monitor Cr(VI) in environmental water or industrial wastewater can evaluate the degree of water pollution and risk warning, thus helping to prevent the spread of Cr(VI) pollution, promote the protection of water resources and the ecological environment, and ensure human safety and sustainable development. On the basis of the regulation of dopamine, boron-doped zinc single-atom nanozymes (Zn/B-NC SAzymes) with three-dimensional nanoflower morphology were controlled in this work. The introduction of B in Zn/B-NC SAzymes and the high metal loading of Zn (6.5 wt%) led to the formation of more active sites, resulting in the material showing excellent enzyme-like activity. H2O2 decomposed to generate superoxide radicals under the catalysis of Zn/B-NC SAzymes, which then oxidized the substrate 3,3′,5,5′-tetramethylbenzidine (TMB) to generate blue oxTMB. When Cr(VI) was introduced into the sensor system, the color of blue oxTMB is deepened, and the colorimetric method of Cr(VI) was constructed. The linear range is 0.2–40 μM, LOD is 59 nM, and the visual detection of Cr (VI) is performed with the aid of the smartphone. This work not only provides experimental and theoretical guidance for understanding the active centers of Zn-SAzymes and their catalytic processes, but also provides a promising and alternative detection strategy for the rapid and even visual on-site detection of Cr(VI) in aquatic environments, which is of great significance for the control of Cr(VI) pollution in the environment and industrial wastewater.

“URBAN REHABILITATION IN RUSSIA BROOKS NO DELAY”: STATE AND SOCIETY IN THE FIGHT AGAINST RIVERS POLLUTION AT THE END OF THE 19th — EARLY 20th CENTURIES

At the turn of the 19th and20th centuries, the growth of urban population and development of urban infrastructure were accompanied by the emergence of environmental problems, including the increase of river pollution, which might cause water supply diffi culties. The central and local authorities, as well as representatives of various public, scientific, professional organizations and business circles, were involved in solving these problems. The order of their interaction could be diff erent, but these joint projects made it possible to achieve the best results in combating river pollution caused by industrial and domestic waste, to determine priorities in the system of water protection and to improve the supply of potable water to the population. Thanks to the activities of such organizations as the Society for Assistance to the Improvement and Development of Manufacturing Industry, Russian Water Supply Congresses, sanitary stations, and the Provisional Committee for the Development of Measures to Protect the Water Bodies of the Moscow Industrial District from Pollution, a rather extensive set of measures was carried out to study the properties, nature, and degree of water pollution in the rivers that served as sources of water supply for city dwellers, and the most eff ective methods of water purifi cation were determined in experiments. Practical recommendations were developed on the use of the most eff ective and cost-efficient methods and facilities for industrial wastewater treatment. The best domestic specialists were involved in solving the identified problems, who utilized international and Russian experience. The lack of sufficient funding for water protection activities resulted in some initiatives not being or being only partially implemented. In addition, a number of practical measures which had been planned in this area had to be postponed because of the outbreak of World War I in 1914

Investigating the impact of artificial intelligence development on water pollution in China

Analysing the impacts of AI development on water pollution is of great significance for improving water environment management measures and promoting global sustainable development. In this study, macro and micro panel data of China from 2008 to 2019 were used to measure the development level of AI at the industry and provincial levels in China, and a panel data regression model was constructed to analyse the effects of AI development on water pollution and regional heterogeneity. The measurement results show that the development level of AI is increasing. Among the six industries, the intelligence level of the manufacturing industry has developed the fastest, by approximately 48.74 times compared with the baseline. At the provincial level, Guangdong Province made the greatest progress in intelligence level, increasing by approximately 23.6 times. The regression results show that AI technology is helpful in reducing the level of water pollution, and this conclusion remains valid after the regression of instrumental variables and robustness testing. In terms of regional heterogeneity, AI technology can significantly reduce the degree of water pollution in eastern and western China. However, the development of AI technology in the central region has no significant impact on water pollution, and a risk of increasing the degree of water pollution exists. The reasons may be that the eastern region has high levels of economic vitality and technological innovation and a strong ability to transform AI achievements, which can significantly improve the water environment. Industrial support policies in the western region are strong, and the application of AI can quickly improve production methods and significantly reduce water pollution levels. In comparison, the levels of economic development, technological innovation, and policy support in the central region need to be strengthened, so the environmental effect of AI is not significant.

Analysis of methods for assessing the degree of water pollution

The most important modern methods for the monitoring of water bodies, their state of pollution and the assessment of water quality are considered. Commonly accepted, standard-ized methods for assessing water quality in water bodies include ground-based sampling, which is untimely and expensive under certain conditions. Best suited for practical use in large areas is the remote approach, which combines ground and satellite measurements to classify changes and detect pollution in closed water bodies. Satellite monitoring is a reliable tool for obtaining operational information on the state of water bodies and their changes with a certain periodicity, thanks to the use of a large set of heterogeneous data. And the availabil-ity of archived data becomes a significant advantage, opening up the possibility of comparing the results obtained and analyzing the factors influencing the state of water bodies and the environment. The paper describes the main methods and datasets that can be used for the ap-plication of remote monitoring methods based on machine learning. The use of Landsat mul-tispectral sensors, including TM (Thematic Mapper), MSS (Multispectral Scanner), ETM (Enhanced Thematic Mapper), and OLI (Operational Land Imager), is proposed as the main data set. Examples of the application of the remote sensing approach to the assessment of wa-ter pollution over large areas will be analyzed. Possible machine learning methods for solv-ing an applied problem are presented.

Rapid Determination of Escherichia coli Concentration in Water Using Multiwavelength Transmission Spectroscopy

Bacterial concentration is an important indicator to measure the degree of water pollution. Realizing rapid and accurate quantification of bacterial concentration in water is of great significance for ensuring water safety and maintaining human health. This paper proposes a method for rapid determination of bacterial concentration by multiwavelength transmission spectroscopy combined with partial least squares regression. Escherichia coli (E. coli) is selected because it is a common indicator microorganism for assessing water pollution status, and it is easy to handle. First, we measure the transmission spectra for E. coli suspensions in the region from 200 to 900 nm and analyze the differences in the spectral characteristics at different concentrations; subsequently, considering that the concentration is affected by the instrument linearity and other factors, the sensitivity, correlation, and detection ability of the spectra at different wavelengths with the change of concentration are analyzed, and the optimal characteristic band is selected according to its wavelength variation characteristics; finally, the determination of E. coli concentrations are completed by using the optimal characteristic band spectra combined with partial least squares regression. We calculate the bacterial concentration, compared with the plate counting, the maximum relative error is 4.500%, the average relative error is 0.677%, respectively, which is less than 5%, and their accuracy and stability are all better than those calculated by the single-wavelength method. This study provides a reference for the rapid and accurate detection of bacterial concentration in water.

Application and comparison of four assessment methods for water quality of Sancha Lake in Central Sichuan Province, China

Abstract In order to analyze and compare the characteristics and applicability of different water quality evaluation methods applied to lake water quality evaluation, four monitoring sections were set up in Sancha Lake in 2019, 2020, and 2021, and 20 water quality parameters were selected. The single factor index method, the comprehensive pollution index method, the Nemerow pollution index method, and the improved Nemerow pollution index method were used to comprehensively evaluate water quality. The research results showed that the single factor index evaluation method is simple to operate and can quickly determine the water quality category by identifying the worst single water quality indicator. The comprehensive pollution index method and the Nemerow pollution index method determine the degree of water pollution based on the numerical values representing the overall pollution level of the representative water body. The evaluation results showed that except for the evaluation results of the single factor evaluation method with categories II and III, the results of other evaluation methods were all category I, indicating that the water quality was good.

Effect of water stratification and mixing on phytoplankton functional groups: a case study of Xikeng Reservoir, China

A shift in reservoir stratification and mixing significantly affects the water column ecosystem, which in turn leads to changes in phytoplankton abundance and community structure. To explore the effects of stratification and mixing on the phytoplankton community structure of a diversion reservoir, a 1-year survey was divided into a stratification period in 2020, a mixing period in 2020, and a stratification period in 2021, and redundancy analysis (RDA), variance partitioning analysis (VPA) and Pearson correlation analysis were used to analyse the key drivers affecting the phytoplankton functional groups, using Xikeng Reservoir as a case study. During the study period, 8 phyla, 69 genera and 9 major functional groups were observed in this reservoir. The dominant functional groups varied significantly, being X1 in the stratified period in 2020; P and D in the mixing period in 2020; and D, X1, and M in the stratified period in 2021. The phytoplankton diversity index was greater in the mixing period than in the stratification period, in agreement with the results of the aquatic ecological status evaluation (Q index, higher in the mixing period than in the stratification period). However, phytoplankton diversity of Xikeng Reservoir was of limited value in assessing the degree of water pollution, so should be considered in combination with the Q index. Water temperature (WT), mixing depth (Zmix), nitrogen–phosphorus ratio (N/P), and total nitrogen (TN) were important drivers of phytoplankton functional group dynamics in different periods. The study provides a valuable reference for assessing the relationship between environmental factors and phytoplankton communities, as well as for the evaluation and conservation of aquatic ecosystems in southern China's water diversion reservoirs.

Significant Dynamic Disturbance of Water Environment Quality in Urban Rivers Flowing through Industrial Areas

The urban water environment is seriously affected by human activities. Rivers in highly industrialized areas, which often carry various types of industrial pollutants, such as metals and nutrients, are especially affected. In this study, the water quality of the Pi River, an industrial base that flows through Chengdu, a large city in Southwest China, was tested for one year. Heavy metal concentrations in the water, sediment, and macrobenthic and algal communities in the river were examined. The water pollution index (WPI) and trophic level index (TLI) were employed to measure the water pollution degree and eutrophication status, respectively. The Shannon—Wiener index (H’) and Margalef’s index (dM) were determined to represent the diversity and richness of macroinvertebrates. The principal component analysis (PCA) was employed to define the main heavy metal influencing factors in the Pi River. Our study showed that the eutrophication status increased with spatial change, and the eutrophication status was the most serious in the downstream reach, which was moderately eutrophic. The water body of the Pi River was seriously polluted by heavy metals, and the content of chromium (Cr) in the sediment and cadmium (Cd) in the water/sediment was far beyond the prescribed limit. In addition, we found that Cd had a serious impact on both the benthic and algal communities, and the benthic community structure was completely changed, destroying the original aquatic environment. We explored the mechanisms of the influence of Cd on aquatic fauna, and this information is of great significance for the future conservation of industrial urban rivers. In this study, the spatial–temporal variations in water quality and aquatic communities revealed the pollution status of a river flowing through industrial areas, which provided a basis for future river conservation and restoration.

Углеводы в поверхностных водах Карелии и их связь с содержанием биогенных и органических веществ

The results of a long-term research of the content of carbohydrates in natural waters of Republic of Karelia (Russia) from 2011 to 2020 are summarized. In total, 34 water bodies (29 lakes and 5 rivers) were studied in different hydrological seasons. The presented sample of water bodies captures almost all types of surface waters in the humid zone in terms of trophicity and humus content. It was found that the carbohydrates concentration varies widely from 0.7 to 53.1 mg/L (average 3.3 mg/L) and its share of total organic matter averages 16%. It was revealed that the content and distribution of carbohydrates in surface waters depends both on natural (the level of trophicity and humus content in the reservoir) and anthropogenic factors (eutrophication, trout farms, industrial wastewater discharge, seepage waters of solid waste landfills, communal wastewater). In addition, all the studied water bodies were categorized into two groups according to the water pollution degree: contaminated and uncontaminated. It was revealed that the concentration of carbohydrates in contaminated water bodies of Karelia is on average 1.4 times higher than in uncontaminated ones. In addition, the content of carbohydrates increases together with such chemical parameters as 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD Cr), permanganate oxygen demand (COD Mn), chlorophyll a, mineral and total phosphorus (Pmin and Р total relatively) and ammonium (N-NH 4+). In particular, these relations are pronounced in contaminated water bodies, where the highest values of the correlation coefficient between the above parameters are noted. The content of carbohydrates in surface waters is a complex indicator of both organic and biogenic water pollution.

Effect of Environmental Conditions on the Composition of Zooplankton in the Middle Stream of the Likhoborka River

The relevance is due to the paucity of official data on the state of surface water ecosystems In Rusia in terms of hydrobiological indicators and the prospects for the development of hydrobiological research as part of engineering and environmental surveys. The aim of the work is to continue the research of the ecological conditions of the Likhoborka basin with the identification of spatial and temporal patterns in the state of zooplankton. The objectives of the work were: to assess the study of the Likhoborka aquatic ecosystem; to perform a comprehensive environmental survey with plankton sampling and hydrobiological analyses; to link the values of water quality indicators along the length of the river to sources of pollution. The article presents the results of an ecological survey of the Likhoborka river watershed: a list of pollution sources, methods of reconnaissance, detailed examination and hydrobiological analysis of samples taken in the middle stream in June 2022. The work is the next stage of the educational environmental monitoring of the water protection zones of the rivers of Moscow. Throughout the surveyed area from the Golovinsky Ponds to Dmitrovskoe Highway, the degree of water pollution according to the Pantle and Buck index is moderate. Daphnia are abundant in Golovinsky ponds. Along the length of the area, rotifers predominate. The total salinity increases from 185 to 821 mg/l. The greatest contribution to pollution is made by polluted waters of the Likhoborka and the Norishka, which are concentrated through the reservoirs. There are practically no living hydrobionts in the Likhoborka reservoir.

Impact of Water Pollution on Fish Physiology - A Study

The freshwater air-breathing teleost, Channa punctatus were exposed to mercuric chloride (0.15 ppm) and cadmium chloride (35.5 ppm) for 1, 2, 7, 15 and 30 days so as to determine short and long-term effects of sub-lethal doses of these industrial pollutants on different haematological parameters. The selection of pollutants and their concentrations was based on the real data, in relation to the degree of water pollution of Damodar River. Blood samples were collected from the fishes exposed to various exposure periods for each pollutant and the blood glucose, haemoglobin content, cholesterol, HDL-cholesterol, LDL- cholesterol, VLDL- cholesterol, triglycerides, total RBC and WBC counts were measured. The blood glucose, haemoglobin content, total RBC and WBC counts progressively decreased. Blood cholesterol, HDL-cholesterol, LDL- cholesterol, VLDL-cholesterol and triglycerides were also depleted. Linear regression analysis with appreciable values of R2 and tratios revealed that the values of different blood parameters were reduced radically with the progress of days, except haemoglobin, signifying negative impact of pollutant of HgCl2. Strong correlation between different blood parameters calls for that adverse variations. Histopathological changes in the hepatopancreas induced by the heavy metals like mercuric chloride and cadmium chloride include degeneration of hepatic cells, clumping of cytoplasmic materials, displacement of nucleus towards the periphery, derangement of the pancreatic acini and coagulation of blood in the sinusoids. Analysis of experimental data suggests the depletion of energy resources and disturbance of the metabolic pathway as indicated by the adverse effects on haematological parameters and histopathological lesions in the haepatopancreas.

Analysis of Ningxia Hui Autonomous District’s Gray Water Footprint from the Perspective of Water Sustainability

Gray water footprint (GWF) is an effective method to evaluate the degree of water pollution and water quality. It is the amount of freshwater needed to dilute water pollutants to meet ambient water quality standards. Accounting and analyzing the GWF will be significant for promoting an improved water environment and sustainable water ecology in Ningxia Autonomous District. We accounted for the GWF of all cities in Ningxia from 2012 to 2020 and evaluated its spatial-temporal variations by the GWF accounting method proposed by Hoekstra. Then, the Logarithmic Mean Divisia Index (LMDI) method was applied to investigate the contributions of four driving factors: the population scale effect, economic development effect, technological effect, and industrial structure effect. And then, the changes in the GWF in the Ningxia region were analyzed. The results showed that the GWF in the Ningxia region changed from 79.21 × 108 to 29.09 × 108 m3/yr during 2012–2020, making a significant decreasing trend. Among all cities, Wuzhong City contributes the most in terms of the GWF. More specifically, economic development and technology structure are the positive and negative drivers of the GWF, respectively. The water pollution levels in Ningxia (0.49–1.3) indicated that the waste assimilation capacity has fallen short of taking up the pollutant load, which had an unfavorable impact on the groundwater according to actual water quality data. NO3-N and NH3-N are detected in the groundwater throughout the Ningxia region, with the highest NH3-N content in the groundwater in Yinchuan, which almost exceeded the groundwater quality standard of category III. Above all, this study reflected the current water pollution situation better by combining the GWF with actual water quality data in Ningxia. The finding of this study is valuable for addressing water quality threats and developing sustainable development.

Diatoms. A viable tool for quantifying surface water pollution

The current work focused on the water quality of the Bega and Timis rivers measured by two methods. One of them is the method by which the water was analyzed from a physical-chemical point of view, and the other aimed at quantifying the degree of water pollution by biological methods. In this sense, diatoms were used. In the study, samples of water and diatoms were taken using specific techniques from the Bega and Timis rivers, starting from near the area of their formation until near the border with Serbia. Four sampling points were chosen on the Timis River plus one sampling point on the Surgani River, which is a tributary of the Timis, and six sampling points on the Bega River. The points were chosen specifically, being located downstream of the major sources of pollution. In order to locate the points, information was collected from the studies carried out as part of an extensive monitoring that spanned several years. The abundance and diversity of diatom species were used to calculate the Biological Diatom Index (BDI) and the Saprobity Index (SI). These two indices provide valuable information about organic or heavy metal pollution of water bodies.

GIS-BASED INTELLIGENT DECISION-MAKING SUPPORT SYSTEM FOR THE DISASTER RESPONSE OF INFECTIOUS DISEASES

Abstract. The study aims to develop GIS technology for managing pathogen contamination disaster situations to cope with the occurrence of disaster situations caused by the climate crisis. This study was conducted in a situation where the budgets of institutions with many emergency rescue workers are being invested worldwide, and there are various risks such as water pollution due to climate change, so it is necessary to develop technologies to respond to them.In this study, methods and technical means for emergency response to pathogen contamination were prepared through professional analysis results based on spatial information, and rapid and accurate pathogen detection, situation recognition, event control and response methods, risk assessment and epidemiological investigation methods, and technologies were developed.Technological means include collecting and analyzing water quality data using satellites and drones, and evaluating the severity and degree of water pollution using social media data and photos. Through these technologies, a GIS platform that can effectively manage and provide data sources, data collection, interoperability, data harmonization, data management, and data processing is established, and commercialization is aimed at real users and field-oriented. These technology developments enable rapid response and response in disaster situations, and can reduce threats to life and safety.

Tracer study of CDOM for nitrogen and phosphorus pollution in the offshore Leizhou Peninsula, China

Colorful dissolved organic matter (CDOM) is an optically important active substance in marine habitats that feature significant biochemical conservatism. Additionally, CDOM is an important tracer and indicator of pollution status in marine water masses. In this study, we use sampling data collected in September 2020 and May 2021 from the marine areas around the Leizhou Peninsula. This information is combined with the Delft 3D numerical simulation analysis to carry out a study on the relationship between the ag (355) in the marine areas and to determine the regional marine pollution levels. The results show that (1) the nearshore areas of the Leizhou Peninsula in spring and autumn are mainly lightly polluted. Compared with the same period in history, the pollution level has significantly decreased, and the ag (355), DIN, and DIP concentrations show a trend of high near the shore and low far from shore. The peak concentrations are mainly in the Zhanjiang Bay, Qiongzhou Strait, Wailuo Port, Liusha Port and Guangxi Tieshan Port. (2) ag (355) can be used as an indicator to characterize the degree of water pollution in the nearshore waters of the Leizhou Peninsula. In spring, the ag (355) interval of [0.115, 0.200] m−1, [0.201, 0.245] m−1 and [0.246, 0.484] m−1 can be considered clean, lightly polluted, and moderately polluted water, respectively. In autumn, the ag (355) interval of [0.180, 0.275] m−1, [0.276, 0.478] m−1, [0.479, 0.642] m−1, [0.643, 0.921] m−1 can be considered clean, lightly polluted, moderately polluted and heavily polluted water, respectively. (3) The response models between the ag (355) and pollutant dispersion trends were constructed in the Zhanjiang Bay and Tieshan Port. The RMSEs of the ag (355) validation points in the models were lower than 0.12 mg/L, and the MAPEs were lower than 30 %, the pollution traceability of CDOM is verified.

Groundwater development and energy utilization of water environment protection based on big data and Internet of Things

The issues related to the big data and energy reports of the Internet of Things (IoT) have become a hot topic in recent years. As a typical representative of issues related to IoT big data and energy reports, groundwater development, energy utilization and water environment protection have attracted the attention of all sectors of society based on the Internet of Things big data. With the rapid development of China’s economy and society, the demand for water resources is growing day by day. As an important part of people’s living and production water, the exploitation of groundwater is also increasing year by year. However, many problems caused by groundwater exploitation and utilization, such as surface subsidence, collapse, ground fissure, seawater intrusion, water quality deterioration, etc., have seriously affected the economy, society and people’s normal life. At present, China is increasingly short of water resources. The problem of environmental pollution is increasingly serious, which seriously affects the survival of the people. Environmental protection based on big data and the Internet of Things is an effective measure to solve the current problems of groundwater development, energy utilization and water environment protection. Therefore, to ensure China’s economic development and residents’ water safety, it is not only necessary to reasonably develop and use water resources, but also to protect the water environment to avoid water shortage caused by water quality problems. On this basis, this paper analyzed and discussed the current situation of groundwater resources utilization in China, with a view to fundamentally solving the problems of groundwater energy utilization and water environment protection in China. Research showed that the energy utilization rate had been in a low state until 2017, with the highest water pollution level of 92% and poor water quality. Since 2018, due to the maturity of the big data technology of the Internet of Things, energy utilization has been generally improved in all regions. The degree of water pollution has reached a new historical low. The quality of water sources has been improved, and the residents’ satisfaction with the energy utilization of groundwater development and water environment protection has reached 96%. The changes in various signs have laid the foundation for the long-term development of the country. The research in this paper has important guiding significance for solving problems related to IoT big data and energy reports.

Study of water purification reactor operating modes

Wastewater treatment is one of the main problems of development and urbanization of the Arctic regions. This article is devoted to the development of a method for assessing the degree of water purification in order to determine the optimum operating parameters of treatment reactors for water treatment by ferrates from industrial and household waste resulting from the development of Arctic regions. Experiments reflecting the influence of the amount of air supplied to the purification plant on the processes of mixing and distribution of water were carried out and analyzed. Based on the experimental data, a method for determining the optimum operating parameters of a new mobile water purification plant has been developed and applied. The operation of the plant is based on the use of the ferrate method. equations and dependencies describing the relationship between the reactor volume, liquid flow rate and the degree of water purification are given. The degree of water pollution is estimated as its fraction which has left the reactor before the time required for complete treatment of the liquid from the moment it enters i the reactor. Optimal parameters of the ferrate reactor, such as volume and air supply, for a mobile water treatment plant were determined.

Quantitative evaluation of water pollution degree based on comprehensive biomarker response index method

Quantitative evaluation of water pollution degree based on comprehensive biomarker response index method

Quantitative evaluation of water pollution degree based on comprehensive biomarker response index method

Quantitative evaluation of water pollution degree based on comprehensive biomarker response index method

Dynamic simulation and coupling coordination evaluation of water footprint sustainability system in Heilongjiang province, China: A combined system dynamics and coupled coordination degree model

With the development of the social economy, a reasonable evaluation of the sustainable utilization capacity of water resources (WR) is of great significance to alleviate the pressures of water shortages and pollution faced by cities. This study first proposed a water footprint sustainability (WFS) system using system dynamics to evaluate the influence of WR on the environment, economy, and society of Heilongjiang province. The WFS assessment used a comprehensive evaluation method, and the coupling coordination degree model was applied to analyze the coupling coordination of the WFS system. The results showed a fluctuating increase tendency in the total water footprint (WF), blue WF, green WF, agricultural WF, and ecological WF from 2000 to 2019. However, the gray WF, domestic WF, and industrial WF presented a fluctuating decrease. The prediction for the next 30 years indicated that the green WF, agricultural WF, and domestic WF would be stable while the other indicators would increase with time. The blue water shortage degree was greater than 1; however, the green water scarcity index and water pollution degree were less than 1. The economic sustainability of the total WF, blue WF, and gray WF increased year by year; however, the social sustainability of the total WF gradually weakened. In addition, the water supply and demand ratio was below 1. Overall, the regional WFS worsened, and the coupling degree and coupling coordination degree of the WFS system varied in the range of 0.85–0.91 and 0.28–0.31, respectively. This study was of great significance in realizing the sustainable management of regional WR.