Water Quality Identification Index Research Articles

Evolution Trend of Water Quality in the Inner Mongolia Section of the Yellow River from 2003 to 2020

The aim of this study was to comprehensively understand the water environment quality status and its change trend in the Inner Mongolia section of the Yellow River Basin. To analyze the water quality in recent years,the water quality data in the Yellow River basin from 2003 to 2020 were firstly collected from five typical monitoring stations．Various data analysis methods, including principal component analysis, cluster analysis, and a long short-term memory model, were used along with an improved comprehensive water quality identification index to explore the spatiotemporal characteristics of water quality in the Yellow River Basin. The results showed that the overall water quality in the basin has improved and stabilized over time. In terms of temporal variation, there was a distinction between the wet season and dry season, with a better status observed during the wet season due to increased agricultural irrigation and higher water volume. Spatially, the five monitoring sections could be divided into three categories based on strong natural factors that maintained their temporal characteristics during the wet season； however, significant differences were observed during the dry season due to urban water usage patterns. Analysis using LSTM models revealed that ammonia nitrogen will continue to decline and have a decreasing impact on the comprehensive water quality. These findings provide valuable insights for the comprehensive management of water quality in Inner Mongolia's Yellow River Basin.

Spatiotemporal characteristics and potential pollution factors of water quality in the eastern route of the South-to-North Water Diversion Project in China

The eastern route of the South-to-North Water Diversion Project (SNWDP-ER) in China, an open-channel cross-basin project, is exposed to multiple potential pollution sources and has changing hydrodynamic conditions between diversion and non-diversion periods. After a decade of pollution control efforts, it is imperative to perceive the water quality conditions and identify potential pollution factors for further maintenance. Combining the water quality identification index (WQII) and multivariate statistical techniques (MSTs), this study conducted an exploratory analysis in SNWDP-ER, based on the monitoring data in 2020–2021. The monitoring and WQII results show that the overall water quality in SNWDP-ER is satisfactory and meets the Class III requirements in China Environmental Quality Standard for Surface Water, except for total nitrogen (TN) which falls into Class V or even worse. The periodic alternations of flow direction between diversion and non-diversion periods tend to deteriorate water quality, particularly in the initial stage of alternations. Water quality appears more stable during the diversion period, and impounding lakes along the project are crucial to water environment restoration in this period. Due to the positive influence brought by the self-purification and environmental carrying in the Luoma Lake, Nansi Lake, and Dongping Lake, water quality exhibits an enhancing trend from upstream to downstream in the Lianghu and Jiaodong reaches. Besides, the monitoring stations in Shandong reach exhibit significant divisional heterogeneity under hierarchical cluster analysis (HCA) with the Nansi Lake and Dongping Lake as the demarcation points, and the results of factor analysis/principal component analysis (FA/PCA) further identified the contributions of mining, shipping, and land use to each section. Based on the findings, the study recommends implementing wastewater discharge control, abandoned mines remediation, and continued water quality monitoring for further maintenance and improvement in SNWDP-ER.

Nitrogen and Phosphorus Pollution Discharge and Water Quality Evaluation in a Small Basin of the Upper Reaches of Lijiang River

The Lijiang River Basin is a humid, subtropical, karst landform in China and is listed as a World Heritage Site. However, with the rapid development of urbanization and tourism activities in recent years, it faces increasingly severe non-point source pollution. To understand the temporal and spatial variations in nitrogen and phosphorus pollution discharge and the changes in river water quality, the Jingui Small Basin, in the upper reaches of the Lijiang River, was chosen as a representative system. Changes in nitrogen and phosphorus concentrations were continuously monitored in the main river channel and the river water quality was evaluated using the comprehensive water quality identification index method. The results indicated that there were obvious seasonal changes in nitrogen and phosphorus discharge loads in the basin. Both nitrogen and phosphorus discharge loads were higher in the crop-growing season than in the non-growing season. No significant difference in nitrogen and phosphorus discharge load between different scales was found, and the scale was not the key factor affecting the nitrogen and phosphorus discharge load of Jingui River. As the river flowed from the initial water source to the outlet of the basin, water quality was characterized by the spatial pattern of the upper reaches > the middle reaches > the lower reaches. Except for the water quality at the outlet of the basin in November and December, which reached Class V, the comprehensive water quality of each sub-basin reached the target water quality of the water function zoning from May to December. The elucidation of the nitrogen and phosphorus pollution discharge patterns in the Jingui River and the changes in water quality provide a reference for the control and management of agricultural non-point source pollution in the Lijiang River Basin.

Evaluation of water quality pollution and analysis of vertical distribution characteristics of typical Rivers in the Pearl River Delta, South China

Water quality comprehensive evaluation is an essential technical measure for water environment management and treatment. The previous research methods were often insufficient for studying black-sticking water bodies' formation and transformation mechanisms. In view of this, the single pollution index method and the comprehensive water quality identification index method (Iwq) were used to evaluate the pollution characteristics of rivers; the main pollution factors and sources of the watershed were determined by principal component analysis (PCA), and the vertical stratification characteristics of the water bodies were analyzed. The results showed that the total nitrogen (TN) values of pollutants in typical rivers in the Pearl River Delta were higher than the class V water quality standard, and the ammonia nitrogen (NH3−N) pollution level was the second-highest. TN concentration ranges from 4.27 to 19.83 mg/g, and NH3-N concentration ranges from 2.44 to 15.37 mg/g. In addition, in the monitoring of 15 rivers, 11 of them were the inferior V surface water, including five rivers' comprehensive water quality categories for black-stinking water bodies. This may be related to the process of water self-purification and pollutant transport, and rivers in densely populated areas are often subject to discharge from domestic sewage and industrial sewage. The results of the PCA extracted three principal components (PC), accounting for 88.825% of the total variance, with the first and third PCs controlled by human activities and the second PC influenced by natural sources. There is a more apparent vertical stratification of water bodies here in the typical rivers of the Pearl River Delta, and DO was an important factor affecting the vertical distribution of chemical oxygen demand (COD), NH3-N, TN, total phosphorus (TP), sulfide, Ferrum (Fe), and manganese (Mn). The severe lack of DO in deep water bodies led to elevated levels of NH3-N, Fe, and Mn, and gases such as hydrogen sulfide was released under anaerobic conditions, resulting in eutrophication and black-sticking levels in water bodies.

Spatiotemporal variation in water quality and identification and quantification of areas sensitive to water quality in Hulun lake, China

This study aimed at characterizing the spatiotemporal variability in water quality in Hulun Lake. In an attempt to assess the water quality status of the lake, data acquired from 13 monitoring points in Hulun Lake from 2012 to 2020 was applied to the improved composite water quality identification index (WQI). The ordinary least squares (OLS) model was used to identify areas of the lake vulnerable to water pollution. The results showed an increase in the WQI value of Hulun Lake and the water quality deteriorated during 2012–2016. The water quality began to improve gradually in 2017. The main variable affecting water quality in the lake transitioned from chemical oxygen demand (CODcr) and total nitrogen (TN) to CODcr and total phosphorus(TP). This shift in major pollutants was an important factor contributing to deterioration in water quality. Seasonal differences in water quality may be attributed to migration of pollutants [CODcr, total dissolved solids (TDS)] to the subglacial water column during the ice-covered period and the subsequent blocking effect of the ice cap. A spatially based OLS model identified the critical impact of Chl.a on water quality. Water transfers were identified as a major factor contributing to an improvement in water quality and to pollutant transformation and contributed to increase in the water quality sensitive area. Despite recent efforts to improve the water quality of Hulun Lake, input of exogenous pollutants, increase in endogenous pollutants, as well as the anaerobic conditions of the ice layer pose significant challenges to the management of Hulun Lake. The implementation of pollutant control measures are, in particular, recommended on the northwest shore for managing the water quality of the lake.

Long-term trends in surface water quality of China's seven major basins based on water quality identification index and big data analysis

Long-term trends in surface water quality of China's seven major basins based on water quality identification index and big data analysis

Water Environment Characteristics and Water Quality Assessment of Water Source of Diversion System of Project from Hanjiang to Weihe River

The water source of the water diversion project from the Hanjiang River to the Weihe River is one of the most important drinking water sources in China. Its water quality is related to the water safety of the long-distance water diversion system from the Hanjiang to Weihe Rivers. In order to explore the spatiotemporal change trend of the water environment characteristics of the water source area and analyze the key factors that have a greater impact on it, this study collected 9 types of water environment physical and chemical parameters from 10 water quality monitoring sections from 2017 to 2019; the water environment characteristics of the water source area of the water diversion system from the Hanjiang River to the Weihe River were analyzed and evaluated by using the variance analysis method, the hierarchical cluster analysis method and the water quality identification index evaluation method. The results were as follows. (1) There was spatiotemporal heterogeneity in a number of physical and chemical parameters in the water body of the water source. In terms of time, the concentrations of CODMn, COD, BOD5 and F- were higher in the flood season (July-October) than in the non-flood season (November-June). The concentrations of DO, TP and TN in the non-flood season were higher than those in the flood season. Spatially, the concentration of physical and chemical parameters of the water body in the Huangjinxia Reservoir area was higher than that in the Sanhekou Reservoir area. (2) The water quality of the water source area was good. The comprehensive water quality reached the Class II water quality standard of surface water environmental quality. Time showed that the comprehensive water quality in the non-flood season was better than that in the flood season. Spatially, the overall water quality of the tributaries was better than that of the mainstream. TN is a key indicator that affects water quality. (3) The spatial and temporal differences in water quality in water source areas are mainly affected by factors such as rainfall, temperature and human activities. This study can provide a scientific and data basis for related research on maintaining and improving the quality of the ecological environment of the water source areas of the Hanjiang to Weihe River Water Diversion System.

An ecological environment impact assessment of municipal solid waste based on grey prediction model

Aiming at the problem of low accuracy in the impact assessment of urban waste on ecological environment, a method of urban waste ecological environment impact assessment based on grey prediction model is proposed. First, the pollution type of urban waste is determined, and the important pollution data of urban waste is extracted with the help of the calculation of comprehensive water quality identification index. Then, the total ranking of pollution data is determined by the square root method, the judgement matrix is set to calculate the weight of pollution data, and the urban waste ecological environment pollution index system is constructed. Lastly, with the help of grey prediction model, the positive correlation between urban waste and ecological environment is determined, and the urban waste ecological environment impact assessment algorithm is designed to complete the impact assessment. The results show that the evaluation accuracy can be effectively improved by using the evaluation method in this paper.

Differential characteristics and source contribution of water pollutants before and after the extreme rainfall event in the Huaihe River Basin

Various pollutants are collected into rivers through runoff when rainstorms occur, which can harm the aquatic ecological environment, therefore, strengthening the analysis of river pollution sources before and after rainstorms can reduce the impact of rainstorm runoff periods in regard to the risk from river water pollutants. In this study, the water pollutant differential characteristics and pollution source identification in the Henan section in the Huaihe River Basin were explored before and after the extreme rainfall event, and the monitoring data for nine water quality indicators in the monitoring sections were selected. The changing and differential characteristics and processes of the water quality indicators in the Huaihe River Basin before and after the rainstorm were analyzed by using statistical analytical methods and the comprehensive water quality identification index (IWq), and the absolute contribution rates of pollution sources were calculated by the absolute principal components-multiple linear regression model (APCS-MLR). The results showed that the values of pH, DO (Dissolved oxygen) and EC (Electrical conductance) after the rainstorm were lower than those before the rainstorm, while the turbidity, CODMn (Permanganate index), NH3−N (Ammonia nitrogen), TP (Total phosphorus) and TN (Total nitrogen) increased after the rainstorm. The correlations between pH and DO and other water quality indicators increased after the rainstorm, while the correlations between WT (Water temperature), turbidity, CODMn, NH3−N, TP and TN decreased significantly after the rainstorm. The water pollution of each monitoring section increased after the rainstorm; for example, the water quality conditions at Zhoukou Kangdian (ZKKD), Xihua Zhifang (XHZF) and Suixian Banqiao (SXBQ) increased by 42.11, 36.84 and 25.73% to Class V of the environmental quality standards for surface water in China, respectively. The absolute contribution rates of the PC1 to CODMn and TP were 33.86 and 41.11% before the rainstorm, respectively. The absolute contribution rates of the PC2 to DO and TN were 50.77 and 60.26% after the rainstorm, respectively.

Water quality assessment using optimized CWQII in Taihu Lake

To improve the rationality of weight allocation and weight proportion of different periods in the process of water quality assessment, the comprehensive water quality identification index (CWQII) model was optimized in this study. A new improved comprehensive water quality identification index (ICWQIIG) model based on game theory was established to combine subjective weight and objective weight. Based on ICWQIIG, an improved comprehensive water quality identification index (ICWQIIP) model with phased period combination weights was established to determine determined the weight proportion of phased periods was established. In this study, CWQII, ICWQIIG, and ICWQIIP were used to evaluate the water quality of seventeen sites in Taihu Lake in 2020. The models selected nine water quality parameters and six water quality indicators. The assessment results of water quality classification were between “slightly polluted” and “moderately polluted”. The pollution level on the east bank was lower than that on the west bank and north bank. Furthermore, it was also affected by seasonal change, water quality was worse in January and February but better in October and November. The mean value of Iwq calculated by CWQII, ICWQIIG, and ICWQIIP were 2.405, 2.833, and 3.000, respectively. The compared results showed that the ICWQIIG method can more representative identify the location of polluted water than CWQII. Moreover, the ICWQIIP method calculation results not only retained the representative polluted water samples in the ICWQIIG method but can also identify more pollution sites and worse polluted water bodies. Both ICWQIIG and ICWQIIP had high reliability and accuracy in assessment results, and ICWQIIP was more accurate under sufficient data conditions. This study can offer a scientific basis for local water resource management in Taihu Lake, while simultaneously proposing a science-based and valid methodology for the assessment of other similar water bodies.

Water Quality Evaluation and Spatiotemporal Variation Characteristics of Wenyu River Based on Comprehensive Water Quality Identification Index Method

In recent years, the water environment management of the Wenyu River has yielded positive outcomes. In comparison to earlier, the general water quality has substantially improved. However, some areas’ water quality has not improved as a result of the overall trend of improvement, which has implications for the surrounding areas and the entire water environment. To further explore the water environmental quality of specific river sections, this paper adopts the five monitoring sections of Shahe Gate, Mafang, Lutuan Gate, Xinbao Gate, and the additional sewage outlet in 2019, and the three main water quality indicators of COD, DO, and NH3-N. The water quality of the Wenyu River was evaluated using the comprehensive water quality identification index method, and the characteristics of its temporal and spatial changes were studied using correlation analysis and spatial clustering. The results have shown that the Wenyu River is generally Grade V water during the flood season, and is inferior to Grade V water during the non-flood season. All indicators have a regular time and space distribution and are highly influenced by environmental and human factors. Overall, the water quality of the Wenyu River may essentially reach the water environment function zoning target value. Improvements to the river portions below the Xinbao sluice, as well as the use of rainwater resources, must be prioritized.

Temporal and spatial variability of water quality in an urban wetland and the effects of season and rainfall: a case study in the Daguan Wetland, China.

Urban wetlands provide multiple functions including water treatment, recreation, and education, but they are also highly vulnerable, so it is important to monitor wetland water quality to ensure wetland health. In this study, water quality parameters of an urban wetland and rainfall were monitored at 6 sites for 1year. The correlation analysis of water quality parameters and spatial-temporal variability analysis of water quality were carried out. Besides, the effects of season and rainfall on the wetland water quality were evaluated by the comprehensive water quality identification index (CWQII). These results have shown that there is a significant correlation between nutrient pollutants and Chl-a. Wetland water quality changed with the seasons, but it also varied due to changes in rainfall and location. The water quality of the shallow areas both had high susceptibility and response to seasonal changes and rainfall, but the water quality of the deepwater area was relatively stable. The CWQIIs in different seasons were ranked: Winter (5.98) > spring (4.67) > autumn (4.66) > summer (4.26), and the CWQIIs of different rainfall intensities were ranked: torrential rain (5.09) > heavy rain (4.88) > light rain (4.50) > no rain (4.39) > moderate rain (3.95). The results of this study distinctly explained the effects of season and rainfall on water quality in an urban wetland in a subtropical monsoon climate zone and would be helpful to the policymakers and concerned authorities in developing better water quality management strategies for these wetlands.

Water Quality Assessment and Spatial-temporal Variation Analysis in Yellow River Basin

During the implementation of ecological protection in the Yellow River basin, understanding the water pollution status and spatio-temporal variation of water quality has become the most important thing for water safety in the basin. To analyze the water quality in recent years, the water quality data in the Yellow River basin from 2004 to 2018 were firstly collected from eight typical monitoring stations. Using a combination of multivariate data analysis methods including the Mann-Kendall (M-K) trend test, hierarchical clustering analysis (HCA), principal component analysis (PCA), and modified comprehensive water quality identification index (WQI), the spatio-temporal variation characteristics of the water quality were then explored in the Yellow River basin. The results indicated that in terms of time variation, the HCA from the water quality time series showed that the water quality of the Yellow River basin could be divided into the wet season, normal season, and dry season, being basically consistent with the hydrological period. Combined with the M-K trend test and WQI-based water quality assessment, the water quality of the Yellow River basin was improving gradually, with 2010 as the critical year. The water quality in the wet season was superior to that in the dry season. The pollution indicator NH4+-N and permanganate index were dominant in both the wet season and dry season. According to the spatial variation analysis, the water quality for all the studied stations improved significantly. Spatial clustering showed that the S6 (Shanxi Yuncheng Hejin Bridge) was obviously different from others, and further comparative study demonstrated that S6 was constantly seriously polluted. The S7 (Henan Jiyuan Xiaolangdi) exhibited different characteristics in the wet and dry season. In all stations, NH4+-N was considered to be the most common pollution indicator, whereas the permanganate index and DO were also relatively serious for S6. In different hydrological seasons, NH4+-N and the permanganate index showed different characteristics, and their variety was related to the fact that the former mainly came from domestic and industrial sources, whereas the latter was mainly derived from agricultural sources. The modified WQI showed obvious advantages over single-factor water quality assessment, and the findings from this study can provide scientific evidence for water pollution control and comprehensive water quality management in the Yellow River basin.

Spatiotemporal Characteristics of the Water Quality and Its Multiscale Relationship with Land Use in the Yangtze River Basin

The spatiotemporal characteristics of river water quality are the key indicators for ecosystem health evaluation in basins. Land use patterns, as one of the main driving forces of water quality change, affect stream water quality differently with the variations in the spatiotemporal scales. Thus, quantitative analysis of the relationship between different land cover types and river water quality contributes to a better understanding of the effects of land cover on water quality, the landscape planning of water quality protection, and integrated water resources management. Based on water quality data of 2006–2018 at 18 typical water quality stations in the Yangtze River basin, this study analyzed the spatial and temporal variation characteristics of water quality by using the single-factor water quality identification index through statistical analysis. Furthermore, the Spearman correlation analysis method was adopted to quantify the spatial-scale and temporal-scale effects of various land uses, including agricultural land (AL), forest land (FL), grassland (GL), water area (WA), and construction land (CL), on the stream water quality of dissolved oxygen (DO), chemical oxygen demand (CODMn), and ammonia (NH3-N). The results showed that (1) in terms of temporal variation, the water quality of the river has improved significantly and the tributaries have improved more than the main rivers; (2) in the spatial variation respect, the water quality pollutants in the tributaries are significantly higher than those in the main stream, and the concentration of pollutants increases with the decrease of the distance from the estuary; and (3) the correlation between DO and land use is low, while that between NH3-N, CODMn, and land use is high. CL and AL have a negative effect on water quality, while FL and GL have a purifying effect on water quality. In particular, AL and CL have a significant positive correlation with pollutants in water. Compared with NH3-N, CODMn has a higher correlation with land use at a larger scale. The results highlight the spatial scale and seasonal dependence of land use on water quality, which can provide a scientific basis for land management and seasonal pollution control.

Temporal and Spatial Variation of water quality in the Yongding River Basin

For exploring the water quality and macroinvertebrate community characteristics of the Yongding River Basin, investigation of water environment and macroinvertebrates was conducted in 34 sampling sites in August 2016 and April 2017. Furthermore, Water Quality Index (WQI) and biological index (BI) were used to assess the water quality of studied rivers. According to the water quality evaluation results of the WQI and the BI method, the water quality of most sites in non-flood season were equal to or better than those in flood season, and these sites were mostly located in urban area. The dominant land use and non-point source pollution was the primary contributor to water quality degradation in rural areas. There are both similarities and differences between BI index and water quality identification index. From the evaluation results of Sanggan River, Yanghe River and Yongding River, the water quality of Yanghe River is better than that of Sanggan River and Yongding River.

Water quality assessment and pollution source analysis of Yaojiang River Basin: a case study of inland rivers in Yuyao City, China

Abstract To fully understand the water quality status of the Yuyao section in the Yaojiang River Basin, we utilized the single factor and comprehensive water quality identification index methods, as well as factor analysis in this study. The single factor water quality assessment results showed that the common parameters exceeding the standard in both the wet and dry seasons included dissolved oxygen and total nitrogen, which were inferior to the target water quality grade III by 1–6 grades. The comprehensive water quality order reaching the target grade III was Hutang River (87.5%), Changling River (50.0%), Yaojiang River (43.8%), and Linzhou River (37.5%). The comprehensive water quality in the dry season (90.0% standard-achieving rate) was better than that in the wet season (25.0% standard-achieving rate). These results suggested that the surface runoff might considerably impact water quality. The factor analysis results showed that the basin surveyed in 2018 was mainly polluted by urban sewage and agricultural sources, while the primary pollution source in 2019 was agricultural pollution. Integrated with comprehensive water quality assessment results, in this study, we demonstrated that the series of water treatment projects carried out in Yuyao City positively impacted municipal sewage treatment.

Correlation Analysis of Landscape Structure and Water Quality in Suzhou National Wetland Park, China

The newly issued “Guideline of General Planning of Wetland Parks”, China, reclassified the functional zoning of national wetland parks into three categories: conservation areas, restoration and reconstruction areas, and rational utilization areas. Therefore, the country is facing a new round of revision and compilation of the general planning of national wetland parks. The purpose of this paper was to provide information to guide wetland park functional zoning and to formulate the water pollution prevention and control strategy. In this study, 53 sampling points of 6 national wetland parks in Suzhou City were selected. Pearson’s correlation analysis, multiple stepwise regression analysis, redundancy analysis, single factor, and comprehensive water quality identification index methods were used to analyze the effects of wetland landscape types and landscape configuration on water quality. (1) Lakes and rivers in the wetland park had positive ecological effects and should be distributed in each functional zone. (2) Grassland ecology is fragile. Grasslands should be distributed in conservation areas and in restoration and reconstruction areas. (3) Woodland and cultivated land have both ecological and economic benefits. They can be used as ecological buffer and entertainment zones, which are respectively distributed in the restoration and reconstruction areas and in the reasonable utilization areas. (4) Built-up land is highly disturbed by humans. It should only occur in the rational utilization areas and far away from the conservation areas.

Water Pollution Characteristics and Source Apportionment in Rapid Urbanization Region of the Lower Yangtze River: Considering the Qinhuai River Catchment

Clarifying the current situation of regional water pollutants and the relationship between pollutants and pollution sources is considered essential for managing the water environment. Water quality identification index (WQI), cluster analysis (CA), positive matrix factorization (PMF), and stable isotope analysis in R (SIAR) were employed to interpret a large and complex water quality data set of the Qinhuai River catchment generated during 2015 to 2019 to monitor of 11 parameters at 29 different sampling sites. WQI analysis indicated that water quality in Qinhuai River catchment is considered to have "moderate pollution," and an improving trend of water quality was observed at the interannual scale. TN was the most deteriorated of all pollution parameters. CA and PMF results on the spatial scale revealed that sampling sites located at downtown of Nanjing and Lishui District or Jangling University town were highly polluted due to the sewage from domestic sewage and business service sewage (28.88%) as well as industrial wastewater (27.43%), while sampling sites located at Hushu Street Administrative District, Ergan River, and Sangan River were slightly polluted by rural domestic wastewater and garbage (28.79%), and agricultural non-point source pollution (24.3%). The middle-lower reaches (Jiangning Development Zone and Moling Street) and middle reaches (Lukou Street Administrative District) were moderately polluted by industrial wastewater (27.25%), sewage from domestic wastewater and business service wastewater (31.62%) as well as inner sources (24.76%). The SIAR results showed that NO3--N was the main nitrogen form, and the NO3--N mainly originated from sewage (61%) and soil (34%) in the Yuntaishan River sub-catchment. These results will aid in the development of measures required to control water pollution in river catchments.

Water quality characteristics and assessment of Yongding New River by improved comprehensive water quality identification index based on game theory

The Yongding New River is essential for the water supplies of Tianjin. To date, there is no comprehensive report that assesses the year-round water quality of the Yongding New River Main stream. Moreover, little attention has been given to determining a combined weight for improving the traditional comprehensive water quality identification index (ICWQII) by the game theory. Seven water quality parameters were investigated monthly along the main stream of the Yongding New River from May 2018 to April 2019. Organic contaminants and nitrogen pollution were mainly caused by point sources pollution, and the total phosphorus mainly by non-point source pollution. Dramatic spatio-temporal variations of water quality parameters were jointly caused by different pollutant sources and hydrometeorological factors. In terms of this study, an improved comprehensive water quality identification index (ICWQII) based on entropy weight or variation coefficient and traditional CWQII underestimated the water qualities, and an ICWQII based on the superstandard multiple method overvalued the assessments. By contrast, water qualities assessments done with an ICWQII based on the game theory matched perfectly with the practical situation. The ICWQII based on game theory proposed in this study takes into account not only the degree of disorder and variation of water quality data, but also the influence of standard-exceeded pollution indicators, whose results are relatively reasonable. All findings and the ICWQII based on game theory can provide scientific support for decisions related to the water environment management of the Yongding New River and other waters.

Spatiotemporal Analysis of Water Quality Using Multivariate Statistical Techniques and the Water Quality Identification Index for the Qinhuai River Basin, East China

Monitoring water quality is indispensable for the identification of threats to water environment and later management of water resources. Accurate monitoring and assessment of water quality have been long-term challenges. In this study, multivariate statistical techniques (MST) and water quality identification index (WQII) were applied to analyze spatiotemporal variation in water quality and determine the major pollution sources in the Qinhuai River, East China. A rotated principal component analysis (PCA) identified three potential pollution sources during the wet season (mixed pollution, physicochemical, and nonpoint sources of nutrients) and the dry season (nutrient, primary environmental, and organic sources) and they explained 81.14% of the total variances in the wet season and 78.42% of total variances in the dry season. The result of redundancy analysis (RDA) showed that population density, urbanization, and wastewater discharge are the main sources of organic pollution, while agricultural fertilizer consumption and industrial wastewater discharge are the main sources of nutrients such as nitrogen and phosphorus. The water quality of the Qinhuai River basin was determined to be mainly Class III (slightly polluted) and Class IV (moderately polluted) based on WQII. Temporally, the change trend of WQII showed that water quality gradually deteriorated between 1990 and 2005, improved between 2006 and 2010, and then deteriorated again. Spatially, the WQII distribution map showed that areas with more developed urbanization were relatively more polluted. Our results show that MST and WQII are useful tools to help the public and decision makers to evaluate the water quality of aquatic environment.