Effects of industry structures on water quality in different urbanized regions using an improved entropy-weighted matter-elementmethodology

Source apportionment and influencing factors of surface water pollution through a combination of multiple receptor models and geodetector

In line with sustainable development goals (SDGs), precise quantification of water pollution and analysis of environmental interactions are crucial for effectively safeguarding water resources. In this study, Nemerow's pollution index was used to evaluate water quality, three receptor models were used to identify pollution sources, and Geodetector analysis was applied to explore environmental interactions in the North Shangyu Plain, Southeast China. Using 5207 surface water samples from September 2023 with 11 physicochemical parameters, the results showed that surface rivers in the North Shangyu Plain exhibited varying degrees of pollution: slight pollution upstream, moderate pollution in midstream and downstream, and concentrated high pollution in certain areas, with TN, CODCr, and TP as the primary pollutants. Multimethod source apportionment significantly improved the accuracy of pollution source attribution and identified five main sources: domestic sewage (1.42%-3.54%) characterized by NO3-N, phytoplankton source (38.43%-50.05%) indicated by chl and PC, agricultural cultivation (16.1%-17.63%) marked by TP and CODMn, industrial wastewater (17.64%-25.1%) primarily associated with TN, and natural source (10.32%-13.26%) characterized by DO, NH3-N, and CODCr. Influencing factor analysis validated the source identification. Natural factors had minor impacts on water parameters, while pollution control from agricultural activities was suggested to diversify fertilizer types rather than merely reduce quantities. The combined effects of industrial and aquaculture activities intensified pollution from TN, chl, and PC, underscoring the need for targeted management practices. This study showed the objectivity and reliability of using a combined approach of multiple receptor models and Geodetector to evaluate the river water quality status, which helps assist decision-makers in formulating more effective water resource protection strategies.

Spatial responses of water quality to river density and connectivity alterations on the Taihu Plain

With the advancement of urbanization, the structure and connectivity of river networks have been changed by the interference of human activities, resulting in a series of water environment problems. Numerous studies have indicated that river networks are associated with water quality; unfortunately, few studies have revealed the contributions of the structure and connectivity of river networks to variations in water quality. Taking one water conservancy region with dense and braided rivers on the Taihu Plain as an example, we depicted the spatial aggregations of water quality using the Getis-Ord Gi* index, quantified the variations in polluted regions using the standard deviational ellipse method, and quantified the influence of river density and connectivity on water quality during the different seasons. The results showed that (1) the water quality during the flood season was better than that during the non-flood season, especially in the western region; (2) the spatial aggregations of most water quality indicators were higher and the polluted regions increased in size during the flood period compared to the non-flood period; and (3) the relative contribution rates of the river density and connectivity exhibited mean values of 62.5% (61.2%) and 37.5% (38.8%) in the flood (non-flood) period. Our results provide theoretical support for enhancing water environment management.

Potential linkage between WWTPs-river-integrated area pollution risk assessment and dissolved organic matter spectral index

The direct discharge of wastewater can cause severe damage to the water environment of the surface water. However, the influence of dissolved organic matter (DOM) present in wastewater on the allocation of DOM, nitrogen (N), and phosphorus (P) in rivers remains largely unexplored. Addressing the urgent need to monitor areas affected by direct wastewater discharge in a long-term and systematic manner is crucial. In this paper, the DOM of overlying water and sediment in the WWTPs-river-integrated area was characterized by ultraviolet-visible absorption spectroscopy (UV-vis), three-dimensional excitation-emission matrix combined with parallel factor (PARAFAC) method. The effects of WWTPs on receiving waters were investigated, and the potential link between DOM and N, P pollution was explored. The pollution risk was fitted and predicted using a spectral index. The results indicate that the improved water quality index (IWQI) is more suitable for the WWTPs-river integration zone. The DOM fraction in this region is dominated by humic-like matter, which is mainly influenced by WWTPs drainage as well as microbial activities. The DOM fractions in sediment and overlying water were extremely similar, but fluorescence intensity possessed more significant spatial differences. The increase in humic-like matter facilitates the production and preservation of P and also inhibits nitrification, thus affecting the N cycle. There is a significant correlation between DOM fraction, fluorescence index, and N, P. Fluorescence index (FI) fitting of overlying water DOM predicted IWQI and trophic level index, and a(254) fitting of sediment DOM predicted nitrogen and phosphorus pollution risk (FF) with good results. These results contribute to a better understanding of the impact of WWTPs on receiving waters and the potential link between DOM and N and P pollution and provide new ideas for monitoring the water environment in highly polluted areas.

Water quality status response to multiple anthropogenic activities in urban river

Water quality evaluation and degrading factors identification are crucial for predicting water quality evolution trends in an urban river. However, under the coupling of multiple factors, these targets face great challenges. The water quality status response to multiple anthropogenic activities in an urban river was evaluated and predicted based on comprehensive assessment methods and random forest (RF) model. We found that the distribution of each physicochemical parameter exhibits an obvious spatial clustering. The mean pollution level and trophic status of the urban river are medium pollution (water quality index = 59.79; Nemerow's pollution index = 2.00) and light eutrophication (trophic level index = 57.30). The water quality status is sensitive to anthropogenic activities, showing the following order of TLI and NPI values: residential district > industrial district > agricultural district and downtown > suburbs > countryside. According to the redundancy analysis, constructed land (F = 15.90, p < 0.01) and domestic sewage (F = 14.20, p < 0.01) evinced as the crucial factors that aggravated the water quality pollution level. Based on the simulation results of the RF model (variation explained = 94.91%; R² = 0.978), improving domestic sewage treatment standards is the most effective measure to improve the water quality (increased by 40.3-49.3%) in residential and industrial districts. While in a suburban district, improving the domestic sewage collection rate has more effectively (23%) than those in the residential and industrial districts. Conclusively, reducing exogenous pollution input and improving domestic sewage treatment standards are vital to urban river restoration. Clinical trial registration Not applicable.

Temporal and Spatial Characteristics of River Water Quality and Its Influence Factors in the TAIHU Basin Plains, Lower Yangtze River, China

Water quality pollution has been a serious problem in the Taihu Basin plains, which is a highly urbanized area in China. This study aims to detect the interannual and seasonal changes and spatial patterns of water quality in this region. Based on cluster analysis, Moran’s I, and standard deviational ellipses, the site clusters, spatial heterogeneity of water quality characteristics and identified polluted regions were clarified. Results showed that (1) water quality improved since 2002, and nutrient concentrations were lower in summer and autumn than in winter and spring. (2) The monitoring sites were divided into six clusters according to the water quality during the period from 2010 to 2014. Water quality worsened from Cluster 1 to Cluster 4. Cluster 1 sites were mostly distributed beside the Yangtze River and Taihu Lake. Cluster 4 sites were mainly located along the southeast border near Shanghai, while the remaining sites were separately distributed in the main cities. (3) A polluted region of both total nitrogen (TN) and total phosphorus (TP) was present in the southeastern part of the study area near the border from 2010 to 2014. In addition, polluted regions were most likely to form near the junctions of main cities. (4) Anthropogenic factors had greater impacts on water quality than natural factors. More attention should be given to water quality protection around impervious surface areas due to the greatest considerable effect.

Evaluation and prediction of water quality in the dammed estuaries and rivers of Taihu Lake

Proper evaluation of water quality is pertinent to estuarine habitat restoration. Identifying the degrading factors of the water environment and predicting the trend of eutrophication are key to restore the habitat. Through trophic level index (TLI), water quality index (WQI), modified Nemerow pollution index (NPI), and the Random Forest (RF) model, water samples collected from various estuaries of Taihu Lake from 2017 to 2019 were evaluated. To predict the water quality development, four scenarios were set viz. S1: add or remove an ecological buffer, S2: increase or reduce the external nutrients, S3: open or close the dam/gate, and S4: increase or decrease the internal release. In Wuli Lake, the nutrient concentrations in the river regions were higher than in the lake regions, while a contrary trend was observed in Gonghu Bay. The estuarine water quality in the dry season (WQI = 40.91, NPI = 1.73) was merely worse than that in the wet season (WQI = 47.27, NPI = 1.67). On the other hand, the eutrophic status in the wet season (TLIWet = 57.93) was worse than that in the dry season (TLIDry = 57.23). The estuarine water quality of Taihu Lake has improved from 2017 to 2019 but still belongs to medium level. The principal component analysis (PCA) revealed that dam construction, land use types, unstable hydrodynamic conditions, and trumpet-shaped estuary were the main factors that aggravated the water quality degradation. The RF model has strong forecasting capabilities for estuarine water quality. When the estuaries are close to residential and industrial districts, controlling the surface runoff and improving sewage treatment efficiency are the most effective measures to improve the water quality. In the estuaries, the sediments are usually disturbed by the wind-waves. Conclusively, reducing sediment disturbance and internal contamination accumulation via biological and engineering measures is the key to estuarine restoration.

Spatial heterogeneity modeling of water quality based on random forest regression and model interpretation

A systematic understanding of the spatial distribution of water quality is critical for successful watershed management; however, the limited number of physical monitoring stations has restricted the evaluation of spatial water quality distribution and the identification of features impacting the water quality. To fill this gap, we developed a modeling process that employed the random forest regression (RFR) to model the water quality distribution for the Taihu Lake basin in Zhejiang Province, China, and adopted the Shapley Additive exPlanations (SHAP) method to interpret the underlying driving forces. We first used RFR to model three water quality parameters: permanganate index (COD_Mn), total phosphorus (TP), and total nitrogen (TN), based on 16 watershed features. We then applied the built models to generate water quality distribution maps for the basin, with the COD_Mn ranging from 1.39 to 6.40 mg/L, TP from 0.02 to 0.23 mg/L, and TN from 1.43 to 4.27 mg/L. These maps showed generally consistent patterns among the COD_Mn, TN, and TP with minor differences in the spatial distribution. The SHAP analysis showed that the TN was mainly affected by agricultural non-point sources, while the COD_Mn and TP were affected by agricultural and domestic sources. Due to differences in sewage collection and treatment between urban and rural areas, the water quality in highly populated urban areas was better than that in rural areas, which led to an unexpected positive relationship between water quality and population density. Overall, with the RFR models and SHAP interpretation, we obtained a continuous distribution pattern of the water quality and identified its driving forces in the basin. These findings provided important information to assist water quality restoration projects.

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.

Comparison between water quality indices in watersheds of the Southern Bahia (Brazil) with different land use

The present study evaluated the influence of land use and occupation on water quality indices (WQI); the WQI developed by the National Sanitation Foundation (NSF), the WQI adapted by the Environmental Company of the São Paulo State (CETESB), WQI proposed by Bascarón and the Canadian Council of Ministers of the Environment (CCME) WQI, obtained for watersheds located in the Eastern Water Planning and Management Region (BA). The study also analyzed the divergences and similarities of these WQI methods. Water quality data were obtained from the Monitoring Program (Monitora) of Environment and Water Resources Institute of Bahia (INEMA), covering the period from 2008 to 2015, at thirteen (13) sampling sites, with quarterly collections, as well as land use and occupation data. The influence of land use and occupation on water quality indices was assessed by principal component analysis (PCA). The PCA showed that urban and agricultural/pasture areas were influencing factors on water quality variables, such as total phosphorus, biochemical oxygen demand, total nitrogen, turbidity total residues and consequently lower WQI values in the Cachoeira watershed. Among the tested methods to evaluate the water quality of watersheds in the study area, the most similar were the NSF WQI, CETESB WQI, and Objective Bascarón WQI.