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Water eutrophication has become one of the prominent problems of environmental protection in inland watersheds. Turbidity, total phosphorus (TP) and total nitrogen (TN) concentrations are key water quality parameters (WQPs) that reflect the level of water eutrophication in inland waters. Due to the complex interaction effects between different water quality in urban rivers, the water quality retrieval models still have the problem of single input features and poor applicability. This paper proposed a robust feature selection method based on machine learning and utilized Sentinel-2 remote sensing images for water quality retrieval of Chan and Ba rivers in Xi'an City. The ReliefF and global sensitivity analysis (GSA) methods (ReliefF-GSA) were used to select the optimal feature combination from the potential feature dataset. Based on the optimal feature combination, Random Forest regression (RFR), LightGBM and XGboost models were constructed for the three WQPs retrieval, respectively. The optimal models were then used to invert the three WQPs and the spatial-temporal variation of WQPs from January 2021 to January 2022 was analysed. The results show that (1) The RelieF-GSA method is suitable for high-dimensional feature filtration and enables optimal feature selection for specific WQPs retrieval. It is revealed that the BOI index (black odour water index) is the key feature for the retrieval of turbidity and TN concentration. (2) The RFR model was found to be better than other models and more appropriate for Chan and Ba rivers, with coefficients of determination (R2) of 0.90, 0.89 and 0.81, respectively. (3) It was found that the water qualities in the Chan and Ba rivers have prominent seasonal characteristics. Turbidity and TP concentrations showed higher, while TN concentration showed relatively low in autumn. The method and conclusions of this paper can further provide a reference for WPQs retrieval in urban rivers. [ABSTRACT FROM AUTHOR]

Agricultural environmental pollution has posed a great challenge to crop production in China, and it is urgent to take effective control of it. Microbe-based environmental remediation technologies, without secondary pollution, are characterized by high efficiency and low operation cost, which has attracted increasing interest. Moreover, the combination of functional microbe and biochar can further improve the efficiency in eliminating environmental pollutants, and positive results have been achieved. In this context, we first summarized the role of functional microorganisms in the remediation of environmental pollutants and the current application status of biochar-loaded microorganisms in the environmental remediation. We then discussed the advantages and challenges of biochar-loaded microorganism technology in the remediation efficiency and resource utilization. Based on the development of current technology, we proposed the direction of further research on the biocharloaded microorganism remediation technology, providing a basis for in-depth understanding of the effectiveness and safety of relevant techniques. [ABSTRACT FROM AUTHOR]

The water eutrophication restricts the development of economy and society in China, which attracts increasing attention. It also affects the health and ecological environment. The evaluation of water eutrophication is very complicated due to the dynamic variability of the water quality data. This paper adopts the hesitant fuzzy set (HFS) to depict the massive data of samples and uncertain preference information of experts, which reduces the complexity of calculation and avoids the loss of information. After that, we construct the projection index function based on the main factors of water eutrophication. The particle swarm optimization (PSO) algorithm is applied to determine the global optimal projection direction by optimizing the projection index function. Therefore, we construct an improved projection pursuit regression (PPR) model. Finally, the water eutrophication evaluation of several lakes in China is used to demonstrate the improved PPR model. Also, the comparative analysis and contribution rate analysis are conducted to validate its rationality and advantages. [ABSTRACT FROM AUTHOR]

Currently, most urban landscape lakes and reservoirs are facing severe water eutrophication and rampant water blooms. To improve water quality environment, a water eutrophication evaluation model and a water bloom strategy model based on fuzzy rough set algorithm are proposed in this study. An improved multidimensional normal cloud model was used to correct assessment uncertainty of water bloom eutrophication. And this experiment used fuzzy rough set to improve casebased reasoning technology to improve water bloom strategy accuracy. The average evaluation accuracy of total nitrogen, total phosphorus, chlorophyll-a, turbidity and chemical oxygen demand in 10 lake cases is 91.56%, 90.83%, 93.15%, 91.69% and 92.77%, respectively. The evaluation results of the simultaneous evaluation model are roughly the same as those of water quality testing center, with an accuracy rate of 95.47%. In addition, the average strategy accuracy based on fuzzy rough set algorithm is 92.15%, and the matching degree for lake A case retrieval is 0.1632, indicating a high degree of similarity. In summary, water eutrophication evaluation model and water bloom strategy model based on fuzzy rough set algorithm proposed by this research institute can accurately evaluate the water eutrophication situation of lakes. And it can accurately search for similar cases of water bloom outbreaks, providing reference value for water body protection and management. [ABSTRACT FROM AUTHOR]

Protecting the water quality of the Yellow River is of great significance to the ecological protection of the Yellow River Basin. The identification of spatiotemporal variations of the water environment and the implementation of measures to control non-point source (NPS) pollution are both key to improving the water quality. Between 2012 and 2021, we conducted assessments of eight indicators, including water temperature, dissolved oxygen (DO) and pH, chemical oxygen demand (CODMn), five-day biological oxygen demand (BOD5), total phosphorus (TP), NO3-N, and NH3-N at six sites in the main stream of the Yellow River in Henan. We explored the causes of changes in water eutrophication using multivariate statistical analysis and formulated recommendations to improve NPS pollution through adjustments in land use patterns. The results showed that temporal water eutrophication markedly decreased and it was most spatially severe in the east. The most effective control of water eutrophication was observed between 2016 and 2018. As the transition from the flood season to the non-flood season took place, the main source of NPS pollution changed from being primarily influenced by precipitation, to being predominantly attributed to agricultural runoff. We recommend addressing the increased soil erosion in the west and controlling the discharge of agricultural effluent in the east. During the flood season, the ecological interception zones can effectively intercept NPS pollution outputs. These findings offer valuable insights for future scientific management strategies to prevent and control NPS pollution in the river. [ABSTRACT FROM AUTHOR]

The presence of complex functional groups and a well-developed pore structure make biochars highly effective in the removal of hazardous substances from water. In this work, peanut shell and orange peel biochars were produced by slow pyrolysis at different temperatures (300°C, 400°C, 500°C) for 6 h. The prepared biochars were used to treat phosphate in water to explore the effect of contact time and initial concentration of phosphate on adsorption performance. The kinetic models were fitted to study the adsorption mechanisms. The results showed that the highest yields of peanut shell (86.7%) and orange peel biochars (81.2%) were achieved at 400°C and 300°C, respectively. 5.0 g of peanut shell biochars removed about 5.94 mg/g phosphate in 26 h and the removal rate was 83.2%, while the same amount of orange peel biochars removed about 5.79 mg/g phosphate in 26 h and the removal rate was 81.1%. The adsorption processes of phosphate by peanut shell and orange peel biochars fitted with the secondary kinetic models, which were dominated by chemical adsorption. [ABSTRACT FROM AUTHOR]

This paper delves into the pivotal role of cleaner production in the pursuit of global water security. Leveraging Biblioshiny, a robust bibliometric analysis tool based on R-Software, the paper examined Scopus data, following PICO protocols and PRISM guidelines. The study's findings underscore the potential of cleaner production strategies on wastewater to underpin water security. To this end, the study proffers three policy interventions: an ''Industrial Cleaner Production Policy,'' a ''Water Eutrophication Prevention Policy,'' and an ''Environmental Sustainability Club Policy.'' These policies collectively constitute a comprehensive framework for ushering in an era of water security anchored in cleaner production principles. In conclusion, the study calls for the seamless integration of cleaner production into global discourse on water security, particularly within the United Nations framework, and its incorporation into various policy documents. This approach ensures cleaner production's central role as a multifaceted intervention tool, enhancing global commitment to water security.

Water eutrophication poses a dual threat to ecological and human well-being. Gaining insight into the intricate dynamics of phytoplankton bloom phenology holds paramount importance in comprehending the complexities of aquatic ecosystems. Remote sensing technologies have gained attention for mapping algal blooms (ABs) effectively, but distinguishing them from aquatic vegetation (AV) remains challenging due to their similar spectral characteristics. To address this issue, we propose a meticulous three-step methodology for AB mapping employing long-term Landsat imagery. Initially, a multi-index decision tree model (DTM) is deployed to identify the vegetation signal (VS) encompassing both AV and ABs. Subsequently, the annual maximum growth range of AV is precisely delineated using vegetation presence frequency (VPF) in conjunction with normal and low water level imagery. Lastly, ABs are accurately extracted by inversely intersecting VS and AV. The performance of our approach is thoroughly validated using the interclass correlation coefficient (ICC) based on a Gaofen-2 Panchromatic Multi-spectral (GF-2 PMS) image, demonstrating strong consistency with notable values of 0.822 longitudinally, 0.771 latitudinally, and 0.797 overall. The method is applied to Landsat images from 1984 to 2022 to quantify the spatial distribution and temporal variations of ABs in Yuqiao Reservoir—a significant national water body spanning a vast area of 135 km2 in China. Our findings reveal a pervasive and uneven dispersion of ABs, predominantly concentrated in the northern sector. Notably, the intensity of ABs experienced an initial surge from 1984 to 2008, followed by a subsequent decline from 2014 to 2022. Importantly, anthropogenic activities, such as fish cage culture, alongside pollution stemming from nearby industrial and agricultural sources, exert a profound influence on the dynamics of water eutrophication. Fortunately, governmental initiatives focused on water purification exhibit commendable efficacy in mitigating the ecological burden on reservoirs and upholding water quality. The methodological framework presented in this study boasts remarkable precision in AB extraction and exhibits considerable potential in addressing the needs of aquatic ecosystems. [ABSTRACT FROM AUTHOR]

Currently, the prediction of cyanobacterial blooms in rivers and lakes is mainly based on data obtained from on-site water quality monitoring, which cannot analyze the overall water area. Remote sensing images can reflect spatiotemporal and spatial information of the overall water area. However, the existing methods cannot effectively predict the spatial and temporal distribution of overall water bloom by pixel-level prediction of remote sensing images, and the raw remote sensing images often have many problems that cannot be directly used for modeling. Therefore, the method of remote sensing image time series pre-processing is firstly proposed in this paper. Secondly, attentional convolution long short-term memory network embedding to 3D U-Net's Pix2Pix (ACL3DPix2Pix) is proposed in this paper to achieve pixel-level prediction of remote sensing images. The model generator is a convolutional long short-term memory network (ConvLSTM) embedded into the 3D U-Net network. The attention mechanism is added to the ConvLSTM, the residual structure is added to the 3D U-Net network, and then the loss function of the overall model is updated to achieve pixel-level prediction of remote sensing images. On this basis, the spatial and temporal distribution prediction of cyanobacterial blooms based on remote sensing image analysis is realized by adjusting the existing eutrophication grading criteria of cyanobacterial bloom water bodies. Finally, the experimental results show that the method is effective in predicting cyanobacterial blooms. [ABSTRACT FROM AUTHOR]

Tri An Reservoir is a vital source of water for agriculture, industry, hydropower, and public usage in Southern Vietnam. Due to human activities, water eutrophication has become a serious problem in recent decades. This study investigated for the first time the impact of land use and land cover (LULC) change on streamflow and nitrate load from the upstream Dong Nai River basin, which is the largest watershed of the reservoir. The study utilized several LULC scenarios, including LULC 2000, 2010, and 2020. The SWAT model was applied to model the watershed during the period 1997–2009. Results showed that the hydrological model performed satisfactorily based on the Nash–Sutcliffe efficiency (NSE) coefficient, the root mean square error observations standard deviation ratio (RSR), and the percent bias (PBIAS). The average simulated values of monthly streamflow and nitrate load were 453.7, 450.0, 446.7 m3/s and 17,699.43, 17,869.13, 17,590.81 tonnes for the LULC 2000, 2010, and 2020 scenarios, respectively. There were no significant differences in streamflow and nitrate load at the basin level under the different LULC scenarios. However, when looking at the subbasin level, there were differences in nitrate load among the scenarios. This suggests that the impacts of LULC on nitrate load may be more pronounced at smaller scales. Overall, our finding underscores the importance of modeling techniques in predicting the impacts of LULC change on streamflow and water quality, which can ultimately aid in the sustainable management of water resources. [ABSTRACT FROM AUTHOR]

Cyanobacterial harmful algal blooms (CyanoHABs) are longstanding aquatic hazards worldwide, of which the mechanism is not yet fully understood, i.e., the process in which cyanobacteria establish dominance over coexisting algae in the same eutrophic waters. The dominance of CyanoHABs represents a deviation from their low abundance under conventional evolution in the oligotrophic state, which has been the case since the origin of cyanobacteria on early Earth. To piece together a comprehensive mechanism of CyanoHABs, we revisit the origin and adaptive radiation of cyanobacteria in oligotrophic Earth, demonstrating ubiquitous adaptive radiation enabled by corresponding biological functions under various oligotrophic conditions. Next, we summarize the biological functions (ecophysiology) which drive CyanoHABs and ecological evidence to synthesize a working mechanism at the population level (the special mechanism) for CyanoHABs: CyanoHABs are the consequence of the synergistic interaction between superior cyanobacterial ecophysiology and elevated nutrients. Interestingly, these biological functions are not a result of positive selection by water eutrophication, but an adaptation to a longstanding oligotrophic state as all the genes in cyanobacteria are under strong negative selection. Last, to address the relative dominance of cyanobacteria over coexisting algae, we postulate a "general" mechanism of CyanoHABs at the community level from an energy and matter perspective: cyanobacteria are simpler life forms and thus have lower per capita nutrient demand for growth than coexisting eukaryotic algae. We prove this by comparing cyanobacteria and eukaryotic algae in cell size and structure, genome size, size of genome-scale metabolic networks, cell content, and finally the golden standard—field studies with nutrient supplementation in the same waters. To sum up, the comprehensive mechanism of CyanoHABs comprises a necessary condition, which is the general mechanism, and a sufficient condition, which is the special mechanism. One prominent prediction based on this tentative comprehensive mechanism is that eukaryotic algal blooms will coexist with or replace CyanoHABs if eutrophication continues and goes over the threshold nutrient levels for eukaryotic algae. This two-fold comprehensive mechanism awaits further theoretic and experimental testing and provides an important guide to control blooms of all algal species. [ABSTRACT FROM AUTHOR]

In global trade, the manufacture and consumption of cotton textile products are intervening in the hydrological cycle. To address the relationship between the product system and the unsustainable use of local water resources, a spatial water footprint assessment is needed. This study presents a spatial water footprint method that was demonstrated in the case of domestically produced cotton T-shirts in three recycle scenarios. The results showed that the water scarcity footprint of conventional T-shirt, eco T-shirt, recycled T-shirt is 2.45 H2O eq, 1.74 H2O eq, 8 × 10−2 H2O eq, respectively, and the water-eutrophication footprint of conventional T-shirt, eco T-shirt, recycled T-shirt is 1.18 × 10−2 PDF·m2·yr−1, 9.47 × 10−3 PDF·m2·yr−1, 4.04 × 10−3 PDF·m2·yr−1, respectively. Two interesting results have been found. Firstly, the hydrosphere has been affected by manufacture and consumption; thus any choice made by manufacturers and consumers may lead to an impact on the water resource in a region that is far from the location. Secondly, the effect of water footprint reduction will be more apparent in places with severe water stress. The spatial water footprint offers a transparent result of each phase's potential contribution to the local environment and could make a quantitative comparison between product stages, products, and local impacts. Thus, spatial water footprint will be a critical component in the sustainability management improvement of the supply chain. [ABSTRACT FROM AUTHOR]

The effective integration of aerial remote sensing data and ground multi-source data has always been one of the difficulties of quantitative remote sensing. A new monitoring mode is designed, which installs the hyperspectral imager on the UAV and places a buoy spectrometer on the river. Water samples are collected simultaneously to obtain in situ assay data of total phosphorus, total nitrogen, COD, turbidity, and chlorophyll during data collection. The cross-correlogram spectral matching (CCSM) algorithm is used to match the data of the buoy spectrometer with the UAV spectral data to significantly reduce the UAV data noise. An absorption characteristics recognition algorithm (ACR) is designed to realize a new method for comparing UAV data with laboratory data. This method takes into account the spectral characteristics and the correlation characteristics of test data synchronously. It is concluded that the most accurate water quality parameters can be calculated by using the regression method under five scales after the regression tests of the multiple linear regression method (MLR), support vector machine method (SVM), and neural network (NN) method. This new working mode of integrating spectral imager data with point spectrometer data will become a trend in water quality monitoring. [ABSTRACT FROM AUTHOR]

Water quality evaluation is the most direct and quantitative description of a reservoir water environment. Due to the lack of biological factor evaluation in water quality evaluation at present, the conventional pollution index evaluation system was used to evaluate water quality and the correlation between the evaluation indexes and the concentration of cyanobacteria was studied. After determining the correlation, a novel calculation method using the cyanobacteria pollution index was determined by principal component analysis (PCA). The results showed that the eutrophication index and nitrogen phosphorus index of the water body were high. Biological pollution in reservoirs cannot be ignored. The correlation between eutrophication index and cyanobacteria concentration was weak (Pearson correlation = 0.242). For the reservoir, it was necessary to establish a special cyanobacteria pollution index. Five variables were used for the cyanobacteria pollution index calculation by the PCA method. The total variance of the two main components was 77.107%, which reflected most of the data information. In the reservoirs of other areas, similar parameters can also be selected to calculate the cyanobacteria pollution index. This research provides a reference for the biological factor evaluation of similar reservoirs in the world. HIGHLIGHTS A special daily water quality test was used in order to make an accurate judgment on water quality.; PCA was selected to establish the calculation method of the cyanobacteria pollution index by considering the relationship between cyanobacteria concentration and other water quality factors.; This research provides a reference for similar areas of the world on water quality evaluation of reservoirs.;

【Background】Water eutrophication has become prevalent in China and the underlying mechanism is the imbalance between nutrients inflow and consumption, which boosts overgrowth of some species. Eutrophication could undermine functions of the aquatic ecosystem, and understanding development of the eutrophication and its determinants is therefore important to ameliorate it. 【Objective】The Pingzhai reservoir in the karst plateau of Guizhou province is an important water source for irrigation and drinking in the province, and the objective of this paper is to unveil its eutrophication and the factors affecting it. 【Method】Water samples were collected from late November 2018 (autumn), January (winter), May (spring) and July (summer) 2019, and for each sample we measured the contents of chlorophyll a (Chla), total phosphorus (TP), total nitrogen (TN), permanganate index (CODMn) and transparency (SD) in it. A model derived based on the fractal interpolation was used to evaluate eutrophication in the reservoir. 【Result】①The TP and CODMn contents in the reservoir meet Class II water quality standard, and the TN content exceeds the class V water quality standard and is the main determinant of the eutrophication. The contents of TN, CODMn and Chla were highest in summer, while the TP content was highest in winter and the SD content was lowest in spring. ②Eutrophication in the reservoir is moderate or above, and the data measured from different locations showed that the reservoir was not oligotrophic, indicating that the reservoir has been eutrophic. ③The reservoir is most eutrophic in summer and least in autumn, with other seasons between. The eutrophication degree was highest at the BS2 and HJ2 monitoring sections, and least at the ZW8 and SG1 sections, with NY3, SG3 and PZ4 sections between. 【Conclusion】In general, the reservoir is highly eutrophic with the increased TN being the main determinant. Controlling inflow and accumulation of nitrogen in the reservoir is hence the top priority to remediate its eutrophication.

Modified maifanite (MMF) was prepared by the synthesized method with sulfuric acid treatment and high-temperature calcination and evaluated as an effective adsorption material to remove the nutrient salt in waste watery. Compared with the raw maifanite (RMF), the MMF exhibited a higher adsorption capacity and higher removal efficiency. The results showed that the adsorption rates of total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (NH3-N), nitrate-nitrogen (NOx-N), and chemical oxygen demand (COD) by MMF were 86.7%, 44.9%, 29.1%, 19.8%, and 11.9%, respectively, and compared to RMF, the average adsorption capacity of these nutrients by MMF increased by 20.5 mg/kg, 126.2 mg/kg, 61.9 mg/kg, 117.18 mg/kg, and 86.9 mg/kg, respectively. MMF maintained the basic structure and composition of maifanite, while having a rougher and looser surface, more irregular pores, wider gaps, and more active materials such as oxidizing Fe. This study suggests that MMF can be further applied to treat domestic sewage and eutrophic water. [ABSTRACT FROM AUTHOR]

At present, there are few studies on known bacterial species and even less on fungi in biological algae control technology. In this paper, the green eutrophic shallow water lake Scenedesmus quadricauda (Turpin) was used as the research object, and white rot fungi, which has a high removal effect on water pollutants, algae and biological toxins, was used for algae control. The extent of the removal effect, physiological characteristics and the internal functional groups of the algae cells in the white rot fungi solution, the supernatant of the white rot fungi solution after centrifugation and the sterilized white rot fungi solution were investigated. The results showed that the best algae solubilization effect of the algae control system was achieved at 250 mg/L, with 8 mg/L of dissolved oxygen and a hydraulic retention time of 48 h. The average algae lysis rate was 85.48%, the average dehydrogenase activity reduction rate was 59.23%, the average soluble protein reduction rate was 65.16% and the average malondialdehyde content increased to 0.128 umol/L. After treatment with the white rot algae control system, the spatial structure of the Turpin cells was severely disrupted, and significant lysis occurred within the algal cells, forcing the release of intracellularly soluble substances, and reducing the dehydrogenase activity of the Turpin cells, thus inhibiting the growth activity of the algae cells. A further reduction in the soluble protein content reduces the nutrients required for the growth of Turpin, exacerbating the rate of reduction in the physiological metabolic activity of the Turpin cells and, ultimately, the inhibition or killing of the algal cells. The results of this research may provide theoretical guidance for the microbial control of water eutrophication; however, whether there will be secondary pollution after the algae dissolution of this process is worthy of further study. [ABSTRACT FROM AUTHOR]

With the improvement of global industrialization and the worsening of ecological environment, the contradiction and problems between industrial agglomeration and ecological pollution, especially water pollution, have become increasingly prominent, but there are few studies on the relationship between industrial agglomeration and water pollution. Based on green development and STIRPAT model, this paper analyzes the empirical theoretical data, discusses the relationship and interaction between regional industrial agglomeration and water pollution, and puts forward specific control measures for the specific impact of the two. The results show that there is a significant positive exponential relationship between industrial agglomeration and water pollution, and the relationship index a is 4.32. Industrial agglomeration causes a large amount of industrial wastewater discharge, and causes the accumulation of various chemical substances in the water body, leading to a chain effect. The content of nitrogen compounds in the water body reaches 103 mg/L, which is far higher than that in the ordinary water 1.02 mg*L. In addition, the paper puts forward reasonable suggestions on water pollution caused by industrial agglomeration, which provides basic reference and basis for regional industrial upgrading and harmonious development of ecological environment. [ABSTRACT FROM AUTHOR]

Abstract In this work, we consider a water eutrophication model with impulsive dredging. We prove that all solutions of the investigated system are uniformly bounded. There exists globally asymptotically stable periodic solution of microorganism-extinction when some condition is satisfied. The condition for permanence of the system is also obtained. It is concluded that the approach of impulsive dredging provides a reliable theoretical basis for the management of water eutrophication.

Quantifying land use heterogeneity helps better understand how it influences biophysical systems. Land use area proportions have been used conventionally to predict water quality variables. Lacking an insight into the combined effect of various spatial characteristics could lead to the statistical bias and confused understanding in previous studies. In this study, using spatial techniques and mathematical models, a diagnostic model was developed and applied for quantifying and incorporating three spatial components, namely, slope, distance to sampling spots, and arrangement. The upper catchment of Miyun Reservoir was studied as the test area. Total nitrogen, total phosphorus, and chemical oxygen demand of water samples from field measurements were used to characterize the surface water quality in 52 sub-watersheds. Using parameter calibrations and determinations, combined spatial characteristics were explored and detected. Adjusted land use proportions were calculated by spatial weights of discriminating the relative contribution of each location to water quality and used to build the integrated models. Compared with traditional methods only using area proportions, our model increased the explanatory power of land use and quantified the effects of spatial information on water quality. This can guide the optimization of land use configuration to control water eutrophication.

The textile industry is one of the most water intensive and polluting industries. China is the world’s largest producer of textile products. For the sustainable development of China’s textile industry, the environmental impacts caused by its water consumption and wastewater discharge must be identified. In this paper, we analysed the water footprint of China’s textile industry based on the water footprint framework proposed in the ISO 14046. The results showed that both water scarcity footprint and water eutrophication footprint increased from 1996 to 2015, despite the fluctuation periods. Water ecotoxicity footprint decreased during the selected researched years. Among the three sub-sectors of China’s textile industry, the water footprints of the manufacture of textiles sector were larger than those of manufacture of textile wearing apparel, foot-ware, and caps sector and manufacture of chemical fibres sector. The water footprint intensity of China’s textile industry has decreased through the efforts of government administrative control measures and producers’ actions on freshwater saving and wastewater treatment. [ABSTRACT FROM AUTHOR]

In order to meet the different needs of water eutrophication evaluation, in view of the diversity and uncertainty of each evaluation index in the evaluation of eutrophication of water body, considering the multi-granularity characteristics of the index, the evaluation model of eutrophication of multi-granularity water body was constructed by using the set pair information particle calculation method. Firstly, the set pair correlation degree of each index of the sample was established at different levels. The evaluation determination degree was determined according to the grade with the maximum positive degree and the smallest negative degree. Secondly, the information entropy of each index was calculated. The importance of the evaluation index was determined according to the entropy. The evaluation determination degree of different granularity under different index subsets was analyzed and the multi-granularity evaluation model of water eutrophication was constructed. Finally, the model was verified with 12 representative lake reservoirs in China and compared with the evaluation results of Gamma-Cloud method, improved rough cloud method, fuzzy variable set method, single index method, neural network method and projection pursuit method, the validity of the model was verified. The results show that the model can reflect the actual situation of water body more objectively and has stronger applicability. [ABSTRACT FROM AUTHOR]

In this study, we aimed to clarify the temporal and spatial variation and main influencing factors of water quality in Hanfeng Lake, which is the largest lake in the Three Gorges Reservoir（TGR）region of China. A total of 14 sampling sites were studied across different regions, including the inflow, main lake body, and outlet areas of the Hanfeng Lake basin. Water samples were collected at each sampling site at the end of each month in 2015 and water quality parameters were analyzed. Multiple statistical techniques were used to identify spatial and temporal variations in water quality. The water quality of Hanfeng Lake could be clustered into four spatial regions, including the incoming water area of Nan River（Region 1）, the incoming water area of East River（Region 2）, the upper reaches of Hanfeng Lake （Region 3）, and the middle and lower reaches of Hanfeng Lake（Region 4）. Variations in water quality could also be grouped into two distinct periods：Storage period（from January to February and September to December）and drainage period（from March to August）. Trophic state analysis indicated that water quality in the regulating dam（HF5）and below the regulating dam（XJ1）, both of which belonged to Region 4, exhibited moderate eutrophication; Sites in other regions showed slight eutrophication. The eutrophication level was lowest in January and December and highest in October, reaching moderate eutrophication levels; other months showed mild eutrophication levels. The concentrations of total nitrogen（TN）, ammonium nitrogen（NH+4 -N）, nitrate nitrogen（NO-3 -N）, total phosphorus（TP）, soluble phosphorus（DP）, orthophosphate（PO34--P）, and permanganate index（CODMn）showed downward trends from upstream to downstream in the Hanfeng Lake basin. Principal component analysis results implied that soil and water losses contributed most to the deterioration of water quality in the Hanfeng Lake and the regulation of water levels related to the TGR also significantly affected the water quality. [ABSTRACT FROM AUTHOR]

Eutrophication and frequent algal blooms have become serious ecological problems. White-rot fungi have been considered as possible microorganisms for controlling algal blooms. In this study, Cryptomonas obovata FACID3-1301, Oscillatoria sp. FACIIB-1083, and Scenedesmus quadncauda FACIIB-507 co-cultured with the white-rot fungus Phanerochaete chrysosporium. All algal cells were damaged within 48 h of coculture. P. chrysosporium apparently decreased the chlorophyll-a content, dehydrogenase activity, and soluble protein content but increased the malondialdehyde content of the algal cells. These results indicate that the algae were greatly inhibited and severely damaged by the fungus. In conclusion, P. chrysosporium can effectively remove algal cells and inhibit algal blooms. [ABSTRACT FROM AUTHOR]

With the frequent occurrence of water pollution, the safety of the surface water environment has become increasingly severe. Studying the changing trend of reservoir water quality and establishing a prediction and early warning system for water eutrophication is of great significance to the management and maintenance of water resources. Based on the time series ARIMA model, the Holt-Winters seasonal model was introduced for optimization, and a universal water quality prediction model with eutrophication indicator Total Phosphorus and Total Nitrogen as parameters was established. And through self-correction, the water quality prediction accuracy rate has been improved to 97.5%. Experiments showed that compared with the traditional water quality prediction model, this model is simpler and more convenient, and it has the advantages of high learning speed, high prediction accuracy, easy multi-dimensional analysis of data, and close connection with the development laws of things. Therefore, the model can be applied to the short-term prediction of different reservoirs, can significantly reduce the predicted cost of reservoir water quality, and provide methods for the study of dynamic changes of reservoir water quality parameters; thus, it will be a scientific basis and decision support for water quality improvement. [ABSTRACT FROM AUTHOR]

• Insoluble humic acid (IHA) could promote P adsorption by sediments. • The equilibrium P concentration (EPC 0) was decreased with increasing of IHA. • Deprotonation of IHA could significantly facilitate P sorption by Fe/Al oxides. • IHA could adsorb P by metal bridge and H-bonding of surface functional groups. • P released from NH 4 Cl-P and BD-P could be re-adsorbed by Al oxides and IHA. Release of phosphorus (P) from the sediments plays a critical role in the eutrophication of aquatic environments. Humic acids (HA), as the main form of carbon storage in the sediments, has essential impacts on the biogeochemical cycle of phosphorus in aquatic systems. Nevertheless, previous studies mainly concentrated on the competitive adsorption of HA solution and P on metal oxides and soils, with little attention paid to the effects of insoluble humic acids (IHA) on P sorption by and release from the sediments. Herein, an investigation on the rivers and lakes in Sichuan Province, China, found that there was a significantly positive correlation between the maximum P adsorption capacity (Q max) of sediments and IHA contents (p < 0.01), but a significantly negative correlation between the zero equilibrium P concentration (EPC 0) and IHA concentrations (p < 0.01). This indicated that IHA might have an inhibitory effect on the release of P from the sediments, which was verified by batch adsorption experiments and static incubation experiments. Adsorption experiments indicated that IHA can promote P adsorption by sediments. With the increase of IHA addition (from 0 to 20 mg/g) in the sediments, Q max of sediments increased (from 0.516 to 0.911 mg/g), while EPC 0 decreased greatly (from 0.264 to 0.005 mg/L). Increases in Fe (Ⅲ) bound-P, Al bound-P and humic bound-P caused by IHA were responsible for this promoting effect. Incubation experiments illustrated that IHA addition can efficiently inhibit P release from the sediments. After 32 days incubation, P concentration in the overlying water of control group (without IHA addition) was 0.651 mg/L, which was 13.29–40.69 times higher than those (0.016–0.049 mg/L) in the test groups (with 5 %-20 % IHA addition). The analysis of P species in sediments showed that transformation from loosely adsorbed-P and Fe (Ⅲ) bound-P to Al bound-P and humic bound-P was responsible for this inhibition of P release by IHA. This study demonstrated that IHA, differing from readily degradable or dissolved organic matter, have great inhibitory effects on internal P release, which provided a novel insight into the association between carbon burial and internal P release and even the management of water eutrophication. [Display omitted] [ABSTRACT FROM AUTHOR]

[Display omitted] • Area and number density of aquaculture ponds were calculated by remote sensing. • Pond aquaculture is an important source of TN and TP in surface water. • Chemical fertilizer expanded fish output while polluted the water environment. • Failure of cyanobacteria control in Taihu is linked to the expanding pond culture. • Lake water eutrophication caused by pond culture is widespread in China. Nitrogen and phosphorus discharges from freshwater pond aquaculture have become an important source of eutrophication in lakes. Based on multi-source remote sensing and Google Earth Engine, we extracted aquaculture ponds nationwide and calculated their quantities and area density distributions. Experimental results reveal that regions with densely distributed aquaculture ponds are also hotspots for severe lake cyanobacterial blooms, especially in the middle and lower reaches of the Yangtze River. Presently, freshwater aquaculture production in this basin accounts for 1/3 of the total in the world. With the increasing pond area, Total Nitrogen (TN) and Total Phosphorus (TP) discharged into the Yangtze River Basin rises year by year, leading to decrease in the water quality of the basin. Downstream of this basin, Taihu Lake, the number and area of ponds have increased fivefold since 1984, reaching 575 km2 in 2016. Using the unit area production and the nitrogen-phosphorus discharge per kilogram of aquatic product (27.7 g/kg of TN, 4.43 g/kg of TP), we calculated that the TN and TP discharge in 2016 was as high as 7,185 tons and 1,150 tons. These discharges essentially enter Lake Taihu through rivers, they would account for 21.7 % and 64.4 % of Taihu Lake's net nitrogen and phosphorus input. From 2000 to 2020, both the scale of aquaculture ponds and floating cyanobacteria inversion results showed an increasing trend, and the failure of cyanobacteria control in Taihu Lake is linked to the increase in TN and TP excretion from these ponds. From 2020 to 2022, the strict zero-Covid policy significantly reduced social gatherings and, consequently, led to a substantial decrease in the demand for aquatic products. However, with the relaxation of control measures, the cyanobacteria in Taihu Lake resurged and cyanobacteria harvesting enters the norm in 2023. The underestimated discharge of nitrogen and phosphorus from aquaculture ponds will affect public health and the sustainability of development. [ABSTRACT FROM AUTHOR]

At present, all kinds of pollutants are discharged into the landscape water body, and the landscape water body is mostly static or slow flow state. This leads to the deepening of water pollution, eutrophication, blackening of water body, and stench and flood disasters occur frequently. This makes the urban landscape water lose its ornamental value, affects the effective operation of ecological function, and will also endanger the health of residents. Reclaimed water is one of the common methods of modern landscape water, but reclaimed water contains a lot of nitrogen and phosphorus, which will make the eutrophication of water body increase, and easily lead to "algal blooms", water quality deterioration, and loss of landscape function. Therefore, understanding the current situation of landscape water eutrophication and effective prevention and control measures has become one of the water environment problems to be solved. [ABSTRACT FROM AUTHOR]

Fish is an important organism in the water and its living environment are a unified whole, interrelating and influencing each other. Changes in fish behavioral trajectories can directly reflect the deterioration degree of water. When the cyanobacteria in the water consume a lot of oxygen during reproduction, death and decomposition, which makes the dissolved oxygen content rapidly decrease, the fish swimming trajectory changes significantly and responds accordingly. In this paper, acoustic tag tracking technology was used to study the swimming ability of fish by simulating the eutrophication process in a simulating natural ecosystems tank and obtain its three-dimensional trajectory to determine the dissolved oxygen threshold when fish behavior changed. The variation regularity of fish behavioral trajectories was investigated with the change of dissolved oxygen content during water eutrophication. The experimental results showed that the individual behavioral response of adult carp was unobvious in the process of oligotropher to light eutropher, but at the state of middle and hyper eutropher was obvious. When the dissolved oxygen is 0.5 mg/L, adult carp began to breathe hard and float on the water surface. When the dissolved oxygen content dropped to 0.2 mg/L, adult carp began to die. During the process of dissolved oxygen content decreasing, the swimming trajectory of adult was convergent in space while they migrated from the bottom of water to surface in the direction of longitudinal water depth, and the swimming speed was slower and slower. Regression analysis was used to analyze the correlation between individual behavioral trajectories of adult carp and dissolved oxygen content. The results indicated that the swimming trajectory of water depth was highly negatively correlated with dissolved oxygen content. The swimming speed of adult carp and dissolved oxygen content had a strong negative correlation. The significant changes in the individual behavioral trajectories of adult carp indicated the environment of water has changed. It was suggested that dissolved oxygen content, which affected the changes of fish behavior, and individual behavioral trajectories of fish as a biological indicator were used to evaluate the water ecological restoration effect and ecological health status of water. It can more accurately reflect the current status of the aquatic ecosystem. [ABSTRACT FROM AUTHOR]

Quantifying land use heterogeneity helps better understand how it influences biophysical systems. Land use area proportions have been used conventionally to predict water quality variables. Lacking an insight into the combined effect of various spatial characteristics could lead to the statistical bias and confused understanding in previous studies. In this study, using spatial techniques and mathematical models, a diagnostic model was developed and applied for quantifying and incorporating three spatial components, namely, slope, distance to sampling spots, and arrangement. The upper catchment of Miyun Reservoir was studied as the test area. Total nitrogen, total phosphorus, and chemical oxygen demand of water samples from field measurements were used to characterize the surface water quality in 52 sub-watersheds. Using parameter calibrations and determinations, combined spatial characteristics were explored and detected. Adjusted land use proportions were calculated by spatial weights of discriminating the relative contribution of each location to water quality and used to build the integrated models. Compared with traditional methods only using area proportions, our model increased the explanatory power of land use and quantified the effects of spatial information on water quality. This can guide the optimization of land use configuration to control water eutrophication. [ABSTRACT FROM AUTHOR]

• Submarine (fresh) groundwater discharge and its associated nutrient fluxes were estimated in an urbanized bay. • Submarine groundwater discharge was an invisible but significant source of nutrients. • Groundwater nutrient inputs to the ocean may result in widespread phosphorus limitation and eutrophication in coastal waters. Driven by the anthropogenic activities associated with coastal settlements, eutrophication has become a global issue. Submarine groundwater discharge (SGD) is a significant continuous pathway for transporting nutrients from land to coastal waters, but its influence on eutrophication in Liaodong Bay (LDB) has received limited attention. In this study, radium isotopes and nutrient data from coastal waters were analyzed to evaluate the SGD flux and its implications for potential eutrophication in LDB. We found that the mean concentrations of dissolved inorganic nitrogen (DIN), phosphorous (DIP), and silicate (DSi) in groundwater were higher than those of seawater and river water. Based on 223Ra and 228Ra mass balance models, the SGD fluxes were estimated to be (0.53–2.03) × 109 m3/d, of which the fresh SGD accounted for 4 %–15 %. SGD is a vital invisible source of nutrients, contributing more than 79 % of the total inputs of DIN, DIP, and DSi into LDB. With high DIN/DIP ratios (average=85.8) and large nutrient inputs, SGD may significantly drive the phosphorus limitation and eutrophication in LDB. This study shows that SGD-derived nutrient fluxes should be considered in the assessment of water eutrophication for the formulation of future environmental management protocols in coastal systems. [Display omitted] [ABSTRACT FROM AUTHOR]

The coast of Laizhou Bay is plagued by a number of environmental issues, such as eutrophication, which are likely to worsen over the next few decades as a result of trends toward industrialization and urbanization. High nutrient levels in the Xiaoqing River are believed to be the main cause of Laizhou Bay becoming eutrophicated. Therefore, we conducted two cruises from the Xiaoqing River estuary to Laizhou Bay in August 2022 and December 2022, respectively, in the wet and dry periods to assess the potential impact of status of eutrophication due to human activities. The results showed that the concentration of DIN was higher than the quality standard for water (f i > 1) in both the wet season (August 2022) and the dry season (December 2022). DIN has major environmental impacts in Laizhou Bay. The eutrophication level index and organic pollution index have obvious spatial and temporal characteristics. In terms of time, the dry season is higher than the wet season. In space, Xiaoqing estuary is higher than Laizhou Bay. In the two surveys, DIN and DIP concentrations were significantly positively correlated, indicating that N and P pollution in the region had a common source and destination, and the spatial distribution was also similar. In addition, the current environmental conditions in the region are not ideal, reaching moderate and severe eutrophication levels, which proves that the ecosystem has the risk of aggravating degradation. As the Xiaoqing River is about to resume full navigation, human-related nutrient input (especially DIN) will continue to increase, and it is expected that the eutrophication risk in this area will increase in the next few years due to the increase in nutrient load. [Display omitted] • Dissolved inorganic nitrogen was a major pollutant in Laizhou Bay coast. • Dissolved inorganic nitrogen and dissolved oxygen were key factors of water quality. • The nutritional status of the research area ranged from mild to severe nutrition. • Environmental parameters had obvious spatio-temporal patterns. [ABSTRACT FROM AUTHOR]

Eutrophication resulting from nutrient enrichment decreases water quality and harms ecosystem structure and function, and its degree is significantly affected by land use in the catchment. Quantifying the relationship between eutrophication and land use can help effectively manage land use to improve water quality. Previous studies principally utilized land use quantity as an indicator to link water quality parameters, but these studies lacked insight into the impact of land use intensity. Taking the upper catchment of Miyun Reservoir as a case study, we developed a method of aggregating land use quantity and intensity to build a new land use indicator and tested its explanatory power on water quality. Six nutrient concentrations from 52 sub-watersheds covering the whole catchment were used to characterize the spatial distribution of eutrophication. Based on spatial techniques, empirical conversion coefficients, remote sensing data, and socio-economic statistical data, land use intensity was measured and mapped visually. The new land use indicator was calculated and linked to nutrient concentrations by Pearson correlation coefficients. Results demonstrated that our new indicator incorporating intensity information can quantify the different nutrient-exporting abilities of different land use areas. Compared to traditional indicators that only incorporate land use quantity, most Pearson correlation coefficients between the new indicator and water nutrient concentrations increased. This new information enhanced the explanatory power of land use on water nutrient concentrations, and so will be able to help us understand the impact of land use on water quality and guide decision making for better land use management. [ABSTRACT FROM AUTHOR]

In Finland, the current water conservation policy sets equal incentives for water conservation, regardless of the environmental condition. Before any policy reform, it is vital to investigate the tendency of landowners to adopt water conservation measures. In this study, we were interested in examining adoption if the soil quality implies a high leaching risk and if the water quality is already poor. By combining survey data with GIS data, we analysed the effect of farm and farmer characteristics and attitudes towards adoption. Our probit models indicated that financial variables were the key determinants of adoption for active farmers, whereas for passive owners, adoption was also explained by attitudes. In contrast to our expectations, adoption in areas under risk was weakly supported by our estimates. Environmental awareness, providing it increases with risk, is not strong enough to motivate adoption. Targeted agri-environmental measures, even though costly, cannot be avoided, and spatially tailored measures can attract adopters in hotspot areas. [ABSTRACT FROM PUBLISHER]

Dianchi Lake belongs to the Jinshajiang River system of the Yangtze River Basin. Due to the fast growth of economic and social development, Dianchi Lake has lost its self-purification capability and suffers from serious eutrophication. This study summarized historic trajectory of the ecological and environmental changes in the lake basin, with emphasis on the changes of physical, chemical, biological, and ecological characteristics of the lake as well as the social development in recent years. Despite the great efforts initiated by the government aiming at restoration of the environmental quality of the lake, the results were not substantially significant. We believe that a comprehensive lake model is imperative to understand the ecological functions of the lake and establish scientifically defined realistic goals for the restoration. In addition, continual modernization of rural area and certain adjustment in population decentralization in the lake basin area will help reduce the environmental pressure. [ABSTRACT FROM AUTHOR]

Increasingly, the characteristics of nitrogen (N) loading have been recognized to be critical for the maintenance and restoration of water quality in agricultural watersheds, in response to the spread of water eutrophication. This paper estimates N loading and investigates its influencing factors in ten small watersheds variously dominated by forest and agricultural land use types in the subtropics of China, over an observation period of 23-29 months. The results indicate that the average concentrations of total nitrogen (TN), NH-N, and NO-N were 0.83, 0.07, and 0.46 mg N L in the forest watersheds and 1.49-5.16, 0.21-3.23, and 0.99-1.30 mg N L in the agricultural watersheds, respectively. Such concentrations exceed the national criteria for nutrient pollution in surface waters considerably, suggesting severe stream pollution in the studied agricultural watersheds. The average annual TN loadings (ANL) were estimated to be 1,640.8 kg N km year in the agricultural watersheds, 63.3-86.1 % of which was composed of dissolved inorganic N (DIN; comprising NO-N and NH-N). The watershed with intensive livestock production (i.e., the maximum livestock density of 2.66 animal units (AU) ha) exhibited the highest ANL (2,928.7 kg N km year) related to N loss with effluent discharge. The results of correlation and principle component analysis suggest that livestock production was the dominant influencing factor for the TN and NH-N loadings and that the percentages of cropland in watersheds can significantly increase the NO-N loading in agricultural watersheds. Therefore, to restore and maintain water quality, animal production regulations and more careful planning of land use are necessary in the agricultural watersheds of subtropical China. [ABSTRACT FROM AUTHOR]