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Managing agricultural watersheds in an environmentally friendly manner necessitate the strategic implementation of well-targeted sustainable land management (SLM) practices that limit soil and nonpoint source pollution losses and translocation. Watershed-scale SLM-scenario modeling has the potential to identify efficient and effective management strategies from the field to the integrated landscape level. In a case study targeting a 66-hectare watershed in Petzenkirchen, Lower Austria, the Soil and Water Assessment Tool (SWAT) was utilized to evaluate a variety of locally adoptable SLM practices. SWAT was calibrated and validated (monthly) at the catchment outlet for flow, sediment, nitrate-nitrogen (NO 3 -N), ammonium nitrogen (NH 4 -N), and mineralized phosphorus (PO 4 -P) using SWATplusR. Considering the locally existing agricultural practices and socioeconomic and environmental factors of the research area, four conservation practices were evaluated: baseline scenario, contour farming (CF), winter cover crops (CC), and a combination of no-till and cover crops (NT + CC). The NT + CC SLM practice was found to be the most effective soil conservation practice in reducing soil loss by around 80%, whereas CF obtained the best results for decreasing the nutrient loads of NO 3 -N and PO 4 -P by 11% and 35%, respectively. The findings of this study imply that the setup SWAT model can serve the context-specific performance assessment and eventual promotion of SLM interventions that mitigate on-site land degradation and the consequential off-site environmental pollution resulting from agricultural nonpoint sources., (© 2023. The Author(s).)

Speeding up the promotion and application of biofuel ethanol has been a national strategy in China, which in turn has affected changes in the raw material planting structure. This study analyzed the response mechanism of water quality to agriculture land-use changes in a cassava fuel ethanol raw material planting area. The results revealed that an increase in cultivated land and construction land would lead to a rise in the load of TN (total nitrogen) and TP (total phosphorus), while an expansion in forest land and grassland area would reduce the load. As for crop structures, corn would have a remarkable positive impact on TN and TP, while rice and cassava performed in an opposite manner. Furthermore, scenarios under the carbon neutralization policy were carried out to forecast the nonpoint source pollutants based on the quantitative relations coefficients. It was proven that cassava planting was suitable for vigorous fuel ethanol development, but the maximum increase area of cassava should be 126 km 2 to ensure economic benefits. Under the change in fuel ethanol policy, this study could provide scientific support for local agriculture land-use management in realizing the carbon neutralization vision and also set a good example for the development of the cassava fuel ethanol industry in other cassava-planting countries.

The effect of rainfall on the water quality of urban lakes is related to the surrounding land use types. Six lakes surrounded by business units (commercial lakes) and park green spaces (park lakes) in the central area of Beijing, China, were monitored between June 2013 and October 2015. A total of 638 water samples were obtained. The results showed that the water quality was generally worse in the rainy season than in the dry season, with the mean dissolved oxygen (DO) concentration declining by 25.1 %. Compared to the rise in DO of park lakes after rainfall, commercial lakes showed a decreased DO. The nitrate nitrogen (NO 3 - -N) concentration decreased after rain, and that in commercial lakes decreased more than that in park lakes. Different from DO and NO 3 - -N, the ammonia nitrogen (NH 4 + -N)), total suspended solids (TSS) and total phosphorus (TP) concentrations of the lakes increased obviously after rain. The values in park lakes increased 138 % (NH 4 + -N)), 120 % (TSS) and 69 % (TP) more than those in commercial lakes. Principal component analysis (PCA) results illustrated that green space was the main source of TSS and TP for urban lakes. Most of the nitrogen (N) comes from artificial impervious surfaces. These results will help target pollutant control for urban lakes., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Nonpoint source (NPS) water quality trading (WQT) has been lauded as a way to reduce water pollution while mitigating costs, but NPS WQT programs often do not account for cumulative landscape-scale impacts to hydrological and ecological processes. In this work, we parameterize the landscape-scale patterns of an emerging NPS WQT market in Virginia (n = 606 transactions) and describe potential tradeoffs and synergies. We also examine program outcomes in the context of Virginia's spatially-explicit conservation and restoration priorities, and discuss ways in which NPS WQT integrates or fails to integrate with these state-level watershed management goals. These spatial and policy analyses demonstrate novel ways to evaluate NPS WQT programs. Our results reveal how NPS WQT has influenced Virginia land management patterns in practice. Specifically, we show that this program has encouraged the transfer of water quality Best Management Practices (BMPs) from urban to rural areas. Impact sites are often far from mitigation sites, at an average of 164.6 km apart measured along the stream network and most often migrated outside the 8-digit Hydrologic Unit Code watershed boundaries. We also find opportunity for improved integration with the state-level management priorities, including that an estimated 22% of the NPS WQT mitigation site area works against state priorities (for example by converting prime farmland to forest), 9% supports state priorities, and 69% neither negates nor supports state priorities. We suggest policy and management actions that can increase the integration of NPS WQT with statewide watershed management goals, and could ultimately improve environmental returns from this fast-growing program., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Pesticide loss during agricultural development has a serious effect on related water quality, and the critical concern is quantifying the potential exposure risks that pesticide loss pose to water quality at the national scale. In this study, an integrated assessment framework is proposed to scale emission factors from 232 monitoring plots to the national scale, while also considering the physicochemical properties of pesticides in dissolved or adsorbed forms. Based on the results of this study, the total pesticide emissions increased by 29.39% from 146.55 tons in 2004 to 189.62 tons in 2013 and the average loss intensities of insecticides, herbicides and fungicides were 35.25 g/km 2 , 44.24 g/km 2 and 48.57 g/km 2 , respectively. Central and Southeastern China are identified as hotspots for pesticide loss, while the proportions of high or extremely high-risk areas mainly comprise >50% of farmland. In addition, single-field crops and single-crop rice are the major cropping patterns for pesticide loss in Northern and Southern China. Our results identify key areas for the management of pesticides at the national scale and have direct implications for environmental policies on reducing the potential exposure risk of agricultural pesticides to water quality., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Microorganism pollution in rivers is of great importance to the protection of watershed water quality and public health management. As a typical watershed of the Haihe River watershed, the Beiyun River was chosen as the study area, and the characteristics and health risk of microorganism pollution were assessed from a comprehensive perspective. The results showed that the microbial contamination of the fecal sources was serious during the wet season, and the microbial amount at most river sections was more than 10 5 MPN·L -1 . During the normal season and dry season, the microbial amount was approximately 10 3 -10 5 MPN·L -1 . Therefore, no obvious change could be observed. The fecal pollution in the agricultural river sections was the most severe, and the water quality of over 60% of these river sections was below the state Grade V level. The fecal microbial biomass of some urban river sections increased from 10 3 MPN·L -1 to 10 6 MPN·L -1 after the rainfall event, indicating an obvious change of fecal microbial pollution during the rainfall process. For the Beiyun River, the exposure risk of the fecal microbial biomass was mainly between 0.015-0.035, while the Lianhua River, Macao River, lower reaches of Qinghe River, and lower reaches of Wenyu River were hotspots for contamination. Greater attention should be paid to these areas.

Studies have shown that the agricultural expansion and land use changes in the Midwest of the U.S. are major drivers for increased nonpoint source pollution throughout the regional river systems. In this study, we empirically examined the relationship of planted area and production of three dominant crops with nitrate flux in the Republican River, Kansas, a sub-watershed of Mississippi River Basin. Our results show that land use in the region could not explain the observed changes in nitrate flux in the river. Instead, after including explanatory variables such as precipitation, growing degree days, and well water irrigation in the regression model we found that irrigation and spring precipitation could explain >85% of the variability in nitrate flux from 2000 to 2014. This suggests that changes in crop acreage and production alone cannot explain variability in nitrate flux. Future agricultural policy for the region should focus on controlling both the timing and amount of fertilizer applied to the field to reduce the potential leaching of excess fertilizer through spring time runoff and/or over-irrigation into nearby river systems.

The Hydrological Simulation Program-Fortran (HSPF) is a hydrological and water quality computer model that was developed by the United States Environmental Protection Agency. Comprehensive performance evaluations were carried out for hydrological and nutrient simulation using the HSPF model in the Xitiaoxi watershed in China. Streamflow simulation was calibrated from 1 January 2002 to 31 December 2007 and then validated from 1 January 2008 to 31 December 2010 using daily observed data, and nutrient simulation was calibrated and validated using monthly observed data during the period from July 2009 to July 2010. These results of model performance evaluation showed that the streamflows were well simulated over the study period. The determination coefficient ( R ²) was 0.87, 0.77 and 0.63, and the Nash-Sutcliffe coefficient of efficiency (Ens) was 0.82, 0.76 and 0.65 for the streamflow simulation in annual, monthly and daily time-steps, respectively. Although limited to monthly observed data, satisfactory performance was still achieved during the quantitative evaluation for nutrients. The R ² was 0.73, 0.82 and 0.92, and the Ens was 0.67, 0.74 and 0.86 for nitrate, ammonium and orthophosphate simulation, respectively. Some issues may affect the application of HSPF were also discussed, such as input data quality, parameter values, etc. Overall, the HSPF model can be successfully used to describe streamflow and nutrients transport in the mesoscale watershed located in the East Asian monsoon climate area. This study is expected to serve as a comprehensive and systematic documentation of understanding the HSPF model for wide application and avoiding possible misuses., Competing Interests: The authors declare no conflict of interest.

This manuscript evaluates the U.S. Recreational Water Quality Criteria (RWQC) of 2012, based upon discussions during a conference held 11-13 March 2013, in Honolulu, Hawaii. The RWQC of 2012 did not meet expectations among the research community because key recommended studies were not completed, new data to assess risks to bathers exposed to non-point sources of fecal indicator bacteria (FIB) were not developed, and the 2012 RWQC did not show marked improvements in strategies for assessing health risks for bathers using all types of recreational waters. The development of the 2012 RWQC was limited in scope because the epidemiologic studies at beach sites were restricted to beaches with point sources of pollution and water samples were monitored for only enterococci. The vision for the future is development of effective RWQC guidelines based on epidemiologic and quantitative microbial risk assessment (QMRA) studies for sewage specific markers, as well as human enteric pathogens so that health risks for bathers at all recreational waters can be determined. The 2012 RWQC introduced a program for states and tribes to develop site-specific water quality criteria, and in theory this approach can be used to address the limitations associated with the measurements of the traditional FIB.

Under the current increasingly serious water pollution situation in urban, the comprehensive treatment and protecting measures in urban small catchment are the necessary step to the water pollution treatment, not only focus on the water bodies themself. In this paper, the Luojiagang river channel and its catchment in Wuhan, which has been heavily impacted by water pollution, are taken as an example for the comparative assessment of pollution control measures in order to explore the effective and sustainable schemes including the LID (Low Impact Development---LID) by using SWMM model (Storm Water Management Model---SWMM). Through the comparison of pollution treatment measures based on scenarios simulation with the baseline scenarios, it was found that the reduction effects of pollutant peak concentrations at the outlet node of Luojiagang River had the decreasing order of: the combined measures (COS) > LID control > the water diversion from Donghu Lake (WAD) > the sewage treatment (SET) > the sediment dredging (SED), and the reduction effects of total pollutant load had the decreasing order of: LID > COS > SET > SED > WAD. The results show that the control of non-point source pollution is the key for the improvement of water quality in Luojiagang River, and LID plays important role in the reduction of both pollutant peak concentrations and load. This study has the implication for the decision making of the water pollution controlling schemes in urban small catchment. [ABSTRACT FROM AUTHOR]

Like many small island communities, the U.S. Virgin Islands (USVI), an unincorporated territory of the U.S., is naturally freshwater scarce. In recent decades, rapid land development in the USVI has increased water demand considerably, exerting extra pressure on freshwater resources. Freshwater quantity and quality data for the USVI are very scarce and scattered, which limits freshwater management capabilities. We draw attention to this information deficit and discuss its implications by reviewing the current state of knowledge of surface and groundwater quantity and quality for the USVI. Our review confirms that long‐term records of surface and groundwater quantity and quality are limited and unreliable. For example, streamflow was most recently monitored in 2006, and the most extensive surface water quality records are from the 1960s and 1980s. Since 2016, mean groundwater levels have been recorded daily, but only for three wells (one on each island of the USVI). Importantly, this lack of information threatens water security for the territory and limits our understanding of how development has impacted water quality and availability over time. This could be addressed using models, such as a groundwater recharge model, in combination with remote sensing and updated field data (i.e., streamflow, groundwater, and ecohydrological characterizations of land use change). [ABSTRACT FROM AUTHOR]

Nonpoint source pollution (NPS) has been known as runoff or diffuse pollution. It is still difficult to real-time monitor and simulate NPS, due to the significantly complex influencing factors. Therefore, the assessment theory of landscape ecological risk can be expected to identify the regional pollution risk from the perspective of landscape pattern and ecological process. In this study, NPS risk assessment was established using the “ source-sink“ landscape pattern theory. The first step was to identify “source-sink“ landscape. Cultivated, residential, transportation and commercial land were identified “ source landscape", while woodland, green land, water area and wetland were identified “sink“ landscape. The second step was the landscape spatial load comparison index (LCI) correction. The output coefficient and empirical model were combined to determine the “ source-sink” landscape pollutant output/interception coefficient. Then, the slope, altitude and distance from river were selected as the pollutions migration factors to correct LCI values. The final step was to evaluate the NPS pollution risk. The risk was calculated by LCI, slope factor and cost distance. The risks were divided into three grades, according to the natural breakpoint. Taking Shenzhen River-bay Basin as an example, the risk of NPS pollution was assessed using the “ source-sink“ landscape pattern theory. The numerical and spatial correlation analysis was conducted with the field monitoring pollutant data to verify the accuracy of the improved model. The research results showed that: (1) No.7, 9, 10, 12 and 13 watersheds were the high risk of NPS in Shenzhen River-Bay watershed in the whole Buji River basin and the lower reaches of Futian River basin. The low-risk areas were except No. 1 and 6 watersheds in the north of study area and No. 16, 17 and 18 watersheds in the east of study area. The rest 8 watersheds were all medium risk areas. NPS risk level was closely related to the “source-sink” landscape area ratio and landscape spatial pollutants load index, but the topographic factor shared the little influence on the basin. The residential land and transportation land showed the largest contribution rate to NPS risk, while the forest land and water area had outstanding effect on pollutant retention. (2) Both average concentrations of total nitrogen (TN) and total phosphorus (TP) in Shenzhen River-Bay basin were fully met the IV standard level of surface water quality. The average concentration exceedance rate of TN and TP were 12.99% and 11.89%, respectively, in rainy season, and 8.61% and 9.44% in the non-rainy reason. The maximum concentrations of pollutions occurred in the rainy season. The pollutants spatial analysis showed that Shenzhen River basin pollution risk was more serious than Shenzhen Bay basin, while the downstream was than in the upstream, and the higher in the coastal area than in the non-coastal area. The pollutants monitoring data showed that the high-risk area of NPS were No.5, 7, 9, 10, 12, 13 watersheds. Except No.5 watershed, the high-risk watersheds were consistent between monitoring and assessment. (3) The NPS risk assessment index using the “source-sink” landscape theory shared a significant correlation with the actual monitoring risk of TN and TP, indicating a highly spatial aggregation. The NPS risk assessment index can also provide the scientific and accurate reference to assess the ecological risk of watershed in regional scale. [ABSTRACT FROM AUTHOR]

Nonpoint source (NPS) pollution has emerged as the predominant water environment issue confronting plateau lakes in central Yunnan. Quantitative analysis of the impact of NPS pollution on water quality constitutes the key to preventing and controlling water pollution. However, currently, there is a dearth of research on identifying NPS pollution risks and exploring their relationship with water quality based on the Minimum Cumulative Resistance (MCR) model in the plateau lake basins of central Yunnan. Particularly, studies on the spatial heterogeneity of the impact of NPS pollution on water quality from a multi-scale perspective are scarce. Therefore, this study focuses on three typical lake basins in the Central Yunnan Plateau–Fuxian Lake, Xingyun Lake, and Qilu Lake (the Three Lakes). Utilizing the MCR model to identify NPS pollution risks, the study analyzes seven different scales, including sub-basins, riparian buffer zones (100 m, 300 m, 500 m, 700 m, and 1,000 m) and lakeshore zones, to reveal the multi-scale effects of NPS pollution on water quality through correlation analysis. The results indicate that: (1) Over 60% of the areas in the Three Lakes Basin are at high or extremely high risk, mainly concentrated in flat terrain and around inflow rivers; (2) The area of NPS pollution from paddy field source landscape (PFSL) is greater than that from construction land source landscape (CLSL), and the high-risk areas of NPS pollution are also larger for PFSL compared to CLSL; (3) The mean resistance values of PFSL and CLSL show a significant negative correlation with monthly mean values of water quality indexes (NH3-N, TP, CODCr), with the 1,000 m riparian buffer zone scale showing the greatest correlation with most water quality indexes, especially NH3-N; (4) The correlation between the mean resistance value of CLSL and the monthly mean values of water quality indexes is significantly higher than that of PFSL, indicating a greater impact of CLSL on water quality compared to PFSL. In summary, PFSL and CLSL are the primary sources of NPS pollution in the Three Lakes Basins. The 1,000 m riparian buffer zone scale is the most sensitive to the impact of NPS pollution on water quality. This study provides scientific references for landscape pattern optimization and precise control of NPS pollution risks in the Central Yunnan Plateau lake basins and offers a new research perspective for exploring multi-scale effects of NPS pollution on water quality. [ABSTRACT FROM AUTHOR]

Non-point source pollution and water eutrophication from agricultural runoff present global challenges that impact ground and surface waters. The search for a feasible and sustainable mitigation strategy to combat this issue remains ongoing. This scoping review aims to explore one potential solution by examining relevant literature on agricultural practices of the past and recent edge-of-field measures, designed to ameliorate the impacts of agricultural runoff on soil and water quality. The study focuses on integrating findings from diverse research fields into a novel myco-phytoremediation approach, which involves the synergistic relationship of plants, arbuscular mycorrhizal fungi, and plant beneficial bacteria within vegetative buffer strips. The implementation of these augmented buffer strips enhances nutrient retention in the soil, reduces runoff volume, promotes biodiversity, and increases plant biomass. This biomass can be converted into biochar, an effective sorbent that can be used to filter dissolved and particulate nutrients from surface waterways. The resulting nutrient-rich biochar can be repurposed as a form of bio-fertiliser, optimizing fertiliser consumption and subsequently reducing the depletion rate of phosphorus, a limited resource. This paper investigates a circular model of abatement of agricultural runoff via maximal nutrient retention and subsequent recycling of nitrogen and phosphorus back into the agricultural system. The key impact lies in its contribution to addressing the issue of non-point source pollution and eutrophication by encouraging multidisciplinary research aimed at solving these complex environmental issues. [ABSTRACT FROM AUTHOR]

Water quality impairment from fertilizer runoff remains a major source of urban-agricultural conflicts when it leads to serious health risks. In this paper, we analyze the role of watershed organizations in Iowa, USA, that include both agricultural and urban stakeholders to address water quality challenges. We conducted three focus group discussions with 14 coordinators representing these watershed organizations to analyze what policy tools these organizations are using to address urban-agricultural conflicts and what outcomes have resulted from their efforts. We used qualitative coding to apply an existing set of policy tools already established in the literature. Coordinators' responses showed that who participates in these organizations has a major impact on the level of problem solving. There were limited instances of joint urban-agricultural engagement strategies, but these were promising in changing individual's perspectives and indicate that strategic targeting of watershed participants may be crucial to overcoming conflicts. [ABSTRACT FROM AUTHOR]

Water quality monitoring is imperative in providing the objective evidence required to make sound decisions about water quality management. This study aimed to examine the water quality status of the Migori River by determining spatio-seasonal variations in water quality parameters, along with associated influencing factors and potential health risks. Therefore, eighteen physico-chemical and bacteriological variables were sampled and analyzed monthly for six months covering the wet and dry seasons from the upstream, midstream, and downstream stations, and a health risk survey was conducted with 90 watershed households. ANOVA and T-test were used to test for the significant spatial and seasonal variations (p < 0.05), respectively; whereas Pearson's correlation was used to identify relationships between parameters. Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) were used to find various spatial patterns in the river water quality datasets, while the Canadian Council of Ministries of the Environment Water Quality Index (CCME-WQI) showed the suitability status of the river water quality. The assessed variables showed significant seasonal variability but no significant spatial differences in the river. HCA generated 3 clusters suggesting that water quality deteriorated downstream from the upstream of the watershed. The PCA extracted four PCs explaining 80.5% of the total variance, which suggested that the variations in water quality are attributed to point and nonpoint sources of pollution. While most of the physico-chemical variables were within maximum permissible limits, the bacteriological levels exceeded the prescribed standards. The index ranked the river's water condition between 'poor' to 'marginal'; upstream has better water condition that gradually decreases toward the downstream, and water quality is better in the wet season than the dry season. The study revealed that the water of the Migori River is polluted and potentially hazardous for human usage, and thus suitable pollution control measures are urgently needed to safeguard public health. [ABSTRACT FROM AUTHOR]

Changes in land use and landscape patterns significantly influence watershed water quality by affecting non-point source (NPS) pollution processes. Understanding the characteristics of water quality and the relationships between landscape patterns and water quality is crucial to informing land-use planning aimed at ensuring water security. In this study, we employed landscape index methods, correlation analysis, and redundancy analysis based on monitored water quality data and land-use types relative to the Yanshan River Basin, Guilin, China. The results show the following features: (1) Water quality in the small watershed exceeded the values of class III during the study period, and total nitrogen (TN) was the main pollutant, with a pollution load ratio reaching 67.9%. (2) Water quality was significantly impacted by the landscape patterns of the small watershed river. The monitored concentrations of TN, ammonia nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), and total phosphorus (TP) were negatively correlated with the proportion of forest area, and the concentrations of NH4+-N and TP were positively correlated with the proportions of building, orchard, and cultivated land areas. Moreover, the influences of landscape patterns during the wet seasons on water quality were stronger than those during the dry seasons. (3) The total interpretation rates of the landscape indices for the water quality indices in the dry and wet seasons were 96.7% and 94.4%, respectively. Moreover, the largest patch and aggregation indices of the building area were the most effective variables in explaining the water quality indices, with contribution rates of 30.8% and 23.2% in the dry seasons and 34.3% and 23.8% in the wet seasons, respectively. By analyzing these relationships, in this study, we obtained insights into how different landscape patterns contribute to variations in water quality. The findings contribute to sustainable land-use planning strategies that aim to mitigate the impacts of land-use changes on water resources. [ABSTRACT FROM AUTHOR]

The landscape pattern controls the energy flow and water sediment process of the watershed, which is an important factor affecting nitrogen and phosphorus loss in small watershed. In order to understand the responses of rainfall-runoff processes and nitrogen and phosphorus exports to landscape pattern, two typical small watersheds, Shuangxi (agroforestry catchment) and Shiqiao (forest catchment) in the upper watershed of Liangzi Lake area of Hubei Province, were selected as the research objects. The water quality and quantity at the outlet of the watersheds were continuously monitored from January to December and a secondary rainfall event in 2016. The results showed that the landscape patterns had a significant impact on responses of rainfall-runoff processes. Compared with Shuangxi, the runoff process in Shiqiao small watershed showed a trend of shorter convergence time, faster runoff response speed and larger runoff modulus. The monthly concentrations of total nitrogen (TN) and total phosphorus (TP) in Shuangxi small watershed were in the range of 1.29~4.28 mg/L and 0.04~0.22 mg/L, which were higher than those of Shiqiao (TN:0.62~1.90 mg/L; TP:0.02~0.11 mg/L), respectively. Nitrate nitrogen (NO-³-N) was the major form of TN in the two small catchments, accounted for 51.8%~88.2%, but the proportion of NO-³-N to TN in Shuangxi small watershed was higher than those of Shiqiao. The concentrations of ammonium (NH+4-N) and nitrite nitrogen (NO-²-N) remained at a low level and exhibited no obvious trend. The emission fluxes of TN and TP in Shuangxi small watershed were in the range of 1.83~20.03 g/s and 0.04~1.45 g/s,which were higher than those of Shiqiao (TN:0.62~10.01 g/s; TP:0.01~0.54g/s), respectively. It was also found that there was a significant positive correlation between the TN and TP emission flux and runoff in the same period. The annual loss intensity of TN and TP in Shuangxi small watershed were 3.68 t/(km² · a) and 0.20 t/(km² · a), which were 1.32 and 1.30 times greater than those of Shiqiao, respectively. The losses of TN and TP in both small watersheds mainly occurred between April and July with frequent rainfall events, accounting for more than 70% of the annual total losses. In conclusion, different landscape patterns had a significant impact on the losses of TN and TP. Accordinglly, rational fertilization to reduce anthropogenic nitrogen and phosphorus loss and optimization of land use to store water and preserve soil are scientific measures to improve the water environment in the watershed. The study could provide more insights for reducing agricultural non-point source pollution in Liangzi Lake region and similar other regions. [ABSTRACT FROM AUTHOR]

Rapid socio-economic development has led to many water environmental issues in small watersheds such as non-compliance with water quality standards, complex pollution sources, and difficulties in water environment management. To achieve a quantitative evaluation of water quality, identify pollution sources, and implement refined management in small watersheds, this study collected monthly seven water quality indexes of four monitoring points from 2010 to 2023, and ten water quality indexes of 23 sampling points in the Shiting River and Mianyuan River which are tributaries of the Tuojiang River Basin. Then, water quality evaluation and pollution source analysis were conducted from both temporal and spatial perspectives using the Water Quality Index (WQI) method, the Absolute Principal Component Scores/Multiple Linear Regression (APCS-MLR) method, and the Positive Matrix Factorization (PMF) receptor modeling technique. The results indicated that except for total nitrogen (TN), the concentrations of other water quality indexes exhibited a decreasing trend, and all were divided into two obvious stages before and after 2016. Furthermore, the proportion of water quality grade of Good and above increased from 73.96 to 84.94% from 2010–2015 to 2016–2023, and the water quality grade of Good and above from upstream to downstream dropped from 100 to 23.33%. From the temporal scale, four and five pollution sources were identified in the first and second stages, respectively. The distinct TN pollutant is mainly affected by agricultural non-point sources (NPS), whose impact is enhanced from 17.76 to 78.31%. Total phosphorus (TP) was affected by the phosphorus chemical industry, whose contribution gradually weakened from 50.8 to 24.9%. From a spatial perspective, four and five pollution sources were identified in the upstream and downstream, respectively. Therefore, even though there are some limitations due to the data availability of water monitory and hydrology data, the proposed research framework of this study can be applied to the water environmental management of other similar watersheds. [ABSTRACT FROM AUTHOR]

• A coupled metal and metalloid transport model were developed based on improved two-dimensional hydrodynamic water quality model and SWAT model. • The contents and spatial-temporal distribution of arsenic were characterized. • Impacts of hydro-climate, hydropower station and non-point source were explored. • Model helps to quantify and analysis the transport of metalloid pollution. With the increasing severity of arsenic (As) pollution, quantifying the environmental behavior of pollutant based on numerical model has become an important approach to determine the potential impacts and finalize the precise control strategies. Taking the industrial-intensive Jinsha River Basin as typical area, a two-dimensional hydrodynamic water quality model coupled with Soil and Water Assessment Tool (SWAT) model was developed to accurately simulate the watershed-scale distribution and transport of As in the terrestrial and aquatic environment at high spatial and temporal resolution. The effects of hydro-climate change, hydropower station construction and non-point source emissions on As were quantified based on the coupled model. The result indicated that higher As concentration areas mainly centralized in urban districts and concentration slowly decreased from upstream to downstream. Due to the enhanced rainfall, the As concentration was significantly higher during the rainy season than the dry season. Hydro-climate change and the construction of hydropower station not only affected the dissolved As concentration, but also affected the adsorption and desorption of As in sediment. Furthermore, As concentration increased with the input of non-point source pollution, with the maximum increase about 30%, resulting that non-point sources contributed important pollutant impacts to waterways. The coupled model used in pollutant behavior analysis is general with high potential application to predict and mitigate water pollution. [Display omitted] [ABSTRACT FROM AUTHOR]

Wetlands are critical ecological infrastructures that improve water quality, serve as habitat for fish and other aquatic life, accumulate floodwaters, and maintain surface water flow during dry periods. However, the health of wetlands has been compromised by anthropogenic activities that affect the constant supply of ecosystem services. This study assessed the impact of anthropogenically modified land use on wetland health in the Witbank Dam Catchment in South Africa, whose land use has been severely modified for agriculture and mining purposes. The study developed a model linking surface runoff generated in the catchment with land use and wetland typology to comprehend diffuse pollution from pollution-source land uses. Runoff data and related wetland spatial information were processed and analysed in a Geographic Information System (GIS) to estimate pollutants (agricultural nutrients and acid mine drainage) from runoff detained and released by wetlands. The analysis facilitated the assessment of the value of wetlands in enhancing water quality, as well as human and environmental health. The runoff volume from pollution-source land uses (urban areas, farmlands, and mining) was used to evaluate annual pollution levels. Wetland types are ranked according to their efficiency levels to filter pollutants. The assumption is that the difference between filtered and unfiltered runoff is the quantity of polluted runoff water discharged into the river system. The analysis has shown that 85% of polluted runoff generated in the catchment ends up in the river system. An important observation is that although wetlands have a substantial ability to absorb excess pollutants, they have finite boundaries. Once they reach their full holding capacity, they can no longer absorb any further pollutants. The excess is discharged into the river system, risking human and environmental health. This explains why the Limpopo River is heavily polluted resulting in the death of fish, crocodiles and other aquatic life. [ABSTRACT FROM AUTHOR]

The issue of agricultural non-point source pollution has attracted global attention. A buffer zone is an effective, eco-friendly, and economically feasible remediation ecosystem to reduce the impact of agricultural non-point source pollution on water bodies. They can effectively remove pollutants in agricultural drainage through physical processes (infiltration, filtration, deposition, etc.), plant absorption and assimilation, and microbial processes, improving the water quality of water bodies. This article provides a comprehensive review of the current studies on using buffer zones to remediate agricultural non-point source pollution, with a focus on the key affecting factors for pollutant removal efficiencies. The main factors included buffer zone width, vegetation type, slope, seasonal variation, soil variation, and vegetation density. The influencing mechanisms of these factors on the pollutant removal efficiencies of buffer zones were also discussed. This review can serve as a reference for a deep understanding of buffer zones and help optimize their design and management in real ecological remediation projects. [ABSTRACT FROM AUTHOR]

Controlling non-point source (NPS) pollution is crucial for implementing water environment management, and simulating the water quality response to NPS pollution emission control schemes is of great importance. Variational mode decomposition (VMD) can overcome endpoint effects and modal aliasing issues, effectively separating intrinsic mode components. Bidirectional long short-term memory (BiLSTM) can fully mine the information contained in time series and has good predictive performance. MIKE21, when coupled with the Ecolab module, can well simulate the diffusion process of NPS pollution. The Weihe River water environment prediction model was constructed using VMD-BiLSTM and MIKE21, with ammonia nitrogen (NH3-N), total phosphorus (TP), and chemical oxygen demand (COD) as pollution indicators, showing the water quality response of the Weihe River within a few years after the implementation of agricultural and urban NPS pollution emission control schemes. Among them, the COD concentration decreased by up to 71.3%, the NH3-N concentration decreased by up to 31.4%, and the TP concentration decreased by up to 43.1%. In the process of streamflow prediction, VMD-BiSLTM shows satisfactory performance with NSE of 0.89 and R2 of 0.92, which will significantly improve the accuracy of modeling the future water environment. The results also show that the water quality of the Weihe River can be significantly improved by controlling NPS pollution emission, and reducing agricultural NPS pollution emission is key to decreasing ammonia nitrogen and total phosphorus concentrations and improving water quality. [ABSTRACT FROM AUTHOR]

Monitoring water quality in urban rivers is crucial for water resource management since point and non-point source pollution remain a major challenge. However, traditional water quality monitoring methods are costly and limited in frequency and spatial coverage. To optimize the monitoring, techniques such as modeling have been proposed. These methods rely on networks of low-cost multiprobes integrated with IoT networks to offer continuous real-time monitoring, with sufficient spatial coverage. But challenges persist in terms of data quality. Here, we propose a framework to verify the reliability and stability of low-cost sensors, focusing on the implementation of multiparameter probes embedding six sensors. Various tests have been developed to validate these sensors. First of all, a calibration check was carried out, indicating good accuracy. We then analyzed the influence of temperature. This revealed that for the conductivity and the oxygen sensors, a temperature compensation was required, and correction coefficients were identified. Temporal stability was verified in the laboratory and in the field (from 3 h to 3 months), which helped identify the frequency of maintenance procedures. To compensate for the sensor drift, weekly calibration and cleaning were required. This paper also explores the feasibility of LoRa technology for real-time data retrieval. However, with the LoRa gateways tested, the communication distance with the sensing device did not exceed 200 m. Based on these results, we propose a validation method to verify and to assure the performance of the low-cost sensors for water quality monitoring. [ABSTRACT FROM AUTHOR]

We explore point source (PS) and non-point source (NPS) pollution impacts on surface water quality in Vinh Long Province, Vietnam. We used data from 60 surface water quality monitoring stations across dry, transitional, and wet seasons from 2017 to 2021, in addition to sampling data collected from 12 wastewater outlets from June to October 2021 to determine the sources of pollution loads. Surface water quality was assessed using both the water quality index (WQI) and the Vietnamese standards QCVN 08:2015, whilst cluster analysis (CA) and principal components analysis (PCA) were used to evaluate spatial variation and key influencing factors. We observed seasonal variation in surface water quality, with a decline in quality during the rainy season. Moreover, the water quality parameters such as chemical oxygen demand (COD), biochemical oxygen demand (BOD5), total nitrogen (TN), and total phosphorus (TP) frequently exceeded the QCVN 08:2015 standard. Across, the different monitoring fixed points and seasons, COD levels were found to range from 8.94 to 15.14 mg/L, while TN levels varied between 0.24 and 0.53 mg/L. The cluster analysis categorized the monitoring fixed points into three groups, based on their water quality parameters, while PCA identified four principal components that explain 69% of the variance, distinguishing between pollution sources and seasonal factors. Our findings emphasize that poor water quality in many areas is affected by non-point source pollution, underscoring the need for watershed and land management. The results and applied methodologies provide insights for watershed management, policy development, and adaptation, applicable to regions facing similar environmental challenges. Article Highlights: Pinpointing and quantifying sector-specific sources of pollution is essential to effective water resource management. Methods exist by which to use water quality data to begin to identify primary sources of pollution in complex watersheds. Water quality declined during the rainy seasons of 2017 to 2021, emphasizing non-point sources (NPS) as as leading causes of the decline. [ABSTRACT FROM AUTHOR]

Tea is an important economic crop worldwide, especially in Asian countries. However, tea cultivation requires substantial fertilizer use and may become a nutrient pollution source and affect water quality. This study presented two objectives: one was to estimate the pollution export coefficients of tea farms, and the other was to assess the performance of bioretention cells in terms of tea farm pollution control. This study employed a tea farm pollutant transport model (TPTM) and a watershed pollutant transport model (WPTM) to link watershed management goals and the tea farm control strategy. Field data collected for Jingualiao Creek in the Feitsui Reservoir watershed in Taipei, Taiwan, were analyzed. The resulting export coefficients for total phosphorus (TP), NH3-N, suspended solids (SS), and chemical oxygen demand (COD) were 2.55, 4.22, 768.39, and 145.71 kg/ha-y, respectively. Bioretention cells, which are low-impact development (LID) facilities and structural best management practices (BMPs), were installed and tested for their ability to reduce nonpoint source pollution. The field investigation and modeling results showed that 1 m2 of bioretention cells could reduce TP, NH3-N, SS, and COD by 18.6, 20.9, 5545.5, and 881.4 g/y, respectively. According to the WPTM results, 540 m2 of bioretention cells could achieve an 85% water quality attainment goal, and 715 m2 could reach 90% water quality attainment. Four tea farms covering 1.43 ha require 30.0 m2 of bioretention cells to achieve an 85% goal and 33.5 m2 to 90% goal. The export coefficients of tea nonpoint pollution sources presented in this study can serve as a valuable tool for estimating potential exported nutrients, and the field test results of bioretention cells are helpful information for policymakers in formulating effective watershed management measures. [ABSTRACT FROM AUTHOR]

Identifying the potential pollution sources of surface water pollutants is essential for the management and protection of regional water environments in drinking water source areas. In this study, absolute principal component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models were applied to assess water quality and identify the potential pollution sources affecting the surface water quality of Xin'an River Basin. For this purpose, a 10-year (2011–2020) dataset of eight water quality indicators (including pH, EC, DO, COD, NH3-N, TN, TP, and FC) covering eight monitoring stations and 7248 monthly observations was used. The results indicated that Pukou section had the worst water quality among the eight monitoring stations, and TN was the most serious water quality index. Both the APCS-MLR and PMF models identified agricultural nonpoint source pollution, urban nonpoint source pollution and rural domestic pollution, and meteorological factors. The sum of these three sources was very close, accounting for 60% and 58%, respectively. The APCS-MLR results demonstrated that for EC, COD, and NH3-N, the major pollution sources were urban nonpoint sources and rural domestic pollution. The major contamination source of TN was agricultural nonpoint source pollution (30.4%). Meanwhile, the major pollution sources of pH, DO, TP, and FC were unidentified factors. The PMF model identified five potential sources, and pH and DO were affected by meteorological factors. NH3-N and TP were influenced mainly by agricultural nonpoint source pollution. Atmospheric deposition was the major pollution source (87.9%) of TN. FC was mostly derived from livestock and poultry breeding (88.3%). EC and COD were mostly affected by urban nonpoint sources and rural domestic pollution. Therefore, receptor models can help managers identify the major sources of pollution in watersheds, but the major factors affecting different pollutants need to be supplemented by other methods. [ABSTRACT FROM AUTHOR]

As the management areas for NPS pollution continue to increase, it is essential to conduct a situation analysis considering the regional characteristics and the scope of pollution reduction. In this study, the focus is on differentiating regional (urban, agricultural) characteristics to enhance water quality and reduce pollution loads in the increasing management areas for NPSs. Furthermore, priority management areas are identified based on urgency and vulnerability, and management strategies are proposed. The assessment involved evaluating both streamflow and water quality (T-P) using long-term monitoring data and watershed models (SWAT and HSPF) that take into account regional characteristics. The results indicated notable regional improvements, with T-P pollution reductions ranging from 20.7% to 26.8% and T-P concentration reductions ranging from 16.4% to 24.7% compared to baseline conditions in unmanaged areas. Based on these research findings, it is anticipated that the efficient and effective management of NPS pollution can be implemented on a regional basis. Moreover, the results of this study will not only contribute to the establishment of pollution standards, but also significantly impact the evaluation and proposal of management objectives, thereby making a substantial contribution to national water quality policies. [ABSTRACT FROM AUTHOR]

Based on the "air-land-water" integrated model system and multi-level collaborative architecture of the basin, this paper proposes a technological system for a non-point source pollution forecasting and warning platform for the Pengxi River basin, and a non-point source pollution forecasting and warning platform for the Pengxi River basin has been established. By automatically collectting and processsing meteorological data, and invoking the meteorological model, land model, hydrodynamic model, and water quality model driven by the control center, the platform can make hourly simulated forecasts of land surface runoff and the flow of pollutants such as TN, TP and NH3-N for the next 3 to 15 days, and warn about the risk of pollutant fluxes, providing technical support for the intelligent basin management and comprehensive control of non-point source pollution. [ABSTRACT FROM AUTHOR]

Uncertainty in water quality trading (WQT) markets is frequently cited as a deterrent for participation, with few studies focusing on uncertainty in future water quality credit needs. To reduce this uncertainty, we present a geographic information system (GIS)‐based methodology for estimating an upper bound of water quality credit needs for a set of spatially referenced planned construction projects over a large geographic region. We demonstrate the methodology by applying it to estimate future credit needs for the Virginia Department of Transportation's (VDOT) 6‐year improvement program. The results show that 25% of the state's 6‐digit hydrologic unit code (HUC) basins lack sufficient current credit supply to meet the estimated future credit need from VDOT's planned projects alone. Furthermore, while 70% of the 8‐digit HUCs containing planned projects have a sufficient current credit supply to meet VDOT credit needs, this is true for only 20% of the 10‐digit HUCs. Finally, nearly 25% of the planned transportation projects, representing potentially $9 million in credit purchases at current market rates, will be constructed in catchments with impaired water bodies. State regulations will initially limit these projects to trade with credit banks collocated at the 12‐digit HUC level. This application demonstrates how the GIS‐based methodology can be applied to reduce uncertainty about future WQT credit needs and how needs are aligned with current credit supply. [ABSTRACT FROM AUTHOR]

The growth of society and population has led to a range of water pollution issues. Among these, non-point source pollution assessment and treatment pose a particular challenge due to its formation mechanism. This has become a focal point and challenge in water pollution treatment research. The study area for this research was the Huanghou basin in Guizhou Province, southwest China. The land use type of the basin was analyzed using remote sensing technology, and water quality data was collected by distributing points throughout the basin, based on source-sink landscape theory. The distribution map of the basin’s source-sink landscape and the results of water quality data accurately and efficiently identified the areas with high risk of non-point source pollution in the western and southwestern residential and agricultural areas of the upper basin. Hence, a strategy of “increasing sinks and decreasing sources” was proposed. The strategy was implemented at both macro and micro levels to address non-point source pollution in the basin using ecological remediation techniques. The work to control karst rocky desertification should continue at a macro level. The rocky desertification area in the basin should gradually transform into grassland and forested land, while increasing the overall area of the sink landscape. Ecological restoration techniques, such as slope planting, riparian zone vegetation restoration, increasing plant abundance, and restoring aquatic plants, can effectively control non-point source pollution at the micro level. Compared to traditional control methods, this remediation strategy focuses on source and process control. It is more effective and does not require large-scale water pollution control projects, which can save a lot of environmental control funds and management costs. Therefore, it has greater research significance and application value. [ABSTRACT FROM AUTHOR]

Implementing best management practices (BMPs) has proven to be an efficient method for reducing non-point source (NPS) pollutants. Agricultural NPS pollution is considered to be a major contributor to water quality impairment. This study aims to assess the variation in hydrologic and water quality outputs at field and watershed scales when BMPs are implemented using modeling approaches. The Yazoo River Watershed (YRW) is the largest watershed basin in the state of Mississippi with approximately 50% agricultural land. Runoff generated from agricultural areas carries sediments and nutrients. The Merigold watershed (MW) is a sub-basin of the YRW and a field-scale watershed with most of the land use being agriculture. It is essential to quantify the streamflow, sediment, total nitrogen (TN), and total phosphorus (TP) when BMPs are implemented. BMPs such as vegetative filter strips (VFS) and cover crops (CC) were tested in this study. The Soil and Water Assessment Tool (SWAT) model was applied to quantify the watershed's hydrologic and water quality outputs. SWAT model accuracy assessment was performed by calibration and validation process using the Nash and Sutcliffe Efficiency Index (NSE). Model performance was satisfactory for monthly streamflow, with NSE values in the range of 0.62 to 0.81, and for daily sediments, TN, and TP load estimation, with NSE values of 0.21, 0.20, and 0.47, respectively. CC was planted after harvesting the main crop. Therefore, it is essential to quantify the seasonal reduction in pollutants. Water quality was improved after BMP implementation, and an overall decrease in streamflow, sediment, TN, and TP loads was observed for both MW and YRW during dry and wet seasons. Previous studies regarding seasonal assessments with CC implementation in the MW and YRW were limited. Therefore, the results from this study could be a unique addition to the scientific literature. [ABSTRACT FROM AUTHOR]

The water quality of Lake Erhai has deteriorated in recent decades due to socioeconomic development in the lake basin. After the massive implementation of water environmental protection measures in Lake Erhai in 2016, the trend of water quality deterioration has been curbed and the intensity and frequency of algal blooms has decreased. However, water quality monitoring data show that pollutant concentrations in Lake Erhai still exceed acceptable values, and there is a risk of water quality standard limits being further exceeded in the future. Therefore, it is urgent to systematically study the variability characteristics of water quality in Lake Erhai to provide practical methods to predict the future evolution of water quality. Based on water quality monitoring data from 2009 to 2019, the current water quality characteristics of Lake Erhai were analyzed, and a two-dimensional hydrodynamic and water quality mathematical model was built to predict the water quality in 2025. The results showed that the total phosphorus (TP) concentration declined after 2016, mainly due to the significant reduction of TP entering the lake due to pollution interception. However, the concentrations of the potassium permanganate index (CODMn) and total nitrogen (TN) increased after 2016, demonstrating that the pollution control measures have had little effect on the improvement of CODMn and TN. The spatial and temporal distribution of pollutants showed that the water quality in winter and spring was better than in summer and autumn, and the water quality in the southern lake was better than in the northern lake. This analysis indicates that non-point source pollution remains the main source of pollution in Lake Erhai, and that rainfall is the main driving force of pollutants exceeding the water quality standard. According to the water quality predictions, without additional pollution control measures, pollutant concentrations in Lake Erhai will exceed the Class II water quality standard by 2025. This study analyzes the water quality characteristics, predicts the direction of future water quality changes, and provides a theoretical basis for the future water quality protection of Lake Erhai. [ABSTRACT FROM AUTHOR]

This study addresses the pressing issue of nonpoint source water pollution in Kentucky, particularly associated with large-scale agriculture. Centered on the outer bluegrass region of Central Kentucky, the research examines the water quality of headwater streams during the agricultural season. The approach involves geospatial land cover classification using aerial imagery. Water quality data were collected during the agricultural growing season from May to October 2018. Land cover classification utilized ERDAS Imagine 2016 and ESRI ArcGIS 10.6 GIS software, while conventional water quality parameters were measured with a YSI ProDSS® multiparameter water probe and a Marsh-McBirney Flo-Mate 2000 flow meter. Statistical analyses show significant differences in stream water chemistry, suggesting the impact of agricultural nonpoint source pollution. Forested streams exhibited more varied conditions, indicating a potentially better environment. As agricultural land percentage increased, water chemistry variation suggested a measurable threshold for changes. Significant differences in water quality between agricultural and forested streams highlight the potential benefits of expanding riparian zones beyond regulations. Enlarging these zones is proposed as a strategy to mitigate nonpoint source pollution in Kentucky's waterways. [ABSTRACT FROM AUTHOR]

Sediment and nutrient pollution in water bodies is threatening human health and the ecosystem, due to rapid land use changes and improper agricultural practices. The impact of the nonpoint source pollution needs to be evaluated for the sustainable use of water resources. An ideal tool like the soil and water assessment tool (SWAT) can assess the impact of pollutant loads on the drainage area, which could be beneficial for developing a water quality management model. This study aims to evaluate the SWAT model's multi-objective and multivariable calibration, validation, and uncertainty analysis at three different sites of the Yarra River drainage area in Victoria, Australia. The drainage area is split into 51 subdrainage areas in the SWAT model. The model is calibrated and validated for streamflow from 1990 to 2008 and sediment and nutrients from 1998 to 2008. The results show that most of the monthly and annual calibration and validation for streamflow, nutrients, and sediment at the three selected sites are found with Nash–Sutcliffe efficiency values greater than 0.50. Furthermore, the uncertainty analysis of the model shows satisfactory results where the p-factor value is reliable by considering 95% prediction uncertainty and the d-factor value is close to zero. The model's results indicate that the model performs well in the river's watershed, which helps construct a water quality management model. Finally, the model application in the cost-effective management of water quality might reduce pollution in water bodies due to land use and agricultural activities, which would be beneficial to water management managers. [ABSTRACT FROM AUTHOR]

Nonpoint source pollution (NPS) has become the most important reason for the deterioration of water quality, while relevant studies are often limited to African river and lake basins with insufficient data. Taking the Simiyu catchment of the Lake Victoria basin as the study area, we set up a NPS model based on the soil and water assessment tool (SWAT). Furthermore, the rationality of this model is verified with the field-measured data. The results manifest that: (1) the temporal variation of NPS load is consistent with the variation pattern of rainfall, the average monthly output of total nitrogen (TN) and total phosphorus (TP) in the rainy season was 1360.6 t and 336.2 t, respectively, while in the dry season was much lower, only 13.5 t and 3.0 t, respectively; (2) in view of spatial distribution among 32 sub-basins, TN load ranged from 2.051 to 24.288 kg/ha with an average load of 12.940 kg/ha, and TP load ranged from 0.263 to 8.103 kg/ha with an average load of 3.321 kg/ha during the 16-month study period; (3) Among the land use types, the cropland contributed the highest proportion of TN and TP pollution with 50.28% and 76.29%, respectively, while the effect of forest on NPS was minimal with 0.05% and 0.02% for TN and TP, respectively. (4) Moreover, the event mean concentration ( E M C ) values of different land use types have been derived based on the SWAT model, which are key parameters for the application of the long-term hydrological impact assessment (L-THIA) model. Therefore, this study facilitates applying the L-THIA model to other similar data-deficient catchments in view of its relatively lower data requirement. [ABSTRACT FROM AUTHOR]

Stormflow runoff is an important non-point source of pollution in drinking water reservoirs. Storm runoff is usually very turbid and contains a high concentration of organic matter, therefore affecting water quality when it enters reservoirs. In order to investigate the impact of storm runoff on spatial–temporal variation and stratification of water quality during this rainstorm event, the inflow process of the storm runoff was studied through a combination of field investigation and simulation using the Delft3D-Flow model. Water samples were collected from Biliuhe Reservoir at four different periods: before storm runoff, storm runoff flood peak period, 1 week after storm runoff, and 5 weeks after storm runoff. The results showed that the input of storm runoff resulted in a significant increase in the nitrogen (N) and phosphorus (P) in the reservoir water, especially in the reservoir entrance. The concentrations of total nitrogen (TN) and total phosphorus (TP) gradually decreased after the flood peak period; however, the average concentrations of TN and TP in the entire reservoir remained higher than those before the storm runoff levels for an extended duration. The storm runoff will greatly contribute to the contamination of water quality in a reservoir, and the water quality cannot be quickly restored by self-purification in the short term. During the flood peak period, under the influence of density current, the electrical conductivity (EC) and turbidity increased significantly in the water depth of 10–15 m, so that the reservoir water had obvious stratification between 10 and 15 m. The form of pollutants in storm runoff was mostly in particle phosphorus. Total particulate phosphorus (TPP) concentration was 0.015 ± 0.011 mg/L, accounting for 44.12% of total phosphorus (TP) concentration in storm runoff flood peak period. The process of a rainstorm caused runoff, which carried high levels of turbidity, particulate phosphorus, and organic matter. The storm runoff disrupts the stratification of the reservoir water. In terms of vertical distribution, the turbidity in the reservoir area increased to 73.75 NTU. Therefore, the occurrence of significant turbidity density flow in the reservoir is frequently accompanied by intense rainfall events. Gaining insights into the impact of storm runoff on the vertical distribution of reservoir turbidity can help managers in selecting an appropriate inlet height to mitigate high turbidity outflow. [ABSTRACT FROM AUTHOR]

The stated goal of the research is to investigate the surface water quality of the Baitarani River in Odisha to ascertain its compatibility for various uses. Large, complex datasets generated during the one-year (2021-2022) monitoring program were collected from 13 locations and encompassed 22 parameters. To examine temporal and spatial fluctuations in and to interpret these datasets, MCDMs like TOPSIS and the Entropy-based Water Quality Index (EWQI) were utilized. The physical and chemical outcomes of the current experiment were compared to WHO standards. According to the analysis's results, turbidity and total coliform (TC) are indicators that have a greater impact on water quality in all locations during both seasons and are directly linked to home and agricultural non-point source pollution. As per EWQI interpretation, 30.77 % of the observations in PRM and POM fall under the poor category. The findings showed how anthropogenic activities have harmed St. 8, 11, 12, and 13 and require effective management. A quantifiable approach was also carried out to decide the efficacy of TOPSIS. Farming attributes, including SAR, % Na, RSC, MR, KI, and PI, were estimated to delineate the agriculturally practicable zones. This work can offer a reference database for the betterment of water quality. [ABSTRACT FROM AUTHOR]

Dissolved oxygen (DO) concentration is a pivotal determinant of water quality in freshwater lake ecosystems. However, rapid population growth and discharge of polluted wastewater, urban stormwater runoff, and agricultural non-point source pollution runoff have triggered a significant decline in DO levels in Lake Erie and other freshwater lakes located in populated temperate regions of the globe. Over eleven million people rely on Lake Erie, which has been adversely impacted by anthropogenic stressors resulting in deficient DO concentrations near the bottom of Lake Erie's Central Basin for extended periods. In the past, hybrid long short-term memory (LSTM) models have been successfully used for the time-series forecasting of water quality in rivers and ponds. However, the prediction errors tend to grow significantly with the forecasting period. Therefore, this research aimed to improve the accuracy of DO forecasting models by taking advantage of Lake Erie's real-time water quality (water temperature and DO concentration) monitoring network to establish temporal and spatial links between adjacent monitoring stations. We developed hybrid LSTM models that combine LSTM, convolutional neuron network LSTM (CNN-LSTM), hybrid CNN with gated recurrent unit (CNN-GRU) models, and convolutional LSTM (ConvLSTM) to forecast near-bottom DO concentrations in Lake Erie's Central Basin. These hybrid LSTM models improve their capacity to handle complicated datasets with spatial and temporal variability. These models can serve as accurate and reliable tools for forecasting DO concentrations in freshwater lakes to help environmental protection agencies better access and manage the health of these vital ecosystems. Following analysis of a 21-site Lake Erie dataset for 2020 and 2021, the ConvLSTM model emerged as the most accurate and reliable, boasting an MSE of 0.51 mg/L, MAE of 0.42 mg/L, and an R-squared of 0.95 over the 12 h prediction range. The model foresees future hypoxia in Lake Erie. Notably, the temperature near site 713 holds significance for Central Basin DO forecasting in Lake Erie, as indicated by outcomes derived from the Shapley additive explanations (SHAP). [ABSTRACT FROM AUTHOR]

Although phytoplankton is well known as robust bioindicators to aquatic environments, their indicating functions based on different community parameters remain to be understood. In order to filter effective bioindicators in aquatic ecosystems, four phytoplankton community parameters including species richness (SR), total biomass (SBP), functional groups (FGBP), and size-fractionated chlorophyll-a (SC) were demonstrated in a subtropical artificial lake with ecological restoration in South China. Our results indicated that all the above four parameters exhibited high sensitivity to environmental variations and illustrated distinct aspects of indicating functions to aquatic environments due to their individual biological characteristics. Based on FGBP, both spatial and temporal differences in phytoplankton community could be identified. SR and SBP only classified the spatial and temporal distributions, respectively, while SC could distinguish the sewage outfalls from other sites. In terms of ecological management, two parameters (SR and FGBP) could distinguish the restored waters from untreated environments as non-point source pollution, and another parameter SC could indicate the sewage outfalls as point source pollution. Therefore, the combination of the above two categories of phytoplankton community parameters could make the strongest indicating functions. Our study provided greater insight into indicating functions of phytoplankton community parameters in an ecological restored lake and enabled better managements in such artificial lakes. [ABSTRACT FROM AUTHOR]

IntroductionBest management practices (BMPs) are important tools for mitigating the impact of non-point source pollutants on water quality. Drivers of the high variance observed in BMP performance field tests are not well documented and present challenges for planning BMP construction and forecasting water quality improvements.MethodsWe conducted a systematic review of published nonpoint source water quality BMP studies conducted in the United States and used a meta-analysis approach to describe variance in pollutant removal performance. We used meta-regression to explore how much BMP pollutant removal process, influent pollutant concentration, and aridity effected BMP performance.ResultsDespite high variance, we found the BMPs on average were effective at reducing fecal indicator bacteria (FIB), total nitrogen (TN), total phosphorus (TP), and total suspended sediment (TSS) concentrations. We found that influent concentration and interaction effect between the BMP pollutant removal process and aridity explained a substantial amount of variance in BMP performance in FIB removal. Influent concentration explained a small amount of variability in BMP removal of TP and orthophosphate (PO4). We did not find evidence that any of our chosen variables moderated BMP performance in nitrogen or TSS removal. Through our systematic review, we found inadequate spatial representation of BMP studies to capture the underlying variability in climate, soil, and other conditions that could impact BMP performance.

Mitigating nonpoint source pollution from stormwater runoff demands effective strategies for treating the first flush depth. Whether through off-stream storage or pass-through treatment devices, designing diversion structures and filtering materials is critical. This study proposes a streamlined procedure for determining first flush design flow rates, employing the modified rational method and rainfall intensity–duration equations applicable to any U.S. location. The dimensionless solution, which is presented as an equation requiring an iterative calculation for the desired flow rates, is complemented by precision graphs. Examples from the semi-arid Southwestern United States illustrate the methodology's utility. [ABSTRACT FROM AUTHOR]

In the wake of frequent and intensive human activities, highly urbanized areas consistently grapple with severe water environmental challenges. It becomes imperative to establish corresponding water environment models for simulating and forecasting regional water quality, addressing the associated environmental risks. The distributed framework water environment modeling system (DF-WEMS) incorporates fundamental principles, including the distributed concept and node concentration mass conservation. It adeptly merges point source and non-point source pollution load models with zero-dimensional, one-dimensional, and two-dimensional water quality models. This integration is specifically tailored for various Hydrological Feature Units (HFUs), encompassing lakes, reservoirs, floodplains, paddy fields, plain rivers, and hydraulic engineering structures. This holistic model enables the simulation and prediction of the water environment conditions within the watershed. In the Taihu Lake basin of China, a highly urbanized region featuring numerous rivers, lakes and gates, the DF-WEMS is meticulously constructed, calibrated, and validated based on 26 key water quality monitoring stations. The results indicate a strong alignment between the simulation of water quality indicators (WQIs) and real-world conditions, demonstrating the model's reliability. This model proves applicable to the simulation, prediction, planning, and management of the water environment within the highly urbanized watershed. [ABSTRACT FROM AUTHOR]

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Urbanization can have substantial effects on water quality due to altered hydrology and introduction of constituents to water bodies. In arid and semi‐arid environments, streams are further stressed by dewatering as a result of diversions. We conducted a high‐resolution synoptic survey of two streams in Colorado, USA that transition abruptly from granitic/metamorphic forested mountains to sedimentary urbanized plains and are both highly managed for water supply, yet differ in degree of urbanization. A synoptic mass balance approach developed for mine drainage applications was adapted to elucidate effects of urbanization, geology, and diversions on stream chemistry during baseflow conditions. Urbanization was a more important driver of stream concentrations than geology. The urban area was a strong source of bromide, calcium, chloride, and manganese, while lanthanum and dissolved organic carbon were primarily sourced from the mountains. A majority of streamflow was removed by diversions near the mountains/plains interface. Groundwater accounted for 31% of the subsequent flow increase to the urbanized stream, and delivered at least 33% of chloride loading. Constituents that were primarily urban‐derived (bromide, calcium, chloride, and manganese) were 2–3 times higher in the urban region due to diversions; without diversions, stream water quality would have largely retained characteristics of forested streams through the urban reach. This study provides insights into processes that affect water quality in highly managed streams of the semi‐arid western USA. Plain Language Summary: Water supplies in the western U.S. are under pressure from increasing population growth, which results in both urban development and more water management to maximize irrigation and public supply use. Urbanization substantially alters hydrology and can introduce an array of contaminants and nutrients to water bodies. Water diversions decrease the amount of water available to dilute urban inputs. A mass balance approach, originally developed for mine drainage sites, was adapted to elucidate effects of nonpoint source urban pollution, geology, and water management in two streams in the Colorado Front Range. The urban environment introduced bromide, calcium, chloride, and manganese to streams, while lanthanum and dissolved organic carbon arose from forested, mountainous inputs. Urbanization was a more important driver of stream concentrations than changes in geology. Water diversions removed a majority of the water from streams, and impacted water quality by limiting the dilution of urban‐derived constituents. This work provides insights into processes that affect water quality in highly managed streams of the semi‐arid western U.S. Key Points: A synoptic mass balance approach was adapted to elucidate effects of urbanization, geology, and water management on stream chemistryA majority of bromide, calcium, chloride, and manganese loading occurred in the urban area, and was partly sourced from groundwaterDiversions removed the majority of water from streams, leading to increased downstream concentrations of urban‐derived constituents [ABSTRACT FROM AUTHOR]

Analyzing 165 data from five national control sites in Baiyangdian Lake, this study unveils its spatiotemporal pattern of water quality. Utilizing machine learning and multivariate statistical techniques, this study elucidates the effects of rainfall and human activities on the lake's water quality. The results show that the main pollutants in Baiyangdian Lake are TN, TP, and IMN. Spatially, human activities are the main drivers of water quality, with the poorest quality observed in the surrounding village area. The temporal dynamics of water quality parameters exhibit three distinct patterns: Firstly, parameters predominantly influenced by point source pollution, like TN and NH4+-N, show lower concentrations during flood periods. Secondly, parameters affected by non-point source pollution, such as TP, show higher concentrations during flood periods. Thirdly, irregular variations were observed in pH, DO, and IMN. The evaluation of Baiyangdian Lake's water quality based on the grey relationship analysis method indicates that its water quality is good, falling within Classes I and II. Time series analysis found that the dilution effect of rainfall and the scouring action of runoff dominate the temporal variation in water quality in Baiyangdian Lake. The major pollution sources were identified as domestic sewage, followed by agricultural non-point source pollution and the release of internal pollutants. Additionally, aquaculture emerged as a significant contributor to the Lake's pollution. This research provides a scientific basis for controlling the continuous deterioration of Baiyangdian Lake's water quality and restoring its ecological function. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Most pollutants found in rivers come from the discharge of raw sewage from both point and nonpoint sources. So, monitoring the pollution levels in surface water sources is essential. River pollution monitoring is a real challenge. Using remote sensing, precise outcomes can be achieved with the help of the selection of the right combination of satellite images and algorithms. Generally, established available algorithms are site-specific, indicating that they may not work at all areas on Earth's surface due to differences in altitude, cloud cover, and sun glint. The present work determined Chlorophyll-a concentrations in the Tapi River at various locations using Landsat-8 satellite images and Acolite software from 2017 to 2021 Period. The outcomes reveal that applying the dark spectrum fitting with sun glint correction when processing Landsat-8 satellite images is needed. In the present study, water quality results were obtained very precisely for the months of January, February, November, and December after processing and analysing satellite images. Due to factors such as sun glare, cloud cover, cloud shadow, and haze, the desired effect could not be achieved in the remaining months of the study period. This research provides a solid foundation for estimating the impact of eutrophication in the water body by estimating chlorophyll- a concentration from satellite images. [ABSTRACT FROM AUTHOR]

Paddy runoff pollution is one of the major contributors to limiting the improvement of water quality in Taihu Lake Basin. Grass buffer strips (GBSs) are an effective measure to control paddy runoff pollution. However, most studies only consider a single inflow condition, and few studies have considered the effect of high-frequency rainfall. In this study, a field runoff simulation experiment was constructed to simulate the effect of GBSs on runoff nitrogen and phosphorus removal at different inflow volumes, inflow velocities, inflow concentrations, and rainfall frequencies. Results demonstrated that the larger the inflow volume, the faster the inflow velocity, and the lower the inflow concentration, the higher the runoff pollutant interception rate that occurred in GBSs, and the interception rate improved significantly with increasing GBS widths. The peak change point of removal rate occurred at a width of 15 m for NO3−-N and TP and at a 25 m width for TN and NH4+-N. The cumulative removal rate increased slowly after the change point. Although the peak cumulative removal rate appeared at a GBS width of 35~45 m. Considering the pollutants intercepted by GBSs and the emerging demand for land in this basin, 25 m was recommended as the optimum width to remove runoff pollutants. [ABSTRACT FROM AUTHOR]

Agriculture remains a leading source of water pollution in the United States, and climate change may exacerbate this relationship. We quantify increases in nutrient runoff following extreme precipitation events, showing that spikes are higher in regions with crop and livestock production. The spike per head is smaller around large‐scale livestock production, relative to small‐scale, and cover crops mitigate runoff. Legacy nutrients enter the surface water following extreme precipitation, regardless of current activity. We shed light on practices to protect water quality with more frequent extreme precipitation events and demonstrate the importance of including these events in empirical models of water quality. [ABSTRACT FROM AUTHOR]