Identifying critical source areas of non-point source pollution to enhance water quality: Integrated SWAT modeling and multi-variable statistical analysis to reveal key variables and thresholds.

By integrating soil and water assessment tool (SWAT) modeling and land use and land cover (LULC) based multi-variable statistical analysis, this study aimed to identify driving factors, potential thresholds, and critical source areas (CSAs) to enhance water quality in southern Alabama and northwest Florida's Choctawhatchee Watershed. The results revealed the significance of forest cover and of the lumped developed areas and cultivated crops ("Source Areas") in influencing water quality. The stepwise linear regression analysis based on self-organizing maps (SOMs) showed that a negative correlation between forest percent cover and total nitrogen (TN), organic nitrogen (ORGN), and organic phosphorus (ORGP), highlighting the importance of forests in reducing nutrient loads. Conversely, Source Area percentage was positively correlated with total phosphorus (TP) loads, indicating the influence of human activities on TP levels. The receiver operating characteristic (ROC) curve analysis determined thresholds for forest percentage and Source Area percentage as 37.47 % and 20.26 %, respectively. These thresholds serve as important reference points for identifying CSAs. The CSAs identified based on these thresholds covered a relatively small portion (28 %) but contributed 47 % of TN and 50 % of TP of the whole watershed. The study underscores the importance of considering both physical process-based modeling and multi-variable statistical analysis for a comprehensive understanding of watershed management, i.e., the identification of CSAs and the associated variables and their tipping points to maintain water quality.

Comprehensive effects of climate, land use/cover and management practices on runoff and nutrient variations in a rapidly urbanizing watershed.

As non-point source pollution has emerged as a significant global and regional concern, climate change (CC), land use/cover transformation (LUCT), and management practices (MP) play vital roles in addressing nutrient pollution. However, current studies lack comprehensive quantification and consistent conclusions on the response to these factors, especially for management practices. To quantify and elucidate the impact of representative environmental factors on rapidly urbanizing regions, this study focused on the Shenzhen River, which serves as the most typical urbanizing watershed. Using a process-based distributed hydrological model with a factor-controlled simulation method, we identified significant differences in nutrient concentrations and the impacts of climate variability, land use/cover changes, and anthropogenic interventions from 2003 to 2020. Moreover, effective measures greatly improved water quality in the Shenzhen River during study period, as evident from trend and cluster analysis. However, ecological water supplements implemented since 2016 have led to a slight reduction in simulated runoff performance, and CC may amplify the synergistic effects of precipitation and temperature on the river system. While the implemented practices have been effective in reducing total nitrogen (TN) and total phosphorus (TP) loads, strong TN pollution control is still needed in rapidly urbanizing areas due to the results of land use/cover type changes. Our findings emphasize the intricate interplay among CC, LUCT, and MP in shaping water quality and hydrological processes in rapidly urbanizing watersheds, and clarify the independent effects of these factors on nutrients. This study contributes to a better understanding of the complex interactions between multiple factors in watersheds and provides guidance for sustainable watershed management.

A spatial optimal allocation method considering multi-attribute decision making and multiple BMPs random combination in sub-watersheds.

Best management practices (BMPs) have been extensively employed in effective watershed management for non-point source pollution. The weights of objective functions and the restrictive conditions of combined BMPs are the vital requirements for BMPs allocation. Therefore, it is more beneficial to explore that a spatial optimal allocation method considering multi-attribute decision making and multiple BMPs random combination. Here is the novel framework based on Soil and Water Assessment Tool (SWAT) and the Non-dominated Sorting Genetic Algorithm II (NSGA-Ⅱ), which considers multiple objectives in deriving watershed-scale pollution control practices by considering BMPs cost and combined reduction rates of total nitrogen (TN) and total phosphorus (TP). The framework also integrates combined Entropy Weight method (EWM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to solve the weights of TN and TP, and considers the attributes of the sub-basin itself, which is more local suitability. Four categories of BMPs, tillage management, nutrient management, vegetative filter strips, and landscape management, were evaluated in the Jing River Basin (JRB) and resulted in reduction rates of 9.77%, 10.53%, 16.40%, and 14.27% averagely, respectively. BMP allocation schemes, derived from multi-objective optimization, are stratified into three financial scenarios. Low-cost scenario, costing up to 2 billion RMB, primarily targets the grain for green program in 28.81% of sub-basins. Medium-cost scenario, between 2 and 6 billion RMB, predominantly utilizes the grain for green in areas with a slope greater than 15°, accounting for 20.00% of sub-basins. High-cost scenario exceeds 6 billion RMB, mainly due to the implementation of multiple combination measures. The three configuration scenarios can provide decision-makers with a trade-off between measure costs and reduction efficiency. Overall, the innovative framework not only facilitates cost-effective implementation but provides a beneficial methodology for selecting cost-effective conservation practices in other regions.

Differences in nonpoint source pollution load losses based on hydrological zone characteristics: a case study of the Shaying River Basin, China.

Agricultural nonpoint source (NPS) pollution loss is closely related to hydrological processes. Understanding the differences in NPS pollution load loss under hydrological processes is useful for the management and prevention of NPS pollution. In this paper, hydrological and water quality data from 2016 to 2018 and monitoring data of physical and chemical indicators in 1347 field soil samples in the Shaying River Basin (SYRB) were used to analyze spatiotemporal variations in NPS pollution using the Soil and Water Assessment Tool and multifactor analysis of variance. The intensities and differences in NPS pollution losses for different soil types and land use patterns were evaluated under different hydrological zones. The annual rainfall in the SYRB decreased gradually from 1136.50 to 404.04 mm, showing a significant zoning. Areas with high loss intensities were mainly distributed in areas with steep slopes and in the 800-1000 mm rainfall zone. Cultivated land had the largest loss of NPS pollution, followed by forest land and rural residential land. Fluvo-aquic soil had the largest loss of NPS pollution, followed by cinnamon soil and lime concretion black soil. A nonlinear regression model was established for rainfall and the NPS pollution loss intensity and had a correlation coefficient of 0.60-0.99 at a 95% confidence level. Slope and rainfall were the main factors influencing the nitrogen and phosphorus losses. In the 800-1000 mm rainfall zone, the soil background nitrogen and phosphorus load was also a major factor influencing the nitrogen and phosphorus loss intensities.

Distribution characteristics of non-point source pollution of TP and identification of key source areas in Nanyi Lake (China) Basin: based on InVEST model and source list method.

The Nanyi Lake basin, located in the middle and lower reaches of the Yangtze River, is a crucial component of the Yangtze River ecosystem. Excessive phosphorus levels lead to eutrophication in rivers and lakes. This study aims to enhance the identification efficiency of key source areas for non-point source pollution of total phosphorus (TP) in the Nanyi Lake Basin and improve decision-making regarding the treatment of these areas. The study employs the InVEST model and utilizes GIS spatial hot spot analysis to identify key source areas of agricultural TP non-point source pollution. The accuracy of the InVEST model's simulation results was verified using the source list method. The findings indicate that paddy fields serve as the primary pollution source. TP non-point source pollution in Nanyi Lake is influenced by pollution sources, pollution load filtration rate, and potential TP runoff mass concentration. Different pollution sources correspond to distinct key source areas, and the pollution generated by these sources in different administrative regions, ultimately affecting the lake, varies as well. The InVEST model demonstrates great applicability in regions where agricultural TP is the primary pollution source. For the Nanyi Lake basin, which predominantly experiences agricultural TP non-point source pollution, a combination of the InVEST model and the source list method is recommended. The InVEST model serves as the primary tool, while the source list method supplements it. This approach not only compensates for any limitations of the InVEST model's simulation results but also avoids unnecessary economic waste. The outcomes of this study contribute to a deeper scientific understanding of TP pollution in the Nanyi Lake Basin. They also aid in effectively identifying key source areas and formulating appropriate measures based on the pollution characteristics, thereby providing guidance for non-point source pollution control in the basin.

A multiscale analysis of the spatially heterogeneous relationships between non-point source pollution-related processes and their main drivers in Chaohu Lake watershed, China.

A better understanding of the relationships between non-point source (NPS) pollution-related processes and their drivers will help to develop scientific watershed management measures. Although various studies have explored the drivers' impact on NPS pollution-related processes, quantitative knowledge of the properties within these relationships is still needed. This study uses the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to produce three related processes of NPS pollution, quick flow (QF), nitrogen export (NE), and sediment export (SE), in the upstream watershed of Chaohu Lake, China. The spatial distributions of QF, NE, and SE and their responses to multiple natural-socioeconomic drivers at nine spatial scales (1 km2, 10 km2, 20 km2, 30 km2, 50 km2, 75 km2, 100 km2, 200 km2, and town) were compared. The results showed that the spatial scale has little impact on the spatial distributions of NPS pollution-related processes. Across the nine scales, the socioeconomic drivers related to agricultural activities, area proportions of cultivated land (cultivated) and paddy field (paddy), have dominant impacts on NE, while the topographical drivers, the connectivity index (IC) and slope, have dominant impacts on both SE and QF. The magnitudes of single and paired natural-socioeconomic drivers' impacts on NPS pollution-related processes increase logarithmically or linearly with increasing spatial scale, but they tend to reach a stable threshold at a certain coarse scale. Our results emphasized the necessity and importance of embracing spatial scale effects in watershed water environmental management.

Agricultural non-point source pollution and rural transformation in a plain river network: Insights from Jiaxing city, China.

Recently, agricultural non-point source pollution (ANPSP) has gained increasing attention in China. However, using a uniform paradigm to analyze ANPSP in all regions is difficult, considering their geographical, economic, and policy differences. In this study, we adopted the inventory analysis method to estimate the ANPSP of Jiaxing City, Zhejiang Province as a representative region of the plain river network area from 2001 to 2020 and analyzed it in the framework of policies and rural transformation development (RTD). The ANPSP showed an overall decreasing trend over 20 years. Compared to 2001, total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) decreased by 33.93%, 25.77%, and 43.94%, respectively, in 2020. COD accounted for the largest annual average (67.02%), whereas TP contributed the most to the equivalent emissions (50.9%). The highest contribution of TN, TP, and COD, which fluctuated and decreased over the past 20 years, originated from livestock and poultry farming. However, the contribution of TN and TP from aquaculture increased. The overall trend of RTD and ANPSP showed an inverted "U" shape with time, and the evolution of both showed similar stage characteristics. With the gradual stabilization of RTD, ANPSP successively went through three stages: high-level stabilization (2001-2009), rapid-decreasing (2010-2014), and low-level stabilization (2015-2020). Additionally, the relationships between pollution loads from different agricultural sources and indicators of different dimensions of RTD varied. These findings provide a reference for the governance and planning of ANPSP in the plain river network area and a new perspective for investigating the relationship between rural development and the environment.

Applying water environment capacity to assess the non-point source pollution risks in watersheds.

Comprehension of the spatial and temporal characteristics of non-point source (NPS) pollution risk in watersheds is essential for NPS pollution research and scientific management. Although the concept of water functional zones (WFZ) has been considered in the NPS pollution risk assessment process. However, no comprehensive study of the NPS pollution risk has been conducted to effectively protect water quality in watersheds with different water environment capacity. Therefore, this study proposes a new NPS pollution risk assessment method that integrates water functional zoning, receiving water body environmental capacity, and space-time distribution of pollution load for quantifying the impact of pollution discharge from sub-catchment on nearby water body quality. Based on the NPS nutrient loss process modeled by the Soil and Water Assessment Tool (SWAT), this method was used to assess the NPS pollution risk in the Le 'an River Watershed at annual and monthly scales. The results showed that the NPS pollution risk is characterized by seasonal and spatial variability and is influenced clearly by the water environment capacity. High NPS pollution loads are not necessarily high pollution risks. Conversely, a low NPS nutrient pollution load does not represent a low regional risk sensitivity. In addition, NPS risk assessment based on the water environment capacity could also distinguish the differences in risk levels that were masked by similar NPS pollutant loss and the same water function zoning to achieve accurate control of NPS pollution management in watersheds.

Contribution of non-point source pollution that migrated with underground runoff process based on the SWAT model and a digital filter algorithm.

Non-point source (NPS) pollution has always been the focus of research worldwide, and understanding the migration process is the basis for effective control of NPS pollution. In this study, the SWAT model and digital filtering algorithm were combined to explore the contribution of NPS pollution that migrated with underground runoff (UR) process to the Xiangxi River watershed. The results showed that the surface runoff (SR) was the main migration process of NPS pollution, while the contribution of NPS pollution that migrated with the UR process only accounted for 30.9%. With the decrease in annual precipitation among the three selected hydrological years, the proportion of NPS pollution that migrated with the UR process for TN decreased, whereas the proportion for TP increased. The contribution of NPS pollution migrated with UR process varied remarkably during different months. Although the maximum total load and the load of NPS pollution that migrated with the UR process for TN and TP all appeared in the wet season, due to the hysteresis effect, the load of NPS pollution that migrated with the UR process for TP appeared 1 month later than the total load of NPS pollution. With an increase in precipitation from the dry season to the wet season, the proportion of NPS pollution that migrated with the UR process for TN and TP decreased gradually, and the degree of decrease in NPS pollution that migrated with the UR process for TP was more evident than that for TN. Besides, being affected by topography, land use, and other factors, the proportion of NPS pollution that migrated with the UR process for TN decreased from 80% in upstream areas to 9% in downstream areas, while that for TP reached a maximum of 20% in downstream areas. Based on the research results, the contribution of soil and groundwater cumulative nitrogen and phosphorus should be considered, and different managements and control measures for different migration routes should be adopted in controlling pollution.

Identifying the critical areas and primary sources for agricultural non-point source pollution management of an emigrant town within the Three Gorges reservoir area.

Agricultural non-point source pollution is threatening water environmental health of the Three Gorges reservoir. However, current studies for precision management of the agricultural non-point source pollution within this area are still limited. The objective of this study was identifying the critical areas and primary sources of agricultural non-point source pollution for precision management. Firstly, the inventory analysis approach was used to estimate the discharge amount of total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) from farmland fertilizer, crop residues, livestock breeding, and daily activities. Afterwards, the deviation standardization method was applied to evaluate the emission intensity of TN, TP, and COD, as well as calculating the comprehensive pollution index (CPI) of each village, based on which the critical areas for agricultural non-point source pollution management could be distinguished. Moreover, the equivalence pollution load method was conducted to identify the primary pollution sources within each critical zone. The above methods were implemented to an emigrant town within the Three Gorges reservoir area named Gufu. Results showed that agricultural non-point source pollution in Gufu town has been alleviated to a certain extent since 2016. Nevertheless, in four areas of the town (i.e., Longzhu, Fuzi, Shendu, and Maicang), the agricultural non-point source pollution still deserved attention and improvement. For the mentioned critical areas, farmland fertilizer and livestock breeding were the primary sources causing agricultural non-point source pollution. The emission amount of TN and TP from farmland fertilizer accounted for 60% and 48% of the total, respectively. And those from livestock breeding were 29% and 46%. Our research could provide definite targets to relieve agricultural non-point source pollution, which had great significance to protect water environment while coordinating regional economic growth after emigrant resettlement.

New method for scaling nonpoint source pollution by integrating the SWAT model and IHA-based indicators.

Nonpoint source (NPS) pollution shows spatial scaling effects because it is affected by topography, river networks, and many other factors. Currently, the lack of an integrated methodology for quantifying the scaling effect has become a crucial barrier in evaluating NPS pollution. In this study, a new method was proposed for scaling NPS pollution by integrating hydrological model and hydrological alteration indicators. Nested catchments were delineated by eight-direction algorithm, and a semidistributed hydrological model was used to simulate the interannual process within the drainage area and to obtain data series of runoff, sediment, and total phosphorus (TP) at different spatial scales. In addition, the average, the extrema, the change rate and feature variables of each type of indicators were proposed to quantitatively describe the pattern of NPS pollution at different spatial scales. The results show the coefficients of variation (CVs) of most runoff and TP indicators are 0.6-0.8, while those of sediment vary greatly from 0.4 to 1.6 with the threshold of those indicators being 0.33. With the increase in drainage area, the NPS load-related indicators show an increasing trend, while load intensity indicators show a decreasing trend and their changing patterns are affected by the heterogeneity of topographic or hydrological information included. Based on logarithmic variance of the change rate, 825 km2 was identified as the turning point for scaling transformation where the slope changes dramatically. The proposed methodology comprehensively describes features of the NPS scaling effect that could be utilized for targeted monitoring and control of NPS pollution in other watersheds.

Assessing the effectiveness of potential best management practices for science-informed decision support at the watershed scale: The case of the Mar Menor coastal lagoon, Spain.

Coastal lagoons are ecosystems of high environmental importance but are quite vulnerable to human activities. The continuous inflow of pollutant loads can trigger negative impacts on the ecological status of these water bodies, which is contrary to the European Green Deal. One example is the Mar Menor coastal lagoon in Spain, which has experienced significant environmental degradation in recent years due to excessive external nutrient input, especially from non-point source (NPS) pollution. Mar Menor is one of the largest coastal lagoons of the Mediterranean region and a site of great ecological and socio-economic value. In this study, the highly anthropogenic and complex watershed of Mar Menor, known as Campo de Cartagena (1244 km2), was modelled with the Soil and Water Assessment Tool (SWAT) to analyse potential options for recovery of this unique system. The model was used to simulate several best management practices (BMP) proposed by recent Mar Menor regulations, such as vegetative filter strips, shoreline buffers, contour farming, removal of illegal agriculture, crop rotation management, waterway vegetation restoration, fertiliser management and greenhouse rainwater harvesting. Sixteen scenarios of individual and combined BMPs were analysed in this study. We found that, as individual measures, vegetative filter strips and contour farming were most effective in nutrient reduction: approximately 30 % for total nitrogen (TN) and 40 % for total phosphorus (TP). Moreover, waterway vegetation restoration showed the highest sediment (S) reduction at approximately 20 %. However, the combination of BMPs demonstrated clear synergistic effects, reducing S export by 38 %, TN by 67 %, and TP by 75 %. Selecting the most appropriate BMPs to be implemented at a watershed scale requires a holistic approach considering effectiveness in reducing NPS pollution loads and BMP implementation costs. Thus, we have demonstrated a way forward for enabling science-informed decision-making when choosing strategies to control NPS contamination at the watershed scale.

Spatial optimization of ecological ditches for non-point source pollutants under urban growth scenarios.

Non-point source (NPS) pollution is regarded as the major threat to water quality worldwide, and ecological ditches (EDs) are considered an important and widely used method to collect and move NPS pollutants from fields to downstream water bodies. However, few studies have been conducted to optimize the spatial locations of EDs, particularly when the watershed experiences urbanization and rapid land-use changes. As land-use patterns change the spatial distribution of NPS loads, this study used a cellular automata-Markov method to simulate future land-use changes in a typical agricultural watershed. Three scenarios are included as follows: historical trend, rapid urbanization, and ecological protection scenarios. The spatial distributions of particulate phosphorus loads were simulated using the revised universal soil loss equation and sediment transport distribution model. The results suggested that the total particulate phosphorus (TP) load in the Zhuxi watershed decreased by 10,555.2 kg from 2000 to 2020, primarily because the quality and quantity of forests in Zhuxi County improved over the last 20 years. The TP load in Zhuxi watershed would be 2588.49, 2639.15, and 2553.32 kg in 2040 in historical trend, rapid urbanization, and ecological protection scenarios, respectively, compared with 2308.1 kg in 2020. This indicated that urban expansion increases the TP load, and the faster the expansion rate, the more the TP load. Consequently, the optimal locations of EDs were determined based on the intercepted loads and the period during which they existed during land-use changes. The results suggested that rapid urbanization would consequently reduce the space available for building EDs and also increase the cost of building EDs to control the NPS pollution in the watershed.

Identification of priority management areas for non-point source pollution based on critical source areas in an agricultural watershed of Northeast China.

Identification of critical source areas (CSAs) for non-point source (NPS) pollution is of great significance for environment governance and prevention. However, the CSAs are generally characterized as great spatial dispersion, and spatially heterogeneous precipitation has a great influence on the spatial distribution of nutrient yields. Therefore, we identify the CSAs for nutrient yields in an agricultural watershed of Northeast China at hydrological response units (HRUs) scale based on the Soil and Water Assessment Tool (SWAT), assess the impacts of spatially heterogeneity of precipitation on the identification of the CSAs, analyze the sensitivity of nutrient yields to precipitation by scenarios analysis method, and further identify priority management areas (PMAs) that have poor ability to retain nutrients. The results showed that the CSAs for nutrient yields identified by uniform precipitation showed greater fluctuation range and coverage area than actual precipitation; the major prevention areas of total nitrogen (TN) yield were mainly distributed in regions nearby main stem of lower reaches, while that of total phosphorus (TP) yield were mostly located in urban area nearby outlet of the watershed; the identification of the PMAs significantly decreased the CSAs for TN yield, whereas that for TP yield was no significant difference with the CSAs. This study could provide scientific guidance for the NPS pollution governance and prevention.

Analysis and estimation of nonpoint source pollution under different land use in Anjiagou watershed, Gansu, China.

Agriculture-related nonpoint source pollution has been a worldwide issue in the past few decades. Estimating pollutant sources at the basin scale remains a challenge due to the complexity of pollutant transport mechanisms affected by land use, variable climatic condition, geological formation, and lack of long-term observation data. This study was based on the long-term plot observational data of surface runoff and water quality and used principal component analysis and other statistical analyses to analyze the variation of water quality affected by different land uses (cropland, tree forest, shrub, grassland, and wildland). The mean concentration method with the local calibrated/verified SWAT (soil and water assessment tool) model was used to quantify the load of nonpoint source (NPS) pollutants on slope areas under different land uses in the Anjiagou Watershed. Our research results determined permanganate index (CODMn), ammonia nitrogen (NH3-N), total nitrogen (TN), fluoride (F-), nitrite nitrogen (NO2-N), total phosphorus (TP), and hexavalent chromium (Cr6+) as the significant pollutants while 5-day biochemical oxygen demand (BOD5) was identified to be below the water quality standards of Grade V (water for agricultural and general landscape use) in the studied watershed. Pollutants were discharged through either hillslope at a total rate of 2.4 kg ha-1, accounting for 67.6% of the total, or through waterway channels (32.4%). The pollutant concentrations were from 23.5 mg L-1 to 37.4 mg L-1, varying with pollutants and land uses. All examined water quality indicators exceeded the minimum safety standards defined by the regulations of the Gansu provincial government by averaging 3.5 times higher than the safety threshold. The pollutants from hillslopes exceeded water quality standards by a factor of 3.4-4.4 times compared with from the waterway channel by 1.9. Implementing soil and water conservation measures can mitigate pollutants to some extent, particularly during the process of highland runoff converging into waterways. At the watershed level, between 33 and 38% of the runoff and pollutants were discharged from croplands, between 59 and 66% from forest land, < 2% from grassland, and 1% from wildland. This study also demonstrates a simple but novel method to estimate NPS pollutants using long-term plot observations in conjunction with SWAT models, which can be used in other watersheds with similar conditions.

[Temporal and Spatial Variation Characteristics and Source Analysis of Agricultural Non-point Source Pollution Load in Guangdong During the Past 20 Years].

The agricultural non-point source pollution (ANPSP) load in Guangdong province is very large and has a serious impact on the regional ecological environment. Inventory analysis was used to assess and analyze the temporal and spatial variation characteristics of the ANPSP load of Guangdong province during 1999-2019, and the sources of ANPSP were discussed, as well as the relationship between them. The results showed that, during the past 20 years, the total ANPSP pollution loads of Guangdong province decreased by 6.08%, and the pollution loads of chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) increased by -11.88%, 4.99%, and 26.17%, respectively. The input intensity of chemical fertilizers and pesticides increased by 112.19% and 60.38%, respectively. The Pearl River Delta had the highest ANPSP loads in Guangdong province, followed by those in northern, western, and eastern Guangdong. Livestock and poultry breeding were the main sources of COD, the total percent fertilizers and livestock and poultry breeding were the main sources of TN, and livestock and poultry breeding and aquaculture were the main sources of TP. In addition, the contribution of pollutants discharged from aquaculture showed an obvious increasing trend. There were certain differences in the pollution sources in different regions. In western Guangdong, northern Guangdong, and eastern Guangdong, livestock and poultry breeding were the main sources of COD and TP, and fertilizer was the main source of TN; by contrast in the Pearl River Delta, aquaculture had become the main source of TN and TP pollution loads. The correlation results showed that the decline in the total ANPSP in Guangdong province was mainly due to the increase in high urbanization rate and the decrease in the proportion of rural population. In general, there were stage changes in the time and differences in spatial characteristics and sources of ANPSP in Guangdong province. A combination of comprehensive treatment and targeted pollution treatment should be adopted, and fertilizer reduction measures and pollution treatment in the aquaculture should be strengthened in an all-around way, focusing on strengthening the treatment of pollution from aquaculture in the Pearl River Delta region and the treatment of rural life pollution in northern Guangdong.

Coupling with high-resolution remote sensing data to evaluate urban non-point source pollution in Tongzhou, China.

Urban non-point source (NPS) pollution has gradually become one of the important factors affecting the urban water environment. The quantitative evaluation of urban NPS pollution is the priority to identify key control area of urban NPS pollution. Current model applied in China is mainly focused on small-scale area, large-scale spatial continuous simulation is lacking. In this study A spatial continuous evaluation method coupled with high-resolution remote sensing data has been established and the method was applied to Tongzhou, China. With the spatial distribution of land-use type and built-up area which were been obtained by remote sensing technology, the accumulative and wash-off load of urban NPS nitrogen and phosphorus were estimated for the prominent problems of nitrogen and phosphorus nutrient pollution in the rivers in the study area. The main sources of urban NPS Nitrogen and phosphorus pollution are roof and road rainfall runoff respectively. Compared to other urban NPS pollution models, the method developed in this study can quickly realize spatial visualization assessment of urban NPS pollution and provide a means to estimate urban NPS loads in entire city or urban agglomeration, it is applicable for common urban NPS pollutants and also has advantages in areas without data.

Cleaner agricultural production in drinking-water source areas for the control of non-point source pollution in China.

With continuous population growth and acceleration of urbanization in China, environmental problems in drinking-water source areas have become increasingly prominent. In some places, domestic wastewater and aquaculture sewage are directly discharged into water bodies without any treatment. Also, large amounts of domestic garbage and aquaculture waste are often randomly stacked, seriously polluting the surrounding groundwater and surface water and deteriorating the water quality. Notably, some agricultural production activities can also cause non-point source pollution, resulting from eutrophication of water bodies. In some instances, these activities can lead to nitrogen losses of 0.7%-83.9% and phosphorus losses of 0.6%-82.8%. In view of this situation, the implementation of cleaner agricultural production is of great significance for protecting the environment in drinking-water source areas and maintaining drinking-water safety. Specific practicable measures include formula fertilization through soil testing, integrated pest management, and water-saving irrigation technology. For the livestock- and poultry-breeding industry, it is necessary for large-scale farms to construct excreta discharge treatment facilities, carry out harmless treatment and resource utilization of organic wastes, establish rural biogas septic tanks, and make use of domestic-sewage and livestock-breeding wastewaters. Also, fixed garbage-dumping sites should be built in rural water-source areas, and a unified garbage-disposal station set up to reduce the pollution discharge of domestic garbage. Moreover, it is crucial to strictly control the development and utilization of hillsides in the middle and upper reaches of the drinking-water source area, as well as strengthen the restoration of vegetation and the construction of soil and water conservation forests in these areas.

Estimation of potential agricultural non-point source pollution for Baiyangdian Basin, China, under different environment protection policies.

To prevent and control non-point source pollution, many policies have been carried out by government in China. However, the effectiveness of these policies has rarely been evaluated. In this study, the potential and spatial distribution of agricultural non-point source pollution in the Baiyangdian Basin are reported. This investigation considers multiple parameters under various policies with county as a basic unit. The results for the potential pollution from chemical oxygen demand (COD), ammonia nitrogen (NH3-N), total nitrogen (TN) and total phosphorus (TP) are 60.89×104, 3.93×104, 87.05×104 and 15.10×104 Mg, with corresponding intensities of 190, 12, 272 and 47 kg ha-1 for the Baiyangdian Basin in 2016. The highest pollution from COD is attributed to livestock and poultry breeding, whereas TN and TP are dominantly produced by rural domestic sources, and NH3-N is mostly derived from planting. Spatially, distribution of the counties producing larger non-point source pollution presented a northeast to southwest direction, consistent with the Taihang mountain alignment in the basin. The counties with high pollution intensities are mostly in the south and east of the basin. Agricultural non-point source pollution control and prevention policies contributed in pollution reduction. Compared with 2016, the total potential pollution of COD, NH3-N, TN and TP in 2020 decrease by 45.1%, 14.7%, 37.9% and 37.4%, respectively, whereas for an assumed future time (F2), the decreases are 59%, 51.4%, 56.2% and 55.7%, respectively. Prevention measures should focus on reducing pollution from livestock and poultry breeding as well as planting.

Non-Point Source Pollution Simulation and Best Management Practices Analysis Based on Control Units in Northern China.

Non-point source (NPS) pollution simulation in control units can identify critical pollution source areas and make Best Management Practices (BMPs) more effective for the responsible parties. In this study, the control unit division method is introduced, and the spatial and temporal distribution characteristics of NPS pollution in the Guishui River Basin of Northern China are analyzed using the Soil Water Assessment Tool (SWAT) model. In addition, five BMP scenarios were designed for environmental and cost-benefit analyses. The results show that the loss of total nitrogen (TN) and total phosphorus (TP) is concentrated in the rainy season, and the loss of TN and TP is mainly distributed in the middle and lower reaches of the main stream of the Guishui River. This area accounts for 22.34% of the basin area. The vegetated filter strips (VFS) scenario had the best environmental benefits with average TN and TP reduction efficiencies of 63.4% and 62.6%, respectively. The Grassed Waterway was the most cost-effective scenario measure, cost-benefit (CE) values of TN and TP were 1798.13 g/€ and 601.56 g/€. Generally, research on NPS pollution using control units can more clearly identify the critical source areas of pollution than other methods, and provides technical support for watershed management decision makers.