Non-point Source Pollution Management Research Articles

Using surface runoff to reveal the mechanisms of landscape patterns driving on various forms of nitrogen in non-point source pollution

Non-point source (NPS) pollution directly threatens river water quality, constrains sustainable economic development, and poses hazards to human health. Comprehension of the impact factors on NPS pollution is essential for scientific river water quality management. Despite the landscape pattern being considered to have a significant impact on NPS pollution, the driving mechanism of landscape patterns on NPS pollution remains unclear. Therefore, this study coupled multi-models including the Soil and Water Assessment Tool (SWAT), Random Forest, and Partial Least Squares Structural Equation Modeling (PLS-SEM) to construct the connection between landscape patterns, NPS pollution, and surface runoff. The results suggested that increased runoff during the wet season enhances the link between landscape patterns and NPS pollution, and the explained NPS pollution variation by landscape pattern increased from 59.6 % (dry season) to 84.9 % (wet season). Furthermore, from the impact pathways, we find that the sink landscape pattern can significantly and indirectly influence NPS pollution by regulating surface runoff during the wet season (0.301*). Meanwhile, the sink and source landscape patterns significantly and directly impact NPS pollution during different seasons. Moreover, we further find that the percentage of paddy land use (Pad_PLAND) and grassland patch density (Gra_PD) metrics can significantly predict the dissolved total nitrogen (DTN) and nitrate nitrogen (NO3−-N) variation. Thus, controlling the runoff migration process by guiding the rational evolution of watershed landscape patterns is an important development direction for watershed NPS pollution management.

Gully regulates snowmelt runoff, sediment and nutrient loss processes in Mollisols region of Northeast China

Gully is a prominent indicator of land degradation in agroecosystems, functioning as a crucial pathway connecting upslopes to downstream channels. However, little is known about how gully regulates runoff, sediment, and nutrient loss processes in the catchment during snowmelt. In this study, we monitored these processes in situ at both the gully head (the upslope accumulated catchment of the gully head, CGH) and outlet of two representative and typical gully-dominated catchments (F1 and F2) during snowmelt in Mollisols region of Northeast China. Our results showed that runoff discharge of CGH and outlet exhibited a multi-peak trend during snowmelt, driven by the transition from snow melting to soil thawing. This transition resulted in distinct runoff patterns in both CGH and outlet, with significant differences in their response to air temperature. The total runoff yield of CGH accounted for 57.8 % in F1 and 40.6 % in F2 of the total runoff yield of the outlet. Notably, the peak sediment concentration displayed a marked lag compared to the peak runoff discharge, primarily dominated by the increased sensitivity of gully erosion after the thawing of gully slopes. Gully erosion was the main source of sediment yield in the catchment, contributing 98.2 % in F1 and 96.6 % in F2. Furthermore, nutrient concentrations exhibited a decreasing trend during snowmelt. The comparison of high nutrient concentrations in CGH and relatively low nutrient concentrations in outlet highlighted the gully's role in intercepting and diluting runoff nutrients. Hysteresis analysis confirmed the differential contribution of CGH and gully to nutrient sources. CGH accounting for 50.9 % and 93.3 % of runoff TN and runoff TP loss, while contributing only 8.3 % and 5.8 % to sediment TN and sediment TP loss, respectively. These findings offer valuable insights for effective erosion control and nonpoint source pollution management in gully-dominated agroecosystems during snowmelt.

Optimizing Non-Point Source Pollution Management: Evaluating Cost-Effective Strategies in a Small Watershed within the Three Gorges Reservoir Area, China

Non-point source (NPS) pollution poses a significant threat to the water environment, yet controlling it at the watershed scale remains a formidable challenge. Understanding the characteristics and drivers of nitrogen (N) and phosphorus (P) outputs at the watershed scale, along with identifying cost-effective best management practices (BMPs), is crucial for effective pollution control. In this study, we utilized the Wangjiaqiao watershed within the Three Gorges Reservoir Area (TGRA) as a case study to explore the characteristics of N and P load outputs and their dominant drivers by combining the SWAT model and a geographic detector. Based on our analysis of N and P loads within the watershed, we employed the entropy weight method to evaluate the reduction efficiency and cost-effectiveness of 64 BMP scenarios, encompassing seven measures (vegetative filter strips, parallel terraces, 10% fertilizer reduction, 30% fertilizer reduction, residue cover tillage, grass mulching, and returning farmland to forest) and their combinations. Our findings revealed the following: (1) spatial heterogeneity in NPS loads within the watershed, primarily influenced by land use, fertilizer application, and surface runoff, with interactive enhancement effects among driving factors; (2) the differential effectiveness of BMPs at the watershed level, with structural measures, particularly terracing, exhibiting higher efficacy and achieving reduction rates of 28.12% for total nitrogen (TN) and 37.69% for total phosphorus (TP); the combined BMPs showed improved reduction efficiency, but not merely additive; and (3) in terms of cost-effectiveness, 30% fertilizer reduction emerged as the most beneficial among the individual measures. Moreover, a combination of vegetative filter strips, parallel terraces, and 30% fertilizer reduction demonstrated significant improvements in TN and TP reductions (48.05% and 61.95%, respectively), suggesting their widespread applicability. Overall, our study provides insights into developing a cost-effective BMP strategy for the Wangjiaqiao watershed and offers valuable guidance for NPS pollution management in similar small watersheds within the TGRA.

Nutrient runoff and leaching under various fertilizer treatments and pedogeographic conditions: A case study in tobacco (Nicotiana tabacum L.) fields of the Erhai Lake basin, China

To ensure water security, it is crucial to understand the characteristics of nitrogen (N) and phosphorus (P) in water and to reduce their inputs. We conducted a 2-year trial (2021–2022) in tobacco fields across three sites in the Erhai Lake basin, China, to comprehensively measure and summarize N and P loss through runoff and leaching for four fertilizer treatments: no fertilizer (CK); farmers' traditional organic fertilizer (FP); chemical fertilizer (CF); and a combination of organic and inorganic fertilizer (OIC). The highest N concentrations were detected in leachate in the early tobacco growth stage, whereas the highest P concentrations occurred in runoff in the middle growth stage. Compared to FP, the OIC treatment improved nutrient uptake in flue-cured tobacco, while also reducing N loss through runoff and leaching by 45.37% and 19.34%, and reducing P loss by 7.22% and 8.26%, respectively. Correlation analyses revealed positive relationships of nutrient loss with soil organic matter content and nutrient inputs; elevation and soil water content exhibited varying correlations with different nutrients. These findings provide a theoretical foundation for the effective management of agricultural non-point source pollution in the Erhai Lake basin and shed light on water pollution pressures worldwide.

Estimation, Management, and Control of Non-Point Source Pollution from Livestock Runoff: A Literature Review

Los nutrientes, como el nitrógeno y el fósforo generan, entre otros impactos, la eutrofización en los cuerpos de agua. Estos impactos son principalmente causados por actividades agrícolas como la ganadería, debido a la aplicación de fertilizantes y/o al estiércol de las vacas. Los nutrientes transportados por la escorrentía llegan a los cuerpos de agua y generan contaminación. Esta problemática ha sido abordada desde la década de los 60, no obstante, se ha logrado poco avance en este tema. Los avances están relacionados con la estimación del aporte de nutrientes de forma teórica y a través de simulaciones, debido a los altos costos que implica tomar datos en el campo. También se han realizado esfuerzos en la implementación de Buenas Prácticas de Gestión para el manejo de las fuentes no puntuales, pero existe poca evidencia de la eficiencia de cada una de estas prácticas. Por otro lado, pese a la falta de información científica necesaria para formular políticas, se ha demostrado que la vía normativa puede ser el mejor mecanismo para controlar la contaminación por fuentes no puntuales. En este artículo, se presenta una revisión de estos tres componentes luego del análisis bibliométrico, estableciendo lo que se conoce actualmente y las brechas de información. Primero, se abordan los avances en la estimación del aporte de las fuentes no puntuales, segundo se presentan las Buenas Prácticas de Gestión, y tercero, se exponen los avances en materia de políticas para el control de la contaminación no puntual.

The Impact of Non-Point Source (NPS) Management on Non-Point Source Reduction and Water Cycle Improvement in an Urban Area

Suwon, the capital and largest city of Gyeonggi-do, South Korea, was designated as a non-point source management area in 2010. The management period ended in 2020, so follow-up measures are needed. In this study, we investigated several projects implemented in Suwon for urban water cycle improvement and non-point source pollution reduction, and the long-term management effects were analyzed to suggest policy directions such as the revision of designation notices. During the 10-year management period in Suwon, the population and lot area continued to increase, and the non-point source-based annual Biochemical Oxygen Demand (BOD) discharge loads also increased by approximately 25% at the half sub-basins Hwangguji-cheon and Woncheonri-cheon in 2020 compared to 2010. Even under these conditions, statistical analyses show that the Biochemical Oxygen Demand (BOD) and Total Phosphorus (TP) concentrations monitored at the outlet of basin were decreased due to the promotion of a large-scale sewer management project as well as non-point source pollution reduction projects. Also, the field monitoring data-based Load Duration Curve (LDC) analysis results indicate that the loads decreased in the high-flow period of 2020 compared to 2015. Also, the Normalized Difference Vegetation Index (NDVI) values calculated using satellite images since 2017 tended to increase slightly during the period when the impervious area estimated using the land registration map increased. It is assumed that using the current calculation method for impervious areas has limitations regarding its ability to reflect changes in the small-scale Low-Impact Development (LID) facility and in ecological/landscape areas. On the other hand, the annual variation in direct runoff estimated at the outlet using three hydrograph separation methods did not show any improvement with regard to storm water retention during the management period. These results reveal that the effects on urban water cycle improvement, such as peak flow reduction and base flow increase, may not be noticeable despite some progress in reducing non-point source pollution and increasing green area. Therefore, additional efforts directed towards non-point source pollution management focused on water cycle improvement are required in the city, especially in the sub-basins with higher pollution loads such as Hwangguji-cheon and Seoho-cheon.

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

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

Quantifying and assessing nitrogen sources and transport in a megacity water supply watershed: Insights for effective non-point source pollution management with mixSIAR and SWAT models

The expansion and intensification of human activities have resulted in excessive nitrogen (N) in rivers, causing worldwide concern. To effectively manage agricultural non-point source pollution and ensure a safe drinking water supply in watersheds, it is crucial to trace and quantify the primary sources and spatial distribution patterns of N. In response to the challenge of unclear sources and agricultural non-point source pollution, this study utilised the Bayesian isotope mixing model and Soil and Water Assessment Toolmodel to identify the dominant nitrate sources and transformation processes. These models were employed to quantify N retention by the mainstream and tributaries in the Bai River Basin, which directly impacts the safety of drinking water in Beijing. Total N (TN) concentrations in the Yunzhou Reservoir (4.22 ± 0.04 mg.L˗1) and Miyun Reservoir (2.88 ± 0.62 mg.L˗1) inlets in autumn and winter were V class (2 mg.L˗1) category as per GB 3838–2002 standards. This implies higher risks of eutrophication and algal blooms exceeding the standards at individual points and seasons in the Bai River. Fertilisers were the main nitrate source in the Bai River Basin, contributing 44.6% during the dry season and 62.9% during the wet season, suggesting that nitrate is more susceptible to leaching and runoff during rainy periods. Rainfall was not a major contributor, with only 3.2% and 2.9% originating from the Hebei and Beijing areas of the Bai River, respectively. Annually, the Bai River Basin exports loads of approximately 629.3 t.a˗1 of TN and 433.7 t.a˗1 of organic N (Org-N) from the Bai River Basin land to the river. The TN and Org-N loads at the final destination in the Miyun Reservoir were 521.3 t.a˗1 and 100.3 t.a˗1, respectively. Of the exported TN and Org-N, 17.16% and 76.87%, respectively, were retained in the river network. Consequently, N transformation occurred in the Bai River, with nitrification–denitrification being particularly dominant. Nitrification was more evident in the nitrate-enriched river.

Optimal design of low impact development at a community scale considering urban non-point source pollution management under uncertainty

Urban non-point source (NPS) pollution management is receiving increased attention because of the environmental and ecological consequences of urbanization. We developed a Storm Water Management Model (SWMM)-based interval double-sided chance-constrained programming (SWMM–IDCCP) model for the optimal design of low impact development (LID) during urban NPS pollution management at a community scale. Pollution control efficiency and economic costs related to LID practices were considered in the SWMM–IDCCP model, simultaneously addressing uncertainties in pollutant output and decision-making processes. Specifically, by combining SWMM, Monte Carlo simulation, interval linear programming, and double-sided chance-constrained programming, the SWMM–IDCCP model can evaluate export loads of urban NPS pollutants and pollution control efficiencies of LID practices and analyze the corresponding uncertainties. Concurrently, the proposed model can provide reliable and optimal implementation schemes for LID practices under different scenarios, dealing with uncertainties such as discrete intervals and double-sided random parameters. The proposed model was applied to the Dongguan University of Technology in Dongguan City, South China. The random distribution characteristics of pollution load were identified. The ranges of pollution load for total suspended solids, chemical oxygen demand, total nitrogen, and total phosphorus were 76,430–165,698, 44,366–74,155, 2118–3,830, and 97–177 kg in 2021, respectively. Probability distribution characteristics of pollution control efficiencies of three LID practices (i.e., bio-retention cell, green roof, and permeable pavement) for the four urban NPS pollutants were obtained. Using the SWMM-IDCCP model, LID configuration schemes were obtained under diverse pollution control targets and confidence levels, taking into account variations in the decision preference of different administrators. This research indicates that the SWMM-IDCCP model can be used to manage urban NPS pollution at a community scale under uncertainty.

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 404.04mm, showing a significant zoning. Areas with high loss intensities were mainly distributed in areas with steep slopes and in the 800-1000mm 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 800-1000mm rainfall zone, the soil background nitrogen and phosphorus load was also a major factor influencing the nitrogen and phosphorus loss intensities.

Research on the Progress of Agricultural Non-Point Source Pollution Management in China: A Review

In the 1980s, China began to recognize the gravity of the problem of non-point agricultural source pollution and conduct research on it. Agricultural non-point source pollution in China, on the other hand, differs from foreign agricultural non-point source pollution and industrial point source pollution. Because the features of agricultural non-point source pollution are complicated, it is critical to investigate a whole-chain management policy system appropriate for China’s agricultural pattern. Based on the current situation of agricultural non-point source pollution in China, this study summarizes the four stages of agricultural non-point source pollution prevention and control policies, namely the discovery stage with macro policies as the main focus, the exploration stage with single research indicators, the initial systematic strengthening stage, and the focused stage with targeted characteristics. Simultaneously, it examined the technological approaches that are suitable for China’s national circumstances and have been investigated by relying on international experience in present-day Chinese management. However, there are still some problems and challenges in agricultural non-point source pollution management policies, such as a lack of non-point source information support, a lack of coordination between different departments, a lack of support in measurement and retroactive calculation and treatment, a lack of an in-depth concept of zoning and classification, a lack of policy, an institutional system, and insufficient capital investment. Based on these problems and combining them with Green Agriculture, Beautiful China, and other goals, this paper puts forward suggestions to strengthen the policy data support of the agricultural non-point source pollution management system, enhance the research and development of the law of pollutant migration and transformation, encourage the innovation of low-cost and high-benefit treatment technology, improve the construction of the management system, strengthen the collaboration of departments, increase the investment of funds, and make other suggestions so as to promote the treatment of agricultural non-point source pollution with high quality and efficiency.

Research on the Features of Rainfall Regime and Its Influence on Surface Runoff and Soil Erosion in the Small Watershed, the Lower Yellow River

Rainfall has a significant impact on surface runoff and erosion in a watershed, and there is a lack of information about the features of rainfall regimes and how they affect runoff and soil erosion. In the paper, based on 59 rainfall events from 2021 to 2022 in the lower Yellow River Culai Mountain sub-watershed, various statistical analysis methods were used to preliminarily explore the rainfall regime features and their influence on surface runoff and soil erosion. The results showed that the rainfall in the watershed was divided into three regimes: Rainfall Regime I had the highest frequency of occurrence, reaching 74.58%, and Rainfall Regime III was the main power source for surface runoff and soil erosion. The paper filtered out three indicators (P, I, and I30) to analyze the degree of influence of rainfall features on surface runoff and erosion, and the results show that precipitation is the main influencing factor affecting the variation in surface runoff, and the maximum 30 min rainfall intensity is the main factor impacting the variation in sediment yield. The results can provide a theoretical basis for soil conservation, hydrological forecasting, and non-point source pollution management.

Classification and Identification of Non-point Source Nitrogen Pollution in Surface Flow of the Shangwu River Watershed in the Qiandao Lake Region

Accurate quantification of non-point source pollution is an important step for non-point source pollution control and management at the watershed scale. Considering the non-point source pollution from baseflow, an improved export coefficient model (IECM) on a weekly scale was established based on the traditional export coefficient model (ECM), which was then used to estimate the surface flow non-point source total nitrogen (TN) loads contributed by different land use types of the Shangwu River watershed in the Qiandao Lake Region. The results showed that IECM performed well for the predictions of TN loads in the studied watershed, with the Nash-Sutcliffe efficiency coefficient (NSE) and R2values of 0.82 and 0.77 (P<0.01) for the calibration period and 0.87 and 0.84 (P<0.01) for the validation period, respectively. The IECM estimated TN exports through surface flow and baseflow were 5.74 kg·(hm2·a)-1and 9.85 kg·(hm2·a)-1 from the Shangwu River watershed in the period of Nov. 2020 to Oct. 2021, which accounted for 36.80% and 63.20% of the corresponding streamflow TN load, respectively. Without consideration of the baseflow non-point source TN pollution, the ECM-estimated surface flow TN loading was 54.21% higher than that estimated by IECM. Obviously, attributing baseflow non-point source pollution to surface flow directly would lead to a serious load overestimation of surface flow. According to IECM, the estimated TN export intensity through surface flow from paddy fields, grasslands, woodlands, rainfed croplands, and residential lands was 10.95, 5.42, 5.20, 12.34, and 2.77 kg·(hm2·a)-1, respectively, which accounted for 5.80%, 4.00%, 26.55%, 0.38%, and 0.03% of the corresponding total streamflow TN loads. Therefore, the future management of non-point source nitrogen pollution in the studied watershed should focus mainly on the prevention and management of groundwater non-point source pollution and control of load export from surface flow on cultivated land (paddy fields and rainfed croplands).

Assessing multivariate effect of best management practices on non-point source pollution management using the coupled Copula-SWAT model

Best management practices (BMPs) have wide application in non-point source (NPS) pollution abatement in agricultural watersheds. Multivariate analysis of BMPs reduction effects taking their randomness and correlations into account is significant to spatial optimization of BMPs configuration. However, quantifying the correlations among high-dimensional random variables of BMPs effects is challenging and remains unexplored thoroughly. This study coupled the SWAT with the Vine Copula model to conduct multivariate analysis of BMPs reduction effects considering their randomness caused by hydro-meteorological variability along with correlations among different indicators (ammonium nitrogen, NH3-N; and total phosphorus, TP) and BMPs. The coupled model was applied to evaluate the multi-indicator effect of individual BMP and combined effect of various BMPs in the upper Boyang River basin, China. Results showed that bivariate copulas and three-dimensional vine copulas can efficaciously describe the dependence of BMPs effects. Simulation results indicate 43–100% probabilities of 45% NH3-N loads reduction, while 0–79% probabilities of 45% TP loads reduction for combined BMPs scenarios. Besides, the joint probabilities of different indicators in combined BMPs scenarios are generally lower than separate probabilities with 0–21% decrease, which is similar to individual BMP. Generally, joint probabilities using copulas can provide more accurate and factual knowledge of the risk and dependability of implementation of BMPs than univariate variables. The proposed model can conduct multivariate analysis of BMPs reduction effects and has great prospect in the future risk-based decision-making of NPS pollution management.

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.

Does Livelihood Determine Attitude? The Impact of Farmers’ Livelihood Capital on the Performance of Agricultural Non-Point Source Pollution Management: An Empirical Investigation in Yilong Lake Basin, China

Agricultural non-point source pollution is intricately connected to the rural population’s production and lifestyle. The heterogeneous composition of livelihood capital results in varied livelihood types, influencing the farmers’ attitudes and perceptions of the treatment projects. This ultimately causes discrepancies in the farmers’ evaluation of agricultural non-point source pollution control. In this study, a participatory evaluation method was employed to evaluate the performance of agricultural non-point source pollution control projects in the Yilong Lake Watershed of Yunnan Province and analyze the underlying reasons for the differing performance evaluations. The findings revealed that pure farmers’ performance evaluation value for agricultural non-point source pollution control projects in Yilong Lake Basin was 0.4811 (with the full mark being 1), with a general evaluation grade. Part-time business households had a performance evaluation value of 0.5969, also with a general evaluation grade, while non-farmers had a performance evaluation value of 0.7057, with a good evaluation grade. The performance evaluation value ranked from highest to lowest is non-farmer &gt; part-time farmer &gt; pure farmer. The main factor affecting the variation in farmers’ performance evaluation is the key index of different livelihood capital. If pollution control projects can promote the adjustment of farmers’ livelihood capital types, it can enhance not only the performance evaluation degree of farmers, but also the sustainability of farmers’ livelihoods and increase their adaptability to livelihood risks. Therefore, pollution control projects should consider farmers’ livelihood capital types and be implemented accurately to improve farmers’ satisfaction and sustainability.

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.

Toward a Better Understanding of Phosphorus Nonpoint Source Pollution from Soil to Water and the Application of Amendment Materials: Research Trends

Phosphorus (P) nonpoint source pollution from soil to water is increasing dramatically, leading to the eutrophication of water bodies. Using amendment materials for P retention in soil is a promising strategy for environmental restoration and nonpoint source pollution management. This strategy has attracted significant attention because of its highly effective P retention. This study reviews management strategies of P nonpoint pollution from soil to water, including the basic P forms and accumulation situation in soil and P loss from soil to water. Recent advances in the use of amendment materials, such as inorganic, organic, and composite amendment materials, to mitigate P pollution from soil to water have also been summarized. Environmental risks of reloss of P retention in soil with different soil properties and water conditions have also been investigated. This review improves the understanding of P nonpoint source pollution from soil to water, providing an innovative perspective for the large-scale application of amendment materials to control water eutrophication.

The spatial spillover effect and impact paths of agricultural industry agglomeration on agricultural non-point source pollution: A case study in Yangtze River Delta, China

The rapid development of Chinese agriculture has brought about serious agricultural non-point source pollution (ANPSP), and the reduction of non-point source pollution is of great practical importance to realize the green transformation of agriculture, the ecological livability of the countryside and the well-being of farmers. Agriculture industrial agglomeration is widespread throughout the world, and it is generally accepted that there are positive economic effects. However, there is still a debate on whether positive or negative externalities dominate the environmental effects of agriculture industrial agglomeration. Therefore, it is of theoretical significance to correctly identify the nonlinear relationship and spatial spillover effects between agriculture industrial agglomeration and ANPSP. As a region with the rapid development of agricultural intensification in China, the environmental effect of agricultural agglomeration in the Yangtze River Delta is more complex compared with other industries, and It has strong research value to realize the coordinated development of agricultural industry clustering and green agriculture. Based on panel data of 37 cities in the Yangtze River Delta from 2000 to 2019, this paper uses the inventory analysis method to measure the agricultural non-point source pollution (ANPSP) of each city. Then, for the law of spatial evolution of ANPSP, the Spatial Durbin Model (SDM) was developed to analyze the specific impact of agricultural industrial agglomeration on ANPSP. The results show that: (1) the ANPSP of the Yangtze River Delta had a downward trend during 2000–2019, with high-high agglomeration and low-low agglomeration characteristics. (2) The effect of agricultural industrial agglomeration on ANPSP showed an inverted U-shape, which was consistent with the EKC curve. However, after considering the spatial spillover effect, it shifted to a U-shape. (3) Economic, structural and technological effects are the main driving effects for the mitigation of ANPSP, with concentration effects increasing pollution. Therefore, in the future, the moderate-scale business should be encouraged to develop, optimize and adjust the agricultural industrial structure, stimulate technological progress and innovation, enhance the spatial spillover capacity of technological and structural effects, and improve the capacity of nonpoint source pollution management.

Model predictive control of stormwater basins coupled with real-time data assimilation enhances flood and pollution control under uncertainty

Smart stormwater systems equipped with real-time controls are transforming urban drainage management by enhancing the flood control and water treatment potential of previously static infrastructure. Real-time control of detention basins, for instance, has been shown to improve contaminant removal by increasing hydraulic retention times while also reducing downstream flood risk. However, to date, few studies have explored optimal real-time control strategies for achieving both water quality and flood control targets. This study advances a new model predictive control (MPC) algorithm for stormwater detention ponds that determines the outlet valve control schedule needed to maximize pollutant removal and minimize flooding using forecasts of the incoming pollutograph and hydrograph. Comparing MPC against three rule-based control strategies, MPC is found to be more effective at balancing between multiple competing control objectives such as preventing overflows, reducing peak discharges, and improving water quality. Moreover, when paired with an online data assimilation scheme based on Extended Kalman Filtering (EKF), MPC is found to be robust to uncertainty in both pollutograph forecasts and water quality measurements. By providing an integrated control strategy that optimizes both water quality and quantity goals while remaining robust to uncertainty in hydrologic and pollutant dynamics, this study paves the way for real-world smart stormwater systems that will achieve improved flood and nonpoint source pollution management.