Non-point Source Pollution Load Research Articles

Simulating the land use change effects on non-point source pollution in the Duliujian River Basin.

The uncertainty in the generation and formation of non-point source pollution makes it challenging to monitor and control this type of pollution. The SWAT model is frequently used to simulate non-point source pollution in watersheds and is mainly applied to natural watersheds that are less affected by human activities. This study focuses on the Duliujian River Basin (Xiqing section), which is characterized by a dense population and rapid urbanization. Based on the calibrated SWAT model, this study analyzed the effects of land use change on non-point source pollution both temporally and spatially. It was found that nitrogen and phosphorus non-point source pollution load losses were closely related to land use type, with agricultural land and high-density urban land (including rural settlements) being the main contributors to riverine nitrogen and phosphorus pollution. This indicates the necessity of analyzing the impact of land use changes on non-point source pollution loads by identifying critical source areas and altering the land use types that contribute heavily to pollution in these areas. The simulation results of land use type changes in these critical source areas showed that the reduction effect on non-point source pollution load is in the order of forest land > grassland > low-density residential area. To effectively curb surface source pollution in the study area, strategies such as modifying urban land use types, increasing vegetation cover and ground infiltration rate, and strictly controlling the discharge of domestic waste and sewage from urban areas can be implemented.

Assessment of Agricultural Non-point Source Pollution Loads Applying Improved Export Coefficient Model (IECM) : A Case Study in Taihu Lake Basin

Accurate and comprehensive estimation of agricultural non-point source pollution (ANPSP) is of vital importance in watershed pollution control, while data inaccessibility and complexity of process-based models may be main restrictions in practice. An estimation methodology framework for ANPSP was established based on improved export coefficient model (IECM) in this research. A series of updated, regional coefficients were collected and/or calculated with multiple pollution sources considered (i.e., animal husbandry, farming and forestry, fishery, and rural domestic sewage) to provide a comprehensive estimation of TN and TP pollution loads in Taihu Lake Basin. According to this model, pollution loads of TN and TP in Taihu Lake Basin were 65791.28 and 11400.38 t in 2016, respectively. Animal husbandry was main source of ANPSP, accounting for 31.05% and 66.70% for TN and TP, respectively, which requires more efficient and clean agricultural production modes and strict pollution control measures. IECM-based estimation framework may provide a reference for ANPSP management practice in large scale watershed.

Evolutionary Trend Analysis of Agricultural Non-Point Source Pollution Load in Chongqing Based on Land Use Simulation

Analysis of the relationship between future land use change and agricultural non-point source pollution (ANPSP) evolution is vital to promoting sustainable regional development. By simulating future land use types, we can identify and analyze the evolution trend of ANPSP. This study takes Chongqing as a case study to establish an integrated solution based on the PLUS model, output coefficient model, and GIS technology. The solution can simulate data, identify trends, and identify key control areas under future development scenarios. The results show that the PLUS model can simulate land use types at the provincial scale with high accuracy, with a Kappa coefficient of around 0.9. The land use type changes show that urban expansion has occupied a large amount of cultivated land. From 2000 to 2020, the proportion of high-load areas with TN pollution load levels was 4.93%, 5.02%, and 4.73%, respectively. Under the two scenarios in 2030–2050, the number of high-load areas decreased, and the average load level decreased from west to east. Sensitivity analysis found that risk changes are more sensitive to the increase in fertilizer application. When the TN and TP output coefficients are increased, the number of towns with increased levels is greater than those with decreased levels when the output coefficients are decreased. Sensitivity analysis can better identify key pollution control areas. The areas sensitive to changes in farmers’ behavior are mainly the Hechuan District, Nanchuan District, Qijiang District, Jiangjin District, and Bishan District. This study provides data and decision-making support for rural green development and water environment improvement.

A stochastic simulation-based chance-constrained programming model for optimizing watershed best management practices for nonpoint source pollution control under uncertainty

In this study, a stochastic simulation-based chance-constrained programming (SSCP) model is developed by integrating soil and water assessment tool (SWAT), generalized likelihood uncertainty estimation (GLUE), chance-constrained programming (CCP) and genetic algorithm (GA) for managing non-point source (NPS) pollution under uncertainty. The SSCP model improves upon conventional simulation-based optimization methods by effectively (i) reflecting the propagation of stochastic uncertainties from the SWAT to the optimization framework by the joint GLUE and CCP (GLUE-CCP) approach, and (ii) identifying the optimal implementation levels of best management practices (BMPs) under different constraint-violation risk levels. The SSCP is solved using a GA with parallel sampling technique after conversion into the corresponding deterministic version. The model is applied to determine the optimal types, sizes and locations of BMPs for NPS pollution control in the Hanjiang River basin, China. The results indicate that, under low-risk conditions, grassed waterways and filter strips should be implemented in the northern part of the basin and larger detention ponds of about 637.8 ∼ 850.4 ha should be installed in the northern and eastern parts of the basin; whereas under high-risk conditions, filter strips should be installed in the northeastern part of the basin and larger detention ponds of about 562.1 ∼ 749.5 ha should be installed in the northern and southwestern parts of the basin. Moreover, as the risk level decreases, stricter control of constraint violations leads to higher BMP implementation costs in order to mitigate the risk of excessive NPS pollution loads. Thus, the proposed model provides valuable insights into the selection of BMP placement schemes at various risk levels, facilitating the reduction of NPS pollution at the outlet of the Hanjiang River basin to acceptable levels while considering the tradeoff between system cost and risk.

Simulation and Application of Water Environment in Highly Urbanized Areas: A Case Study in Taihu Lake Basin

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.

Agricultural nonpoint source pollutant loads into water bodies in a typical basin in the middle reach of the Yangtze River

Phosphorus and nitrogen pollution from agricultural nonpoint sources heavily burden the water environment, and a scientific calculating system is needed to calculate the pollutant loads under the water pollution treatment. This study established a system to calculate the coefficients of agricultural nonpoint source pollutants into water bodies in the subregion in Poyang Lake basin in the middle reach of the Yangtze River combining with multiple driving factors. Validation results showed that the errors of the typical unit were 30.58% for total phosphorus (TP), 13.43% for total nitrogen (TN) and 33.93% for ammonia nitrogen (NH3-N), respectively. The errors of the subregion were 26.92% for TP, 31.83% for TN and 29.15% for NH3-N, respectively. Besides, there were higher TP and TN loads in the east area of subregion in both units and county scales, which indicated the heavy phosphorus and nitrogen burden on water environment. In contrast, higher NH3-N loads occurred in the north area of subregion. The establishment of coefficient system for agricultural pollutants into water bodies and the pollutant loads calculation would provide enlightenment for water pollution treatment and agricultural nonpoint source pollution controlling.

Green production efficiency of China's hog breeding industry: Spatial divergence and its driving factors.

This paper analyzes the green production efficiency (GPE) and spatial divergence of the hog breeding industry, with the aim of providing a foundation for the rational layout of hog breeding and promoting the industry's high-quality development. The paper uses the SBM model to estimate GPE in 29 provinces, cities, and districts of China from 2006 to 2019. Furthermore, it analyzes the spatial divergence of GPE and its driving factors using divergence indexes and the Geodetector. The results show that China's GPE of the hog breeding industry increased from 0.409 to 0.496 between 2006 and 2019. The highest efficiency occurred during the I-period, while the lowest efficiency was observed during the II-period. The highest efficiency was in the key development region, and the lowest efficiency was in the potential growth region. The spatial divergence of GPE in the hog breeding industry expanded, with labor input, non-point source pollution, resource endowment, and environmental load bearing being the main driving factors for the expansion in each period. The potential growth region had the largest spatial divergence, mainly affected by resource endowment. In contrast, the constrained development region had the smallest spatial divergence, mainly affected by resource endowment and pollutant emissions. The spatial divergence of moderate and key development regions was considerable, mainly affected by environmental investment, environmental load bearing, and pollutant emissions. Therefore, the key to improving the GPE of the hog breeding industry is to promote the adoption of advanced technology, such as labor-saving, material-saving, and emission reduction technologies. Moreover, several actions should be taken to reduce the spatial divergence among different regions, such as integrated breeding, clean standards, large-scale breeding, and high-end boutique.

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.

Quantification and variation characteristics of baseflow nonpoint source pollution in Yiluo River Basin, China

Baseflow is an important component of runoff that is one of the essential mediums for groundwater pollution to migrate to runoff. Effective water-quality management requires full understanding of the nonpoint source (NPS) pollutants pathways. However, the contributions of baseflow and baseflow NPS pollutants at multiple scales are still challenging. In this study, the baseflow was quantified and compared by the nonlinear reservoir method, the digital filtering method and the Soil and water Assessment Tool (SWAT) in the Yiluo River, and SWAT model was used to simulate and quantify the NPS and baseflow NPS pollution. Then the scaling effect of baseflow NPS pollution was studied. The results indicated that the average annual baseflow of the basin outlet section and baseflow index of the whole basin was 38.07 m3/s and 0.58 during the studied years (2001–2017). The multiyear average baseflow pollution load for TN and TP was 4216.18 t/a and 293.33 t/a. The spatial distribution of the NPS pollution and baseflow NPS pollution showed higher in the northeast and lower in the southwest, and the baseflow NPS pollution contribution rate in most basins was more than 50 %. The spatial scale effects of NPS pollution load became more obvious with the increase of basin area, and the contribution of baseflow NPS pollution increased. The precipitation and temperature played important roles in baseflow pollution, especially baseflow TN load.

An Overview of Non-Point Source Pollution Modeling: Current Status and Future Prospect

Non-point source (NPS) pollution control is an increasingly important topic in aquatic environment protection due to its significant adverse effect on water quality. Characterizing NPS pollution loads is crucial for preparing BMPs to improve water quality and protect the aquatic ecosystem. Modeling tools are commonly used for simulating NPS pollution in watersheds; however, the modeling process contains uncertainties and complications, which makes the prediction of NPS pollution loads challenging and complicated. To deal with this issue, significant progress has been made to address NPS pollution modeling problems in the past few decades. The current study reviews different approaches being used for NPS pollution modeling. In this context, the main methods in NPS modeling are described and classified into three categories. 1. Empirical models, 2. Physically based models, and 3. Simulation based optimization models. The present study contributes to fulfilling the gaps in the classification of NPS pollution modeling approaches and highlights the advantages and drawbacks of each approach in order to set a standard for choosing a proper simulation tool for estimating NPS pollution loads based on the limitations and requirements of the understudy circumstance

Study on the planning and influential factors of the safe width of riparian buffer zones in the upper and middle reaches of the Ziwu River, China.

In this study, we employed the random forest model to identify the riparian buffer zone in the upper and middle reaches of the Ziwu River, used the Soil and Water Assessment Tool (SWAT) to simulate and calculate the nonpoint source pollution load in the riparian buffer zone, and used empirical formulas to estimate the pollutant concentration when surface runoff passes the edge of the riparian buffer zone. Moreover, through correlation analysis, we identified the main factors that affect the safe width of the riparian buffer zone. By combining these factors with the characteristic parameters of the riparian buffer zone and the water quality demand, we analyzed and calculated the safe width of the riparian buffer zone. Our findings are as follows: ① the simulated values of the SWAT model were highly consistent with the measured values. Specifically, the calibration and verification results of the hydrological station achieved Ens ≥ 0.65, RE < ± 15%, and R2 ≥ 0.85, while the overall total nitrogen and total phosphorus loads achieved Ens ≥ 0.65, RE < ± 15%, and R2 > 0.65. ② We found that the total nitrogen (TN) and total phosphorus (TP) loads in the riparian buffer zone gradually increased from upstream to downstream. Among these loads, the normal season had the largest TN and TP concentrations reaching the edge of the riparian buffer zone, while the dry season had the minimum concentrations. ③ The factors affecting the safe width of the riparian buffer zone included the connectivity, slope of the buffer zone, cultivated land area, and regional population density. For the effective protection of water quality, it is recommended that the upstream, midstream, and downstream buffer zones be at least 77.9m, 33.37m, and 60.25m wide, respectively.

Pollutant Burden on Pollution Sources in the Wai Batu Merah Watershed, Sirimau District, Ambon City

This study aims to identify sources of pollution and determine the magnitude of the potential pollution load from pollutant sources in the Wai Batu Merah watershed, Sirimau District, Ambon City. The method for identifying sources of pollution is carried out by using saturated or census sampling methods, calculating pollutant loads using direct methods for point source pollutant sources and indirect methods for non-point sources . The direct calculation method uses wastewater discharge data and the results of wastewater quality analysis results from measurements directly at the point source pollutant wastewater treatment plant (WWTP). The wastewater sampling technique uses the grab sampling method. While the indirect method uses effluent factors and supporting data from non-point source pollution sources that have been identified in the Wai Batu Merah watershed. The results showed that the pollutant sources found in the Wai Batu Merah watershed were point sources originating from hotel and health facility activities and non-point sources originating from domestic activities from residential areas, agricultural and livestock businesses, non-point source land (forest and open land), micro, small and medium enterprises (MSMEs), small scale industries and waste. The dominant pollutant source in the Wai Batu Merah watershed comes from domestic non-point sources. The highest point source pollution loads for BOD, COD and TSS parameters in the Wai Batu Merah watershed came from hotel activities in segment 6 with the contribution of each parameter of 17.82 kg/day, 23.82 kg/day and 0.029 kg/day. Meanwhile, the highest non-point source pollution load for BOD, COD and TSS parameters came from non-point source waste in segment 6 with the contribution of each parameter of 2825.3 kg/day, 3884.8 kg/day and 2684.03 kg/day.

Analysis of Spatial Distribution Characteristics of Non-Point Source Pollution in Liaoning Province

As a major agricultural province, understanding the spatial distribution characteristics of non-point source pollution in Liaoning Province plays a crucial role in preventing and controlling non-point source pollution. This paper uses the pollution discharge coefficient method to calculate the TN and TP load of non-point source pollution in each city of Liaoning Province in 2019. The results indicate that: (1) In 2019, the emissions of TN and TP from non-point source pollution in Liaoning Province were 245.6 thousand t and 23.2 thousand t, respectively. Livestock and poultry farming is the main source of TN and TP pollution. (2) The total amount of standard pollution load was 361.269 billion m3. TN is the main source of non-point source pollution, with TN and TP accounting for 67.96% and 32.04%, respectively. Overall, pollution in the central and western regions is more serious than in the eastern regions, while pollution in the plain areas is worse than in the mountainous and hilly areas. Chaoyang should be a key focus in terms of the prevention and control of non-point source pollution, and the abundant total water resources play a crucial role in reducing pollution levels.

Nonpoint Source Pollution in Plot-Scale and Small Watershed Studies under Natural Rainfall: An Analysis of the China Experience

Agricultural nonpoint source (NPS) pollution is still the main factor that affects the quality of rivers, lakes, and reservoirs. Starting from the study of the mechanism of NPS, taking the Yangliu small watershed in the Shaanxi section of the Hanjiang River Basin in China as an example, and based on the combination of measured data and models, this paper focused on the analysis of the characteristics of NPS between the runoff plot and small watershed. The results showed that with the rainfall and surface runoff, the nutrient concentration increased first and then decreased, and the highest occurred in the first half of the whole rainfall process. Rainfall, maximum rainfall intensity at 60 min (I60), runoff, and suspended sediment (SS) were all related to nutrient diversion loss. However, the correlation among rainfall, I60, and runoff and the content of various forms of nitrogen and phosphorus were significantly higher than that of SS. Crop interplanting and terrace planting could play a significant role in reducing sediment and nutrient loss. For the analysis of NPS pollution in small watersheds, the time-variant gain model (TVGM) was used to simulate the missing flow in some months of the basin during the flood season. The average concentration method was used to calculate the NPS pollution load in flood season. It was found that total nitrogen (TN) and total phosphorus (TP) accounted for more than 92% and 69%, respectively. This study is expected to provide scientific basis for NPS pollution control in areas both regionally and worldwide.

Assessing agricultural non-point source pollution loads in typical basins of upper Yellow River by incorporating critical impacting factors

Phosphorus and nitrogen pollutions from agricultural non-point source put heavy burden on water environment. Total nitrogen (TN), total phosphorus (TP) and ammonia nitrogen (NH3-N) are important pollutants in the study of agricultural non-point source pollution. This study presents a technical system that accurately calculated the coefficient of pollutants (TN, NH3-N and TP) entering water to grasp the situation of agricultural non-point source pollution. The system used for coefficient calculation is based on a main framework of driving factor-transmission factor-infiltration factor-interception factor, incorporating critical impacting factors including rainfall, topography, surface runoff, underground runoff, and interception factors. The coefficient was calculated by selecting typical units and extrapolated to the main stream area of the upper reaches of the Yellow River. Our study provides reference and practical basis for the development and application of coefficient model. It provides enlightenment for the calculation of agricultural non-point source pollutants.

The response of non-point source pollution to land use change and risk assessment based on model simulation and grey water footprint theory in an agricultural river basin of Yangtze River, China

Non-point source (NPS) pollution has gradually become the main source of water environmental pollution with the rapid economic development during the recent decades, especially for the economically developed Yangtze River Basin of China. Due to rapid urbanization, the pressure of the water environment in the Poyang Lake basin (PYLB) has been increasing. In this study, the spatial and temporal variations of NPS pollution loads including total nitrogen (TN) and total phosphorus (TP) in the PYLB during the period 2003–2012 were firstly investigated by using the SWAT; then the changes in NPS pollution loads under different land use types were identified by using the SWAT, land use transition matrix, statistical analysis and scenario analysis methods; finally, the NPS pollution risk assessment were achieved by means of the grey water footprint theory. The results showed that the NPS pollution loads in the PYLB were concentrated from April to June with a large inter-annual variability. The Gan River basin contributed the largest proportion of pollutants entering into the Poyang lake while the Xiu River basin produced the smallest pollution loads. Under the background of the policy of “Grain for Green Project” since 2002, the areas of cultivated land, grassland and bare land decreased during the period 2000–2010, while those of forest land and settlement increased. As the main source of NPS pollution, the area of cultivated land has decreased, while the unit load intensity under cultivated land has significantly increased. By calculating the annual GWF of TN and TP loads and their corresponding WPL, which all showed an upward trend. The results obtained in this study have practical significance for reducing the NPS pollution loads in the PYLB and controlling the environmental pollution in the Yangtze River.

Spatial and temporal distribution characteristics of typical pollution loads based on SWAT model across Tuojiang River watershed located in Sichuan Province, Southwest of China.

Tuojiang River watershed is an economically developed and densely populated area in Sichuan Province (southwest of China), which is also an important tributary of the Yangtze River. Nitrogen (N) and phosphorus (P) are the main pollutants affecting water quality, but there is still lack of study on the spatial and temporal distribution characteristics of these two pollutants. In this study, the typical non-point source pollution loads in the Tuojiang River watershed are simulated by Soil and Water Assessment Tool (SWAT) model, and the spatial autocorrelation method is used to reveal the spatial and temporal distribution characteristics of the pollution loads from the annual average and water periods. Combined with redundancy analysis (RDA) and geographically weighted regression (GWR) analysis, the main driving factors affecting the typical non-point source pollution loads in the Tuojiang River watershed are discussed from the global and local perspectives. The results show that (1) from different water periods, the pollution loads of total nitrogen (TN) and total phosphorus (TP) in three water periods show obviously different, is the highest in the abundant water period, with 323.4kg/ha and 47.9kg/ha, followed by the normal water period, with 95.7kg/ha and 14.1kg/ha, and the lowest in the dry water period, with 28.4kg/ha and 4.2kg/ha. The annual average value of TN pollution load is higher than that of TP, with 447.5kg/ha and 66.1kg/ha, respectively; (2) the TN and TP pollution loads are stable on the whole, and the overall level in the middle reaches is higher. The pollution loads of Shifang City and Mianzhu City are higher in all three water periods. (3) Elevation and slope are two main driving factors affecting the TN and TP pollution loads in the Tuojiang River watershed. Therefore, the visualization and quantification of temporal and spatial distribution characteristics of typical non-point source pollution loads in the Tuojiang River watershed are helpful to provide the basis for scientific prevention and control of pollution in the Tuojiang River watershed and are of great significance to promote the sustainable, coordinated, and healthy development of water environment and economy in the watershed.

Role of Landscape and Land-Use Transformation on Nonpoint Source Pollution and Runoff Distribution in the Dongsheng Basin, China

Non-point source pollution (NSP) and runoff intensities and distribution are primarily affected by landscape structure and composition. Multiple causalities hinder our ability to determine significant variables that influence NSP. Therefore, we developed an approach that integrates the Soil and Water Assessment Tool (SWAT), random forest regression model, redundancy analysis, and correlation coefficient to assess the role of landscape structure on runoff and NSP in the Dongsheng basin. We used R to calculate landscape metrics and the SWAT to simulate NSP loads from 1990 to 2019. redundancy analysis (RDA), random forest, and Pearson correlation were used to analyze the relationships among landscape metrics and NSP variables. The largest patch index (LPI) shows a significant negative correlation with NSP, with an R2 of −0.58 for TP and TN and −0.62 for sediment load. The findings indicate that landscapes with larger patch sizes, a high number of patches, and aggregation of patches largely influence pollution distribution. Overall, the results suggest that the role of landscape patterns on NSP outweighs that of runoff. Moreover, the findings infer that the aggregation and connectivity of forest patches contribute to the decline in NSP load and vice versa for cropland cover. Thus, for sustainable watershed management, it is crucial to encourage unfragmented landscapes, especially pollutant-intercepting landcovers such as forests.

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.

Influence of concrete material of runoff collection containers on monitoring of nitrogen and phosphorus pollutants.

The accurate monitoring of N and P surface runoff losses from farmland is crucial to control agricultural nonpoint source pollution. A pond constructed with concrete material (CM) is a common collection container used during field experiments in China, but the adsorption characteristics of concrete may cause a considerable underestimation of surface runoff losses from farmland. To characterize any neglected error caused by the collection container material, a laboratory experiment was conducted comparing the N and P contents of runoff samples collected from CM and plastic material (PM) containers. The results indicated that CM containers significantly lowered N and P sample contents compared with PM containers, which was attributed to the adsorption capacity of pollutants by CM containers. This was confirmed by scanning electron microscopy (SEM) images of particles retained in CM containers. In an attempt to alleviate this error, three common water-repellent materials were applied to CM containers that significantly limited the pollutant adsorption of CM containers. Moreover, it was shown that there was no significant difference between the calculated concentration of runoff losses and the total amount of pollutants. To calibrate the observational error from CM containers, stepwise multiple regression models of different forms of N and P pollutants were developed. The results of this study suggest that treating CM containers with water repellent is an effective measure for improving the accuracy of new-built monitor points of agricultural nonpoint source pollutants. In addition, the calibration of observational error from CM containers and delayed sampling is essential to estimate agricultural nonpoint source pollution load via the surface runoff from farmland based on data from monitor points.