Agricultural Non-Point Source Pollutant Loading Research Articles

Study on Non-Point Source Pollution Prevention and Control System in Nansi Lake Basin Based on System Dynamics Approach

Agriculture, as an important activity on which human beings depend for their livelihood, brings serious environmental problems while meeting the needs of human survival, among which agricultural non-point source (NPS) pollution is one of the most urgent environmental problems. This study quantitatively assessed the loading characteristics spatial and temporal evolution patterns of two agricultural NPS pollutants, chemical oxygen demand (COD) and ammonia nitrogen (NH3-N), from 2010 to 2020 in the Nansi Lake Basin as an example, and constructed a system dynamics (SD) simulation model to simulate and analyze agricultural NPS pollution under different development and treatment scenarios, based on an investigation of the regional prevention and control strategy of agricultural NPS pollution and the technological system. The results show that the current status of agricultural NPS pollution load in the Nansi Lake Basin is poor, and the level of pollution load is high, showing obvious geographical differences. In terms of temporal changes, the pollution loads of the two pollutants showed a decreasing trend from 2010 to 2020, among which the pollution load of NH3-N showed the largest change. Spatially, the spatial distribution of each type of pollutant has some similarities, with smaller pollution loads in Jining and Zaozhuang and relatively larger pollution loads in Heze and Ningyang. The main source of COD pollution in the Nansi Lake Basin is rural life, with an emission proportion of 52.85%, and the main sources of NH3-N pollution from agricultural NPS pollution in the area are rural life and livestock and poultry farming, with emission proportions of 47.55% and 35.36%, respectively. Under the status quo continuum scenario, the pollution load values for COD are consistently higher than those for NH3-N, so the relative impact of COD is greater. In this study, the principles and methods of SD in system science are adopted to deal with the agricultural NPS pollution of Nansi Lake Basin, and the evolution of its behavioral characteristics are simulated, forecasted, and predicted, and policy experiments are conducted, with a view to providing references for the prevention and control of agricultural NPS pollution in Nansi Lake Basin and further research.

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.

Identifying the Spatial Risk Patterns of Agricultural Non-Point Source Pollution in a Basin of the Upper Yangtze River

Agricultural non-point source pollution (ANPSP) is a primary cause of watershed water quality deterioration, and over 50% of NPS pollutants are estimated to come from ANPSP. Based on the “source-sink” theory and minimum cumulative resistance (MCR) model, ANPSP source and key resistance factors were integrated to identify areas at risk of ANPSP production and transportation into the waters of the upper Yangtze River basin. The results showed a spatial difference in the agricultural pollution sources of the basin, which were determined using both ANPSP loads and land-use types. Soil type, rainfall erosivity, and elevation were the three most important resistance factors in pollution transportation, weighting 0.373, 0.241, and 0.147, respectively. There was a spatial effect on the comprehensive resistance of ANPSP transportation, which was lower in mountainous terrain at the central basin. On the coupling of source and resistance processes, regions at serious risk of ANPSP were found to be concentrated in the southwest area. Areas at very high risk of NH3-N and TP pollution accounted for 37.6% and 38.1%, respectively, in the total town/street area. The spatial risk patterns identified in this study could be used for decision making and policy regulation of ANPSP and for aquatic environmental protection.

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.

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.

Estimation of Agricultural Non-point Source TN and TP Export Coefficients Based on Soil Loss

Taking the Yellow River Delta as a typical research area, we constructed a coastal agricultural TN and TP non-point source pollution estimating model by analyzing the relationship between the surface soil pollutant loss risks and the monitored pollutant flux into the sea. On this basis, TN and TP non-point source export coefficients of paddy fields, irrigated land, and dry land were calculated, and the verification showed that the estimated export coefficients were acceptable. In the study area, the TN and TP export coefficients into the sea of arable land were 18.33 kg·(hm2·a)-1 and 1.02 kg·(hm2·a)-1, respectively. The agricultural non-point source pollution loads of arable land were relatively high in summer. The sub-basins with larger agricultural non-point source pollution loads were mainly located in the control areas of the Zhimai River, Guangli River, and Xiaodao River. The administrative regions with larger total agricultural TN and TP loads were mainly in the northern Huanghekou Town and Yong'an Town, and areas with larger loads per unit area were in the southwest. Therefore, it is necessary to pay more attention to the temporal effects of agricultural non-point source pollution, simultaneously coordinate the social and economic development, and formulate comprehensive agricultural non-point source pollution prevention and control strategies from the perspective of sub-basins and administrative units. This will allow us to improve the offshore pollution status from the perspective of land and sea coordination.

Evaluation of management practices on agricultural nonpoint source pollution discharges into the rivers under climate change effects

In recent years, agricultural non-point source pollution (ANPSP) has become the biggest threat to Aras River water quality by completing the Mughan irrigation and drainage network. Nutrient pollutants, including nitrate and phosphate, released into the river through drains have created a range of obstacles for locals living around the river. Agricultural activities are generally considered the largest source of non-point pollution. They have no complex and uniform impact along the river. Thus, the spatial distribution of ANPS and highly polluted areas should be identified to manage watershed management. This study proposes a simple framework for identifying pollutant-sensitive areas along the river and management strategies to improve water quality. To this aim, the main factors affecting ANPSP were identified, and the effectiveness of the scenarios selected to comply with water quality regulations for drinking and environment during 1993–2007 were simulated. Based on the sensitivity analysis, land use and fertilizer are the main factors affecting river ANPSP. Thus, their changes were modeled in different scenarios. Based on the results, the ANPSP load was higher downstream. The agricultural lands in region 3 were considered the main source of pollution. Comparing the management scenarios showed that the amount of nitrate and phosphate leaching into the river decreased to 18.1 and 8.35 %, respectively, by reducing the consumption of urea and phosphate fertilizers by 50 %. The results help watershed managers implement eco-friendly land use and nutrient management programs at specific locations during specific periods to control ANPSP along the rivers.

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.

Understanding the nonpoint source pollution loads' spatiotemporal dynamic response to intensive land use in rural China

The extensive use of land resources and environmental pollution in rural areas are two major problems prevalent in China and even the world. It is unknown whether improving the degree of intensive use of rural land can reduce environmental pollution; whether environmental pollution will be promoted or inhibited still lacks in-depth discussion. This paper first provides a theoretical analysis of the generation process of nonpoint source pollution loads (NPSP) in rural land use (RLU) and the mechanism and path of intensive rural land use (IRLU) to reduce agricultural nonpoint source pollution loads (ANPSP). Then, it takes 31 provinces in China from 1978 to 2019 as the research object to examine the temporal and spatial evolution features of IRLU and ANPSP. Furthermore, the paper uses the decoupling model and the Environmental Kuznets curve (EKC) model to test the linear and nonlinear relationship between the two. The research shows that the degree of IRLU in China decreased from 0.54 in 1978 to 0.27 in 2006, and then continuously increased to 0.56 in 2019. Moreover, the ANPSP continued to increase from 1955.14 t in 1978–3622.74 t in 2019. The decoupling relationship between the degree of IRLU and environmental pollution experienced the evolution process of “negative decoupling-decoupling”, and the EKC had an “inverted N-shaped” characteristic. Overall, China shows that the IRLU helps to reduce ANPSP. At the same time, it was also found that there is obvious heterogeneity among the 31 provinces used in this research in China. Among them, the degree of intensive land use (ILU) in the principal grain-producing regions tends to be better and stable, while other areas show fluctuating changes. The ANPSP in economically developed areas gradually decreases, while that in underdeveloped areas continues to increase. More than 80% of the provinces in China show a trend of IRLU to advance the reduction of ANPSP, but there has also been an increase in the over-intensification of RLU in some major grain-producing areas. The research concludes that there is an inevitable relationship between RLU and ANPSP. Appropriately increasing ILU has a positive effect on decreasing ANPSP.

Assessment and analysis of agricultural non-point source pollution loads in China: 1978–2017

China's successful agriculture development has resulted in public concerned environmental problems. However, continuous and detailed data about Chinese agricultural non-point source pollution (ANPSP) loads are lacking. To assess and analyze Chinese ANPSP loads from 1978 to 2017, an inventory analysis was performed, and a socioeconomic and spatiotemporal analysis in the scale of provinces was conducted. The results showed that the pollution loads of chemical oxygen demand (COD), total nitrogen (TN) and total phosphorus (TP) increased by 91.0%, 196.2% and 244.1%, respectively, and their variation underwent a free development stage, reform promotion stage, market regulation stage and policy incentive stage. The results of the pollution source analysis showed that over the past 40 years, the total percent contribution to COD by livestock and poultry breeding (LPB) and rural household waste (RHW) accounted for 83.1%–96.6%, the total percent contribution to TN by mineral fertilizers (MF) and LPB accounted for 72.3%–80.8%, and the total percent contribution to TP by LPB, RHW and MF accounted for 69.1%–88.6%. In addition, Shandong, Guangdong, Sichuan, and Henan were the top producers of ANPSP loads, and their COD, TN, and TP loads accounted for approximately 32%, 30%, and 35% of the national totals, respectively. The discharge intensity of COD, TN and TP decreased by 79.2%, 67.8%, and 62.6%, respectively. The discharge intensity exhibited a phasic feature that aligned with the national economic plan in the temporal scale and was closely related to the agricultural conditions in the spatial scale.

Analysis of the Characteristics of Nitrogen and Phosphorus Emissions from Agricultural Non-Point Sources Pollution and Pollution Risk in Tianjin City, China

In order to understand the current status of agricultural non-point source pollution in Tianjin and figure out the main pollution source and areas, the evaluation and spatial distribution of agricultural non-point source pollution were analyzed. The pollution discharge coefficient method was used to estimate the agricultural non-point source pollution in Tianjin. The spatial distribution pattern of agricultural non-point source pollution load was analyzed by ArcGIS software, the pollution evaluation and sources analysis were carried out by equivalent pollution load method. The results show that the pollution load of TN and TP in Tianjin in 2017 was 11760.7 and 871.86 tonnes per year respectively, and the equivalent pollution loads were 11760.70 and 8718.68 m3 separately. Among the districts, the Baodi District, Wuqing District and Jinghai District have higher pollution loads, which are the key control areas. The spatial analysis showed the similar distribution characteristics of pollution load and intensity, which was higher in the middle and lower in the north and south in Tianjin. It is necessary to separately develop targeted pollution prevention measures to strengthen management and control.

Effect of irrigation amount and fertilization on agriculture non-point source pollution in the paddy field

It is the key point to reveal the effect of irrigation water and fertilization conditions on the agriculture non-point pollution in the paddy field. In this study, the estimation model of agricultural non-point source pollution loads at field scale was established on the basis of agricultural drainage irrigation model and combined with pollutant concentration predication model. Based on the estimation model of agricultural non-point source pollution in the field and experimental data, the load of agricultural non-point source pollution in different irrigate amount and fertilization schedule in paddy field was calculated. The results showed that the variation of field drainage varies greatly under different irrigation conditions, and there is an "inflection point" between the irrigation water amount and field drainage amount. The non-point pollution load increased with the increase of irrigation water and showed a significant power correlation. Under the different irrigation condition, the increase amplitude of non-point pollution load with the increase of irrigation water was different. When the irrigation water is smaller, the non-point pollution load increase relatively less, and when the irrigation water increased to inflection point, the non-point pollution load will increase considerably. In addition, there was a positive correlation between the fertilization and non-point pollution load. The non-point pollution load had obvious difference in different fertilization schedule even with same fertilization level, in which the fertilizer pollution load increased the most in the period of turning green to tillering. The results provide some basis for the field control and management of agricultural non-point source pollution.

Establishment and application of the estimation model for pollutant concentrfation in agriculture drain

It is the key point of quantitative research on agricultural non-point source pollution load, the estimation of pollutant concentration in agricultural drain. In the guidance of uncertainty theory, the synthesis of fertilization and irrigation is used as an impulse input to the farmland, meanwhile, the pollutant concentration in agricultural drain is looked as the response process corresponding to the impulse input. The migration and transformation of pollutant in soil is expressed by Inverse Gaussian Probability Density Function. The law of pollutants migration and transformation in soil at crop different growth periods is reflected by adjusting parameters of Inverse Gaussian Distribution. Based on above, the estimation model for pollutant concentration in agricultural drain at field scale was constructed. Taking the of Qing Tong Xia Irrigation District in Ningxia as an example, the concentration of nitrate nitrogen and total phosphorus in agricultural drain was simulated by this model. The results show that the simulated results accorded with measured data approximately and Nash-Sutcliffe coefficients were 0.972 and 0.964, respectively.

A national assessment of the effect of intensive agro-land use practices on nonpoint source pollution using emission scenarios and geo-spatial data.

China's intensive agriculture has led to a broad range of adverse impacts upon ecosystems and thereby caused environmental quality degradation. One of the fundamental problems that face land managers when dealing with agricultural nonpoint source (NPS) pollution is to quantitatively assess the NPS pollution loads from different sources at a national scale. In this study, export scenarios and geo-spatial data were used to calculate the agricultural NPS pollution loads of nutrient, pesticide, plastic film residue, and crop straw burning in China. The results provided the comprehensive and baseline knowledge of agricultural NPS pollution from China's arable farming system in 2014. First, the nitrogen (N) and phosphorus (P) emission loads to water environment were estimated to be 1.44Tg N and 0.06Tg P, respectively. East and south China showed the highest load intensities of nutrient release to aquatic system. Second, the amount of pesticide loss to water of seven pesticides that are widely used in China was estimated to be 30.04tons (active ingredient (ai)). Acetochlor was the major source of pesticide loss to water, contributing 77.65% to the total loss. The environmental impacts of pesticide usage in east and south China were higher than other parts. Third, 19.75% of the plastic film application resided in arable soils. It contributed a lot to soil phthalate ester (PAE) contamination. Fourth, 14.11% of straw produce were burnt in situ, most occurring in May to July (post-winter wheat harvest) in North China Plain and October to November (post-rice harvest days) in southeast China. All the above agricultural NPS pollution loadings were unevenly distributed across China. The spatial correlations between pollution loads at land unit scale were also estimated. Rising labor cost in rural China might be a possible explanation for the general positive correlations of the NPS pollution loads. It also indicated a co-occurred higher NPS pollution loads and a higher human exposure risk in eastern regions. Results from this research might provide full-scale information on the status and spatial variation of various agricultural NPS pollution loads for policy makers to control the NPS pollution in China.

Characterization and Placement of Wetlands for Integrated Conservation Practice Planning

Constructed wetlands have been recognized as an efficient and cost-effective conservation practice to protect water quality through reducing the transport of sediments and nutrients from upstream croplands to downstream water bodies. The challenge resides in targeting the strategic location of wetlands within agricultural watersheds to maximize the reduction in nutrient loads while minimizing their impact on crop production. Furthermore, agricultural watersheds involve complex interrelated processes requiring a systems approach to evaluate the inherent relationships between wetlands and multiple sediment/nutrient sources (sheet, rill, ephemeral gully, channels) and other conservation practices (filter strips). This study describes new capabilities of the USDA‘s Annualized Agricultural Non-Point Source pollutant loading model, AnnAGNPS. A developed AnnAGNPS GIS-based wetland component, AgWet, is introduced to identify potential sites and characterize individual artificial or natural wetlands at a watershed scale. AgWet provides a simplified, semi-automated, and spatially distributed approach to quantitatively evaluate wetlands as potential conservation management alternatives. AgWet is integrated with other AnnAGNPS components providing seamless capabilities of estimating the potential sediment/nutrient reduction of individual wetlands. This technology provides conservationists the capability for improved management of watershed systems and support for nutrient credit trading programs.

Cumulative effect of land use and cover changes in Naoli River basin in Sanjiang Plain on agricultural nonpoint source pollution load

Unreasonable land use pattern is the one main driving factor of nonpoint source pollution (NPSP). Based on effect of land use change (reclaiming wetland into cultivated land) on NPSP, this paper analyzed the contents of main forms of nitrogen (N) and phosphorus (P) as well as key climate parameters in Naoli River Basin in Sanjiang Plain through field monitoring, sampling and indoor test. N and P are major non-point source pollutants. The spatial–temporal variation law of non-point pollution factors under different land use patterns and durations was analyzed. The cumulative effect of long-term land use and cover changes on non-point source pollution was simulated quantitatively by ArcSWAT model. The indoor test reported that (1) paddy field has the higher soil N and P contents, followed by dry land, wetland and forest land, successively; (2) in the whole river basin, mid-downstream shows the highest N and P nutrients in water, followed by midstream, downstream, mid-upstream and upstream, successively. N and P distributions in soil are similar to those in water. According to the quantitative simulation of NPSP in the Naoli River Basin, NPSP mainly concentrates on the two sides of the main stream. Compared to forest land, paddy field and dry land contribute more to NPSP. Cultivated land occupies 58 % of the whole basin area, which contributes at least 89.6 and 91.7 % of TP and TN. All of these areas were reclaimed from wetland, indicating that area and spatial position changes of wetland are the main causes of intensifying NPSP in the Naoli River Basin. The cumulative effect analysis revealed that since TN and TP in per unit of cultivated land area increase continuously, land use changes exert cumulative effect on NPSP. In other words, reclamation of wetland will accelerate increase of TP and TN loads.

Environmental Kuznets Curve Analysis of the Economic Development and Nonpoint Source Pollution in the Ningxia Yellow River Irrigation Districts in China

This study applies the environmental Kuznets curve to test the relationship between the regional economic growth and the different types of agricultural nonpoint source pollution loads in the Ningxia Yellow River irrigation area by using the Johnes export coefficient method. Results show that the pollution load generated by crop cultivation and livestock-breeding industries in the Ningxia Yellow River irrigation area shows an inverted U-shaped feature; however, this feature is absent in living-sewage pollution load. Crop pollution has shown a decreasing trend since 1997 because of the increased per capita income of farmers. Livestock-breeding pollution load reached its turning point when the per capita income of farmers reached 8386.74 RMB. Therefore, an increase in the per capita income of farmers corresponds to an increase in the livestock-breeding pollution load in the Ningxia Yellow River irrigation area.

Assessment of Runoff and Sediment Yields Using the AnnAGNPS Model in a Three-Gorge Watershed of China

Soil erosion has been recognized as one of the major threats to our environment and water quality worldwide, especially in China. To mitigate nonpoint source water quality problems caused by soil erosion, best management practices (BMPs) and/or conservation programs have been adopted. Watershed models, such as the Annualized Agricultural Non-Point Source Pollutant Loading model (AnnAGNPS), have been developed to aid in the evaluation of watershed response to watershed management practices. The model has been applied worldwide and proven to be a very effective tool in identifying the critical areas which had serious erosion, and in aiding in decision-making processes for adopting BMPs and/or conservation programs so that cost/benefit can be maximized and non-point source pollution control can be achieved in the most efficient way. The main goal of this study was to assess the characteristics of soil erosion, sediment and sediment delivery of a watershed so that effective conservation measures can be implemented. To achieve the overall objective of this study, all necessary data for the 4,184 km2 Daning River watershed in the Three-Gorge region of the Yangtze River of China were assembled. The model was calibrated using observed monthly runoff from 1998 to 1999 (Nash-Sutcliffe coefficient of efficiency of 0.94 and R2 of 0.94) and validated using the observed monthly runoff from 2003 to 2005 (Nash-Sutcliffe coefficient of efficiency of 0.93 and R2 of 0.93). Additionally, the model was validated using annual average sediment of 2000–2002 (relative error of −0.34) and 2003–2004 (relative error of 0.18) at Wuxi station. Post validation simulation showed that approximately 48% of the watershed was under the soil loss tolerance released by the Ministry of Water Resources of China (500 t·km−2·y−1). However, 8% of the watershed had soil erosion of exceeding 5,000 t·km−2·y−1. Sloping areas and low coverage areas are the main source of soil loss in the watershed.

Agricultural non-point source pollution load intensity of the paddy field in different water and fertilization conditions

Agricultural non-point source pollution load intensity of the paddy field in different water and fertilization conditions