Assessment Of Non-point Source Pollution Research Articles

Risk Assessment of Non-Point Source Pollution Based on the Minimum Cumulative Resistance Model: A Case Study of Shenyang, China

Urban non-point source (NPS) pollution is an important risk factor that leads to the deterioration of urban water quality, affects human health, and destroys the ecological balance of the water environment. Reasonable risk prevention and control of urban NPS pollution are conducive to reducing the cost of pollution management. Therefore, based on the theory of “source–sink” in landscape ecology, combined with the minimum cumulative resistance (MCR) model, this study considered the influence of geographic-environment factors in Shenyang’s built-up area on pollutants in the process of entering the water body under the action of surface runoff, and evaluated its risk. The results indicated that the highest pollution loads are generated by road surfaces. High-density residential zones and industrial zones are the main sources of urban NPS pollution. Impervious surface ratios and patch density were the dominant environmental factors affecting pollutant transport, with contributions of 56% and 40%, respectively. The minimum cumulative resistance to urban NPS pollution transport is significantly and positively correlated with the distance from water bodies and roads. Higher risk areas are mainly concentrated in the center of built-up areas and roads near the Hun River. Green spaces, business zones, public service zones, development zones, and educational zones demonstrate the highest average risk index values, exceeding 29. In contrast, preservation zones showed the lowest risk index (7.3). Compared with the traditional risk index method, the method proposed in this study could accurately estimate the risk of urban NPS pollution and provide a new reference for risk assessments of urban NPS pollution.

An Imputation Method for Simulating 3D Well Screen Locations from Limited Regional Well Log Data.

In groundwater modeling studies, accurate spatial and intensity identification of water sources and sinks is of critical importance. Precise construction data about wells (water sinks) are particularly difficult to obtain. The collection of well log data is expensive and laborious, and government records of historic well log data are often imprecise and incomplete with respect to the precise location or pumping rate. In many groundwater modeling studies, such as groundwater quality assessments, a precise representation of the horizontal and vertical distribution of well screens is required to accurately estimate contaminant breakthrough curves. The number of wells under consideration may be very large, for example, in the assessment of nonpoint source pollution. In this paper, we propose an imputation framework that allows for proper reconstruction of missing well data. Our approach exploits available information and tolerates data gaps and imprecisions. We demonstrate the value of this method for a subregion of the Central Valley aquifer (California, USA). We show that our framework imputes missing values that preserve statistical properties of available data and that remain consistent with the known spatial distribution of well screens and pumping rates in the three-dimensional aquifer system.

Integrated Application of SWAT and L-THIA Models for Nonpoint Source Pollution Assessment in Data Scarce Regions

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

Output characteristics and driving factors of non-point source nitrogen (N) and phosphorus (P) in the Three Gorges reservoir area (TGRA) based on migration process: 1995–2020

Although physical models at present have made important achievements in the assessment of non-point source pollution (NPSP), the requirement for large volumes of data and their accuracy limit their application. Therefore, constructing a scientific evaluation model of NPS nitrogen (N) and phosphorus (P) output is of great significance for the identification of N and P sources as well as pollution prevention and control in the basin. We considered runoff, leaching and landscape interception conditions, and constructed an input-migration-output (IMO) model based on the classic export coefficient model (ECM), and identified the main driving factors of NPSP using geographical detector (GD) in Three Gorges Reservoir area (TGRA). The results showed that, compared with the traditional export coefficient model, the prediction accuracy of the improved model for total nitrogen (TN) and total phosphorus (TP) increased by 15.46 % and 20.17 % respectively, and the error rates with the measured data were 9.43 % and 10.62 %. It was found that the total input volume of TN in the TGRA had declined from 58.16 × 104 t to 48.37 × 104 t, while the TP input volume increased from 2.76 × 104 t to 4.11 × 104 t, and then decreased to 4.01 × 104 t. In addition Pengxi River, Huangjin River and the northern part of Qi River were high value areas of NPSP input and output, but the range of high value areas of migration factors has narrowed. Pig breeding, rural population and dry land area were the main driving factors of N and P export. The IMO model can effectively improve prediction accuracy, and has significant implications for the prevention and control of NPSP.

Risk Assessment of Nonpoint Source Pollution in the Huaihe River Basin

After years of treatment, the water pollution situation in the Huaihe River Basin (HRB) is still grim, and agricultural nonpoint source pollution has become the leading cause of the problem. However, agricultural nonpoint source pollution in the HRB is complicated due to the compounding effects of multiple factors. In this study, we first applied the export coefficient model to estimate the total nitrogen (TN) and total phosphorus (TP) loads used as two pollution source indicators in HRB. Then we constructed an index evaluation system of nonpoint source pollution risk by coupling the two source indicators with five additional indicators: rainfall erosion, river network distribution, soil erodibility, slope length, and land use. The primary source of TN and TP loads is fertilizer application (81.96%), followed by livestock and poultry breeding (16.3%) and rural domestic wastes (1.74%). The risk assessment results indicate that 66.43% of the HRB is at medium to high risk of nonpoint source pollution, 12.37% is at high risk, and 11.20% is at low risk. Moreover, the medium-to-high-risk areas are mainly concentrated in the Henan and Anhui provinces. In contrast, the medium-risk regions are mainly distributed along the mainstream of the Huaihe River. Finally, the observed water quality categories were used to verify our findings. The controlling areas of nonpoint source pollution in HRB are identified. This study could provide a scientific basis for effectively preventing and treating water pollution in the HRB.

Risk assessment of non-point source pollution in karst reservoirs based on ‘source–sink’ landscape theory

Abstract The quantitative identification of areas at risk for such pollution is conducive to allocating limited government funds to critical areas and the efficient and economical management of water environments. Here, the Baihua Lake watershed, an important drinking water source for Guiyang City, was taken as the study area. The location-weighted landscape contrast index (LCI) and non-point source pollution risk index (NSPRI) were developed based on the ‘source–sink’ landscape theory. The method takes into account the risk of pollution source formation and pollutant transport. A total of 348 natural sub-watersheds were used as assessment units by estimating the nitrogen and phosphorus pollution emission (absorption) potentials of different landscape types in the sub-watersheds and considering the influence of vegetation cover, distance from the reservoir, and slope in the transmission process, a quantitative assessment of Baihua Lake's pollution was carried out; the reliability of the method was verified by comparing the assessment results with measured water quality data and field surveys. The results indicate (1) 132 sub-watersheds (37.93%) dominated by source effects, mainly distributed in Yanshanhong Township, Yeya Township, and the Qinglong Subdistrict, with construction land and farmland as the main landscape types, and 216 sub-watersheds (62.07%) dominated by sink effects, mainly distributed in Zhanjie and Baihuahu Townships, with forests as the primary landscape type. (2) Additionally, 17 sub-watersheds (4.89%) show extremely high risk for non-point source pollution; these watersheds are mainly distributed in the Qinglong Subdistrict and mainly consist of urban residential areas and schools. These sub-watersheds discharge a large volume of sewage, which threatens the water quality of the upper reaches of Baihua Lake and must be managed. (3) The rivers corresponding to relatively high-risk, high-risk, and extremely high-risk sub-watersheds include the Dongmenqiao, Limu, Changchong, and Maixi Rivers.

基于“源-汇”景观的典型半城市化小流域非点源污染风险评价

PDF HTML阅读 XML下载 导出引用 引用提醒 基于“源-汇”景观的典型半城市化小流域非点源污染风险评价 DOI: 10.5846/stxb202109162610 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划课题（2016YFC0502902）；中国科学院战略性先导科技专项（A类）（XDA23030105） Risk assessment of non-point source pollution in a typical semi-urbanized small watershed based on source-sink landscape Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:小流域的水质恶化主要由点源污染和非点源污染引起，随着点源污染控制水平达到一定程度后，非点源污染已成为首要污染源。当前对非点源污染的管控仍存在难监测和难治理的问题，明晰非点源污染发生风险以及背后的原因是亟需解决的问题，因此开展非点源污染风险分析和评价具有重要意义。采用高分辨率影像解译了2010年、2015年和2020年三期厦门市后溪流域土地利用数据；基于"源-汇"景观格局方法计算研究区网格单元的网格污染指数（GPI）；结合土地利用变化数据分析非点源污染风险的时空变异，对风险区成因进行了分析。研究结果表明：当前，"汇"景观占流域面积的67.86%，非点源污染发生风险分布呈现北低南高；十年中，非点源污染风险呈现上升趋势，目前非点源污染发生风险处于低风险水平（GPI=0.27）。通过分析风险区的土地利用构成发现耕地面积的缩减（减少67.08%）和建设用地面积扩张（增加43.02%）是污染风险发生变动的主要原因。计算了风险区转移矩阵，发现非点源污染发生风险区呈现出中高风险区向低风险区和"汇"景观区域转移的趋势。基于"源-汇"景观格局理论计算的网格污染指数（GPI）可以有效地对流域非点源污染风险值进行表征，是评价和分析流域非点源污染发生风险的可用方法。 Abstract:The deterioration of water quality in small watershed is mainly caused by point source pollution and non-point source pollution. With the control level of point source pollution reaching a certain level, non-point source pollution has become the primary pollution source. At present, the control of non-point source pollution is still difficult to monitor and control. It is urgent to clarify the occurrence risk of non-point source pollution and the reasons behind it. Therefore, it is of great significance to conduct the risk analysis and evaluation of non-point source pollution. Land use data of Houxi Basin in Xiamen City in 2010, 2015 and 2020 were interpreted by high-resolution images. The grid pollution index (GPI) of grid units in the study area was calculated based on source-sink landscape pattern method. Combined with land use change data, the spatial and temporal variation of non-point source pollution risk was analyzed, and the causes of risk areas were analyzed. The results showed that sink landscape accounted for 67.86% of the Basin area, and the risk distribution of non-point source pollution was lower in the north and higher in the south. In the past decade, the risk of non-point source pollution showed an increasing trend, and the occurrence risk of non-point source pollution was at a low level (GPI=0.27). By analyzing the land use composition of the risk area, it was found that the decrease of the cultivated land area (67.08%) and the expansion of construction land area (43.02%) were the main reasons for the change of pollution risk. The risk area transfer matrix was calculated. It was found that the risk area of non-point source pollution presented a trend of transfer from the middle and high-risk area to the low-risk area and the sink landscape area. The grid pollution index (GPI) calculated based on the source-sink landscape pattern theory can effectively characterize the risk value of non-point source pollution in a watershed, and is a useful method to evaluate and analyze the occurrence risk of non-point source pollution in a watershed. 参考文献 相似文献 引证文献

Risk assessment of non-point source pollution based on landscape pattern in the Hanjiang River basin, China.

Non-point source (NPS) pollution has become a vital contaminant source affecting the water environment because of its wide distribution, hydrodynamic complexity, and difficulty in prevention and control. In this study, the identification and evaluation of NPS pollution risk based on landscape pattern were carried out in the Hanjiang River basin above Ankang hydrological section, Shaanxi province, China. Landscape distribution information was obtained through land use data, analyzing the contribution of "source-sink" landscape to NPS pollution through the location-weighted landscape contrast index. Using the NPS pollution risk index to identify and evaluate the regional NPS pollution risk considering the slope, cost distance, soil erosion, and precipitation erosion affect migration of pollutants. The results showed that (i) the pollution risk was generally high in the whole watershed, and the sub-watersheds dominated by "source" landscapes account for 74.61% of the whole basin; (ii) the high-risk areas were distributed in the central, eastern, and western regions of the river basin; the extremely high-risk areas accounted for 12.7% of the whole watershed; and the southern and northern regions were dominated by forestland and grassland with little pollution risk; (iii) "source" landscapes were mostly distributed in areas close to the river course, which had a great impact on environment, and the landscape pattern units near the water body needed to be further adjusted to reduce the influence of NPS pollution.

Risk assessment of non-point source pollution of land use system of mountainous watershed and spatially referenced regressions on watershed attributes simulation under geological environment assessment

In order to evaluate and analyze the non-point source pollution risk of mountainous watershed, the multi-criteria analysis method is used for assessment, and the Spatially Referenced Regressions on Watershed Attributes (SPARROW) model is adopted for simulation analysis. The non-point source pollution risk is evaluated based on the geological environment assessment and the relevant theories of the land use system combined with the multi-criteria analysis method. According to the evaluation results, subarea governance is implemented in the mountainous watershed. Besides, the SPARROW model is applied to simulate and analyze the total nitrogen transport in the watershed. The evaluation results reveal that the NPA value, the non-point source pollution risk assessment index, of some areas of the mountainous watershed has reached 0.9 or higher, which belong to heavily polluted areas. The pollution sources mainly come from agricultural production, and deep application of fertilizer can reduce total nitrogen emission. The simulation results show that the pH of the soil is instrumental in the total nitrogen reduction, with the total nitrogen loading coefficient being about 2.74. The research provides important reference for the control and governance of non-point source pollution in mountainous watershed.

Identifying feasible nonpoint source pollutant sampling intervals for watersheds with paddy field and urban land uses

Abstract Monitoring provides data and information necessary for water quality assessment, but often it is prohibitive, especially when frequent sampling is required. In this study, we explored feasible sampling intervals for improved efficiency of nonpoint source (NPS) pollution assessment. We compared NPS pollutant loads calculated with concentration samples collected at 1, 2, 3, 4, and 6-hour intervals for the first 24 hours of 13 storm events and investigated the effect of different sampling intervals on load estimation for three watersheds that have different land uses. When compared to load estimates made from concentrations sampled at the reference (1-hour) interval, differences in load estimates were less than 10% in the cases of the 2-hour and 3-hour intervals in the urbanized and agricultural watersheds, respectively, except in the case of suspended solids (SS). When it comes to the total load estimation, up to 3-hour interval sampling provided load estimates with acceptable accuracy, except for SS. Thus, the 3-hour sampling interval was considered feasible for long-term pollutant load assessment, while the 2-hour sampling interval was suggested for SS. Such findings are expected to facilitate NPS pollution assessment by providing information required to improve monitoring efficiency.

A framework for evaluating county-level non-point source pollution: Joint use of monitoring and model assessment

It is believed that non-point source (NPS) pollution threatens the regional environment. Because of the disconnection between the hydrological scale and the administrative scale of implementing feasible management policies in existing research, watershed-based management measures have limited application in current NPS control. In this study, a framework for county-level monitoring and evaluation is proposed, which contains a cascade monitoring scheme and an adaptable assessment scheme. The cascade monitoring scheme is based on the principle of “pollution source-transport pathways-receiving waters” layout method and the adaptable assessment scheme makes full use of monitoring data in the model. A set of processes was designed to monitor and assess county-level NPS pollution, from the initial step of county basic situation investigations to the final step of NPS pollution assessment. Two schemes are included in the process to improve the feasibility of the results. Here, the importance of the joint use of monitoring and simulation for environmental policy and management is stressed, and focus is on the characteristics of administrative boundaries. A case study involving Nanle County is presented, and a detailed layout scheme and the assessment results are given in this paper.

Statistical assessment of nonpoint source pollution in agricultural watersheds in the Lower Grand River watershed, MO, USA

The water quality in many Midwestern streams and lakes is negatively impacted by agricultural activities. Although the agricultural inputs that degrade water quality are well known, the impact of these inputs varies as a function of geologic and topographic parameters. To better understand how a range of land use, geologic, and topographic factors affect water quality in Midwestern watersheds, we sampled surface water quality parameters, including nitrate, phosphate, dissolved oxygen, turbidity, bacteria, pH, specific conductance, temperature, and biotic index (BI) in 35 independent sub-watersheds within the Lower Grand River Watershed in northern Missouri. For each sub-watershed, the land use/land cover, soil texture, depth to bedrock, depth to the water table, recent precipitation area, total stream length, watershed shape/relief ratio, topographic complexity, mean elevation, and slope were determined. Water quality sampling was conducted twice: in the spring and in the late summer/early fall. A pairwise comparison of water quality parameters acquired in the fall and spring showed that each of these factors varies considerably with season, suggesting that the timing is critical when comparing water quality indicators. Correlation analysis between water quality indicators and watershed characteristics revealed that both geologic and land use characteristics correlated significantly with water quality parameters. The water quality index had the highest correlation with the biotic index during the spring, implying that the lower water quality conditions observed in the spring might be more representative of the longer-term water quality conditions in these watersheds than the higher quality conditions observed in the fall. An assessment of macroinvertebrates indicated that the biotic index was primarily influenced by nutrient loading due to excessive amounts of phosphorus (P) and nitrogen (N) discharge from agricultural land uses. The PCA analysis found a correlation between turbidity, E. coli, and BI, suggesting that livestock grazing may adversely affect the water quality in this watershed. Moreover, this analysis found that N, P, and SC contribute greatly to the observed water quality variability. The results of this study can be used to improve decision-making strategies to improve water quality for the entire river basin.

Long-Term Hydrologic Impact Assessment of Non-point Source Pollution Measured Through Land Use/Land Cover (LULC) Changes in a Tropical Complex Catchment

The contribution of non-point source pollution (NPS) to the contamination of surface water is an issue of growing concern. Non-point source (NPS) pollutants are of various types and altered by several site-specific factors making them difficult to control due to complex uncertainties involve in their behavior. Kelantan River basin, Malaysia is a tropical catchment receiving heavy monsoon rainfall coupled with intense land use/land cover (LULC) changes making the area consistently flood prone thereby deteriorating the surface water quality in the area. This study was conducted to determine the spatio-temporal variation of NPS pollutant loads among different LULC changes and to establish a NPS pollutant loads relationships among LULC conditions and sub-basins in each catchment. Four pollutants parameters such as total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN) and ammonia nitrogen (AN) were chosen with their corresponding event mean concentration values (EMC). Soil map and LULC change maps corresponding to 1984, 2002 and 2013 were used for the calculation of runoff and NPS pollutant loads using numeric integration in a GIS environment. Analysis of Variance (ANOVA) was conducted for the comparison of NPS pollutant loads among the three LULC conditions used and the sub-basins in each catchment. The results showed that the spatio-temporal variation of pollutant loads in almost all the catchments increased with changes in LULC condition as one moves from 1984 to 2013, with 2013 LULC condition found as the dominant in almost all cases. NPS pollutant loads among different LULC changes also increased with changes in LULC condition from 1984 to 2013. While urbanization was found to be the dominant LULC change with the highest pollutant load in all the catchments. Results from ANOVA reveals that statistically most significant (p < 0.05) pollutant loads were obtained from 2013 LULC conditions, while statistically least significant (p < 0.05) pollutant loads were obtained under 1984 LULC condition. This reveals the clear effect of LULC changes on NPS pollution. The findings of this study may be useful to water resource planners in controlling water pollution for future planning.

Impact of Climate Variability and Landscape Patterns on Water Budget and Nutrient Loads in a Peri-urban Watershed: A Coupled Analysis Using Process-based Hydrological Model and Landscape Indices.

Nutrient discharge into peri-urban streams and reservoirs constitutes a significant pressure on environmental management, but quantitative assessment of non-point source pollution under climate variability in fast changing peri-urban watersheds is challenging. Soil and Water Assessment Tool (SWAT) was used to simulate water budget and nutrient loads for landscape patterns representing a 30-year progression of urbanization in a peri-urban watershed near Tianjin metropolis, China. A suite of landscape pattern indices was related to nitrogen (N) and phosphorous (P) loads under dry and wet climate using CANOCO redundancy analysis. The calibrated SWAT model was adequate to simulate runoff and nutrient loads for this peri-urban watershed, with Nash-Sutcliffe coefficient (NSE) and coefficient of determination (R2) > 0.70 and percentage bias (PBIAS) between -7 and +18 for calibration and validation periods. With the progression of urbanization, forest remained the main "sink" landscape while cultivated and urban lands remained the main "source" landscapes with the role of orchard and grassland being uncertain and changing with time. Compared to 1984, the landscape use pattern in 2013 increased nutrient discharge by 10%. Nutrient loads modelled under wet climate were 3-4 times higher than that under dry climate for the same landscape pattern. Results indicate that climate change could impose a far greater impact on runoff and nutrient discharge in a peri-urban watershed than landscape pattern change.

Estimation of and Control Strategies for Pollution Loads from Non-point Sources in the Chenghai Watershed

The calculation of non-point source (NPS) pollutant loads of nitrogen and phosphorus is the key step in preparing a pollution control plan. This study modified the export coefficient model by taking into account the precipitation, slope, distance between pollution sources and water bodies, and other relevant factors. The NPS pollution load assessment method established in this study can be applied to data-scarce basins and is suitable for plateau lake regions affected by terrain and precipitation. In this study, Chenghai Lake, which belongs to one of the nine major plateau lakes in Yunnan Province, is selected for the case study. This study first verifies the rationality of the improved export coefficient model based on actual observed values, and then utilizes the improved export coefficient model to assess the loads of dissolved nitrogen (DN) and dissolved phosphorus (DP) pollution. As indicated by the results, in 2014, the loads of DN and DP into Chenghai Lake are 158.48 t·a-1 and 24.70 t·a-1, respectively. The maximum contributions of DN and DP pollution load into Chenghai Lake are from agricultural cultivated land are 46.19% and 48.16%, respectively, in terms of land use. The results present a relatively consistent spatial distribution of DN and DP that indicates that the south bank is a key area for governance. Livestock and rural living are the main pollution sources influencing the load of DN and DP into Chenghai Lake and should be prioritized for control. If the pollution from rural living, livestock, fertilizer loss, and land use can be effectively controlled, the load of DN and DP into Chenghai Lake will be decreased by a maximum of 38.47% and 40.76%, respectively. The results of this study suggest that the improved export coefficient model can be applied for study of the NPS pollution assessment of plateau lake regions and can provide a theoretical basis for the NPS pollution control of the Chenghai Lake basin.

Nonpoint Source Pollution.

This research article depicts a comprehensive review of scientific research advancement on nonpoint source pollution (NPS) in 2016. The causes, impacts, and methods used to mitigate nonpoint source pollution were reviewed. In addition, the assessment of nonpoint source pollution using different modeling techniques, coupled with evaluation and management tools were reviewed. Innovative technologies to reduce nonpoint source pollution were also reviewed in this paper.

Research on Nonpoint Source Pollution Assessment Method in Data Sparse Regions: A Case Study of Xichong River Basin, China

The NPS pollution is difficult to manage and control due to its complicated generation and formation mechanism, especially in the data sparse area. Thus the ECM and BTOPMC were, respectively, adopted to develop an easy and practical assessment method, and a comparison between the outputs of them is then conducted in this paper. The literature survey and field data were acquired to confirm the export coefficients of the ECM, and the loads of TN and TP were statistically analyzed in the study area. Based on hydrological similarity, runoff data from nearby gauged sites were pooled to compensate for the lack of at-site data and the water quality submodel of BTOPMC was then applied to simulate the monthly pollutant fluxes in the two sections from 2010 to 2012. The results showed agricultural fertilizer, rural sewage, and livestock and poultry sewage were the main pollution sources, and under the consideration of self-purification capacity of river, the outputs of the two models were almost identical. The proposed method with a main thought of combining and comparing an empirical model and a mechanistic model can assess the water quality conditions in the study area scientifically, which indicated it has a good potential for popularization in other regions.

Integrated assessment of nonpoint source pollution of a drinking water reservoir in a typical acid rain region

Nonpoint source pollution generated by agricultural production and city construction has been studied for decades, but very few researches have been conducted on the regional assessment of nonpoint source pollution in the acid rain regions, particularly relating to the control of pollutant in the drinking water source areas. In this study, an integrated framework was applied to estimate nitrogen and phosphorous load in a typical acid rain influenced reservoir, China. The method comprised three separate steps: (1) a watershed model—soil and water assessment tools—was used to estimate nitrogen and phosphorous load from the upper stream watershed; (2) collection of acid rain samples, together with a GIS-based calculation to estimate the atmospheric deposition flux; (3) introduction of a simple export coefficient method. The case study indicated atmospheric deposition accounted for 56.75 % of total nitrogen load during the year, with the highest level of deposition load taking place during the wet season. Maximum phosphorous (93.37 %) was linked to the upstream runoff, originating from the upper watershed. Further analysis by watershed model and export coefficient method indicated forest exported most total nitrogen (27.72 %) and total phosphorous (58.78 %) in the upstream watershed. Results indicated that in the region influenced by acid rain, the nitrogen management should encompass the management of land use practices and the control of acid rain in catchments feeding into drinking water storage areas. It could be inferred that NOX emissions might cause both globe warming and eutrophication in the drinking water sources. This paper could provide a basis for water quality management in such regions.

Assessment of non-point source pollution using a spatial multicriteria analysis approach

Eutrophication caused by the enrichment of nutrients from diffusing sources is degrading surface water quality throughout the world. Assessing the potential contributions of different land areas in diffuse nutrient export has become an important task in non-point source (NPS) pollution control. Existing methods were often limited by the availability of local data and the complexity of model formulation. This study developed a spatial multicriteria method to evaluate the nitrogen loss potential at the basin level. Four criteria were formulated to characterize the source capacity of nitrogen export, the flow path to water body, the efficiency of runoff generation and the climatic driving force. The proposed method is a low-effort approach since the required data is either already available in a global context or easily produced with limited inputs. Being implemented in GIS environment, this method generates maps that can be easily interpreted to provide decision support. The method was applied to the Huai River Basin, China. The results were validated based on the correlation between the nitrogen loss potential of sub-basin and the water quality class of river. The maps of nitrogen loss potential were helpful for examining the regional pattern of diffuse nitrogen loss, and could facilitate the decisions of NPS pollution management at the provincial or basin level.

A Review of effectiveness of vegetative buffers on sediment trapping in agricultural areas

AbstractIn recent years, there has been growing recognition of the importance of riparian buffers between agricultural fields and waterbodies. Riparian buffers play an important role in mitigating the impacts of land use activities on water quality and aquatic ecosystems. However, evaluating the effectiveness of riparian buffer systems on a watershed scale is complex, and watershed models have limited capabilities for simulating riparian buffer processes. Thus, the overall objective of this paper is to develop an understanding of riparian buffer processes towards water quality modelling/monitoring and nonpoint source pollution assessment. The paper provides a thorough review of relevant literature on the performance of vegetative buffers on sediment reduction. It was found that although sediment trapping capacities are site‐ and vegetation‐specific, and many factors influence the sediment trapping efficiency, the width of a buffer is important in filtering agricultural runoff and wider buffers tended to trap more sediment. Sediment trapping efficiency is also affected by slope, but the overall relationship is not consistent among studies. Overall, sediment trapping efficiency did not vary by vegetation type and grass buffers and forest buffers have roughly the same sediment trapping efficiency. This analysis can be used as the basis for planning future studies on watershed scale simulation of riparian buffer systems, design of effective riparian buffers for nonpoint source pollution control or water quality restoration and design of riparian buffer monitoring programs in watersheds. Published in 2009 by John Wiley &amp; Sons, Ltd.