Areas Of Nonpoint Source Pollution Research Articles

Occurrence and distribution of legacy and novel brominated flame retardants in river and sediments in southwest China: A seasonal investigation

Brominated flame retardants (BFRs) and their substitutes are prevalent in the environment, especially near industrial point sources. In non-point source pollution areas, it is crucial to investigate the seasonal pollution characteristics to identify the pollution sources. In this study, compositional profiles, seasonal variations, and ecological risks of legacy BFRs and novel BFRs (NBFRs) in the water and sediment from the Tuojiang River located in southwest China were investigated. The results indicated that ΣBFRs ranged from not detected (n.d.) to 42.0 ng/L in water and from 0.13 to 17.6 ng/g in sediment, while ΣNBFRs ranged from n.d. to 15.8 ng/L in water, and from 0.25 to 6.82 ng/g in sediment. A significant seasonal variation was observed in water and sediments with high proportions of legacy BFRs (median percentage of 68.8% and 51.3% in water and sediment) in the dry season, while NBFRs (median percentage of 53.2% and 71.6% in water and sediment) exhibited predominance in the wet season. This highlighted the importance of surface runoff and atmospheric deposition as important sources of NBFRs in aquatic environments. Moreover, there were high ratios of decabromodiphenyl ethane (DBDPE) and BDE-209 (average: 1.38 and 2.76 in dry and wet season) in sediments adjacent to the residual areas, indicating a consumption shift from legacy BFRs to NBFRs in China. It was observed that legacy BFRs showed higher ecological risks compared to NBFRs in both water and sediment environments, with BDE-209 posing low to medium risks to sediment organisms. This study provides better understanding of contamination characteristics and sources of legacy BFRs and NBFRs in non-point source pollution areas.

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

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

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.

Hydrological and water quality simulation and future runoff prediction under CMIP6 scenario in the upstream basin of Miyun Reservoir

AbstractWater resources are a key factor restricting human survival and social and economic development. The Miyun Reservoir, which is the only surface drinking water source in Beijing and the water storage reservoir of the South-to-North Water Diversion Project, plays a decisive role in ensuring water-use sustainability of the capital. This study focused on the Baihe River Basin, which is one of the important inflows of the Miyun Reservoir. The mathematical data on the climate and hydrological changes of the Baihe River Basin over the past 30 years were obtained, and the evolution law of the Baihe River runoff and its influencing factors was analyzed. Our analysis used the data obtained via multi-source meteorology to establish the Soil and Water Assessment Tool (SWAT) model of the Baihe River Basin. Sequential Uncertainty Fitting version 2 (SUFI-2) and Generalized Likelihood Uncertainty Estimation (GLUE) were used to simulate runoff from 1990 to 2017 on a monthly scale, along with sediment, total nitrogen (TN), and total phosphorus (TP) contents from 1990 to 2010. Then, the parameter uncertainty of the SWAT model and the applicability of the SWAT model in the Baihe River Basin were determined. The land-use transfer matrix showed that land-use changes are complex and the transformation forms are diverse. The simulation results showed that the transformation of land-use patterns in 1990 and 2010 had slight impacts on the hydrologic and water quality of the basin. By identifying the key source areas of non-point source pollution in the basin, the impacts of three management measures on the hydrological and water quality of the basin were simulated. The results showed that the reductions in flow rates, sediment content, TN, and TP (4.37, 31.93, 23.13, and 35.30%, respectively) obtained through terrace engineering were significantly better than those acquired via stubble mulch and contour planting. Additionally, this study uses the Sixth International Coupling Mode Comparison Program (CMIP6) climate change scenario and the BCC-CSM2-MR climate model coupled with the corrected SWAT model to predict future runoff, thereby providing references and suggestions for managing the Baihe River Basin and the Miyun Reservoir.

Identifying critical source areas of nonpoint source pollution in a watershed with SWAT–ECM and AHP methods

Abstract Identification of critical source areas (CSAs) is pivotal for the management of nonpoint source (NPS) pollution of watersheds. Most studies focus on source (S) factors and ignore the driving (D) factors of such pollution. The Soil and Water Assessment Tool (SWAT) model and the export coefficient method (ECM) were incorporated to quantify the S factors of ammonia nitrogen (NH4-N) and total phosphorus (TP) as NPS pollution. Specifically, S factors coupled with D factors, including precipitation, slope, soil and land use, were regarded as multi-factors. Moreover, the analytical hierarchy process (AHP) method was adopted to determine the respective weights of multi-factors after overlaying the factor maps to identify the CSAs. These CSAs accounted for 23.86% of the total area, and generated 54.94% of NH4-N and 42.59% of the TP loads. In contrast with single and multi-factors, we found that using multi-factors having differing weights was more accurate for identifying CSAs. Our study results indicate this approach is reasonable for CSAs' identification in watersheds, and it can provide insights into different pollution sources and migration, thus providing a sounder basis for future decision-making.

Identification and Regulation of Critical Source Areas of Non-Point Source Pollution in Medium and Small Watersheds Based on Source-Sink Theory

The identification and regulation of the critical source areas (CSAs) of non-point source (NPS) pollution have been proven as economical and effective ways to control such pollution in watersheds. However, the traditional models for the identification of CSAs have complex operation processes, and comprehensive systematic methods for the regulation of CSAs are still lacking. This study systematically developed a new methodological framework for the identification and regulation of CSAs in medium and small watersheds based on source-sink theory, which included the following: (1) a grid-based CSAs identification model involving the evaluation of the rationality of the source-sink landscape pattern and three geographical factors (landscape slope, relative elevation, and the distance from the river), and identifying CSAs by the calculation and division of the integrated grid pollution index (IGPI); (2) a comprehensive CSAs regulation strategy that was formulated based on three landscape levels/regulation intensities—including the optimization of the overall source-sink landscape pattern, the conversion of the landscape type or landscape combination, and local optimization for single source landscape—to meet various regulatory intensity requirements in watersheds. The Jiulong River watershed in Fujian Province of China was taken as a case study. The results indicate that: (1) the identified CSAs of the Jiulong River watershed covered 656.91 km2, equivalent to 4.44% of the watershed, and through adopting multiple-intensity regulation measures for 10 key control zones that had spatially concentrated high values of the IGPI among the CSAs, the watershed IGPIs were predicted to be generally reduced and the area of CSAs was predicted to decrease by 23.84% (31.43% in Zhangzhou, the major city in the watershed); (2) the identification model can identify the CSAs with easy data access and simple operation, and the utilization of neighborhood impact analysis makes the grid-based research more scientific in the evaluation of the rationality of the source-sink landscape pattern; (3) the application of multi-scale landscape planning framework and the principle of source-sink landscape pattern regulation make the CSAs regulation strategy systematic and cost-effective, and the provision of different intensity regulation strategies makes the regulation strategy easy to implement and relatively lower cost. The proposed methodological framework can provide technical support for governments to quickly and accurately identify the CSAs of NPS pollution and effectively control such CSAs in medium and small watersheds.

Present and potential future critical source areas of nonpoint source pollution: a case of the Nakdong River watershed, South Korea

Identifying critical source areas (CSAs) is the first step to effectively managing nonpoint source (NPS) pollution. Increasing variability in climate can affect identification of CSAs. In this study, we identified present and future CSAs of NPS pollution in the Nakdong River watershed and examined how climate change will influence the identification of CSAs. Nine NPS pollution-related factors affecting the watershed environment and water quality were considered. These factors were rescaled through a min-max normalization to propose an index system that ranks basins based on the sensitivity of basins to climate change on identifying CSAs. For analyses, past rainfall was replaced with future rainfall under two RCP scenarios, RCP 2.6 and RCP 8.5. Results showed insignificant differences in the spatial distribution of CSAs between the present and the future and between the future scenarios. Basins that are on or adjacent to the Nakdong River mainstream were mainly identified as CSAs, in addition to many basins of the Geumho and Nam rivers. Highly ranked CSAs including the level 1 CSAs, were mainly distributed in the mid- and downstream areas of the Nakdong River, indicating high need of NPS pollution management. This study can provide a foundation for the effective management of NPS pollution in the present and the future.

Cooperative identification for critical periods and critical source areas of nonpoint source pollution in a typical watershed in China.

Critical periods (CPs) and critical source areas (CSAs) refer to the high-risk periods and areas of nonpoint source (NPS) pollution in a watershed, respectively, and they play a significant role in NPS pollution control. The upstream Daning River Basin is a typical watershed in the Three Gorges Reservoir area. In this study, a Hydrological Simulation Program-Fortran (HSPF) model was used to simulate phosphorus loss in the upstream Daning River Basin. Co-analysis of critical periods and critical source areas (CACC) is a quantitative collaborative analysis method for the identification of CSAs in CPs, and it was used to classify the periods and areas of NPS pollution as CPs, sub-CPs, non-CPs, CSAs, and non-CSAs. The CPs occurred in months 5-7 and accounted for 53.7% of the total phosphorus (TP) loads, and the sub-CPs occurred in months 1, 3, 4, and 8 and accounted for 29.2% of the TP loads. In CSAs, 49.4% of the TP loads occurred in 26.8% of the basin. Furthermore, we proposed the following multilevel priority control measure for NPS pollution in the upstream Daning River Basin: CSAs in CPs (with load-area rate of 1.4), CSAs in sub-CPs (0.7), CSAs in non-CPs (0.4), non-CSAs in CPs (0.3), non-CSAs in sub-CPs (0.2), and non-CSAs in non-CPs (0.1). CSAs in CPs accounted for 25.8% of the TP loads from 19.0% of the areas in only 3months while 49.4% of the TP loads from similar areas over an entire year. These findings indicated that the CSAs in CPs located in farmland along the Daning, Dongxi, and Houxi Rivers should be prioritized for pollution management measures.

Accumulation and wash-off characteristics of surface pollutant and identification of risk areas on urban land uses in a lakeside city, Wuxi, China

ABSTRACTThis paper selected administration and public services, residential areas, roads, green space, parking areas, industrial areas and commercial and business facilities in Wuxi city, China, to analyze the characteristics of pollution accumulation, wash-off and potential risk areas of pollutants over different urban land uses and pavement surface materials. Results showed that green space, residential areas and roads sequestrated higher pollutants than that of other land uses. Materials of masonry and cement pavement accumulated higher pollutant concentration than that on the marble and asphalt pavement. The potential risk areas of non-point source pollution were located in the old residential areas in the downtown region. The results of wash-off simulation showed that the first flushing effect was obvious during the initial period of rainfall. Eighty percent of the accumulative total nitrogen or total suspended solid could be washed-off during the first 25.6–50.2% period of the rainfall events.

주암댐 유역 비점오염부하량 우심지역 평가를 통한 오염물질 저감시설 최적 설치지점 선정 연구

This study analyzes potentially hazardous sub-watersheds from non-point source pollution areas using an HSPF model. The watershed of the Juam dam reservoir was divided into 29 sub-watersheds, and the flow, BOD, TN and TP concentration for the Juam dam watershed were evaluated from 2009 to 2012 using a watershed model, with a warming period from 2009 to 2010. The results of the watershed model agreed well with the flow and water quality field measurements. The calculated average non-point source loadings were BOD of 8.8 and in 2011 and 2012, respectively; TN of 9.7 and in 2011 and 2012, respectively; and TP of 0.30 and in 2011 and 2012, respectively. The non-point source loading of the Bonghwa stream watershed was calculated, and predominantly assessed upstream of the Boseong river. Additionally, the Miryeok, Jangpyeong, Yuleo, Guam, Seokgyo, Mundeok, Incheon, and Bongnae stream watersheds, with extensive agricultural areas, were assessed to be potentially hazardous areas in terms of non-point source management. In this study, HSPF model was applied in order to aid in the selection of non-point source reduction facilities for the Juam dam watershed, where they were evaluated as to whether they would be applicable for non-point source management.

The precipitation driven correlation based mapping method (PCM) for identifying the critical source areas of non-point source pollution

Summary Critical source areas (CSAs) are the areas that are relatively more erosion-prone and contribute significantly more pollutants per unit area. They have been widely recognized as optimal locations for the control of non-point source (NPS) pollution. Modeling approach has been frequently used to identify the CSAs of NPS pollution on a basin scale. In previous studies, CSAs were identified based on the simulated average annual nutrient yields for the simulation period at the levels of sub-basin or hydrologic response unit (HRU). However, this method did not consider the impact of uneven spatial distribution of precipitation, which is considered to be the driven force of NPS pollution. In many cases, due to limited length of qualified monitoring data collected, the simulation period may not cover a full spectrum of the precipitation characteristics so that some potential CSAs may be missed. In the present study, the precipitation driven correlation based mapping method (PCM) was proposed, which can reduce the impact of uncertain spatial–temporal distribution of precipitation and identify the CSAs of NPS pollution with a better coverage. This method was applied to the Zhang River Basin, a watershed in North China that occupies an area of 18,072 km 2 . The SWAT (Soil and Water Assessment Tool) was used for simulation purposes. By using PCM, the maps of CSAs for controlling total nitrogen (TN) and total phosphorus (TP) were produced. This study has found that the monthly precipitation is highly correlated with the TN and TP yields. It was observed that TN yields have slightly higher correlation value with the precipitation than TP yields. Hence, the precipitation has more impacts on TN yields than TP yields. The impact is more substantial in urban areas than other areas.

Accommodating environmental thresholds and extreme events in hydrological models: A Bayesian approach

Extreme events appear to play an important role in pollutant export and the overall functioning of watershed systems. Because they are expected to increase in frequency as urbanization and recent climate change trends continue, the development of techniques that can effectively accommodate the behavior of watersheds during extreme events is one of the challenges of the contemporary modeling practice. In this regard, we present a Bayesian framework which postulates that the watershed response to precipitation occurs in distinct states. Precipitation depth above a certain threshold triggers an extreme state, which is characterized by a qualitatively different response of the watershed to precipitation. Our calibration framework allows us to identify these extreme states and to characterize the different watershed behavior by allowing parameter values to vary between states. We applied this framework to SWAT model implementations in two creeks in the Hamilton Harbour watershed of Redhill Creek, an urban catchment, and Grindstone Creek, an agricultural one. We found that our framework is able to coherently identify watershed states and state-specific parameters, with extreme states being characterized by a higher propensity for runoff generation. Our framework resulted in better model fit above the precipitation threshold, although there were not consistent improvements of model fit overall. We demonstrate that accommodating threshold-type of behavior may improve the use of models in locating critical source areas of non-point source pollution.

Identifying critical source areas of nonpoint source pollution with SWAT and GWLF

Identification of critical source areas (CSAs) (areas contributing most of the pollutants in a watershed) is important for cost-effective implementation of best management practices. Identification of such areas is often done through watershed modeling. Various watershed models are available for this purpose, however it is not clear if the choice (and complexity) of a model would lead to differences in locations of CSAs. The objective of this study was to use two models of different complexity for identifying CSAs. The relatively complex Soil and Water Assessment Tool (SWAT) and the simpler Generalized Watershed Loading Function (GWLF) were used to identify CSAs of sediment and nutrients in the Saugahatchee Creek watershed in east central Alabama. Models were calibrated and validated for streamflow, sediment, total nitrogen (TN) and total phosphorus (TP) at a monthly time scale. While both models performed well for streamflow, SWAT performed slightly better than GWLF for sediment, TN and TP. Sub-watersheds dominated by urban land use were among those producing the highest amount of sediment, TN and TP loads, and thus identified as CSAs. Sub-watersheds with some amount of agricultural crops were also identified as CSAs of TP and TN. A few hay/pasture dominated sub-watersheds were identified as CSAs of TN. The identified land use source areas were also supported by field collected water quality data. A combined index was used to identify the sub-watersheds (CSAs) that need to be targeted for overall reduction of sediment, TN and TP. While many CSAs identified by SWAT and GWLF were the same, some CSAs were different. Therefore, this study concludes that model choice will affect the location of some CSAs.

Assessment of seasonal and spatial variation of surface water quality, identification of factors associated with water quality variability, and the modeling of critical nonpoint source pollution areas in an agricultural watershed

Surface water quality impairment in agricultural watersheds is a major environmental concern in the United States. To assess seasonal and spatial variability of surface water quality and identify factors associated with surface water quality variability, we monitored surface water quality at seven locations in Bayou Plaquemine Brule Watershed in Louisiana twice monthly from March of 2002 to February of 2008 and performed multivariate analyses of the dataset. Using the Soil and Water Assessment Tool (SWAT) model, we identified critical areas of nonpoint source pollution in the watershed. While temperature, turbidity, dissolved oxygen (DO), conductivity and pH were determined in the field using YSI Sonde (YSI Incorporated, Yellow Springs, Ohio), surface water samples were analyzed for total nitrogen (TN), total phosphorus (TP), nitrate/nitrite-N (NO₃/NO₂-N), soluble reactive phosphate (SRP), total suspended solids (TSS), and five-day biological oxygen demand (BOD₅) in laboratory. The monthly water quality sampling included a regular sampling and an after-rain-event sampling. Average DO for the summer months, March through November, was 4.91 ± 0.08 mg L⁻¹ (4.91 ± 0.08 ppm), while average DO for the winter months, December through February, was 8.32 ± 0.12 mg L⁻¹ (8.32 ± 0.12 ppm). Dissolved oxygen was negatively correlated with TN (<i>r</i> = −0.22, <i>p</i> ≤ 0.001), SRP (<i>r</i> = −0.17, <i>p</i> ≤ 0.001), TP (<i>r</i> = −0.17, <i>p</i> ≤ 0.001), BOD₅ (<i>r</i> = −0.25, <i>p</i> ≤ 0.001), and surface water temperature (<i>r</i> = −0.70, <i>p</i> ≤ 0.001). Turbidity was strongly correlated with TSS (<i>r</i> = 0.59, <i>p</i> ≤ 0.001), suggesting that most turbidity in the water body comes from suspended solids. Similarly BOD₅ was significantly positively correlated with TN (<i>r</i> = 0.43, <i>p</i> ≤ 0.001), NO₃/NO₂-N (<i>r</i> = 0.26, <i>p</i> ≤ 0.001), TP (<i>r</i> = 0.25, <i>p</i> ≤ 0.001), and SRP (<i>r</i> = 0.18, <i>p</i> ≤ 0.001). Results of factor analyses showed sediment, phosphorus (P), nitrogen (N), surface water temperature, dissolved solids, and acidity/alkalinity as the most important factors associated with surface water quality variability in this watershed. Although relatively higher concentrations of sediments, TP, and TN were observed in the upper reaches of the watershed based on water quality monitoring, the SWAT simulation results showed the critical nonpoint source pollution areas of sediment, P, and N in the lower reaches of the watershed. Lower reaches of the watershed have mainly rice and crawfish production, while the upper reaches include primarily sugarcane, pasturelands, and soybean production. Information on seasonal variability of surface water quality, factors associated with surface water quality variability, and the critical areas for nonpoint source pollution will be valuable inputs for developing a watershed management plan for effective nonpoint source pollution control in an agricultural watershed.

Hydrologic-Economic Analysis of Best Management Practices for Sediment Control in the Santa Fe Watershed, New Mexico

The Santa Fe River Watershed in Santa Fe County, New Mexico was identified as one of the top five high risk nonpoint source pollution areas out in the Rio Grande Basin. This watershed was selected to demonstrate the use of hydrologic modeling as a powerful tool for assessing the impacts of land management practices on erosion and sediment control at the watershed level. A method based on the Hydrologic Simulation Program-Fortran was used to address the local nonpoint sediment pollution concerns. The model was modified to reflect predicted future land uses related to expected urban expansion in the watershed. Six scenarios were created and the costs and benefits of each were weighed. The total estimated costs ranged from under $1 million to over $66 million. Total average annual sediment yields at the watershed outlet ranged from 3,441 to 4,111 tonnes/year, depending on management practices employed. These results indicate the magnitude of expected sediment reductions under various management strategies. Additionally, they provide an indication of the magnitude of expected sediment reductions in the Santa Fe Watershed and the estimated cost of each management practice.

Dynamic riparian buffer widths from potential non-point source pollution areas in forested watersheds

Efforts to manage National Forests in the USA for wood production, while protecting water quality, are currently constrained by models that do not address the temporal dynamics of variable non-point source (NPS) areas. NPS areas are diffuse sources of contaminants contributed mostly by runoff as a result of different land use activities. Riparian vegetative buffers are often used to control contaminants from NPS areas but defining suitable widths require different policy considerations. In this study, the approach for defining suitable buffer widths is to apply a distributed process-based model that predicts potential NPS areas prone to generating runoff in relation to overland flow distances. A case study of the concept was applied to the 72 km 2 Pete King watershed located in the Clearwater National Forest (CNF) in central Idaho, USA. This grid modeling approach is based on a Geographic Information System (GIS) and it integrates the soil moisture routing (SMR) model with probabilistic analysis. The SMR model is a daily water balance model that simulates the hydrology of forested watersheds using real or stochastically generated climate data, a digital elevation model, soil, and land use data. The probabilistic analysis incorporates the variability of soil depth and accounts for uncertainties associated with the prediction of NPS areas using Monte Carlo simulation. A 1-year simulation for the case study location was performed to examine the spatial and temporal changes in NPS areas prone to generating runoff. The results of the simulation indicate that the seasonal variability of saturated areas determines the spatial dynamics of the potential NPS pollution. Use of this model for the design of riparian buffer widths would increase the effectiveness of decision-making in forest management and planning by mapping or delineating NPS areas likely to transport contaminants to perennial surface water bodies.

Control division of agricultural non-point source pollution at medium-sized watershed scale in Southeast China

This paper presents the study carried out for controlling agricultural non-point source pollution (NSP) in a medium-sized watershed covering 1.47 × 104 km2 in Southeast China using quantitative analysis coupled with geographic information system (GIS), universal soil loss equation (USLE), soil conservation service-curve number (SCS-CN), nutrient loss equations, and annualized agricultural nonpoint source model (AnnAGNPS). Based on the quantitative results derived from GIS and environmental models, five control division units were generated for NSP control in Jiulong River watershed, namely, controlling unit for soil losses, controlling unit for livestock breeding and soil losses, controlling unit for excessive fertilizer use and livestock breeding, controlling unit for soil losses and fertilizer use, and controlling unit for excessive fertilizer use and soil losses. This study proved that integrating GIS with environmental models can be adopted to efficiently evaluate major sources and contributors of NSP, and identify the critical source areas of NSP, which enables adjusting measures to local conditions by further control division units developed through such study for control and management of water quality degradation induced by NSP in the Jiulong River watershed.

Nutrient loss from various land-use areas in Shixia small watershed of Miyun County, Beijing, China

In the Shixia small watershed, twenty experimental plots and two monitoring channels, the residential area and livestock areas were used to monitor the flow, runoff and erosion. Nitrogen and phosphorous concentrations associated with various land uses were analyzed at the same time. The results are presented as follows: (1 ) TP, TN and COD concentrations of runoff samples in the residential area and livestock areas are nearly 10 times those in other land-use areas. High nutrient loads are associated with village land use, which is due to unsuitable livestock rising. These areas should be treated as the critical areas of non-point source pollution. (2 ) Different land-use influences intensity the loss of nutrients, especially slope tillings in agricultural land. The amount of nutrient loss from agricultural land per unit is highest, that from forestry is intermediate and that from pastures is lowest. However, in consideration of the variability of land-use areas, agricultural land contributes the greatest to TP and forestry land to TN. (3 ) The concentrations of TN and TP in sediments from gangues are highest, those in forestry land are intermediate, and those in agricultural land are lowest. Nutrient loss from hilly areas is much greater than from mountainous areas.

Identificação das áreas potenciais de produção de sedimentos com o modelo AGNPS e técnicas de SIG em uma microbacia hidrográfica

O planejamento de uso do solo em bacias hidrográficas deveria ter, como base, a identificação de áreas agrícolas suscetíveis aos processos erosivos, visto que a avaliação de sistemas integrados de manejo de solo e culturas em microbacias é campo ideal para esta investigação, uma vez que a qualidade final das águas dos rios é o reflexo das atividades ali desenvolvidas. Objetivou-se determinar áreas potenciais de poluição não pontual e avaliar práticas conservacionistas de solo, empregando-se o modelo matemático AGNPS, associado a técnicas de SIG. O estudo foi conduzido na microbacia hidrográfica córrego Água Grande e Ribeirão Pensamento, no município de Mamborê, PR, sobre as reais condições de produção agrícola. A estimativa da produção de sedimentos foi realizada através de simulações para diferentes cenários de uso do solo, referindo-se a distintos eventos de precipitação em uma seqüência de quatro anos agrícolas. Foram identificadas as causas de produção de sedimentos e as áreas potenciais, verificando-se que a modificação das técnicas de cultivo reduziu a produção de sedimentos.

SIMULATION OF URBAN NON‐POINT SOURCE POLLUTION1

ABSTRACT: Public Law 92–00 has mandated the need for evaluating the impact of nonpoint source pollution on receiving water quality, primarily through Section 208 Areawide Planning. The Management of Urban Non‐Point Pollution (MUNP) model was developed to estimate the accumulation of eight non‐point pollutants on urban streets, their removal by both rainfall and street sweeping operations. The model can simulate the following pollutants: total solids or sediment‐like material, volatile solids, five‐day biochemical oxygen demand, chemical oxygen demand, Kjeldahl nitrogen, nitrates, phosphates, and total heavy metals. The simulated results can be used for investigation of non‐point pollution management alternatives. The model is capable of reflecting variation in such diverse factors as physical and chemical characteristics of accumulated pollutants, land use characteristics, rainfall characteristics, street sweeper characteristics, roadway characteristics, and traffic conditions. By using mean estimates of many input variables for large segments of a city, the MUNP model could be used to quickly assess the magnitude of pollutants annually entering receiving waterways due to nonpoint source pollution alone. If the results indicate that non‐point pollution loadings are sizeable and require futher analysis, the MUNP model could be used to define the specific nonpoint source pollution areas within a city. Hypothetical locations and actual rainfall data for Washigton D.C. were used to demonstrate some capabilities of the MUNP model.