Performance Of Best Management Practices Research Articles

Modeling BMP and Vegetative Cover Performance for Highway Stormwater Runoff Reduction

Urbanization generally leads to increases of impervious surfaces, changes of the natural hydrologic conditions and watershed's response to stormwater runoff. The application of Best Management Practices (BMPs) can provide a solution for on-site management of post-construction stormwater runoff. This study investigated the effectiveness of various BMP alternatives for retaining the first inch of runoff from highways and roads in Illinois with the Personal Computer Stormwater Management Model (PCSWMM) and idealized catchment areas. The modeled scenarios included pre-BMP construction when there is no BMP and post-BMP construction with bioswale, infiltration trench and vegetated filter strip. The effects of vegetated covers such as turf or prairie grass on infiltration of various soil types with and without BMPs were also evaluated. For all scenarios, one-inch rainfall 24-hour accumulated precipitation was applied. Typical dimensions and sizing for BMPs were extracted from Illinois Department of Transportation (IDOT) projects. This study found that runoff reduction for bioswale, infiltration trench, and vegetated filter strip are 70 to 83%; 100%; and 68 to 78%, respectively. Results also showed that prairie grass cover is more effective than turf grass in reducing runoff on various soil types.

Reliability analysis for evaluation of factors affecting pollutant load reduction in urban stormwater BMP systems

Detention basins are used in best management practices (BMPs) of urban stormwater systems, and total suspended solids (TSS) are used as an indicator of urban nonpoint-source pollutant. To characterize the uncertainty of BMP effluent loads resulting from uncertainty in BMP performance models, this study incorporated uncertainty analysis into a model that predicts the performance of stormwater BMPs based on watershed imperviousness, BMP volume, and BMP surface area. The objective of this study was to examine an approach to urban stormwater BMPs for use in performance analyses. The k-C* model, which incorporates uncertainty analysis, was applied to the uncertainty of stormwater effluent concentrations in urban stormwater systems. To characterize the uncertainty of BMP effluent loads, frequency analysis of the runoff volume and BMP overflow was done, and the load frequency curve (LFC) was simulated with and without BMP conditions, and then verified using the observed TSS load. Finally, the effects of watershed imperviousness, BMP volume, and BMP surface area were investigated using reliability analysis. The results of this study could be used to estimate the appropriate BMP size to achieve a specific watershed-runoff-pollutant load. They could also be used to produce appropriate BMPs to meet the defined nonpoint-source pollutant regulations, including the total maximum daily load.

Suburban watershed nitrogen retention: Estimating the effectiveness of stormwater management structures

Excess nitrogen (N) is a primary driver of freshwater and coastal eutrophication globally, and urban stormwater is a rapidly growing source of N pollution. Stormwater best management practices (BMPs) are used widely to remove excess N from runoff in urban and suburban areas, and are expected to perform under a wide variety of environmental conditions. Yet the capacity of BMPs to retain excess N varies; and both the variation and the drivers thereof are largely unknown, hindering the ability of water resource managers to meet water quality targets in a cost-effective way. Here, we use structured expert judgment (SEJ), a performance-weighted method of expert elicitation, to quantify the uncertainty in BMP performance under a range of site-specific environmental conditions and to estimate the extent to which key environmental factors influence variation in BMP performance. We hypothesized that rain event frequency and magnitude, BMP type and size, and physiographic province would significantly influence the experts’ estimates of N retention by BMPs common to suburban Piedmont and Coastal Plain watersheds of the Chesapeake Bay region. Expert knowledge indicated wide uncertainty in BMP performance, with N removal efficiencies ranging from 40%. Experts believed that the amount of rain was the primary identifiable source of variability in BMP efficiency, which is relevant given climate projections of more frequent heavy rain events in the mid-Atlantic. To assess the extent to which those projected changes might alter N export from suburban BMPs and watersheds, we combined downscaled estimates of rainfall with distributions of N loads for different-sized rain events derived from our elicitation. The model predicted higher and more variable N loads under a projected future climate regime, suggesting that current BMP regulations for reducing nutrients may be inadequate in the future.

Challenges and a Strategy for Agricultural BMP Monitoring and Remediation of Nitrate Contamination in Unconsolidated Aquifers

AbstractNitrate in groundwater and surface water is among the most common contamination problems in the world. Efforts to reduce the loss of excess nutrients at the regional scale currently focus on Best Management Practices (BMPs) designed to facilitate the optimal use of fertilizers, adjusted for specific site conditions. Performance monitoring of regional BMPs has proven to be problematic owing to the large areal scales, the inherent heterogeneity of nutrient mobility on landscapes and in the subsurface, and the extended time lag between implementation and overall improvements in groundwater quality. In order to shorten the time for useful assessments of progress and for the beneficial results to be realized, a strategy is proposed here with specific application to unconsolidated granular aquifers. First, a novel approach for quantifying BMP performance in the short term is demonstrated involving the monitoring of transient nitrate storage in the unsaturated zone. Secondly, a temporary remediation method based on in situ denitrification is implemented for reducing nitrate levels in public supply wells in the interim period until the full influence of the regional nutrient management BMPs is realized. The remediation approach incorporates a passive component that necessitates enhanced site characterization methods including high definition assessments of aquifer properties and groundwater velocity. The preliminary findings from a series of field investigations conducted between 2004 and 2011 at a site in southern Ontario indicate that this combined two‐step strategy may be capable of providing short‐term quantifiable evidence of BMP performance and also of attenuating nitrate to desirable levels during the time lag period between implementation of the BMPs and the arrival of their desired beneficial effects on the quality of public well water supplies. This may avoid the need to construct permanent above‐ground water treatment facilities that could eventually become redundant.

Enhancing a rainfall-runoff model to assess the impacts of BMPs and LID practices on storm runoff

Best management practices (BMPs) and low impact development (LID) practices are increasingly being used as stormwater management techniques to reduce the impacts of urban development on hydrology and water quality. To assist planners and decision-makers at various stages of development projects (planning, implementation, and evaluation), user-friendly tools are needed to assess the effectiveness of BMPs and LID practices. This study describes a simple tool, the Long-Term Hydrologic Impact Assessment-LID (L-THIA-LID), which is enhanced with additional BMPs and LID practices, improved approaches to estimate hydrology and water quality, and representation of practices in series (meaning combined implementation). The tool was used to evaluate the performance of BMPs and LID practices individually and in series with 30 years of daily rainfall data in four types of idealized land use units and watersheds (low density residential, high density residential, industrial, and commercial). Simulation results were compared with the results of other published studies. The simulated results showed that reductions in runoff volume and pollutant loads after implementing BMPs and LID practices, both individually and in series, were comparable with the observed impacts of these practices. The L-THIA-LID 2.0 model is capable of assisting decision makers in evaluating environmental impacts of BMPs and LID practices, thereby improving the effectiveness of stormwater management decisions.

Nitrogen Removal by Stormwater Management Structures: A Data Synthesis

AbstractA comprehensive synthesis of data from empirically based published studies and a widely used stormwater best management practice (BMP) database were used to assess the variability in nitrogen (N) removal performance of urban stormwater ponds, wetlands, and swales and to identify factors that may explain this variability. While the data suggest that BMPs were generally effective on average, removal efficiencies of ammonium (NH4), nitrate (NO3), and total nitrogen (TN) were highly variable ranging from negative (i.e., BMPs acting as sources of N) to 100%. For example, removal of NO3 varied from (median ±1 SD) −15 ± 49% for dry ponds, 32 ± 120% for wet ponds, 58 ± 210% for wetlands, and 37 ± 29% for swales. Across the same BMP types, TN removal was 27 ± 24%, 40 ± 31%, 61 ± 30%, and 50 ± 29%. NH4 removal was 9 ± 36%, 29 ± 72%, 31 ± 24%, and 45 ± 34%. BMP size, age, and location explained some of the variability. For example, small and shallow ponds and wetlands were more effective than larger, deeper ones in removing N. Despite well‐known intra‐annual variation in N fluxes, most measurements have been made over short time periods using concentrations, not flow‐weighted N fluxes. Urban N export is increasing in some areas as large storms become more frequent. Thus, accounting for the full range of BMP performance under such conditions is crucial. A select number of long‐term flux‐based BMP studies that rigorously measure rainfall, hydrology, and site conditions could improve BMP implementation.

Effects of Surface Area and Inflow on the Performance of Stormwater Best Management Practices with Uncertainty Analysis

The performance of stormwater best management practices (BMPs) is affected by BMP geometric and hydrologic factors. The objective of this study was to investigate the effect of BMP surface area and inflow on BMP performance using the k-C* model with uncertainty analysis. Observed total suspended solids (TSS) from detention basins and retention ponds data sets in the International Stormwater BMP Database were used to build and evaluate the model. Detention basins are regarded as dry ponds because they do not always have water, whereas retention ponds have a permanent pool and are considered wet ponds. In this study, Latin hypercube sampling (LHS) was applied to consider uncertainty in both influent event mean concentration (EMC), C(in), and the areal removal constant, k. The latter was estimated from the hydraulic loading rate, q, through use of a power function relationship. Results show that effluent EMC, C(out), decreased as inflow decreased and as BMP surface area increased in both detention basins and retention ponds. However, the change in C(out), depending on inflow and BMP surface area for detention basins, differed from the change in C(out) for retention ponds. Specifically, C(in) was more dominantly associated with the performance of the k-C* model of detention basins than were BMP surface area and inflow. For retention ponds, however, results suggest that BMP surface area and inflow both influenced changes in C(out) as well as C(in). These results suggest that sensitive factors in the performance of the k-C* model are limited to C(in) for detention basins, whereas BMP surface area, inflow, and C(in) are important for retention ponds.

Barriers to adopting satellite remote sensing for water quality management

Sustainable practices require a long-term commitment to creating solutions to environmental, social, and economic issues. The most direct way to ensure that management practices achieve sustainability is to monitor the environment. Remote sensing technology has the potential to accelerate the engagement of communities and managers in the implementation and performance of best management practices. Over the last few decades, satellite technology has allowed measurements on a global scale over long time periods, and is now proving useful in coastal waters, estuaries, lakes, and reservoirs, which are relevant to water quality managers. Comprehensive water quality climate data records have the potential to provide rapid water quality assessments, thus providing new and enhanced decision analysis methodologies and improved temporal/spatial diagnostics. To best realize the full application potential of these emerging technologies an open and effective dialogue is needed between scientists, policy makers, environmental managers, and stakeholders at the federal, state, and local levels. Results from an internal US Environmental Protection Agency qualitative survey were used to determine perceptions regarding the use of satellite remote sensing for monitoring water quality. The goal of the survey was to begin understanding why management decisions do not typically rely on satellite-derived water quality products.

Assessing uncertainty in best management practice effectiveness under future climate scenarios

AbstractUncertainty of best management practice (BMP) performance in future climates is an important consideration for water resources managers. The objective of this study was to quantify the level of uncertainty in performance of seven agricultural BMPs due to climate change in reducing sediment, total nitrogen, and total phosphorus loads. The Soil and Water Assessment Tool coupled with mid‐21st century climate data from the Community Climate System Model were used to develop climate change scenarios for the Tuttle Creek Lake Watershed of Kansas and Nebraska. Uncertainty level of each BMP was determined using Latin Hypercube Sampling, a constrained Monte Carlo sampling technique. Samples were taken from distributions of several variables (monthly precipitation, temperature, CO2, and BMP implementation parameters). Cumulative distribution functions were constructed for each BMP, pollutant, and climate scenario combination. Results demonstrated that BMP performance uncertainty is amplified in the extreme climate scenario. Among BMPs, native grass replacement generally had higher uncertainty level but also had the greatest reductions. This study highlights the importance of incorporating uncertainty analysis into mitigation strategies aiming to reduce negative impacts of climate change on water resources. Copyright © 2013 John Wiley & Sons, Ltd.

Implementation of BMP Strategies for Adaptation to Climate Change and Land Use Change in a Pasture-Dominated Watershed

Implementing a suite of best management practices (BMPs) can reduce non-point source (NPS) pollutants from various land use activities. Watershed models are generally used to evaluate the effectiveness of BMP performance in improving water quality as the basis for watershed management recommendations. This study evaluates 171 management practice combinations that incorporate nutrient management, vegetated filter strips (VFS) and grazing management for their performances in improving water quality in a pasture-dominated watershed with dynamic land use changes during 1992–2007 by using the Soil and Water Assessment Tool (SWAT). These selected BMPs were further examined with future climate conditions (2010–2069) downscaled from three general circulation models (GCMs) for understanding how climate change may impact BMP performance. Simulation results indicate that total nitrogen (TN) and total phosphorus (TP) losses increase with increasing litter application rates. Alum-treated litter applications resulted in greater TN losses, and fewer TP losses than the losses from untreated poultry litter applications. For the same litter application rates, sediment and TP losses are greater for summer applications than fall and spring applications, while TN losses are greater for fall applications. Overgrazing management resulted in the greatest sediment and phosphorus losses, and VFS is the most influential management practice in reducing pollutant losses. Simulations also indicate that climate change impacts TSS losses the most, resulting in a larger magnitude of TSS losses. However, the performance of selected BMPs in reducing TN and TP losses was more stable in future climate change conditions than in the BMP performance in the historical climate condition. We recommend that selection of BMPs to reduce TSS losses should be a priority concern when multiple uses of BMPs that benefit nutrient reductions are considered in a watershed. Therefore, the BMP combination of spring litter application, optimum grazing management and filter strip with a VFS ratio of 42 could be a promising alternative for use in mitigating future climate change.

Treatability aspects of urban stormwater stressors

Pollution from diffuse sources (pollution from contaminants picked up and carried into surface waters by stormwater runoff) has been identified as a significant source of water quality problems in the U.S. scientists and engineers continue to seek solutions that will allow them to optimize existing technologies and develop new ones that will provide the best possible protection to people, wildlife, and the environment. This paper addresses the various pollutants or stressors in urban stormwater, including flow (shear force), pathogens, suspended solids/sediment, toxicants (organic and metals), nutrients, oxygen demanding substances, and coarse solids. A broad overview of the pollutants removed and the removal mechanisms by and of conventional best management practices (BMPs) is also presented. The principal treatment mechanisms of conventional wet ponds, vegetative swales/buffer strips, and wetlands are sedimentation and filtration. These mechanisms have the capability to remove significant amounts of suspended solids or particulate matter and are a vital component of strategies to reduce pollutant loads to receiving waters. In addition, because most of the nation’s receiving water violations are caused by pathogen indicator bacteria, it is of utmost importance that research efforts address this problem. Further research is also needed on the treatment of emerging contaminants in BMPs and on the costs and affects of maintenance and maintenance schedules on the long-term performance of BMPs.

Evaluation of pollutant loads from stormwater BMPs to receiving water using load frequency curves with uncertainty analysis

This study examined pollutant loads released to receiving water from a typical urban watershed in the Los Angeles (LA) Basin of California by applying a best management practice (BMP) performance model that includes uncertainty. This BMP performance model uses the k-C* model and incorporates uncertainty analysis and the first-order second-moment (FOSM) method to assess the effectiveness of BMPs for removing stormwater pollutants. Uncertainties were considered for the influent event mean concentration (EMC) and the aerial removal rate constant of the k-C* model. The storage treatment overflow and runoff model (STORM) was used to simulate the flow volume from watershed, the bypass flow volume and the flow volume that passes through the BMP. Detention basins and total suspended solids (TSS) were chosen as representatives of stormwater BMP and pollutant, respectively. This paper applies load frequency curves (LFCs), which replace the exceedance percentage with an exceedance frequency as an alternative to load duration curves (LDCs), to evaluate the effectiveness of BMPs. An evaluation method based on uncertainty analysis is suggested because it applies a water quality standard exceedance based on frequency and magnitude. As a result, the incorporation of uncertainty in the estimates of pollutant loads can assist stormwater managers in determining the degree of total daily maximum load (TMDL) compliance that could be expected from a given BMP in a watershed.

Sensitivity Analysis of Best Management Practices Under Climate Change Scenarios1

Woznicki, Sean A. and A. Pouyan Nejadhashemi, 2011. Sensitivity Analysis of Best Management Practices Under Climate Change Scenarios. Journal of the American Water Resources Association (JAWRA) 48(1): 90‐112. DOI: 10.1111/j.1752‐1688.2011.00598.xAbstract: Understanding the sensitivity of best management practices (BMPs) implementation as climate changes will be important for water resources management. The objective of this study was to determine how the sensitivity of BMPs performance vary due to changes in precipitation, temperature, and CO2 using the Soil and Water Assessment Tool. Sediment, total nitrogen, and total phosphorus loads on an annual and monthly basis were estimated before and after implementation of eight agricultural BMPs for different climate scenarios. Downscaled climate change data were obtained from the National Center for Atmospheric Research Community Climate System Model for the Tuttle Creek Lake watershed in Kansas and Nebraska. Using a relative sensitivity index, native grass, grazing management, and filter strips were determined to be the most sensitive for all climate change scenarios, whereas porous gully plugs, no‐tillage, and conservation tillage were the least sensitive on an annual basis. The monthly sensitivity analysis revealed that BMP sensitivity varies largely on a seasonal basis for all climate change scenarios. The results of this research suggest that the majority of agricultural BMPs tested in this study are significantly sensitive to climate change. Therefore, caution should be exercised in the decision‐making processes.

Planning of LID–BMPs for urban runoff control: The case of Beijing Olympic Village

In this paper, a planning analysis of implementing low impact development (LID) type of stormwater best management practices (BMPs) for urban runoff control is presented. The Beijing Olympic Village (BOV) residential area in China was used as a case study. The original BOV stormwater system incorporated some LID BMPs such as porous pavements, green roofs and rainwater cisterns. After the 2008 Olympics, the BOV was converted to a residential complex and some stormwater facilities were modified for landscaping purposes. The performance of the original stormwater management system at the BOV residential area was first evaluated by using the model BMPDSS. BMPDSS is a best management practice (BMP) planning and analysis tool, which is capable of simulating BMP performance and optimizing BMP placement and design. The Storm Water Management Model (SWMM) was used to simulate pipe network hydraulics for the BOV. The present study then examined the performance associated with the BMP modifications for landscaping purposes, and then further BMP modifications designed for enhancing runoff control capabilities of the system. Using the 2008 rainfall data for Beijing, peak flow rate and runoff volume reductions under the three scenarios were calculated by using the coupled SWMM–BMPDSS framework and compared. Optimization analysis for BMP design aimed at achieving either maximum runoff control or total minimum system cost was then conducted. The results were used to form recommendations to the Beijing authorities for modifying the present stormwater management system in order to achieve more runoff control benefits.

Best Management Practices and Long-Term Water Quality Trends in the Everglades Agricultural Area

The Everglades Agricultural Area (EAA) in South Florida, part of the historical Everglades, was initially drained in the early 20th century for agriculture and flood protection. The organic soils have been subject to subsidence caused by organic matter oxidation. Soils are deeper east of Lake Okeechobee compared to soils south of the lake. The area is mostly planted to sugarcane and other crops such as rice, vegetables, and sod. Concerns about quality of water leaving the EAA led to a regulatory program for mandatory best management practices (BMP) since 1995 to reduce phosphorus (P) loads out of the EAA by 25% compared to historical levels. The program is highly successful, with 100% grower participation and exceeding P load reduction required by law. Trend analysis conducted on selected EAA farms, subbasins, and whole basin show, in general, decreasing trends in P concentrations, drainage flow, and P loads. Differences are noted between farms and subbasins due to factors that include rainfall distribution, water management practices, irrigation water quality, soil type/depth, and cropping systems. Water management practices were the dominant factors affecting P loads out of the EAA. Water management research that targets farms with deeper soils is recommended to achieve additional P load reductions. Other practices to improve BMP performance include minimizing generation and transport of sediments from farm canals. The quality of irrigation water from Lake Okeechobee is of concern of its impact on BMP performance.

Influent Pollutant Concentrations as Predictors of Effluent Pollutant Concentrations for Mid-Atlantic Bioretention

The water quality performance of best management practices (BMPs) has been frequently assessed by the removal efficiency metric. Recent findings show that the removal efficiency metric is flawed be...

Assessing Best Management Practice Implementation Strategies under Climate Change Scenarios

As climate changes, the uncertainty of water availability, changing magnitudes of nonpoint-source pollution, and uncertainty of best management practice (BMPs) effectiveness are issues that watershed managers and stakeholders must consider and plan for. The objective of this study was to determine how BMP effectiveness will be affected by climate change using the Soil and Water Assessment Tool (SWAT). Using downscaled monthly precipitation and temperature data output from the Community Climate System Model (CCSM), daily precipitation and temperature data were produced based on observed weather station data for the Tuttle Creek Lake watershed in Kansas and Nebraska. The A1B, A2, and B1 SRES emissions scenarios were compared to historical CCSM model output. Eight agricultural BMPs were physically represented within SWAT and compared across climate scenarios. Water yield, surface runoff, baseflow, sediment load, nitrogen load, and phosphorus load increased in all three future climate scenarios. Terraces, contour farming, and native grass were determined to be the most effective in pollution load reduction and percent efficiency at the field and watershed scales in future scenarios. Porous gully plugs and filter strips showed no significant changes in pollution load or percent reduction. Grazing management, no-tillage, conservation tillage, and grazing management percent and load reduction in future scenarios varied at the field and watershed scales. This study demonstrates that BMP performance in terms of sediment, nitrogen, and phosphorus reduction significantly changes in future climate scenarios at the field scale, while performance generally does not change significantly at the watershed scale.

Incorporating Social Context Variables Into Paired Watershed Designs to Test Nonpoint Source Program Effectiveness1

Prokopy, Linda Stalker, Z. Asligül Göçmen, Jing Gao, Shorna Broussard Allred, Joseph E. Bonnell, Kenneth Genskow, Alicia Molloy, and Rebecca Power, 2011. Incorporating Social Context Variables Into Paired Watershed Designs to Test Nonpoint Source Program Effectiveness. Journal of the American Water Resources Association (JAWRA) 47(1):196-202. DOI: 10.1111/j.1752-1688.2010.00508.x Abstract: In a traditional paired watershed study, watersheds are selected to be as similar as possible so that conclusions may be drawn about the performance of Best Management Practices. We have extended the paired watershed concept to examine the effectiveness of watershed management programs by adding comparative criteria for social characteristics. For four different 8 or 11/12 digit hydrologic unit code (HUC) watersheds in the Midwest, we have piloted a systematic method for selecting paired subwatersheds. First, we developed a list of 11 key variables. Next, a factor analysis was conducted to determine the underlying structure of the 11 input variables. Finally, in each of the four watersheds, potential paired subwatersheds (all 14 digit HUCs) were selected using the factors in a cluster analysis. Informal interviews were then held with key informants in each watershed to provide qualitative assessments of criteria that could impact the comparability of the subwatersheds. This method for selecting paired watersheds should be helpful for other researchers to test the effectiveness of watershed management programs focused on behavior change.

The Runoff Reduction Method

Abstract:The Runoff Reduction Method (RRM) provides an innovative approach to crediting the total performance of stormwater best management practices (BMPs). Total BMP performance refers to the pollutant removal and runoff volume reduction capabilities. The RRM tracks the implementation of stormwater BMPs, including Low Impact Development (LID) strategies such as permeable pavement, rainwater harvesting, downspout disconnection, soil amendments, etc., and credits the appropriate runoff volume reduction, pollutant concentration reduction, or both towards compliance with stormwater quality and quantity requirements. By providing a mechanism to credit the volume reduction associated with these LID strategies the RRM also documents an allowable reduction of the overall size and footprint of structural detention practices, thereby providing an economic incentive for the development community to implement LID providing a better overall solution for minimizing the impact of development on the hydrologic cycle.

Effectiveness of best management practices in improving water quality in a pasture-dominated watershed

The nonpoint source pollution problem can be controlled by implementing various best management practices (BMPs) in the watershed. However, before such practices are adopted, their effectiveness at various spatial and temporal scales must be evaluated. The objective of this research was to evaluate a suite of BMPs in a pasture-dominated watershed in their effectiveness at controlling nutrient losses. A total of 171 different BMP combinations incorporating grazing and pasture management, riparian and buffer zones, and poultry litter applications were evaluated for their effectiveness using the Soil and Water Assessment Tool (SWAT) model. The SWAT model was parameterized using detailed farm and watershed-scale data. The stochasticity in weather was captured by generating 250 various possible weather realizations for a 25-year period, using measured historical climate data for the watershed. Model results indicated that losses of both total nitrogen, mineral phosphorus, and total phosphorus increased with an increase in litter application rates. For the same application rates, greatest losses were predicted for fall application timings compared to spring and summer applications. Overgrazing resulted in greater nutrient losses compared to baseline conditions for all application rates, timings, and litter characteristics, indicating that overgrazing of pasture areas must be avoided if any improvement in the water quality is to be expected. Variability in weather conditions significantly affected BMP performance; under certain weather conditions, an increase in pollutant losses can be greater than reductions due to BMPs implemented in the watershed. Buffer strips and grazing management were two most important BMPs affecting the losses of total nitrogen and total phosphorus from the pasture areas.