WATERSHED OPTIMIZATION OF AGRICULTURAL BEST MANAGEMENT PRACTICES: CONTINUOUS SIMULATION VERSUS DESIGN STORMS1

ABSTRACT: Nonpoint source (NPS) models and expert opinions are often used to prescribe best management practices (BMPs) for controlling NPS pollution. An optimization algorithm (e.g., a genetic algorithm, or GA) linked with a NPS model (e.g., Annualized AGricultural Nonpoint Source pollution model, or AnnAGNPS), can be used to more objectively prescribe BMPs and to optimize NPS pollution control measures by maximizing pollutant reduction and net monetary return from a watershed. Pollutant loads from design storms and annual loads from a continuous simulation can both be used for optimizing BMP schemes. However, which strategy results in a better solution (in terms of providing water quality protection) for a watershed is not clear. The specific objective of the study was to determine the differences in watershed pollutant loads, in an experimental watershed in Pennsylvania, resulting from optimization analyses performed using pollutant loads from a series of five 2‐yr 24‐hr storm events, a series of five 5‐yr 24‐hr storm events, and cumulative pollutant loads from a continuous simulation of five years of weather data. For each of these three different event alternatives, 100 near optimal solutions (BMP schemes) were generated. Sediment (Sed), sediment nitrogen (SedN), dissolved N (SolN), sediment organic carbon (SedOC), and sediment phosphorus (SedP) loads from a different five‐year period (an evaluation period) suggest that the optimal BMP schemes resulting from the use of annual cumulative pollutant loads from a continuous simulation of five years of weather data provide smaller cumulative NPS pollutant loads at the watershed outlet.     

Optimal nonpoint source pollution control strategies for a reservoir watershed in Taiwan

The purpose of this study is to develop a model for optimal nonpoint source pollution control for the Fei-Tsui Reservoir watershed in Northern Taiwan. Several structural best management practices (BMPs) are selected to treat stormwater runoff. The complete model consists of two interacting components: an optimization model based on discrete differential dynamic programming (DDDP) and a zero-dimensional reservoir water quality model. A predefined procedure is used to locate suitable sites for construction of various selected BMPs in the watershed. In the optimization model, the objective function is to find the best combination of BMP type and placement, which minimizes the total construction and operation, maintenance, and repair (OMR) costs of the BMPs. The constraints are the water quality standards for total phosphorus (TP) and total suspended solids (TSS) concentrations in the reservoir. A zero-dimensional reservoir water quality model of the Vollenweider type is embedded in the optimization framework to simulate pollutant concentrations in Fei-Tsui Reservoir. The resulting optimal cost and benefit of water quality improvement are depicted by the model-derived trade-off curves. The modeling framework developed in the present study could be used as an efficient tool for planning a watershed-wide implementation of BMPs for mitigating stormwater pollution impact on the receiving water bodies.     

Agricultural BMP Effectiveness and Dominant Hydrological Flow Paths: Concepts and a Review

We present a conceptual framework that relates agricultural best management practice (BMP) effectiveness with dominant hydrological flow paths to improve nonpoint source (NPS) pollution management. We use the framework to analyze plot, field and watershed scale published studies on BMP effectiveness to develop transferable recommendations for BMP selection and placement at the watershed scale. The framework is based on the location of the restrictive layer in the soil profile and distinguishes three hydrologic land types. Hydrologic land type A has the restrictive layer at the surface and BMPs that increase infiltration are effective. In land type B1, the surface soil has an infiltration rate greater than the prevailing precipitation intensity, but there is a shallow restrictive layer causing lateral flow and saturation excess overland flow. Few structural practices are effective for these land types, but pollutant source management plans can significantly reduce pollutant loading. Hydrologic land type B2 has deep, well‐draining soils without restrictive layers that transport pollutants to groundwater via percolation. Practices that increased pollutant residence time in the mixing layer or increased plant water uptake were found as the most effective BMPs in B2 land types. Matching BMPs to the appropriate land type allows for better targeting of hydrologically sensitive areas within a watershed, and potentially more significant reductions of NPS pollutant loading.     

A LONG‐TERM,WATERSHED‐SCALE,EVALUATION OF THE IMPACTS OF ANIMAL WASTE BMPs ON INDICATOR BACTERIA CONCENTRATIONS1

ABSTRACT: Driven by increasing concerns about bacterial pollution from agricultural sources, states such as Virginia have initiated cost sharing programs that encourage the use of animal waste best management practices (BMPs) to control this pollution. Although a few studies have shown that waste management BMPs are effective at the field scale, their effectiveness at the watershed scale and over the long term is unknown. The focus of this research was to evaluate the effectiveness of BMPs in reducing bacterial pollution at the watershed scale and over the long term. To accomplish this goal, a 1,163 ha watershed located in the Piedmont region of Virginia was monitored over a ten‐year period. Fecal coliforms (FC) and fecal streptococci (FS) were measured as indicators of bacterial pollution. A pre‐BMP versus post‐BMP design was adopted. Major BMPs implemented were manure storage facilities, stream fencing, water troughs, and nutrient management. Seasonal Kendall trend analysis revealed a significant decreasing trend during the post‐BMP period for FC concentrations at the watershed outlet, but not at the subwatershed level. Implementation of BMPs also resulted in a significant reduction in the geometric mean of FS concentrations. FC concentrations in streamflow at the watershed outlet exceeded the Virginia primary standard 86 and 74 percent of the time during pre‐BMP and post‐BMP periods, respectively. Corresponding exceedances for the secondary standard were 50 and 41 percent. Violations decreased only slightly during the post‐BMP period. The findings of this study suggest that although BMP implementation can be expected to accomplish some improvement in water quality, BMP implementation alone may not ensure compliance with current water quality standards.     

Identifying Key Factors in Homeowner’s Adoption of Water Quality Best Management Practices

The recognition of the significance of the residential environment in contributing to non-point source (NPS) pollution and the inherently dispersed nature of NPS pollution itself that presents significant challenges to effective regulation has led to the creation and dissemination of best management practices (BMPs) that can reduce the impacts of NPS pollution (Environmental Protection Agency US, Protecting water quality from urban runoff, http://www.epa.gov/npdes/pubs/nps_urban-facts_final.pdf, 2003). However, very few studies have examined the factors that influence the adoption of BMPs by residential homeowners, despite the fact that residential environments have been identified as one of the most significant contributors to NPS pollution. Given this need, the purpose of this project was to explore how demographic and knowledge-based factors predict adoption of residential BMPs in an urbanizing watershed in Northern Illinois using statistical analyses of survey data collected as part of a watershed planning process. The findings indicate that broad knowledge of BMPs is the strongest predictor of use for a specific BMP. Knowledge of BMPs is strongly correlated with their use, which reinforces the need for educational programs, even among those assumed to be knowledgeable about BMPs.     

OPTIMIZATION PROCEDURE FOR COST EFFECTIVE BMP PLACEMENT AT A WATERSHED SCALE1

ABSTRACT: A combinatorial optimization procedure for best management practice (BMP) placement at the watershed level facilitates selection of cost effective BMP scenarios to control non point source (NFS) pollution. A genetic algorithm (GA) was selected from among several optimization heuristics. The GA combines an optimization component written in the C++ language with spatially variable NFS pollution prediction and economic analysis components written within the Arc View geographic information system. The procedure is modular in design, allowing for component modifications while maintaining the basic conceptual framework. An objective function was developed to lexicographically optimize pollution reduction followed by cost increase. Scenario cost effectiveness is then calculated for scenario comparisons. The NPS pollutant fitness score allows for evaluation of multiple pollutants, based on prioritization of each pollutant. The economic component considers farm level public and private costs, cost distribution, and land area requirements. Development of a sediment transport function, used with the Universal Soil Loss Equation, allows the optimization procedure to run within a reasonable timeframe. The procedure identifies multiple near optimal solutions, providing an indication of which fields have a more critical impact on overall cost effectiveness and flexibility in the final solution selected for implementation. The procedure was demonstrated for a 1,014‐ha watershed in the Ridge and Valley physiographic region of Virginia.     

Cost‐Effective Placement of Best Management Practices in a Watershed: Lessons Learned from Conservation Effects Assessment Project

This article reviews the key, cross‐cutting findings concerning watershed‐scale cost‐effective placement of best management practices (BMPs) emerging from the National Institute of Food and Agriculture Conservation Effects Assessment Project (CEAP) competitive grants watershed studies. The synthesis focuses on two fundamental aspects of the cost‐effectiveness problem: (1) how to assess the location‐ and farmer‐specific costs of BMP implementation, and (2) how to decide on which BMPs need to be implemented and where within a given watershed. Major lessons learned are that (1) data availability remains a significant limiting factor in capturing within‐watershed BMP cost variability; (2) strong watershed community connections help overcome the cost estimation challenges; (3) detailing cost components facilitates the transferability of estimates to alternative locations and/or economic conditions; and (4) implicit costs vary significantly across space and farmers. Furthermore, CEAP studies showed that (5) evolutionary algorithms provide workable ways to identify cost‐effective BMP placements; (6) tradeoffs between total conservation costs and watershed‐scale cost‐effective water quality improvements are commonly large; (7) quality baseline information is essential to solving cost‐effectiveness problem; and (8) systemic and modeling uncertainties alter cost‐effective BMP placements considerably.     

An Open Source GIS‐Based Decision Support System for Watershed Evaluation of Best Management Practices

Economic costs, water quantity/quality benefits, and cost effectiveness of agricultural best management practices (BMPs) at a watershed scale are increasingly examined using integrated economic‐hydrologic models. However, these models are typically complex and not user‐friendly for examining the effects of various BMP scenarios. In this study, an open source geographic information system (GIS)‐based decision support system (DSS), named the watershed evaluation of BMPs (WEBs), was developed for creating BMP scenarios and simulating economic costs and water quantity/quality benefits at farm field, subbasin, and watershed scales. This DSS or WEBs interface integrated a farm economic model, the Soil and Water Assessment Tool (SWAT), and an optimization model within Whitebox Geospatial Analysis Tools (GAT), an open source GIS software. The DSS was applied to the 14.3‐km² Gully Creek watershed, a coastal watershed in southern Ontario, Canada that drains directly into Lake Huron. BMPs that were evaluated included conservation tillage, nutrient management, cover crop, and water and sediment control basins. In addition to assessing economic costs, water quantity/quality benefits, and cost effectiveness of BMPs, the DSS can be also used to examine prioritized BMP types/locations and corresponding economic and water quantity/quality tradeoffs in the study watershed based on environmental targets or budget constraints. Further developments of the DSS including interface transfer to other watersheds are also discussed. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Combined monitoring and modeling indicate the most effective agricultural best management practices

Although water quality problems associated with agricultural nonpoint source (NPS) pollution have prompted the rapid and widespread adoption of a variety of so called "best management practices" (BMPs), there have been few realistic efforts to assess their combined effectiveness in reducing NPS pollution. This study used the Variable Source Loading Function (VSLF) model, a distributed watershed model, to simulate phosphorus (P) loading from an upstate New York dairy farm before and after the implementation of a suite of BMPs. With minimal calibration, the model calculates the dissolved P (DP) losses from impervious surfaces (e.g., barnyards), the plant/soil complex, field-applied manure, and loads associated with baseflow conditions. The simulated DP loads agreed well with measured loads for both the pre-BMP and post-BMP periods. More importantly, results showed that BMPs reduced DP loads by 35%, which is over half of the expected reduction if all manure was removed from the watershed, i.e., approximately 50% reduction. The model results indicate that had no BMPs been installed DP loads would be approximately 37% greater than observed at the watershed outlet. The most effective BMPs were those that disassociated pollutant loading areas from areas prone to generating runoff, i.e., hydrologically sensitive areas. By contrast, attempts to reduce P content in manure were somewhat less effective. This study demonstrates that a combination of distributed, mechanistic modeling and long-term monitoring provides better insights into the effectiveness of water quality protection efforts than either individually.     

Optimizing Agricultural Best Management Practices in a Lake Erie Watershed

Implementing agricultural best management practices (BMPs) is influenced by a balance of desired environmental outcomes, economic feasibility, and stakeholder familiarity, the latter taken to be related to BMP acceptability. To explore this balance, we developed a multi‐objective decision support system for allocating BMP type and placement by coupling the Soil and Water Assessment Tool with a nondominated sorted genetic algorithm that minimizes total phosphorus (TP) yields from agricultural hydrologic response units (HRUs) and costs, while using stakeholder BMP familiarity as a constraint; conventional tillage, no tillage, nutrient management, riparian buffers, and contour cropping were explored. Using constraints representing current conditions, the optimization resulted in 59.6 to 81.0% reduction in agricultural TP yield from HRUs at costs ranging between US $0.8 and US $5.3 million. The constrained optimization tended to select mostly single BMPs or at most two BMPs for a given HRU due to these BMPs having higher acceptability to stakeholders. In contrast, the unconstrained case, representing full familiarity, selected 2‐ and 3‐BMP applications. There was little difference in costs between the constrained and unconstrained cases below an 80% TP yield reduction; however, significant differences were found at larger reductions, supporting the value of stakeholder education and extension efforts. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

A WATER QUALITY‐BASED APPROACH FOR WATERSHED WIDE BMP STRATEGIES1

ABSTRACT: Watershed management strategies generally involve controlling nonpoint source pollution by implementing various best management practices (BMPs). Currently, stormwater management programs in most states use a performance‐based approach to implement onsite BMPs. This approach fails to link the onsite BMP performance directly to receiving water quality benefits, and it does not take into account the combined treatment effects of all the stormwater management practices within a watershed. To address these issues, this paper proposes a water quality‐based BMP planning approach for effective nonpoint source pollution control at a watershed scale. A coupled modeling system consisting of a watershed model (HSPF) and a receiving water quality model (CE‐QUAL‐W2) was developed to establish the linkage between BMP performance and receiving water quality targets. A Monte Carlo simulation approach was utilized to develop alternative BMP strategies at a watershed level. The developed methodology was applied to the Swift Creek Reservoir watershed in Virginia, and the results show that the proposed approach allows for the development of BMP strategies that lead to full compliance with water quality requirements.     

LAWS AND PROGRAMS FOR CONTROLLING NONPOINT SOURCE POLLUTION IN FOREST AREAS1

ABSTRACT: Recent federal legislation strengthened nonpoint source pollution regulations and helped to support and standardize pollution control efforts. A comprehensive review of current state and federal programs for forest areas reveals a substantial increase in agency water quality protection activities. These new efforts emphasize monitoring to assess the use and effectiveness of best management practices (BMPs). Recent monitoring reveals that BMP use is increasing and that such use typically maintains water quality within standards. However, information is generally lacking about the cost effectiveness of BMP programs. Carefully designed and executed monitoring is the key to better specification of BMPs and more cost effective water quality protection. (KEY TERMS: water quality; nonpoint source pollution; water law; watershed management; forestry; best management practices.)     

A Benefit‐Cost Analysis of Total Maximum Daily Load Implementation1

Abstract: Total Maximum Daily Load (TMDL) implementation generates benefits and costs from water quality improvements, which are rarely quantified. This analysis examines a TMDL written to address bacteria and aquatic‐life‐use impairments on Abrams and Opequon Creeks in Virginia. Benefits were estimated using a contingent valuation survey of local residents. Costs were based on the number and type of best management practices (BMPs) necessary to achieve TMDL pollution reduction goals. BMPs were quantified using watershed‐scale water quality simulation models (Generalized Watershed Loading Function and Hydrological Simulation Program‐FORTRAN). Based on our projections, the costs to achieve TMDL induced pollution reduction goals outweigh the estimated benefits. Benefit‐cost ratios ranged between 0.1 and 0.3.     

BMP IMPACTS ON WATERSHED RUNOFF,SEDIMENT, AND NUTRIENT YIELDS1

ABSTRACT: To quantify the effectiveness of best management practice (BMP) implementation on runoff, sediment, and nutrient yields from a watershed, the Nomini Creek watershed and water quality monitoring project was initiated in 1985, in Westmoreland County, Virginia. The changes in nonpoint source (NPS) loadings resulting from BMPs were evaluated by comparing selected parameters from data series obtained before, during, and after periods of BMP implementation. The results indicated that the watershed-averaged curve number, sediment, and nutrient (N and P) concentrations were reduced by approximately 5, 20, and 40 percent, respectively, due to BMP implementation. The nutrient yield model developed by Frere et al. (1980) was applied to the water quality parameters from 175 storms, but it failed to adequately describe the observed phenomena. Seasonal changes in nutrient availability factors were not consistent with field conditions, nor were they significantly different in the pm- and post-BMP periods. An extended period of monitoring, with intensive BMP implementation over a larger portion of the watershed, is required to identify BMP effectiveness.     

WATERSHEDSS: A DECISION SUPPORT SYSTEM FOR WATERSHED-SCALE NONPOINT SOURCE WATER QUALITY PROBLEMS1

ABSTRACT: A significant portion of all pollutants entering surface waters (streams, lakes, estuaries, and wetlands) derives from non-point source (NPS) pollution and, in particular, agricultural activities. The first step in restoring a water resource is to focus on the primary water quality problem in the watershed. The most appropriate NPS control measures, which include best management practices (BMPs) and landscape features, such as wetlands and riparian areas, can then be selected and positioned to minimize or mitigate the identified pollutant(s). A computer-based decision sup. port and educational software system, WATERSHEDSS (WATER, Soil, and Hydro-Environmental Decision Support System), has been developed to aid managers in defining their water quality problems and selecting appropriate NPS control measures. The three primary objectives of WATERSHEDSS are (1) to transfer water quality and land treatment information to watershed managers in order to assist them with appropriate land management/land treatment decisions; (2) to assess NPS pollution in a watershed based on user-supplied information and decisions; and (3) to evaluate, through geographical information systems-assisted modeling, the water quality effects of alternative land treatment scenarios. WATERSHEDSS is available on the World Wide Web (Web) at http://h2osparc.wq.ncsu.edu .     

Water Quality Assessment of Large‐scale Bioenergy Cropping Scenarios for the Upper Mississippi and Ohio‐Tennessee River Basins

The Upper Mississippi River Basin and Ohio‐Tennessee River Basin comprise the majority of the United States Corn Belt region, resulting in degraded Mississippi River and Gulf of Mexico water quality. To address the water quality implications of increased biofuel production, biofuel scenarios were tested with a Soil and Water Assessment Tool (SWAT) model revision featuring improved biofuel crop representation. Scenarios included corn stover removal and the inclusion of two perennial bioenergy crops, switchgrass and Miscanthus, grown on marginal lands (slopes >2% and erosion rates >2 t/ha) and nonmarginal lands. The SWAT model estimates show water quality is not very sensitive to stover removal. The perennial bioenergy crops reduce simulated sediment, nitrogen (N), and phosphorus (P) yields by up to 60%. Simulated sediment and P reductions in marginal lands were generally twice that occurring in the nonmarginal lands. The highest unit area reductions of N occurred in the less sloping tile‐drained lands. Productivity showed corn grain yield was independent from stover removal, while yields of the two perennial bioenergy crops were similar in the marginal and nonmarginal lands. The results suggest planning for biofuel production in the Corn Belt could include the removal of stover in productive corn areas, and the planting of perennial bioenergy crops in marginal land and in low‐sloped tile‐drained areas characterized by high N pollution. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Assessing Watershed-Scale, Long-Term Hydrologic Impacts of Land-Use Change Using a GIS-NPS Model

Land-use change, dominated by an increase in urban/impervious areas, has a significant impact on water resources. This includes impacts on nonpoint source (NPS) pollution, which is the leading cause of degraded water quality in the United States. Traditional hydrologic models focus on estimating peak discharges and NPS pollution from high-magnitude, episodic storms and successfully address short-term, local-scale surface water management issues. However, runoff from small, low-frequency storms dominates long-term hydrologic impacts, and existing hydrologic models are usually of limited use in assessing the long-term impacts of land-use change. A long-term hydrologic impact assessment (L-THIA) model has been developed using the curve number (CN) method. Long-term climatic records are used in combination with soils and land-use information to calculate average annual runoff and NPS pollution at a watershed scale. The model is linked to a geographic information system (GIS) for convenient generation and management of model input and output data, and advanced visualization of model results. The L-THIA/NPS GIS model was applied to the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana, USA. Historical land-use scenarios for 1973, 1984, and 1991 were analyzed to track land-use change in the watershed and to assess impacts on annual average runoff and NPS pollution from the watershed and its five subbasins. For the entire watershed between 1973 and 1991, an 18% increase in urban or impervious areas resulted in an estimated 80% increase in annual average runoff volume and estimated increases of more than 50% in annual average loads for lead, copper, and zinc. Estimated nutrient (nitrogen and phosphorus) loads decreased by 15% mainly because of loss of agricultural areas. The L-THIA/NPS GIS model is a powerful tool for identifying environmentally sensitive areas in terms of NPS pollution potential and for evaluating alternative land use scenarios for NPS pollution management.     

Flood Risk Reduction from Agricultural Best Management Practices

Best management practices (BMPs) play an important role in improving impaired water quality from conventional row crop agriculture. In addition to reducing nutrient and sediment loads, BMPs such as fertilizer management, reduced tillage, and cover crops could alter the hydrology of agricultural systems and reduce surface water runoff. While attention is devoted to the water quality benefits of BMPs, the potential co‐benefits of flood loss reduction are often overlooked. This study quantifies the effects of selected commonly applied BMPs on expected flood loss to agricultural and urban areas in four Iowa watersheds. The analysis combines a watershed hydrologic model, hydraulic model outputs, and a loss estimation model to determine relationships between hydrologic changes from BMP implementations and annual economic flood loss. The results indicate a modest reduction in peak discharge and economic loss, although loss reduction is substantial when urban centers or other high‐value assets are located downstream in the watershed. Among the BMPs, wetlands, and cover crops reduce losses the most. The research demonstrates that watershed‐scale implementation of agricultural BMPs could provide benefits of flood loss reduction in addition to water quality improvements.     

EFFECTWENESS OF INTEGRATED STORMWATER MANAGEMENT IN A PORTLAND,OREGON, WATERSHED1

ABSTRACT: The City of Portland's stormwater management program, winner of EPA's Environmental Excellence Award for 1996, is committed to partnership-based, cost-effective, “green” approaches to healthy neighborhoods and water quality. The stormwater program encourages innovative, non-structural pollution reduction techniques like native landscaping, stormwater pollution reduction bioswales and ponds, and public involvement and education. Effectiveness of stormwater best management practices (BMPs) has been difficult to determine on a citywide basis. Recognizing this problem, the City of Portland launched the Parkrose Pilot Project in 1994 to test the effectiveness of a wide range of BMPs in a small watershed in north Portland, the Parkrose catchment, and monitor the results prior to citywide implementation. This catchment was selected because of its small size (144 acres), its representative mix of land uses, and an extensive record of water quality monitoring data. This paper examines the City's strategy in selecting the Parkrose study area as a pilot watershed, the BMPs chosen for use in the watershed, and the results of the program to date. Final success of the Parkrose project will be gauged by the attainment of measurable pollution reduction within the catchment while providing opportunities for meaningful participation by the local community in achieving water quality. Involvement by private citizens in the community is crucial to the success of the project and to ensure compliance with the federal mandate to reduce pollutants to the maximum extent practicable.