Application of a Multi-Objective Optimization Method to Provide Least Cost Alternatives for NPS Pollution Control

Nonpoint source (NPS) pollutants such as phosphorus, nitrogen, sediment, and pesticides are the foremost sources of water contamination in many of the water bodies in the Midwestern agricultural watersheds. This problem is expected to increase in the future with the increasing demand to provide corn as grain or stover for biofuel production. Best management practices (BMPs) have been proven to effectively reduce the NPS pollutant loads from agricultural areas. However, in a watershed with multiple farms and multiple BMPs feasible for implementation, it becomes a daunting task to choose a right combination of BMPs that provide maximum pollution reduction for least implementation costs. Multi-objective algorithms capable of searching from a large number of solutions are required to meet the given watershed management objectives. Genetic algorithms have been the most popular optimization algorithms for the BMP selection and placement. However, previous BMP optimization models did not study pesticide which is very commonly used in corn areas. Also, with corn stover being projected as a viable alternative for biofuel production there might be unintended consequences of the reduced residue in the corn fields on water quality. Therefore, there is a need to study the impact of different levels of residue management in combination with other BMPs at a watershed scale. In this research the following BMPs were selected for placement in the watershed: (a) residue management, (b) filter strips, (c) parallel terraces, (d) contour farming, and (e) tillage. We present a novel method of combing different NPS pollutants into a single objective function, which, along with the net costs, were used as the two objective functions during optimization. In this study we used BMP tool, a database that contains the pollution reduction and cost information of different BMPs under consideration which provides pollutant loads during optimization. The BMP optimization was performed using a NSGA-II based search method. The model was tested for the selection and placement of BMPs in Wildcat Creek Watershed, a corn dominated watershed located in northcentral Indiana, to reduce nitrogen, phosphorus, sediment, and pesticide losses from the watershed. The Pareto optimal fronts (plotted as spider plots) generated between the optimized objective functions can be used to make management decisions to achieve desired water quality goals with minimum BMP implementation and maintenance cost for the watershed. Also these solutions were geographically mapped to show the locations where various BMPs should be implemented. The solutions with larger pollution reduction consisted of buffer filter strips that lead to larger pollution reduction with greater costs compared to other alternatives.     

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.     

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.     

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 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.     

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.     

PLANNING OF URBAN BEST MANAGEMENT PRACTICES1

ABSTRACT: A “user-friendly” computer program has been developed for application in personal computers for preliminary design, evaluation, and cost effectiveness analysis of various best management practice (BMP) measures to control stormwater quantity and quality. The algorithms utilize the SCS TR-55 method for calculating runoff hydrographs for a single storm event and a first order pollutant washoff equation to generate pollutographs. Sensitivity analyses based on different policy scenarios is performed on a hypothetical watershed for the purpose of illustration. Three types of BMP measures, namely detention ponds (dry, wet, and extended wet ponds), infiltration trenches, and porous pavements are considered. It is found that the extended wet ponds have the best cost effective performance of the measures evaluated.     

Spatial Optimization of Six Conservation Practices Using Swat in Tile‐Drained Agricultural Watersheds

Targeting of agricultural conservation practices to the most effective locations in a watershed can promote wise use of conservation funds to protect surface waters from agricultural nonpoint source pollution. A spatial optimization procedure using the Soil and Water Assessment Tool was used to target six widely used conservation practices, namely no‐tillage, cereal rye cover crops (CC), filter strips (FS), grassed waterways (GW), created wetlands, and restored prairie habitats, in two west‐central Indiana watersheds. These watersheds were small, fairly flat, extensively agricultural, and heavily subsurface tile‐drained. The targeting approach was also used to evaluate the model's representation of conservation practices in cost and water quality improvement, defined as export of total nitrogen, total phosphorus, and sediment from cropped fields. FS, GW, and habitats were the most effective at improving water quality, while CC and wetlands made the greatest water quality improvement in lands with multiple existing conservation practices. Spatial optimization resulted in similar cost‐environmental benefit tradeoff curves for each watershed, with the greatest possible water quality improvement being a reduction in total pollutant loads by approximately 60%, with nitrogen reduced by 20‐30%, phosphorus by 70%, and sediment by 80‐90%.     

WATERSHED LEVEL BEST MANAGEMENT PRACTICE SELECTION AND PLACEMENT IN THE TOWN BROOK WATERSHED, NEW YORK1

Abstract: For a number of years, best management practices (BMPs) have been implemented within the Town Brook watershed as part of a watershed wide effort to reduce phosphorus losses to the New York City water supply reservoirs. Currently, there are no quantitative indications of the effectiveness of these practices at the watershed scale. Additionally, work is needed to evaluate management practice solutions for costs in relation to effectiveness. In this study we develop a methodology for evaluating management solutions to determine the best way(s) to select and place management practices so that pollutant removal targets are met at minimum cost. The study combines phosphorus losses as simulated by the Soil and Water Assessment Tool (SWAT), management practice effectiveness estimates from a predeveloped characterization tool, and practice costs in optimizations using a genetic algorithm. For a user defined target phosphorus removal (60 percent for this study), optimization favors nutrient management plans, crop rotations, contour strip cropping, and riparian forest buffers; the most cost effective scenario achieves a cost effectiveness of 24/kg phosphorus removal per year compared to the 34/kg phosphorus removal per year associated with the current basic implementation scheme. The study suggests that there is a need to evaluate potential solutions prior to implementation and offers a means of generating and evaluating the solutions.     

Reducing surface water pollution through the assessment of the cost-effectiveness of BMPs at different spatial scales

Two kinds of agricultural Best Management Practices (BMPs) were examined with respect to cost-effectiveness (CE) in reducing sediment, nitrates-nitrogen (NO₃–N) and total phosphorus (TP) losses to surface waters of the Arachtos catchment in Western Greece. The establishment of filter strips at the edge of fields and a non-structural measure, namely fertilization reduction in alfalfa, combined with contour farming and zero-tillage in corn and reduction of animal numbers in pastureland, were evaluated. The Soil and Water Assessment Tool (SWAT) model was used as the non-point-source (NPS) estimator, while a simple economic component was developed estimating BMP implementation cost as the mean annual expenses needed to undertake and operate the practice for a 5-year period. After each BMP implementation, the ratio of their CE in reducing pollution was calculated for each Hydrologic Response Unit (HRU) separately, for each agricultural land use type entirely and for the whole catchment. The results at the HRU scale are presented comprehensively on a map, demonstrating the spatial differentiation of CE ratios across the catchment that enhances the identification of locations where each BMP is most advisable for implementation. Based on the analysis, a catchment management solution of affordable total cost would include the expensive measure of filter strips in corn and only in a small number of pastureland fields, in combination with the profitable measure of reducing fertilization to alfalfa fields. When examined for its impact on river loads at the outlet, the latter measure led to a 20 tn or 8% annual decrease of TP from the baseline with savings of 15€/kg of pollutant reduction. Filter strips in corn fields reduced annual sediments by 66 Ktn or 5%, NO₃–N by 71 tn or 9.5% and TP by 27 tn or 10%, with an additional cost of 3.1 €/tn, 3.3 €/kg and 8.1 €/kg of each pollutant respectively. The study concludes that considerable reductions of several pollutant types at the same time can be achieved, even at low total cost, by combining targeted BMP implementation strategies only in small parts of the catchment, also enabling policy makers to take local socio-economic constraints into consideration. The methodology and the results presented aim to facilitate decision making for a cost-effective management of diffuse pollution by enabling modelers and researchers to make rapid and reliable BMP cost estimations and thus being able to calculate their CE at the local level in order to identify the most suitable areas for their implementation.     

A Cooperative Approach to Reduce Water Pollution Abatement Cost in an Interjurisdictional Lake Basin

A cooperative approach via transfer fee was developed to improve the cost‐effectiveness of water pollution control in interjurisdictional lake basin management in China. Different from the existing literature that studies water quality trading and pollution reduction at micro levels (i.e., focusing on enterprises and firms), this article explores cooperative pollution reduction strategies from a macro level, targeting multiple jurisdictional regions. The merits of this new approach include: (1) improving the cost‐effectiveness of pollution reduction by making use of the cost differentiation in pollution reduction between industries and municipal sewage plants, and between different administrative areas; (2) managing payments for ecosystem services by horizontal transfer payment; and (3) incorporating the concepts of game, cooperation, coordination, and watershed‐based management in implementation. For empirical demonstration, a bilevel optimization model was built and calibrated using the 2005 data of the Lake Tai basin to work out the optimal solutions for cooperative chemical oxygen demand (COD) reduction. Results show that policies based on this new approach can significantly reduce the overall COD abatement costs for the basin as well as the individual jurisdictional regions compared to the current practice.     

Application of Tabu Search Algorithm With a Coupled AnnAGNPS‐CCHE1D Model to Optimize Agricultural Land Use1

Abstract: A principal contributor to soil erosion and nonpoint source pollution, agricultural activities have a major influence on the environmental quality of a watershed. Impact of agricultural activities on the quality of water resources can be minimized by implementing suitable agriculture land‐use types. Currently, land uses are designed (location, type, and operational schedule) based on field study results, and do not involve a science‐based approach to ensure their efficiency under particular regional, climatic, geological, and economical conditions. At present, there is a real need for new methodologies that can optimize the selection, design, and operation of agricultural land uses at the watershed scale by taking into account environmental, technical, and economical considerations, based on realistic simulations of watershed response. In this respect, the present study proposes a new approach, which integrates computational modeling of watershed processes, fluvial processes in the drainage network, and modern heuristic optimization techniques to design cost effective land‐use plans. The watershed model AnnAGNPS and the channel network model CCHE1D are linked together to simulate the sediment and pollutant transport processes. Based on the computational results, a multi‐objective function is set up to minimize soil losses, nutrient yields, and total associated costs, while the production profits from agriculture are maximized. The selected iterative optimization algorithm uses adaptive Tabu Search heuristic to flip (switching from one alternative to another) land‐change variables. USDA’s Goodwin Creek experimental watershed, located in Northern Mississippi, is used to demonstrate the capabilities of the proposed approach. The results show that the optimized land‐use design with BMPs using an integrated approach at the watershed level can provide efficient and cost‐effective conservation of the environmental quality by taking into account both productivity and profitability.     

Modeling Watershed‐Scale Impacts of Stormwater Management with Traditional versus Low Impact Development Design

Stormwater runoff and associated pollutants from urban areas in the greater Chesapeake Bay Watershed (CBW) impair local streams and downstream ecosystems, despite urbanized land comprising only 7% of the CBW area. More recently, stormwater best management practices (BMPs) have been implemented in a low impact development (LID) manner to treat stormwater runoff closer to its source. This approach included the development of a novel BMP model to compare traditional and LID design, pioneering the use of comprehensively digitized storm sewer infrastructure and BMP design connectivity with spatial patterns in a geographic information system at the watershed scale. The goal was to compare total watershed pollutant removal efficiency in two study watersheds with differing spatial patterns of BMP design (traditional and LID), by quantifying the improved water quality benefit of LID BMP design. An estimate of uncertainty was included in the modeling framework by using ranges for BMP pollutant removal efficiencies that were based on the literature. Our model, using Monte Carlo analysis, predicted that the LID watershed removed approximately 78 kg more nitrogen, 3 kg more phosphorus, and 1,592 kg more sediment per square kilometer as compared with the traditional watershed on an annual basis. Our research provides planners a valuable model to prioritize watersheds for BMP design based on model results or in optimizing BMP selection.     

UNCERTAINTY ANALYSIS OF BMP EFFECTWENESS FOR CONTROLLING NITROGEN FROM URBAN NONPOINT SOURCES1

ABSTRACT: The effectiveness of urban Best Management Practices (BMPs) in achieving the No-Net-Increase Policy (NNTP), a policy designed to limit nonpoint nitrogen loading to Long Island Sound (US), is analyzed. A unit loading model is used to simulate annual nitrogen exported from the Norwalk River watershed (Connecticut) under current and future conditions. A probabilistic uncertainty analysis is used to incorporate uncertainty in nitrogen export coefficients and BMP nitrogen removal effectiveness. The inclusion of uncertainty in BMP effectiveness and nitrogen export coefficients implies that additional BMPs, or BMPs with a greater effectiveness in nitrogen removal, will be required to achieve the NNIP. Even though including uncertainty leads to an increase in BMP implementation rates or BMP effectiveness, this type of analysis provides the decision maker with a more realistic assessment of the likelihood that implementing BMPs as a management strategy will be successful. Monte Carlo simulation results indicate that applying BMPs to new urban developments alone will not be sufficient to achieve the NNIP since BMPs are not 100 percent effective in removing the increase in nitrogen caused by urbanization. BMPs must also be applied to selected existing urban areas. BMPs with a nitrogen removal effectiveness of 40–60 percent, probably the highest level of removal that can be expected over an entire watershed, must be applied to at least 75 percent of the existing urban area to achieve the NNIP This high rate of application is not likely to be achieved in urbanized watersheds in the LIS watershed; therefore, additional point source control will be necessary to achieve the NNIP     

流域污染物通量测算方法研究

流域水系内污染物通量不仅能够用于评价各类污染源的水污染物入河负荷,也是对流域污染特征,水污染物在河流水体中复杂迁移、转化过程的最直观反应。准确测算流域水系内污染物跨界通量及其时空分布是进行流域水环境风险预警和风险管理的重要前提之一。针对目前多种污染物通量测算方法在进行污染物年通量估算时,结果不确定性大这一突出问题,以流域水质监测站年内逐日流量、悬浮颗粒物监测数据作为悬浮颗粒物年通量参考值,基于以月、半月、周为周期的监测策略,将逐日流量、悬浮颗粒物监测数据重新筛选抽样构造,由此,系统分析了不同流域集水面积、污染通量监测频次和目前常用通量估算方法对污染物年通量估算不确定性的影响。所得方法和结论可为进一步制定流域污染物通量的测算规范提供方法指引和技术支持。     

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.