Cost Of Best Management Practices Research Articles

An integrated tool for cost-effectively applying nutrient management practices for corn, soybeans, and wheat.

Harmful algal blooms (HABs) problem in Lake Erie has become critical recently-primarily triggered by phosphorus losses from cropland in the Maumee River watershed (major crops of corn/soybeans/wheat). Implementing agricultural best management practices (BMPs) is crucial to reduce excess nutrient loadings. Nutrient management is the management of nutrient applications for crop production that maximizes nutrient use efficiencies and minimizes nutrient losses. However, an integrated watershed-scale tool is needed for cost-effectively applying nutrient management practices for corn/soybeans/wheat considering the 4Rs (Right nutrient source, Right rate, Right time, and Right place of nutrient applications). In this study, by combining an improved Soil and Water Assessment Tool (SWAT) for nutrient management (SWAT-NM) and an improved BMP Cost Evaluation Tool (BMP-COST) for economic evaluations of nutrient management (BMP-COST-NM) considering the 4Rs for corn/soybeans/wheat, an integrated tool SWAT-COST-NM was created. SWAT-COST-NM was demonstrated in the AXL watershed (a typical agricultural area in the Maumee River watershed). The impacts of single nutrient management practices (single-NM, which separately changed the rate, place, time, or nutrient source of fertilizer applications) and combined-NM practices (multiple single-NM practices combined as one nutrient management practice) for corn/soybeans/wheat were evaluated. Tradeoffs in yearly net costs, crop yields, and March-July/yearly nutrient losses (Total Phosphorus-TP, Dissolved Reactive Phosphorus-DRP, and Total Nitrogen-TN) existed. Nutrient management did not necessarily lead to sufficient increases in crop yields to generate extra revenues that match or exceed the additional costs of the activities (compared to existing practices). One of the combined-NM practices could simultaneously reduce March-July TP, DRP, and TN losses by 5.89%, 8.19%, and 8.23%, respectively, while increasing crop yields with additional income (0.50 $/ha/yr of cropped area). SWAT-COST-NM, which can quantify various factors and tradeoffs when evaluating the impacts of nutrient management practices for corn/soybeans/wheat, can assist decision-makers in cost-effectively applying nutrient management practices considering the 4Rs.

A spatial optimal allocation method considering multi-attribute decision making and multiple BMPs random combination in sub-watersheds

Best management practices (BMPs) have been extensively employed in effective watershed management for non-point source pollution. The weights of objective functions and the restrictive conditions of combined BMPs are the vital requirements for BMPs allocation. Therefore, it is more beneficial to explore that a spatial optimal allocation method considering multi-attribute decision making and multiple BMPs random combination. Here is the novel framework based on Soil and Water Assessment Tool (SWAT) and the Non-dominated Sorting Genetic Algorithm II (NSGA-Ⅱ), which considers multiple objectives in deriving watershed-scale pollution control practices by considering BMPs cost and combined reduction rates of total nitrogen (TN) and total phosphorus (TP). The framework also integrates combined Entropy Weight method (EWM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to solve the weights of TN and TP, and considers the attributes of the sub-basin itself, which is more local suitability. Four categories of BMPs, tillage management, nutrient management, vegetative filter strips, and landscape management, were evaluated in the Jing River Basin (JRB) and resulted in reduction rates of 9.77%, 10.53%, 16.40%, and 14.27% averagely, respectively. BMP allocation schemes, derived from multi-objective optimization, are stratified into three financial scenarios. Low-cost scenario, costing up to 2 billion RMB, primarily targets the grain for green program in 28.81% of sub-basins. Medium-cost scenario, between 2 and 6 billion RMB, predominantly utilizes the grain for green in areas with a slope greater than 15°, accounting for 20.00% of sub-basins. High-cost scenario exceeds 6 billion RMB, mainly due to the implementation of multiple combination measures. The three configuration scenarios can provide decision-makers with a trade-off between measure costs and reduction efficiency. Overall, the innovative framework not only facilitates cost-effective implementation but provides a beneficial methodology for selecting cost-effective conservation practices in other regions.

The role of cost, scale, and property attributes in landowner choice of stormwater management option

Cities throughout the world are experimenting with Low Impact Development (LID) strategies to replace ecosystem services degraded by urbanization. Stormwater management may need both centralized/publicly-managed infrastructure and decentralized provision by landowners. For landowners to participate in these programs they will need some latitude in the choice of techniques and siting. However, these landowner choices will affect the bundle of ecosystem services provided (such as infiltration, aesthetics, pollution filtering, and others) as well as their spatial distribution. We studied the Santa Monica (CA) stormwater regulations that require stormwater management on a large portion of development and redevelopment but allow a significant degree of landowner choice over the method of rainwater management. We use a novel dataset to investigate both the cost of rainwater best management practices (BMPs) and landowner choice of rainwater BMP. We find strong evidence of economies of scale in capital costs for the smaller size ranges of the BMPs in our data, and that property factors such as land use and overall redevelopment project cost affect rainwater BMP costs. In addition, our results are consistent with the hypothesis that property factors such as building density and land value are important factors in the landowner’s choice of rainwater management option.

Addressing the spatial disconnect between national-scale total maximum daily loads and localized land management decisions.

Regulatory watershed mitigation programs typically emphasize widespread adoption of best management practices (BMPs) to meet total maximum daily load (TMDL) goals. To comply with the Chesapeake Bay TMDL, jurisdictions must develop watershed implementation plans (WIPs) to determine the number and type of BMPs to implement. However, the spatial resolution of the bay‐level model used to determine these load reduction goals is so coarse that the regulatory plan cannot consider heterogeneity in local conditions, which affects BMP effectiveness. Using the Topo‐SWAT modification of the Soil and Water Assessment Tool (SWAT), we simulated two BMP adoption scenarios in the Spring Creek watershed in central Pennsylvania to determine if leveraging fine‐scale spatial heterogeneity to place BMPs could achieve the same (or better) nutrient and sediment reduction at a lower cost than the state‐level WIP BMP adoption recommendations. Topo‐SWAT was initialized with detailed land use and management practice information, systematically calibrated, and validated against 12 yr of observed data. After determining individual BMP cost effectiveness, results were ranked to design a cost‐effective BMP adoption scenario that achieved equal or greater load reduction as the WIP scenario for 74% of the cost using eight management‐based BMPs: no‐till, manure injection, cover cropping, riparian buffers, land retirement, manure application timing, wetland restoration, and nitrogen management (15% less N input). Because watersheds of this size typically represent the smallest modeling unit in the Chesapeake Bay Model, results demonstrate the potential to use watershed models with finer inference scales to improve recommendations for BMP implementation under the Chesapeake Bay TMDL.

Evaluating efficiencies and cost-effectiveness of best management practices in improving agricultural water quality using integrated SWAT and cost evaluation tool

Agricultural conservation practices, or agricultural best management practices (BMPs), can reduce nutrient loading and help address harmful algal blooms (HABs). HABs in the western basin of Lake Erie, which are largely caused by phosphorus losses from the Maumee River watershed, are critical in the recent years. In this study, a new BMP cost tool was developed. Then the Soil and Water Assessment Tool (SWAT) and the new BMP cost tool were integrated to explore efficiencies and cost-effectiveness of BMPs in an agricultural catchment of the Maumee River watershed with various scenarios. The scenarios included individual BMPs applied in 100% of suitable areas, individual BMPs targeting Dissolved Reactive Phosphorus (DRP) and Total Phosphorus (TP) critical areas, and BMPs implemented in series. In addition, a cost-effective approach for the selections and placements of BMPs in agricultural watersheds was developed as an alternative to running complex optimization tools that are not applicable to large watersheds. The cost-effective approach applied BMPs based on cost-effectiveness rankings starting from the most cost-effective one. Results showed that: (1) BMPs implemented in series, which reduced pollutant loads more than individual BMPs, were not as cost-effective as some individual BMPs; (2) among all scenarios, filter strips targeting DRP/TP critical areas were the most cost-effective in reducing yearly/spring DRP/TP losses; (3) to obtain the watershed management plan goal of reducing March-July DRP/TP losses by 40%, implementing BMPs one by one in critical areas based on the cost-effectiveness rankings of individual BMPs in DRP/TP critical areas was the most cost-effective; and (4) the simulation results, modeling tools, and cost-effective approach can help create agricultural BMP strategies to cost-efficiently improve water quality.

A SWAT-based optimization tool for obtaining cost-effective strategies for agricultural conservation practice implementation at watershed scales.

To address the harmful algal blooms problem in Lake Erie, one solution is to determine the most cost-effective strategies for implementing agricultural best management practices (BMPs) in the Maumee River watershed. An optimization tool, which combines multi-objective optimization algorithms, SWAT (Soil and Water Assessment Tool), and a computational efficient framework, was created to optimally identify agricultural BMPs at watershed scales. The optimization tool was demonstrated in the Matson Ditch watershed, an agricultural watershed in the Maumee River basin considering critical areas (25% of the watershed with the greatest pollutant loadings per area) and the entire watershed. The initial implementation of BMPs with low expenditures greatly reduced pollutant loadings; beyond certain levels of pollutant reductions, additional expenditures resulted in less significant reductions in pollutant loadings. Compared to optimization for the entire watershed, optimization in critical areas can greatly reduce computational time and obtain similar optimization results for initial reductions in pollutant loadings, which were 10% for Dissolved Reactive Phosphorus (DRP) and 38% for Total Phosphorus (TP); however, for greater reductions in pollutant loadings, critical area optimization was less cost-effective. With the target of simultaneously reducing March-July DRP/TP losses by 40%, the optimized scenario that reduced DRP losses by 40% was found to reduce 51.1% of TP; however, the optimized scenario that reduced TP losses by 40% can only decrease 11.3% of DRP. The optimization tool can help stakeholders identify optimal types, quantities, and spatial locations of BMPs that can maximize reductions in pollutant loadings with the lowest BMP costs.

A coupled model system to optimize the best management practices for nonpoint source pollution control

Agricultural nonpoint source pollution (NPS) is the main water-use impairment in the upper watershed of the Miyun Reservoir in Beijing, China. Selection and placement of best management practices (BMPs) in heterogeneous watersheds, requires a multi-objective optimization framework to identify the most cost-effective conservation strategy to achieve desired water quality goals. In this paper, a novel optimization methodology was developed, utilizing a BMP database that includes BMP reduction efficiencies and costs, using a multi-objective sorting genetic algorithm (NSGA-II, nondominated sorting genetic algorithm-II) combined with the Soil Water and Assessment Tool (SWAT) served as the NPS watershed model. Cost-effectiveness curves (optimal fronts) between pollutant reduction and total net cost input were obtained for the upper watershed of Miyun Reservoir. The optimal combination of BMP, which include a combination of conservation tillage, careful timing of 30% less fertilizer application, contour planting, and use of a 10-m edge-of-field buffer strip, indicate that the least costly scenario reduced total nitrogen (TN) and total phosphorus (TP) loads by 33% at a cost of 1.02 × 106 China Yuan. The cost-effective scenario reduced TN and TP loads 44% and 68% at a cost of 2.52 × 107 and 5.64 × 107China Yuan. The greatest reduction scenario reduced TN and TP loads 55% and 76%, respectively, at a cost of 2.01 × 108 and 2.48 × 108 China Yuan. Watershed with poultry operations, required a 30% reduction in number of birds, along with a 30% reduction in the amount of manure applied was needed to achieve water quality goals. Use of the coupled BMP optimization model can assist the policy makers achieve a cost-effective implementation of best management practices to mitigate agricultural nonpoint sources at a watershed scale.

面源污染最佳管理措施多目标协同优化配置研究进展

PDF HTML阅读 XML下载 导出引用 引用提醒 面源污染最佳管理措施多目标协同优化配置研究进展 DOI: 10.5846/stxb201804140860 作者: 作者单位: 生态环境部环境与经济政策研究中心,生态环境部环境与经济政策研究中心,生态环境部环境与经济政策研究中心,生态环境部环境与经济政策研究中心,生态环境部环境与经济政策研究中心 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金青年科学基金项目（41601551）；第二次全国污染源普查项目《农业源污染物入水体负荷核算方法及系数体系构建》（2110399）；环保部第三批城环总规试点项目（YGCQ-GGQY-201418） A review: multi-objective collaborative optimization of best management practices for non-point sources pollution control Author: Affiliation: Policy Research Center for Environment and Economy, Ministry of Ecology and Environment Protection, P.R.China,,Policy Research Center for Environment and Economy, Ministry of Ecology and Environment Protection, P.R.China,, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:随着点源污染逐渐得到有效控制，面源污染逐渐成为我国多数地区影响水环境质量安全的主要因素。推广实施最佳管理措施（Best Management Practices，BMPs）被认为是控制面源污染的有效途径。受到区域种植制度、耕作方式、政策以及经济成本等因素的影响，导致流域尺度配置BMPs存在一定的困难，特别是随着流域空间尺度的变化，会进一步加大BMPs配置难度，使得BMPs的配置工作变为了一项多目标决策优化问题，即如何在有限的成本投入下，实现水环境质量改善的目标。需要在不同空间尺度下对流域BMPs进行多目标协同优化配置。从面源污染关键源区识别、BMPs削减效率评估以及BMPs多目标协同优化模拟3个方面对面源污染BMPs多目标协同优化配置研究进行了综述。结果表明：1）包含地块尺度和流域尺度的多尺度模型耦合系统的构建，将是实现关键源区精准识别的有效途径；2）BMPs削减效率对水质改善响应的滞后性、不确定性、时空异质性、污染物形态转换风险等均是今后BMPs削减效率评估中需要重点解决的关键问题；3）建立流域污染物负荷削减量与水质改善之间的非线性响应关系，并以此为基础将BMPs组合数据库、成本数据库以及基于进化算法的的优化配置方案进行耦合，进而构建多目标决策支持系统，以获取BMPs空间优化配置方案以及多目标成本-效益最优曲线。 Abstract:With point source pollution gradually being controlled, non-point source pollution has become a threat for water quality in most regions of China. Best management practices (BMPs) have been regarded as the most effective way to control non-point source pollution. However, the effectiveness of regional cropping systems, cultivation methods, policies, and economic costs lead to difficulties in BMP allocation at the watershed scale. In particular, the difficulties further increase with the changes at spatial scale. As a result, the allocation of BMPs has been moved to a multi-objective decision optimization program, to achieve water quality improvement targets under limited inputs. Therefore, there is a need for multi-objective collaborative optimization of BMPs at different spatial scales. Herein, we reviewed the current research pertaining to multi-objective collaborative optimization of BMPs for non-point source pollution with respect to three aspects: identify the critical source areas (CSAs) of non-point source pollution, assessment of BMPs cutting efficiency, and imitate multi-objective collaborative optimization of BMPs. The results indicate that: i) building multi-scale model coupling system, including land scale and watershed scale, would be the most efficient way to accurately identify CSAs; ii) reducing time lag, uncertainty, and spatial and temporal heterogeneity as well as the risk of pollution to improve water quality will be the key to the cutting efficiency of BMPs; iii) building a nonlinear response relation between watershed pollutant reduction and water quality improvement is essential. The BMP database, cost database, and scientific allocation schemes based on evolutionary algorithm (EA) can be combined to build a multi-scale decision supporting system. The allocation scheme of BMPs and the optimum curve of multi-scale cost-effectiveness can then be acquired. 参考文献 相似文献 引证文献

Identifying efficient agricultural irrigation strategies in Crete

Water scarcity and droughts are a major concern in most Mediterranean countries. Agriculture is a major user of water in the region and releases significant amounts of surface and ground waters, endangering the sustainable use of the available resources. Best Management Practices (BMPs) can mitigate the agriculture impacts on quantity of surface waters in agricultural catchments. However, identification of efficient BMPs strategies is a complex task, because BMPs costs and effectiveness can vary significantly within a basin. In this study, sustainable agricultural practices were studied based on optimal allocation of irrigation water use for dominant irrigated crops in the island of Crete, Greece. A decision support tool that integrates the Soil and Water Assessment Tool (SWAT) watershed model, an economic model, and multi-objective optimization routines, was used to identify and locate optimal irrigation strategies by considering crop water requirements, impact of irrigation changes on crop productivity, management strategies costs, and crop market prices. Three spatial scales (crop type, fields, and administrative regions) were considered to point out different approaches of efficient management. According to the analysis, depending on the spatial scale and complexity of spatial optimization, water irrigation volumes could be reduced by 32%–70% while preserving current agricultural benefit. Specific management strategies also looked at ways to relocate water between administrative regions (4 prefectures in the case of Crete) to optimize crop benefit while reducing global water use. It was estimated that an optimal reallocation of water could reduce irrigation water volumes by 52% (148 Mm3/y) at the cost of a 7% (48 M€) loss of agricultural income, but maintaining the current agricultural benefit (626.9 M€). The study showed how the identification of optimal, cost-effective irrigation management strategies can potentially address the water scarcity issue that is becoming crucial for the viability of agriculture in the Mediterranean region.

Cost-effectiveness analysis of different watershed management scenarios developed by simulation–optimization model

The effort to control sediment yield at watershed scale is an ongoing challenge that needs to take into account trade-offs between two conflicting objective functions, i.e. economic and hydrologic criteria. Therefore, researchers have coupled hydrologic and multi-objective optimization models to find Pareto-optimal solutions. However, very limited studies have been conducted to analyse the cost-effectiveness (C/E) of scenarios obtained in the Pareto-front optimal. This could provide new information leading to effective watershed management. Therefore, in the present study, the Soil and Water Assessment Tool (SWAT) was used to simulate sediment yield under different combinations of best management practices (BMPs) and was coupled with the Non-dominated Sorting Genetic Algorithm (NSGA-II). The model attends to providing the Pareto-optimal solutions by minimizing the costs of BMPs and maximizing sediment reduction. The results of the application of the cost-effective optimization model in Mehran watershed, Iran, showed that the solutions in the Pareto-optimal front reduce sediment yield between 2% and 40.5% from baseline at costs of between $6,500 and $72,100, respectively. Finally, comparison of four sediment reduction solutions (i.e. 10%, 20%, 30%, and 40%) showed that the total cost and C/E ratio of solutions increased as the sediment reduction criteria increased.

한강수계 비점오염원 저감시설의 생애주기비용 평가

환경부는 비점오염원 관리를 위해 시범사업으로 12개의 비점오염 저감시설을 경안천 유역에 설치하였으며, 2006년부터 모니터링이 시작되었다. 본 연구는 비점오염 저감시설의 오염부하량, 저감효율, 유지관리 활동 등의 장기간 수행된 모니터링 결과를 바탕으로 각 시설의 경제성을 평가하기 위해 수행되었으며, 생애주기비용(Lifecycle cost, LCC)을 분석하였다. 비점오염 저감시설의 유지관리는 시설경관을 향상시키기 위한 심미적 관리가 중점적으로 수행된 것으로 나타났으며, 저류형 시설(Retention Pond, RP)이 년간 8,483$, 침투형 시설(Infiltration System, IS)이 8,888$로 대부분 비슷한 비용이 발생한 것으로 분석되었다. LCC는 인공습지(Constructed Wetland, CW)가 가장 높은 것($418,324)으로 나타났으며, 반면에 식생형 시설(Vegetated System, VS)이 가장 낮은 것($210,418)으로 분석되었다. 본 연구에서 조사된 비점오염 저감시설의 LCC와 하수처리장 등 수질처리시설의 LCC를 비교한 결과 비점오염 저감시설이 낮은 것으로 나타났다. 한편, 처리용량 대비 생애주기비용이 높아질수록 TSS와 TN의 저감효율은 높아지는 것으로 나타났다. 이러한 연구결과는 비용효율적인 비점오염 저감시설을 설계하는데 유용하게 활용될 것으로 기대되며, 향후 LCC 모델의 기초자료에도 활용될 수 있을 것으로 판단된다. Diffuse pollution management in Korea initiated by the Ministry of Environment (MOE) resulted to the construction of pilot facilities termed Best Management Practices (BMPs). Twelve BMPs installed for the diffuse pollution management in the Kyung-An Stream were monitored since 2006. Data on the mass loading, removal efficiency, maintenance activities, etc. were gathered and utilized to conduct the evaluation of long-term performance of BMPs. The financial data such as actual construction, design and maintenance cost were also collected to evaluate the lifecycle cost (LCC) of BMPs. In this study, most of the maintenance activity was focused in the aesthetic maintenance that resulted to the annual maintenance cost of the four BMP types was closely similar ranging from 8,483 $/yr for retention pond to 8,888 $/yr infiltration system. The highest LCC were observed in constructed wetland ($418,324) while vegetated system had the lowest LCC ($210,418). LCC of BMPs was not so high as compared with the conventional treatment facility and sewage treatment plant. On the other hand, the relationship of removal efficiency on unit cost for TSS and TN was significant. This study will be used to design the cost effective BMP for diffuse pollution management and become models for LCC analysis.

Spatial optimization of watershed management practices for nitrogen load reduction using a modeling-optimization framework

Best management practices (BMPs) can be used effectively to reduce nutrient loads transported from non-point sources to receiving water bodies. However, methodologies of BMP selection and placement in a cost-effective way are needed to assist watershed management planners and stakeholders. We developed a novel modeling-optimization framework that can be used to find cost-effective solutions of BMP placement to attain nutrient load reduction targets. This was accomplished by integrating a GIS-based BMP siting method, a WQM-TMDL-N modeling approach to estimate total nitrogen (TN) loading, and a multi-objective optimization algorithm. Wetland restoration and buffer strip implementation were the two BMP categories used to explore the performance of this framework, both differing greatly in complexity of spatial analysis for site identification. Minimizing TN load and BMP cost were the two objective functions for the optimization process. The performance of this framework was demonstrated in the Tippecanoe River watershed, Indiana, USA. Optimized scenario-based load reduction indicated that the wetland subset selected by the minimum scenario had the greatest N removal efficiency. Buffer strips were more effective for load removal than wetlands. The optimized solutions provided a range of trade-offs between the two objective functions for both BMPs. This framework can be expanded conveniently to a regional scale because the NHDPlus catchment serves as its spatial computational unit. The present study demonstrated the potential of this framework to find cost-effective solutions to meet a water quality target, such as a 20% TN load reduction, under different conditions.

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

AbstractThis 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.

Optimization of the restructuring cost of an urban drainage network

Urban drainage networks are subjected to increased runoff caused by urbanization and climate change. Wear and tear, coupled with a lack of network maintenance, reduces the hydraulic capacity of these networks and results in surcharged flows, discharges and overflows calling for the need to institute effective restructuring strategies. The purpose of this study was to develop an optimization model for the optimal selection and placement of structural best management practices (BMPs). In this research, four types of structural BMPs were being considered (i.e., retention pond, green roofs, infiltration trenches and vegetated depressions). The objective function was to minimize the total cost of BMPs, within the constraints of (1) draining infrequent heavy rainfall without surcharging the conduits and (2) driving frequent small rainfall into the water-treatment plant without overflows. The model was tested on a case study in the Greater Montreal Area and the results obtained from the model effectively demonstrated its capacity to improve the hydraulic and environmental performances by adopting optimal BMPs placement strategies.

Agricultural Water Quality BMPs: A Standardized Approach to Financial Analysis

Addressing water quality issues continues to emerge as a challenge to be faced by agricultural interests across the Cornbelt. Agricultural Extension has a role to play in assisting farmers in complying with water quality regulations and adoption of Best Management Practices (BMP) to address water quality impacts. Despite the clear importance of financial information in BMP decision-making, often, published cost assessments are rare and lack transparency. This article provides a framework for Extension personnel who provide water quality BMP cost assessments while also highlighting financial information necessary for creating Extension publications that have transparent and dynamic financial assessments.

Cost of best management practices to combat agricultural runoff and comparison with the local populations’ willingness to pay: Case of the Austreberthe watershed (Normandy, France)

Land Use and Cover Changes (LUCCs) significantly increase the frequency of mudflows in the silty areas of north-western Europe and particularly in the NUTS 3 Seine-Maritime region (France). Predicting the effects of a range of possible LUCCs helps local authorities choose policies that can help to mitigate the risks to which local populations are exposed. In this article we build scenarios for changes in farming systems, with a 2015 horizon and with 2007 as the initial situation. These scenarios are assessed through combined biophysical and economic approaches. Two scenarios for the disappearance of dairy farming are chosen. One scenario has no public-action program (StopMilk), while the other one has a program based on the funding of best management practices (StopMilk-E). These scenarios are assessed at the small watershed scale (7km2) in terms of both changes in farming systems and effects on runoff (use of the STREAM model). Finally, the economic evaluation of additional costs of StopMilk-E is extrapolated at the level of the Austreberthe watershed syndicate (214km2), using the French Land Parcel Identification System (LPIS) with a spatially referenced database of cropping plans. StopMilk leads to a significant increase in runoff whereas the local public-action program proposed under StopMilk-E reduces runoff to below the 2007 level. The Austreberthe watershed residents’ willingness to pay for a 15-year program is around €395,000/year, which is not sufficient to balance the cost of the modified farming practices (€640,000/year over the first 3 years). Funding of the practices would require either subsidies from a higher level (Europe), borrowing by the community, and/or a more selective approach in the type and the location of farming practices to be funded. The method used for calculating costs at the watershed syndicate level shows the huge potential of new databases like LPIS (available in France since 2006) for the assessment of environmental issues.

Application of analytical hierarchy process for effective selection of agricultural best management practices

In this study an analytical hierarchy process (AHP) was used for ranking best management practices (BMPs) in the Saginaw River Watershed based on environmental, economic and social factors. Three spatial targeting methods were used for placement of BMPs on critical source areas (CSAs). The environment factors include sediment, total nitrogen, and total phosphorus reductions at the subbasin level and the watershed outlet. Economic factors were based on total BMP cost, including installation, maintenance, and opportunity costs. Social factors were divided into three favorability rankings (most favorable, moderately favorable, and least favorable) based on area allocated to each BMP. Equal weights (1/3) were considered for the three main factors while calculating the BMP rank by AHP. In this study three scenarios were compared. A comprehensive approach in which environmental, economic, and social aspects are simultaneously considered (Scenario 1) versus more traditional approaches in which both environmental and economic aspects were considered (Scenario 2) or only environmental aspects (sediment, TN, and TP) were considered (Scenario 3). In Scenario 1, only stripcropping (moderately favorable) was selected on all CSAs at the subbasin level, whereas stripcropping (49–69% of CSAs) and residue management (most favorable, 31–51% of CSAs) were selected by AHP based on the watershed outlet and three spatial targeting methods. In Scenario 2, native grass was eliminated by moderately preferable BMPs (stripcropping) both at the subbasin and watershed outlet levels due the lower BMP implementations cost compared to native grass. Finally, in Scenario 3, at subbasin level, the least socially preferable BMP (native grass) was selected in 100% of CSAs due to greater pollution reduction capacity compared to other BMPs. At watershed level, nearly 50% the CSAs selected stripcropping, and the remaining 50% of CSAs selected native grass and residue management equally.

Reliability-Based Flood Management in Urban Watersheds Considering Climate Change Impacts

AbstractResearch has revealed the impacts of climate change on the hydrologic cycle. These impacts are intensified in the urban water system due to special characteristics of urban watersheds, such as a high percentage of impervious areas and the presence of a microclimate. A slight change in rainfall intensity and duration can cause severe floods, with a significant incremental increase in life and property losses. Therefore, it is a key issue to modify the urban watershed characteristics in a systematic way to deal with these probable changes. In this paper, a multicriteria optimization model is developed to select best management practices (BMPs) for flood management in urban watershed systems. The addressed criteria include maximizing reliability of the drainage system, as well as minimizing flood damages and BMP costs. A new reliability index for dealing with floods is suggested in this study that considers both severity and duration of flooding. The optimization model is solved using a two-stage mul...

Multi-objective optimization for combined quality–quantity urban runoff control

Abstract. Urban development affects the quantity and quality of urban surface runoff. In recent years, the best management practices (BMPs) concept has been widely promoted for control of both quality and quantity of urban floods. However, means to optimize the BMPs in a conjunctive quantity/quality framework are still under research. In this paper, three objective functions were considered: (1) minimization of the total flood damages, cost of BMP implementation and cost of land-use development; (2) reducing the amount of TSS (total suspended solid) and BOD5 (biological oxygen demand), representing the pollution characteristics, to below the threshold level; and (3) minimizing the total runoff volume. The biological oxygen demand and total suspended solid values were employed as two measures of urban runoff quality. The total surface runoff volume produced by sub-basins was representative of the runoff quantity. The construction and maintenance costs of the BMPs were also estimated based on the local price standards. Urban runoff quantity and quality in the case study watershed were simulated with the Storm Water Management Model (SWMM). The NSGA-II (Non-dominated Sorting Genetic Algorithm II) optimization technique was applied to derive the optimal trade off curve between various objectives. In the proposed structure for the NSGA-II algorithm, a continuous structure and intermediate crossover were used because they perform better as far as the optimization efficiency is concerned. Finally, urban runoff management scenarios were presented based on the optimal trade-off curve using the k-means method. Subsequently, a specific runoff control scenario was proposed to the urban managers.

Effectiveness and implementation costs of overland skid trail closure techniques in the Virginia Piedmont

Soil erosion is influenced by factors such as soil properties, slope, ground cover, climatic conditions, and forest management activities, including skid trails. Skid trails typically represent 2% to 10% of a timber harvest9s area; therefore, the potential to negatively affect site productivity and water quality as a result of harvesting is of concern. Soil erosion can reduce site nutrient reserves and increase sedimentation of nearby streams. Forestry best management practices (BMPs) are designed to provide effective techniques for maintaining environmental stability. Although BMPs are widely implemented, few data exist regarding the efficacy and costs of different BMP options for skid trail closure. The study objectives were to evaluate erosion control effectiveness and implementation costs of five overland skid trail closure techniques. The closure techniques were (1) waterbar only (Control), (2) waterbar plus seed (Seed), (3) waterbar plus seed and mulch (Mulch), (4) waterbar plus hardwood slash (Hardwood), and (5) waterbar plus pine slash (Pine). Each treatment was installed following harvesting and replicated on four trails to provide twenty experimental erosion plots. Geotextile sediment traps (Dirtbags) were used to filter skid trail sediment. Accumulated sediments were weighed monthly for one year, and erosion rates were determined for each treatment. Two commonly used erosion models, Universal Soil Loss Equation as modified for forests (USLE-Forest) and Water Erosion Prediction Project for Forest Roads (WEPP-Roads), were also applied to each treatment. Sediment collected from traps indicated that the Mulch treatment was the most effective for reducing erosion (3.29 Mg ha−1 y−1 [1.47 tn ac−1 yr−1]), followed by Hardwood (5.08 Mg ha−1 y−1 [2.27 tn ac−1 yr−1]), Pine (5.40 Mg ha−1 y−1 [2.41 tn ac−1 yr−1]), Seed (13.57 Mg ha−1 y−1 [6.06 tn ac−1 yr−1]), and Control (24.24 Mg ha−1 y−1 [10.82 tn ac−1 yr−1]). Overall, WEPP-Roads estimates were more similar to measured erosion than USLE-Forest estimates, but both models generally agreed with actual erosion trends. The Seed treatment was the least expensive beyond waterbars alone, but it was only moderately effective at limiting erosion. Incorporating slash dispersal and compaction onto overland skid trails during harvesting activities may be the best option for reducing BMP costs and long term soil stability on disturbed soils associated with log skidding.