Best Management Practices Database Research Articles

Effects of Regional Climate and BMP Type on Stormwater Nutrient Concentrations in BMPs: A Meta-Analysis.

Nutrient treatment performance of stormwater best management practices (BMPs) is highly variable. Improved nutrient management with BMPs requires a better understanding of factors that influence stormwater BMP treatment processes. We conducted a meta-analysis of vegetated BMPs in the International Stormwater BMP Database and compared influent and effluent nitrogen and phosphorus concentrations to quantify the BMP effect on nutrient management across climates. BMP effect on nutrient concentration change was compared between vegetated BMPs in wet and dry climates. We examined paired dissolved inorganic nitrogen (DIN), total nitrogen (TN), dissolved inorganic phosphorus (DIP), total phosphorus (TP), and combinations of these analytes as dissolved inorganic ratios and N:P ratios. Meta-analysis with subgroup analysis was used to determine differences between wet and dry climates and among vegetated BMP types. We found that across both wet and dry climates, BMPs leach DIP and TP, increase the fraction of dissolved inorganic P (DIP:TP), and decrease dissolved N:P ratios. Dry-climate BMPs leach DIP and TP more consistently and at a higher magnitude than wet-climate BMPs, and bioretention leaches more DIP than grass strips and swales. These findings generally align with biogeochemical cycling, differences in influent chemistry, and BMP design types and goals.

Regionalization of Default Parameters for Urban Stormwater Quality Models

AbstractAccurate parameterization of water quality routines within stormwater models can improve simulation, prediction of system behavior, and lead to more informed decision making. This work recognizes that factors controlling runoff concentrations and treatment in stormwater best management practices (BMPs) vary with region, assumes region is a proxy for these factors, and seeks to improve tool parameterization by (1) identifying a regionalization scheme that best explains variability in national datasets of runoff water quality and BMP performance, (2) generating region‐specific model parameter values, and (3) demonstrating how model output varies when using national vs. regional parameters. Of the four regionalization schemes tested, the National Climatic Data Center’s Regions best explained variance in pollutant runoff concentrations from the National Stormwater Quality Database, accounting for more data variability (1.1%) than the watershed’s land use (0.4%). For BMP performance extracted from the International Stormwater BMP Database, the United States (U.S.) Environmental Protection Agency’s Rain Zones explained the most variance (1.1%), which is one‐fifth of the variance explained by BMP type (5.0%). These results were used to generate regional parameter lookup tables for stormwater quality modeling. Test cases from the 100 most populous cites in the U.S. showed national parameters predicted BMP effluent concentrations that were 15% lower than the regional parameters for five pollutants.

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

Web GIS기반의 복합적 토양 질 평가 시스템 개발

It has been known that torrential rainfall events have been occurring worldwide due to climate change. The accelerated soil erosion has caused negative impacts on water quality and ecosystem of receiving waterbodies. Since soil security issues have been arising in various areas of the world, intensive interests have been given to topsoil management in Korea. Thus in this study, Web GIS-based computing system of physical, chemical, and biological topsoil quality indices were developed. In this study, five soil quality maps at national scale and top soil erosion potential were prepared for evaluation of soil quality based on soil erosion potential. For this system, the open source Web GIS engine, OpenGeo, was used as core engine of the system. With this system, decision makers or related personnel in areas of soil erosion Best Management Practices (BMPs) would be able to find the most appropriate soil erosion BMPs based on soil erosion potential and soil quality at the area of interest. The Web GIS system would be efficiently used in decision making processes because of ease-of-use interface and scientific data used in this system. This Web GIS system would be efficiently used because this system could provide scientific knowledge to decision makers or stakeholders. Currently various BMP database are being built to be used as a decision support system in topsoil management and topsoil quality areas.

Developing and testing a best management practices tool for estimating effectiveness of nonpoint source pollution control

Best management practices (BMPs) are being implemented to reduce nonpoint sources pollution in China and worldwide. The effectiveness of individual BMPs is usually assessed through controlled experiments. Field evaluation of the effectiveness of a great majority of BMPs is limited by cost of implementation, site-specific response, and length of time needed to document reliable response. Nonpoint source pollution (NPS) models are increasingly relied upon to estimate water quality response to BMP implementation. This study has developed and tested a tool for estimating the effectiveness of BMPs in controlling NPS pollution by collecting and analyzing existing data from previous studies. It includes 60 BMPs grouped into six classes. Data from combined soil and slope analyses were used to design a BMP effectiveness estimator driven by hydrologic soil groups and slope classes using Visual Basic for Applications and Structured Query Language. This tool includes five primary functions, namely: (1) effectiveness assessment for single or combined BMP, (2) statistical analyses for BMP effectiveness; (3) informational inquiry about individual BMPs; (4) updating and editing the BMPs database; and (5) external expansion as new information becomes available. The tool was tested and validated for BMPs selection in a 27.28 km2 watershed, located within the upper watershed of the Miyun Reservoir in Beijing. Results demonstrate that the tool can be served as an efficient and easy tool for identifying potentially useful BMPs in agricultural areas in China. Overall, this will also allow water environmental professionals to make more confident and accurate BMP recommendations and manage watersheds more effectively.

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

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

Special Issue on Urban Storm-Water Management in the 21st Century

As the practice of storm-water management evolves, so has our understanding of the tools. As we move away from a myopic flood control perspective, new tools to include what we now call green infrastructure best management practices (BMPs) were developed. Green roofs, rain gardens, and porous pavements appeared, with much of the design elements based on reasonable estimates of performance, thus the term “best.” Now we as a profession are moving toward a more engineered approach, with designs based on scientific knowledge of the processes, from soil physics and chemistry to hydrology and hydraulics. Soon it may be time to retire BMPs and move forward with the term “storm-water control measures,” as recommended by the National Academies authors of Urban Stormwater in the United States (National Research Council 2008). This issue of the Journal of Irrigation and Drainage Engineering is devoted to this evolving field of storm-water sustainability, and the effort to predict performance of our storm-water control measures. The 10 papers in this special issue reflect this evolution. Papers range from evaluating the concentration of effluent scoured from catch basins to cost-estimation tools, plus the inclusion of green-infrastructure tools within the International Stormwater BMP Database. Green and stone roofs are represented as are level spreaders. Bioretention/bioinfiltration rain gardens, however, received the most attention with papers on media depth, phosphorus removal, process modeling, mounding, and fines accumulation. This collection truly demonstrates our increasing knowledge base. This effort is a result of collaboration between the Stormwater Infrastructure Committee and Urban Water Resources Research Council, together with the Journal of Irrigation and Drainage Engineering Publications Committee. Conference proceedings from recent Environmental and Water Resources Institute (EWRI) congresses and low-impact development (LID) conferences were reviewed, and a select group of authors was invited to expand and revise their work. These papers passed through the standard journal peer-review process. We hope that this set of papers is of use to the profession. We would like to thank all the contributing authors, the reviewers, and William Ritter, as editor, for their efforts in this special issue.

Performance Modeling of Storm Water Best Management Practices with Uncertainty Analysis

The performance of storm water best management practices (BMPs) contains many uncertainties that make predicting BMP performance difficult. The objective of this study is to build a BMP performance model that incorporates uncertainty analysis and to evaluate this model using observed total suspended solids (TSS) from detention basin data sets in the International Stormwater BMP Database. The representative storage-treatment performance model, the k-C* model, was chosen to represent BMP performance. Its input parameters, influent event mean concentration (EMC) (Cin), and the areal removal rate constant (k) are considered with the uncertainty analysis. To estimate the variance associated with k, the prediction interval method is applied to the linear regression equation relating hydraulic loading rate (q) to k. To estimate the variance of Cin, observed Cin data in the BMP database are used. This study assumes that both Cin and k can be represented by lognormal distributions. The probability density function...

Integration of Low-Impact Development into the International Stormwater BMP Database

Low impact development (LID) strategies are being encouraged in many communities as an approach to reduce potential adverse impacts of development on receiving streams. Many questions exist regarding how well various LID strategies perform in different settings, just as similar questions have been raised regarding performance of traditional stormwater best management practices (BMPs). Whereas historical focus on BMP performance has been water quality concentrations or loads, characterization of volume reduction benefits for both conventional and LID practices is increasingly an objective of researchers and stormwater managers. More than a decade ago, Urban Water Resources Research Council (UWRRC) members worked to develop a set of standardized monitoring and reporting protocols for traditional BMPs and to establish a master database for the purpose of evaluating BMP performance and the factors affecting performance. This effort culminated in the International Stormwater BMP Database (www.bmpdatabase.org), which contains data for more than 360 BMPs and continues to operate as a clearinghouse for stormwater BMP data and performance analyses. During 2008–2009, the International Stormwater BMP Database project expanded to better integrate LID into the database and develop a set of metrics that can be used to characterize BMP performance with regard to surface runoff volume reduction. This paper provides a condensed overview and progress report on the LID-focused effort, including the following topics: (1) monitoring guidance for LID at the overall site development level, (2) an overview of recent changes to the International Stormwater BMP Database to better accommodate LID studies, (3) a summary of LID studies currently included in the database, and (4) a proposed approach for evaluating performance of LID studies with regard to reducing surface runoff volumes.

Comparison of BMP Performance Using the International BMP Database

This paper explores the performance and relative pollutant removal of several common best management practices (BMPs) using data contained in the International Stormwater BMP Database. These BMPs include retention (wet) ponds, extended detention basins, vegetated swales, and sand filters. Although the database contains numerous studies with varying amounts of detail, this comparison is based on the performance of only those sites with reported basic design characteristics and water quality data (event mean concentrations) so that constituent concentrations can be accurately determined and related to the design of the individual BMP. The use of selected BMPs has a number of advantages. Some of the variability in performance observed for facilities of a specific type can be explained by differences in design and/or watershed characteristics; consequently, the expected performance for a given set of conditions can be predicted more accurately. In addition, the differences in performance among BMP types for a given set of conditions can also be established with a higher degree of certainty. The principle measure for comparing the performance between the selected BMPs is their discharge quality, which was found to be a function of the influent concentrations for many constituents. A comparison of the discharge quality as a function of the concentration in untreated runoff demonstrates substantial differences in performance among these BMPs for many constituents.

An Alabama BMP Database for Evaluating Water Quality Impacts of Alternative Management Practices

Best management practices (BMPs) are often used to control nonpoint source (NPS) pollutants from agricultural, forested, and urban watersheds. NPS models are used to estimate pollutant loads, devise NPS abatement plans, and develop and implement Total Maximum Daily Load (TMDL) plans. Accuracy of NPS model prediction depends on, among other things, the accuracy of input data, which includes accurate description of BMPs. Although detailed BMP description can be obtained by using extension manuals and talking to experts, a comprehensive BMP database for use by watershed modelers and water resource managers are usually unavailable. In the absence of regionally appropriate BMP database, simplified assumptions are often used. This practice can introduce input data uncertainty in models, which can lead to poor model predictability and mistrust in models. To alleviate this problem, a comprehensive database of commonly used agricultural and forestry BMPs in Alabama was developed. Using this database, various NPS pollution abatement measures can be evaluated using the SWAT (Soil and Water Assessment Tool) or other distributed parameter, continuous simulation NPS model. Specific objectives were: (1) to develop a database of commonly used BMPs in agriculture and forestry for the State of Alabama and (2) to create an ArcView 3.X GIS (Geographic Information System) extension to load the database into the SWAT model. The complete database containing hundreds of BMPs and supporting documents are available at http://www.eng.auburn.edu/users/srivapu. The database provides environmental professionals with detailed information on management of agricultural and forested lands. This type of detailed information is currently unavailable in Alabama and many other states. Using the BMP database with the SWAT model, environmental professionals will be able to evaluate the site-specific effectiveness of BMPs and conduct more accurate assessments of NPS pollutant loads, TMDLs, pollutant trading, and BMP implementation plans. Overall, this will allow environmental professionals to make more confident BMP recommendations and manage watersheds more effectively. Additionally, the methodology presented can be used by other states to develop region-specific BMP databases.

INTERNATIONAL STORMWATER BMP DATABASE ENHANCEMENTS AND UPDATED FINDINGS

INTERNATIONAL STORMWATER BMP DATABASE ENHANCEMENTS AND UPDATED FINDINGSIn the 1990's, the U.S. Environmental Protection Agency (USEPA) mandated that most municipalities in the United States with populations larger than 10,000 obtain a stormwater runoff discharge permit. One of the requirements of this permit program is the use of nonstructural and structural best management practices (BMPs) appropriate to local conditions for new development and significant...Author(s)Jane ClaryMarcus QuigleyJonathan JonesEric StreckerSourceProceedings of the Water Environment FederationSubjectSession 70: Managing Stormy Weather: Best PracticesDocument typeConference PaperPublisherWater Environment FederationPrint publication date Jan, 2007ISSN1938-6478SICI1938-6478(20070101)2007:13L.5603;1-DOI10.2175/193864707787969360Volume / Issue2007 / 13Content sourceWEFTECFirst / last page(s)5603 - 5616Copyright2007Word count411