Environmental Review Toolkit
Water, Wetlands, and Wildlife

Great Lakes Stormwater Workshop

Quantification Initiative Concept Paper

Background

Conventional development practices often result in a high percentage of impervious surfaces, which can have serious adverse consequences for the environment. Among the significant ways development practices can affect the environment are increased run-off volumes (and flow velocities), increased pollutant loadings to streams, rivers and lakes, and decreased groundwater recharge.

Traditional storm water management design features are intended to efficiently remove excess rain water from sites by limiting peak flow amounts and storing the run-off in a controlled manner. These practices do help reduce some impacts on streams and rivers and lakes, however, they do not completely solve the run-off problem. Traditional storm water sewers move the water - and the pollutants typical of urban areas - quickly away from the site and release it from holding systems over a longer period of time, resulting in run-off volumes that are still much higher than the pre-development conditions. This may lead to downstream flooding, degraded stream quality, and disruptions in aquifer recharge.

"Green" design features and management practices, such as rain gardens, vegetated swales, and permeable paving systems, are intended to address some of these water management issues by managing some or all of the storm water on a site through infiltration and evapotranspiration. By increasing the time of concentration and decreasing the volume of run-off, green design features and management practices can help protect water resources. Additionally, many green design features and management practices may result in improved groundwater recharge. Also, in some cases, using green design features and management practices may be more cost-effective than conventional design practices which focus on use of "grey" infrastructure for managing storm water.

Quantification Project Objectives

The lack of compiled, analyzed, and easily-accessible information on the performance of green design features and management practices is a barrier to their implementation. Storm water engineers, planners, lenders, developers, and project decision-makers need accurate, reliable, and quantified information on the performance and benefits of green design features and management practices, and they need that data presented - at least initially - as part of their commonly used models. Without performance data, engineers working on sites or infrastructure projects cannot account for the performance of the green features, and may end up designing redundant systems or may even avoid green design features entirely. Without the information being presented in a professionally accepted mode, it is unlikely that the data will be consistently used. Project decision-makers also need quantified information on the performance and benefits of green design features and management practices so they can ensure their project dollars are being well-spent.

There are numerous case studies examining the performance of management practices at individual sites. Many of these case studies are documented in the International Storm Water Best Management Practices Database (http://www.bmpdatabase.org/). However, the database does not include case studies for all types of green design features and management practices at all types of sites (sites will vary in terms of climate zone, soil types, and other factors which will influence green design feature and management practice performance). Performance varies with surficial soils, lower soil horizons, depth to water table, climate, slope size of catchment, size of BMP, season, maintenance, antecedent conditions, storm characteristics, etc. The number of possible combinations of site, green design feature or management practice, and hydrologic conditions is effectively infinite. As a result, developing a database that describes all combinations is not feasible. In addition, there has not been a systematic analysis of the performance of green design features and management practices across the case studies to generalize about and predict performance in different settings. However, with data from a well-designed sampling of a subset of the different possible combinations, we can describe the anticipated behavior of the feature as different parameters are changed. This can be incorporated into simulation models that allow reasonable prediction of the anticipated performance of many combinations of sites, green design features and management practices, and hydrologic conditions. In parallel, research projects can be conducted across the country to fill gaps in performance data.

The long-term goal of the project is to feed the run-off prediction models with enough complete, precise, and quality-assured data that engineers and planners will have the same level of confidence in their green storm water management features as they currently have in their conventional systems. It is also expected that analyses of alternatives will reveal that in many cases the green approaches will perform as well or better than conventional storm water features, and at a comparable or possibly lower cost. This will result in increased implementation of green design features and management practices, and better protection of water resources.

Project Approach

Analysis of Existing Information
The first step of the quantification project will be to engage a university partner(s) to compile and analyze all existing information that can be found on the performance of green design features and management practices. As information is reviewed, the setting where the practices were implemented and the experimental design methodology will be recorded. The deliverable will be a compilation of existing information (e.g., a table or database providing information on the performance of the BMPs) and a research agenda detailing the key data gaps and research needs on the performance of specific practices in particular settings.

Integration of Performance Data into Models
Many design engineers and regulatory agencies use models such as TR-55, TR-20, L-THIA, SWMM, and/or SWAT to predict the peak rate of run-off and/or the volume of run-off from a study area, and green design features and management practices affect the volume of flow and the time-of-concentration. One or more of these models are often required with submission of storm water design plans by state or local governments. If the affects of green practices can be reliably determined (possibly as a range with confidence intervals) in terms of volume and the time-of-concentration, the performance of the design features and management practices could be simulated using these models. It may be possible to plug performance data into a module of one or more of these models. Concurrently with the first step of the project, the research team will work with the Natural Resource Conservation Service (TR-55 and TR-20), Purdue University (L-THIA), U.S. EPA (SWMM), the Center for Neighborhood Technology (Green Infrastructure Calculator), etc., to assess the best way to enumerate the design feature/management practice performance data so that the information can be used in conjunction with different run-off models. A subset of the data from existing studies will then be systematically analyzed in order to generalize and predict performance in different settings. At the same time, the researchers will develop confidence intervals for the data when there are limitations on the certainty of the information being presented. Initial performance information will be formatted and rolled out for easy incorporation in simulation models, in addition to making it available in tables/databases.

Development of Methodology, Initiation of Research Projects, and Rollout of Enhanced Data
In order to rigorously carryout the data gap research agenda, a specific experimental design and documentation methodology will be developed. This will ensure that the research conducted is fully documented, scientifically valid, and presented in a way that is useful for this project. Once that is completed, small groups of researchers in universities, municipalities, and/or private practice will implement the key projects catalogued in the research agenda. As research proceeds to fill data gaps and increase the accuracy of predictions on the performance and benefits of green practices, the project team will continue to seek input from institutions maintaining models and from planners, engineers, and municipal officials. This will ensure that the data generated is consistent with industry needs and delivered in a format that is most useful to a broad range of run-off calculation models. After the studies are completed, there will be a roll-out of enhanced dataset(s) on the performance and benefits of green design features and management practices. This roll-out will include quantified information on the performance of green practices that is sufficiently complete, precise, and quality-assured, so that it can be used in the design of storm water systems. The information will be complied and presented in ways that it can be used in a database setting and in run-off models.

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Questions and feedback should be directed to Susan Jones (Susan.Jones@dot.gov, 202-493-2139) and Marcel Tchaou (Marcel.Tchaou@dot.gov, 202-366-4196).

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