National Academies Press: OpenBook

A Watershed Approach to Mitigating Stormwater Impacts (2017)

Chapter: Chapter 2 - Watershed-Based Mitigation Datasets

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Suggested Citation:"Chapter 2 - Watershed-Based Mitigation Datasets." National Academies of Sciences, Engineering, and Medicine. 2017. A Watershed Approach to Mitigating Stormwater Impacts. Washington, DC: The National Academies Press. doi: 10.17226/24753.
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Suggested Citation:"Chapter 2 - Watershed-Based Mitigation Datasets." National Academies of Sciences, Engineering, and Medicine. 2017. A Watershed Approach to Mitigating Stormwater Impacts. Washington, DC: The National Academies Press. doi: 10.17226/24753.
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Suggested Citation:"Chapter 2 - Watershed-Based Mitigation Datasets." National Academies of Sciences, Engineering, and Medicine. 2017. A Watershed Approach to Mitigating Stormwater Impacts. Washington, DC: The National Academies Press. doi: 10.17226/24753.
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Suggested Citation:"Chapter 2 - Watershed-Based Mitigation Datasets." National Academies of Sciences, Engineering, and Medicine. 2017. A Watershed Approach to Mitigating Stormwater Impacts. Washington, DC: The National Academies Press. doi: 10.17226/24753.
×
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Suggested Citation:"Chapter 2 - Watershed-Based Mitigation Datasets." National Academies of Sciences, Engineering, and Medicine. 2017. A Watershed Approach to Mitigating Stormwater Impacts. Washington, DC: The National Academies Press. doi: 10.17226/24753.
×
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Suggested Citation:"Chapter 2 - Watershed-Based Mitigation Datasets." National Academies of Sciences, Engineering, and Medicine. 2017. A Watershed Approach to Mitigating Stormwater Impacts. Washington, DC: The National Academies Press. doi: 10.17226/24753.
×
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Suggested Citation:"Chapter 2 - Watershed-Based Mitigation Datasets." National Academies of Sciences, Engineering, and Medicine. 2017. A Watershed Approach to Mitigating Stormwater Impacts. Washington, DC: The National Academies Press. doi: 10.17226/24753.
×
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Suggested Citation:"Chapter 2 - Watershed-Based Mitigation Datasets." National Academies of Sciences, Engineering, and Medicine. 2017. A Watershed Approach to Mitigating Stormwater Impacts. Washington, DC: The National Academies Press. doi: 10.17226/24753.
×
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Suggested Citation:"Chapter 2 - Watershed-Based Mitigation Datasets." National Academies of Sciences, Engineering, and Medicine. 2017. A Watershed Approach to Mitigating Stormwater Impacts. Washington, DC: The National Academies Press. doi: 10.17226/24753.
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6Background A first step in comparing on-site BMP effectiveness with other potential stormwater mitigation measures is to identify the data necessary to conduct a baseline watershed assessment using data analysis and GIS technology. Baseline assessments provide an accounting of existing watershed conditions and allow state DOTs a way to identify and prioritize areas for environmental improvement. While there is a wealth of data available, only a limited number of nationally available datasets exist that can be used to compare potential stormwater mitigation options that are at a sufficient scale, level of detail, and sufficient degree of confidence. Some of this data is more applicable for NPDES compliance projects and watershed- based assessments than others. Utilizing online data and standard watershed characterization information during the planning process can minimize time and costs and provide local and state interagency watershed planning teams a common base from which to begin to identify goals on a watershed basis. Readily avail- able watershed characterization data provided by the U.S. Environmental Protection Agency (USEPA) and U.S. Geological Survey (USGS) can help DOTs implement a watershed approach while avoiding significant impacts to staff workloads. This chapter provides the process and criteria used to identify applicable datasets for the WBSMT. Three data sources are highlighted for gathering data for use in any baseline assessment to pro- vide a fundamental understanding of watershed conditions: the USEPA Enviro Atlas, the U.S. Department of Agriculture (USDA) Natural Resource Conservation Service (NRCS) Web Soil Survey, and the National Oceanic and Atmospheric Administration’s (NOAA) National Centers for Environmental Information (NCEI) Precipitation and Climate Information. DOTs may choose to incorporate regional and local datasets of various scales to supplement the information in their toolbox in order to meet specific regulatory or resource protection program needs. Understanding the Basic Data Needs The basic types of geographic information included in a baseline watershed conditions analysis can be broken into two types: physical and political. Physical geographic features refer to the built and natural environment, such as roads, water bodies, elevations, soils, and other landscape ele- ments. Political geographic features refer to those lines imposed on the landscape by people, such as the boundaries of towns, watersheds, and other areas that are political units or have been set aside by government or others for a particular purpose. Watershed-Based Mitigation Datasets C H A P T E R 2 To find the WBSMT, go to the TRB website and search for NCHRP Research Report 840.

Watershed-Based Mitigation Datasets 7 Physical Geographic Features Political Geographic Features Topography and soils Protected/endangered species habitat Hydrology (surface water flow data; gauging data) and pollution characteristics Watershed boundaries (most commonly being the Hydrologic Unit Code [HUC]) Floodplains and riparian areas Waters with special designations, such as a Wild and Scenic River (Federal designation), High Quality Waters (Maryland), or Outstanding National Resources Waters (New Mexico) Streams (perennial, intermittent, and ephemeral) Surface and groundwater resources Water quality categorization, including receiving water impairment issues and areas where water quality parameters exceed federal and state standards (303d listings and TMDLs) Areas ranked high for ecosystem services Aquifer recharge areas Climate/precipitation/meteorological data Septic and stormwater infrastructure Roads, railroads, and landmarks Land use and land ownership Impervious area and land cover Town, city and state boundaries Table 1. Common data types utilized in watershed assessments. Table 1 provides an example of the types of common information utilized when conduct- ing a watershed assessment. The purpose of gathering the data is to document the current condition of water and natural resources, sources of pollution, and other relevant factors in the watershed in which the DOT project is located and to identify and prioritize areas for envi- ronmental improvement. Which spatial data are incorporated depends on the specific goals of the prioritization effort. For example, the identification and prioritization of stormwater mitigation projects must first consider water quality improvement needs. This is accomplished by an analysis of physical and regulatory factors. This includes estimating runoff volumes, pollutant loads, and stressors by analyzing land use, imperviousness, receiving water impair- ments from state lists of impaired and threatened waters (303d listings) and TMDLs, and local monitoring data (when available). Additional data may also be considered based on the DOT’s specific needs. Examples include geomorphic attributes of stream reaches, critical habitat areas, geological hazards, designated open space, brownfield areas, and areas for urban development and redevelopment. Data Selection Criteria The datasets available for watershed assessments cover a wide range of scale, function, rigor, documentation, ease of use, and level of acceptance by regulatory and resource pro- tection agencies and the scientific and engineering communities. Watershed assessments can occur at various scales. For transportation planning, the 12-digit Hydrologic Unit Code (HUC) scale is commonly used. Watersheds in the United States and the Caribbean have been delineated by the USGS using a national standard hierarchical system based on sur- face hydrologic features and georeferenced to USGS 1:24,000 scale topographic base maps. HUC-12 is considered a local subwatershed level that captures tributary systems and with an average size of 37 square miles (Alley et al. 2013). It is the smallest unit at which nationwide data is collected. Datasets utilized in watershed assessments must be acceptable in scientific rigor to project stakeholders. From a DOT staff perspective, it is important that data utilized for watershed assess- ments is also practical, cost-effective, and readily available if baseline assessments are to help inform the selection and placement of post-construction BMPs. Four screening criteria were applied to identify and rank datasets for use by DOTs on a nationwide basis. This publication

8 A Watershed Approach to Mitigating Stormwater Impacts focuses on nationally available datasets, though the same selection criteria can be used to evaluate other available datasets: • Criteria 1: Availability. Data are easily accessible and available for use on a nationwide basis or, at a minimum, within the 48 contiguous states to serve the purpose of tool creation for a national audience. • Criteria 2: Applicability. Data used in analysis has clear applicability to the assessment of environmental benefits. • Criteria 3: Acceptability. Data used in analysis is able to technically support the evaluation objectives. Data and information should be rigorous and acceptable to regulatory and resource protection agencies. Preferably, such information should also be easy to understand such that review can be conducted with minimal effort. • Criteria 4: Manageability. Data collection, interpretation, training, and upkeep requirements are minimal for the DOT. The data should be generated and maintained by a third party and avoid additionally burdening the already over-stretched professionals involved in the regula- tory process, at all agencies. The intent is to extend effectiveness without greatly impacting the time needed. Criteria 1: Availability Datasets should be openly accessible and as widely available as possible so that the data are transparent and easily shared with involved stakeholders. Utilizing common datasets that are readily available and at an appropriate scale can both ease application and help standardize effec- tive new approaches, especially when federal agencies are involved. Stakeholders for a given DOT project can be numerous and may include various regulatory agencies, elected officials, and/or members of the community at large who may be affected by project impacts. Data can be obtained from government agencies (federal, state, or local), non-governmental organizations (NGOs), and/or private entities, provided that there is a level of confidence that this source of information is reputable within the scientific community (see Criteria 3: Acceptability). Data may be available via online access or data may need to be requested directly. For exam- ple, all data for natural resources decision-making in Florida is provided by resource agencies as part of Florida DOT’s multi-agency Efficient Transportation Decision Making Process (FHWA, no date). Some organizations charge fees to access their data. For this reason, freely available public agency data, or high value scientific data to which federal agencies have already negotiated access, at least in part was given higher priority. In addition, freely available agency data typically undergoes agency-required quality control review. This and the potential for wide, agency buy-in, along with increasing standardization in analytical practices nationwide, all add reasons to prefer data made available by federal, state, or local resource agencies. Criteria 2: Applicability Datasets must be applicable to environmental management of stormwater impacts for DOT projects and the benefits that may be achieved by related mitigation. Nationally available data at the 12-digit HUC is sufficient for many aspects. For other aspects, it may be advantageous to supplement nationally available data with local, more refined data. Data should be able to be used for at least one of the following environmental evaluations to be included in analysis and used in decision-making: • Water quantity assessment – The data can be used to evaluate water quantity-based mitiga- tion approaches (e.g., those addressing volume or rate). • Water quality assessment – The data can be used to evaluate water quality-based mitigation approaches (e.g., those based on pollutant loading or concentration).

Watershed-Based Mitigation Datasets 9 • Watershed characterization – The data can be used to evaluate watershed conditions (e.g., habitat, water quality, or ecosystem functions) that may be addressed or that may benefit from the DOT’s action to mitigate in alternative ways to traditional stormwater BMPs, for storm- water impacts. • Ecosystem services evaluation – The data can be used as part of an ecosystem services evalu- ation, comparing the overall societal benefits that may be achieved by one type of ecological enhancement over another, and in one location over another. • Watershed priority evaluation – The data can be used to identify watershed priorities or goals. • Spatial linkage – The data can spatially link project impacts and mitigation benefits within the watershed. Criteria 3: Acceptability Datasets must be relevant to watershed mitigation objectives in that the type and quality of the data must address the technical needs of the evaluation. Various qualities of a dataset or factors in its collection make a dataset relevant or irrelevant to the task at hand: • Transparency – The data gathering method is transparent and explained to verify the process and quality control of the data. The data is also collected in a manner that provides confidence in the accuracy of data measurements. • Application flexibility – The data is appropriate for addressing a variety of watershed condi- tions or parameters in order to meet local requirements. • Output resolution – There is sufficient level of detail in the data, and the data does not have large gaps of missing information. • Metadata quality –The dataset has sufficiently descriptive metadata documenting the collec- tion methods, observation location and conditions, and the level of quality control that has been applied to the data. The data have consistent units and descriptions, or classifications. Criteria 4: Manageability DOTs and other agencies responsible for datasets must be able to provide a minimum level of organizational and technical effort in all aspects of data management. This includes data acquisi- tion, usage, and management of the data selected for use in watershed level efforts and statewide programmatic assessments. Dataset manageability as it relates to data selection takes into account the efforts required by agency personnel throughout the watershed-based mitigation approach process including the following: • Collection method – The three typical methods of acquiring data for use in mitigation assess- ment, in order of most intensive/less manageable (Level 1) to least intensive/more manageable (Level 3), are: – Level 1 – On-the-ground data collection requiring specific instrumentation and sampling; – Level 2 – Simplified typical observational field data collection; and – Level 3 – Readily accessible databases and GIS datasets. Larger landscape and/or watershed analysis requires Level 3 data for practical and widespread application by DOTs and resource agencies. An efficient, cost-effective process uses Level 3 data supplemented with Levels 1 and 2 data as needed. • Processing time – The time required for DOT staff to collect, verify, and use the data varies based on the size of the dataset, the number of datasets used, and any issues that need to be addressed regarding the quality and format of the data is a consideration for DOTs. • Maintenance needs – The resources required to maintain data vary based on factors such as the type of data and the upkeep required to collect new data or adjust existing data based on new or updated information. Many DOTs involved in planning-level interagency review efforts

10 A Watershed Approach to Mitigating Stormwater Impacts rely on datasets maintained by resource agencies. In some cases, programmatic agreements or memorandums of understanding record required data maintenance efforts, reducing both the maintenance burden on the DOTs and the agreed quality and applicability of the data among the partner agencies. Both the Florida Department of Transportation’s Efficient Transporta- tion Decision Making effort (https://etdmpub.fla-etat.org/est/) and the Maryland Watershed Resources Registry (http://watershedresourcesregistry.com/) provide examples of how this may be done. Dataset Analysis The use of GIS data to help establish watershed and ecosystem restoration priorities has grown over the past decade. As a result, there are an increasing number of datasets available that are relevant to establishing a watershed- and ecosystem-based approach for post-construction storm- water management along highway corridors. These datasets cover a wide range of scale, function, rigor, documentation, ease of use, and level of acceptance by regulatory and re source protection agencies and by the scientific and engineering communities. Federal agencies such as the USEPA, NOAA, and the USGS have developed several tools and databases that bring together GIS data necessary to compare on- and off-site storm water mitiga- tion options. Examples include the How’s My Waterway (http://watersgeo.epa.gov/mywaterway/), the My Watershed Assessment, Tracking and Environmental Results System (MyWATERS) Map- per (http://watersgeo.epa.gov/mwm/) and the EnviroAtlas (https://www.epa.gov/enviroatlas) data- bases and tools available through the USEPA’s website; The National Map (http://nationalmap. gov/), which is available through the USGS; and the NCEI (https://www.ncei.noaa.gov/). Relevant regional, state, and local level GIS-driven data and planning efforts were also reviewed. The purpose was to determine what data was employed in the various comparative assessment tools and restoration prioritization projects and to determine their utility for developing a nation- wide tool to establish restoration priorities and compare on- and off-site mitigation opportunities for transportation projects. Table 2 provides a summary of data source types that were reviewed. Datasets were assessed for their ability to be used to describe water quantity, water quality, and ecosystem services, to help characterize watersheds, and to help to identify watershed priorities. The utility and applicability of specific datasets and tools were assessed using two main criteria: the associated level of effort involved in data collection and the rigor of the resulting datasets. Assessing the labor intensity of the data collection effort involved evaluating the extent of the resources a DOT would need to allocate to an analysis approach using this particular tool. The rigors of the resulting datasets were assessed based on transparency, flexibility, resolution, and data quality. Data Description and Sources Waterway, impaired waters, climate information, and sustainability data from the USEPA, NOAA, and USGS State and regional agency plans, including statewide long-range transportation plans and state wildlife action plans Local agency plans including land use plans, comprehensive plans, conservation plans, and watershed restoration plans NGO conservation and restoration plans, including local and regional land trust plans National species conservation and natural heritage program data Other data, including reach and protected area databases, national hydrography and soils datasets, state and municipal wetland and watershed plans, and greenways and green infrastructure initiatives Table 2. Summary of data sources reviewed.

Watershed-Based Mitigation Datasets 11 The majority of the watershed assessment datasets reviewed placed greater emphasis on the ecol- ogy of the system in order to identify high priority habitat or wetland restoration opportunities. Including ecosystem services analyses in watershed assessments can help track the economic and social consequences of changes to ecological conditions and provide a unique approach to determining equivalency of impacts that are often not considered in stormwater mitigation efforts. Watershed characterizations may often include some degree of an ecosystem services assessment. A full ecosystem services analysis within the watershed can provide a more system- atic and comprehensive assessment of the complete effects of the ecological changes being pro- posed for the project or a proposed offset. Although the primary focus of the data identification was on NPDES compliance, the datasets identified are also very useful for supporting ecosystem services analysis. Datasets Used in the Toolbox The USEPA’s EnviroAtlas was identified as the most appropriate single source of data for use in the WBSMT, augmented by information from NOAA’s NCEI and the USDA NRCS Web Soil Survey. The USEPA’s EnviroAtlas is the relative newcomer to the field of online data platforms at the national scale and serves to combine over 300 separate data layers from the EPA, USGS, USDA, and other federal and non-federal agencies to help decision-makers understand the envi- ronmental implications of planning and policy decisions. Most importantly for the WBSMT, EnviroAtlas interprets and summarizes data by 12-digit HUC, which was identified as the desired scale for evaluating DOT BMP options at the planning level. EnviroAtlas EnviroAtlas (www.epa.gov/enviroatlas) is a relatively new open-access geospatial tool devel- oped by the USEPA in partnership with USGS, the U.S. Department of Agriculture’s Forest Service and NRCS, and LandScope America. It combines a series of indicator data available for the contiguous United States that is to be updated as new foundational data is released. Indicator data are organized into seven categories: • Clean Air • Clean and Plentiful Water • Natural Hazard Mitigation • Climate Stabilization • Recreation, Culture, and Aesthetics • Food, Fuel, and Materials • Biodiversity Conservation EnviroAtlas also includes reference data related to the built environment such as data on demographics, land cover, political boundaries, watershed boundaries, NPDES permit status, and impaired and listed waters to enable the user to evaluate resources, change, and trends over time. Indicator data is developed down to the HUC-12 scale for the contiguous United States, allowing for information to be compared across areas and at multiple scales. For example, a community can view stream reach level data and information on 303d-impaired waters as well as information on land use and reference data in order to craft localized solutions tailored to benefit water quality (Pickard et al. 2015). EnviroAtlas has been used for a variety of projects. The USEPA’s Office of Water is utilizing EnviroAtlas to help prioritize watersheds to address water quality impairments based on recov- ery potential. In Durham, NC, city planners utilized EnviroAtlas data to identify schools for tree plantings based on ecosystems values and needs (Pickard et al. 2015).

12 A Watershed Approach to Mitigating Stormwater Impacts Table 3 provides a description of the qualitative scoring criteria used to evaluate datasets avail- able through EnviroAtlas based on availability, applicability, acceptability, and manageability needs. The evaluation of datasets was limited primarily to those of potential use for compar- ing stormwater mitigation options, with some additional datasets evaluated that have value for comparing ecosystem services. Tables 4 and 5 provide a summary of how the datasets fared when evaluated using the four scoring criteria. The robust nature of EnviroAtlas, its ability to be scaled up and down, and stated focus on regular updates as new base information becomes available makes the EnviroAtlas well-suited to the WBSMT. Datasets that were older in age, such as those based on the 2006 National Land Cover Database (NLCD), ranked lower in terms of data collec- tion and maintenance efforts, as the age of such datasets may require a DOT to substitute their own, newer data in the place of older datasets. NCEI Precipitation and Climate Information NCEI is the world’s largest provider of weather and climate data. Climatic data are available for many U.S. cities for monthly, daily, and hourly time steps and is an important consider- ation when designing stormwater mitigation projects. The NCEI’s precipitation and climatic data enables users to determine volumetric runoff estimates to size BMPs based on project impervious area when an on-site range gauge is not available. Precipitation data is also available for many cities in 15 minute and hourly time steps. Raw data is often available for use in analysis. This informa- tion is useful for developing BMPs for water quality and quantity purposes and for calculating the potential volumes to be treated at the project and off-site locations. A full list of available data is available on the NCEI website (http://www.ncdc.noaa.gov/data-access/quick-links). Criteria Description Scoring Criteria 1: Availability Applicable scale Watershed scale of data (site, subwatershed (6th digit HUCs), watershed (5th digit HUCs), region, state, nationwide, etc.) N/A Criteria 2: Applicability Describes water quantity Data can be used to evaluate water quantity-based mitigation approaches (e.g., those addressing volume or rate) Yes/No Describes water quality Data can be used to evaluate water quality-based mitigation approaches (e.g., those based on pollutant loading/concentration) Yes/No Watershed characterization Data can be used to evaluate watershed conditions (e.g., habitat, water quality, or ecosystem functions) that may be addressed by or benefit from mitigation Yes/No Ecosystem services evaluation Data relates ecosystem services provided by watershed to activities to allow comparison of mitigation options Yes/No Watershed priority evaluation Data can be used to identify watershed priorities or goals Yes/No Spatial linkage Data can spatially link project impacts and mitigation benefits within the watershed Yes/No Criteria 3: Acceptability Data collection transparency Data gathering method is transparent and explained to verify the process and quality control of the data 1 – 3* Application flexibility Ease of data or tool application to measure required watershed conditions or parameters 1 – 3* Output resolution Level of detail in the data layer or tool output 1 – 3* Metadata quality Documentation (metadata) is available to describe the data and its limitations and applicability under different scenarios 1 – 3* Criteria 4: Manageability Data collection and maintenance effort Level of rigor and labor intensiveness associated with data collection, processing, and maintenance 1 – 3* Note: *Scoring from 1-3, with 3 being the highest/best. Table 3. Database scoring criteria.

Watershed-Based Mitigation Datasets 13 Criteria Criteria 1: Availability Criteria 2: Applicability D es cr ib es w at er qu an tit y D es cr ib es w at er qu al ity W at er sh ed ch ar ac te riz at io n Ev al ua te s ec o sy st em se rv ic es H el ps id en tif y an d ev al ua te w at er sh ed pr io rit ie s Sp at ia lly li nk s pr oje ct to m iti ga tio n ne ed / o pp or tu ni ty ENVIROATLAS DATA LAYER Acres of crops that have no nearby pollinator habitat SW N N Y Y Y N Atmospheric nitrogen deposition data by 12-digit HUC (2006 and 2002) SW N Y Y Y Y Y Average annual precipitation 1981-2010 by HUC-12 SW Y N Y N Y N Biodiversity conservation metrics SW N N N Y Y Y Biological nitrogen fixation in natural/semi-natural ecosystems by SW N Y Y Y Y Y Ecosystem rarity metrics by 12-digit HUC 12-digit HUC HUC-12 SW N N Y Y Y Y HUC-12 polygons SW N N Y N Y Y Land cover NW N N Y Y Y Y Land cover on wet areas SW N N Y Y Y Y Morphological Spatial Pattern Analysis connectivity SW N N Y Y Y Y NatureServe analysis of imperiled or Federally listed species by R/NW N N Y Y Y Y Percent impervious NW N N Y Y Y Y Percent urban land cover by 12-digit HUC SW N N Y Y Y Y Percent stream buffer zone as natural land cover SW N N Y Y Y Y Potentially restorable wetlands S N N Y Y Y Y Protected lands SW N N Y Y Y Y Rare ecosystems R/NW N N Y Y Y Y Synthetic N fertilizer application to agricultural lands by 12-digit HUC SW N Y Y Y Y Y 303(d) impairments by 12-digit HUC SW N Y Y Y Y Y Note: S– Site, SW – Subwatershed, W – Watershed, R – Region, ST – State, NW – Nationwide, Y – Yes, N – No Table 4. EnviroAtlas evaluation criteria: availability and applicability. USDA NRCS Web Soil Survey The WBSMT relies on users providing dominant hydrologic soil group (HSG) classifications for their project area and overall watershed. These ratings are used to estimate runoff potential for pervious areas as part of the stormwater runoff volume and load calculations to BMPs. They can be obtained from the USDA NRCS Web Soil Survey (http://websoilsurvey.sc.egov.usda.gov/). HSG classifications can vary by location, which means that soils with the same map unit name but located in different counties may have different hydrologic soil group classifications. It is impor- tant to understand that the ratings provided by the Web Soil Survey are often for natural soil condi- tions, not an altered condition as is common in almost every stormwater BMP project within the ROW. Therefore, the user has the ability to select a more representative HSG for their project area. Limitations of Datasets and Models Reliance on nationally available datasets at the HUC-12 scale provides a solid basis for com- paring stormwater mitigation options with a sufficient level of confidence at the planning level, but it is important to understand the limitations. Examples include data that is too old, too coarse, or unreliable. In many cases, more complex and detailed analysis may be required. Local data may be used or collected if the DOT finds such investment is justified where data and knowledge gaps occur or datasets are considered overly coarse. The latter may be based on the

14 A Watershed Approach to Mitigating Stormwater Impacts value and amount of transportation activities occurring in the watershed. Depending on the confidence in the dataset, users may decide to apply a factor of safety to account for uncertainty or lack of information. This factor of safety should be developed to provide a level of confidence that the quality of data attributed to these datasets is commensurate with the national, agency produced data. The factor of safety is designed to make the data acceptable for use. Many of the limitations to successful implementation of watershed approaches revolve around the inability of such approaches to make direct connections with typical water quality and quantity data in ways that different solutions can be compared at different locations in the watershed. This step is critical to determine the potential stormwater and the ecosystem services benefits at the watershed scale. Nevertheless, more information may need to be collected in one area, at a more defined scale, or through monitoring, to obtain information on watershed responses to the mitiga- tion approaches. New models that quantify benefits from mitigation approaches in terms of pollutant load reductions both for traditional and watershed-based mitigation are expected to become available. The risks of using these new analysis techniques may exceed the capacity, intent, or resolution of the datasets. DOTs must have confidence in models and be able to verify the projected outcomes. In many instances, an iterative approach may be required to establish mitigation credits against project stormwater impacts. Safety factors may also be necessary and built into the calculations to increase confidence levels when uncertainty exists in the data or the computations involved. Criteria 3: Acceptability Criteria 4: Maintenance D at a co lle ct io n tr an sp ar en cy A pp lic at io n fle xi bi lit y O ut pu t re so lu tio n M et ad at a qu al ity D at a co lle ct io n an d m ai nt en an ce ef fo rt ENVIROATLAS DATA LAYER Acres of crops that have no nearby pollinator habitat 3 1 2 3 3 Atmospheric nitrogen deposition data by 12-digit HUC (2006 and 2002) 3 3 3 3 2 Average annual precipitation 1981-2010 by HUC-12 3 3 2 3 3 Biodiversity conservation metrics 3 3 3 3 3 Biological nitrogen fixation in natural/semi-natural ecosystems by 12-digit HUC 3 2 2 3 2 Ecosystem rarity metrics by 12-digit HUC 3 1 3 3 3 HUC-12 polygons 3 3 3 3 3 Land cover 3 2 2 2 2 Land cover on wet areas 3 3 2 2 2 Morphological Spatial Pattern Analysis connectivity 3 1 3 3 2 NatureServe analysis of imperiled or Federally listed species by HUC-12 3 1 2 3 3 Percent impervious 3 2 2 2 2 Percent urban land cover by 12-digit HUC 3 3 2 3 2 Percent stream buffer zone as natural land cover 3 2 2 3 2 Potentially restorable wetlands 3 2 2 3 3 Protected lands 3 1 2 3 3 Rare ecosystems 3 1 2 3 3 Synthetic N fertilizer application to agricultural lands by 12-digit HUC, 2006 3 2 2 3 2 303(d) impairments by 12-digit HUC 3 3 3 3 3 Note: Scoring from 1-3, with 3 being the highest/best. Table 5. EnviroAtlas evaluation criteria: acceptability and maintenance.

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TRB's National Cooperative Highway Research Program (NCHRP) Research Report 840: A Watershed Approach to Mitigating Stormwater Impacts provides a practical decision-making framework that will enable state departments of transportation (DOTs) to identify and implement offsite cost-effective and environmentally beneficial water quality solutions for stormwater impacts when onsite treatment and/or mitigation is not possible within the right-of-way.

The report is accompanied by the Watershed-Based Stormwater Mitigation Toolbox, a Microsoft Excel-based program to facilitate the characterization of the project watershed and the identification of mitigation options at the planning level.

Disclaimer - This tool is offered as is, without warranty or promise of support of any kind either expressed or implied. Under no circumstance will the National Academy of Sciences, Engineering, and Medicine or the Transportation Research Board (collectively "TRB") be liable for any loss or damage caused by the installation or operation of this product. TRB makes no representation or warranty of any kind, expressed or implied, in fact or in law, including without limitation, the warranty of merchantability or the warranty of fitness for a particular purpose, and shall not in any case be liable for any consequential or special damages.

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