EPA Nonpoint Source (NPS) Baseline Analysis Workgroup Summary Workgroup Members Name Affiliation Email Joanna Ashford KY Division of Water joanna.ashford@ky.gov Katie Basiotis KS Department of Health and Environment Katie.Basiotis@ks.gov Kamilah Carter EPA Region 4 carter.kamilah@epa.gov Chris Janssen KS Department of Health and Environment (moved to new position at EPA) janssen.christopher@epa.gov Aseem Kumar NY Department of Environmental Conservation aseem.kumar@dec.ny.gov Robyn Leto EPA Region 3 Leto.Robyn@epa.gov Maria Lopez EPA Region 10 Lopez.Maria@epa.gov Cindy Osborn Minnesota Pollution Control Agency cynthia.osborn@state.mn.us Pete Vincent Ml Department of Environment Great Lakes and Energy vincentp@michigan.gov NPS Equity Initiative and Workgroup Background The Baseline Analysis Workgroup was initiated as part of the EPA Nonpoint Source (NPS) program's efforts to assess and expand equity and inclusion across the national program. This work was initiated by the Near-term Actions to Support Environmental Justice in the Nonpoint Source Program memo. In the memo EPA has committed to take actions to ensure equitable and fair access to the benefits from environmental programs including the Nonpoint Source Program. A piece of this commitment is the "Baseline Analysis" which is a geospatial study that includes developing a methodology to assess how Section 319 state project funds have historically been distributed when compared to overburdened/underserved communities. Additionally, this analysis should develop a means for state programs to assess how future work may better target NPS water quality problems in overburdened/underserved communities. EPA NPS HQ program staff began developing this analysis in early 2022 as the program conducted a series of regional, state, and tribal listening sessions on equity and inclusion in the NPS program. During this time the team received some initial feedback on data and methods from agency experts in environmental justice and public health research. Following these listening sessions, a series of workgroups consisting of EPA, state, territory, and tribal program staff were initiated to further explore topics that emerged as common themes in the listening sessions. ------- Baseline Analysis Workgroup Goals and Topics The overarching goal of this workgroup was to receive feedback and input on the draft Baseline Analysis data and methodology, and on how to begin in engaging with state programs in piloting the Analysis and ground truthing findings. This workgroup met between April 4 - June 7 and consisted of four 1.5-2 hour meetings (some split into multiple time blocks). Specific goals and topics explored by the Baseline Analysis workgroup include: • Existing/ongoing state EJ analysis/mapping efforts • Data sources and layers to be included • Methods for conducting the Analysis (including use of EPA's Recovery Potential Screening Tool) • Engaging with state programs on the Baseline Analysis This summary was drafted using notes taken during each of the workgroup meetings. Workgroup Themes/Findings Data and Methodology 1. In determining where NPS management efforts can be focused to improve equity and inclusion across the program, this analysis should consider both social and environmental data. Specifically, in conducting this analysis the program should endeavor to identify and consider where the NPS efforts will be useful/able to address water quality issues. a. Inclusion of water quality data related to nonpoint source b. Program dollars if available (by state) c. Public water supply data d. Parse out NPS specific TMDLs 2. Issues related to the scale of the analysis/available datasets a. The workgroup noted several challenges that can arise when conducting this analysis using national-scale datasets (i.e., Watershed Index Online (WSIO) data library) and attempting to set a uniform threshold for determining overburdened/underserved communities for a national program. Points included: i. The socioeconomic context will vary by state. Many factors that contribute to a community being overburdened/underserved including, urban vs rural distribution within a state, average income, cultural context/makeup, climate risk/vulnerability, etc. will differ across the country. A particular concern raised was that states with majority rural/agricultural areas will not have EJ issues adequately captured if overburdened/underserved communities are defined only at the national level. This was of interest to the group as many NPS programs focus significant effort on agricultural areas/NPS issues. ii. CWA Section 319 funding, NPS issues, and priorities also vary greatly by state. Workgroup members highlighted differences in types of NPS their program focuses on (i.e., groundwater/drinking water in KS, agriculture NPS issues in KY). ------- Because a "one size fits all" approach does not fit the national NPS program, workgroup members expressed the desire for similar flexibility in identifying overburdened/underserved areas in their states and where to focus future work. iii. To address these issues in state variability, one suggestion is to approach the Baseline Analysis with a two-part methodology. Phase one includes setting course national baseline so the program can be evaluated at the national level. Phase two will then allow for states to work one on one with HQ to conduct more in-depth analysis. A draft procedure is detailed in the "Future Analysis/Engagement Process" section, b. Varying geographic scales of available data (watershed vs census/block group level) i. This analysis takes a suite of data sources into account, and the geographic scales of these datasets range from the HUC12 watershed scale to the block group scale. Both workgroup members and agency experts that have been consulted on this project have indicated that the watershed scale is too broad to understand if and how program funds have been spent in overburdened/underserved communities. Because watersheds often cover multiple communities/census blocks/block groups, which are the units of measure most often used in EJ research, the team acknowledges that there may be a diverse makeup of communities within one watershed. The HUC12 watershed scale was chosen as the primary guiding unit of measure in this analysis be because that is the level of granularity available for both Section 319 funding data and in the WSIO data library. ii. The workgroup raised that the 319 Grants Reporting and Tracking System (GRTS) allows users to more specifically geolocate project BMPs. This could be highlighted as an option for states looking to better understand where work is occurring in relation to census/block group level demographic data. iii. If there are state-level datasets that map 319 projects, these maps may also be included in a state-specific analysis conducted between the state and EPA HQ. iv. Data layers from EJSCREEN are available in the Baseline Analysis map. Watershed scale can be used to home in on areas of interest, and EJSCREEN data can be used to understand block group makeup with the watershed. 3. Workgroup members expressed the desire to have the ability to consider additional state and local data sources in a state-specific analysis, as opposed to relying solely on the national-scale data that is currently available. The data layers that are currently included in the Baseline Analysis are hosted on a data viewer in EPA's GeoPlatform which allows the user to add and run analysis using additional datasets map. a. Example datasets that workgroup members expressed interest in including in an analysis of their state: Map of ongoing state efforts to target work in vulnerable communities (e.g., KS groundwater well mapping with goal to conduct work in low-income areas), NPS program priority areas, funding/project areas from other programs (i.e., SRF funding (if available), other state agency priority areas). 4. Recovery Potential Screening (RPS) tool ------- a. Some workgroup members have used the RPS tool in their states as a way to assess watershed recovery potential. Those with RPS experience had a generally positive opinion about the tool. b. Workgroup suggestion: Use RPS as a potential method of identifying target watersheds based on social and ecological factors, then bringing into GISto compare against historical 319 funding. This method works toward the goal of identifying areas that are potentially overburden/underserved and are experiencing water quality issues that may be NPS related and/or may be addressed by the NPS program. c. RPS allows the user to consider indicators from the Watershed Index Online (WSIO) data library. When using RPS we would primarily rely on WSIO data because it is available at a national scale. WSIO indicators were discussed in the workgroup and may be considered include: Ecological Stressor Social % Natural Cover (N-lndex) % Agriculture % Low- Income Population in WS % Forest Number of Septic Systems % Minority Population in WS % Wetlands % Impervious Cover %< HS Educated Population in WS % Woody Vegetation % Tile Drained Cropland % Linguistically Isolated Population in WS Soil Resilience Linear % Channel Through % Vulnerable Age Group Agriculture Population in WS % Stream Length Unimpaired % Urban Watershed Shape Channelization Watershed Size Hydrologic Alteration Bank Stability/Soils Water Use Intensity Bank Stability/Woody Number of 303(d) Listed Causes Vegetation Corridor Slope CSS or MS4 Areas Natural Channel Form Severity of Loading Channel Slope SPARROW Nitrogen Loading Estimate Sinuosity SPARROW Phosphorus Loading Estimate Natural Flow Regime Stream Miles Impaired Median Flow Maintenance Waterbody Acres Impaired Low Flow Maintenance Number of Impaired Segments Strahler Stream Order Specialized Agricultural Practices Biotic Community Integrity Impaired Waters % of Watershed Trophic State Nutrient Impaired Waters % of Watershed Stream Density Sediment Impaired Waters % of Watershed Contiguity with Green Infrastructure Corridor Proximity to Green Infrastructure Hub ------- d. Workgroup members expressed the desire to maintain flexibility to include state- specific datasets in RPS analyses. So, in a more in-depth analysis, a state could also choose to import state/local datasets for consideration as well. i. Examples of state-specific data to consider that were mentioned by the workgroup include: Mining areas, floodplains/flood risk maps, harmful algal bloom (HAB) data, Karst area, and groundwater watersheds. e. RPS allows the user to weight different factors 0-1 based on relative importance. Workgroup members have not used variable weighting in their RPS work. If weighting was explored, it should be done in partnership between EPA and the state with supporting data/reasoning. Baseline Analysis Limitations 1. Currently, the Baseline Analysis overlays socioeconomic, environmental, and 319 funding data to directly compare these datasets within watersheds. This approach limits the ability to capture and understand upstream work that may be benefitting communities downstream. Workgroup members had a few suggestions for addressing this issue including: a. Strahler stream order in a more in-depth analysis - look at order 3 or above as target perennial streams - recognizing 1-3 have sig impact but perhaps 3-5 order stream may have higher impact. b. Floodplain targeting - Map floodplain areas to better understand the range of land targeted that likely expands based on size of order of stream. c. Factor in any load reduction modeling conducted as part of state NPS projects i. Workgroup members also expressed the desire to have access to NRCS EQIP data 2. Limitations in available data a. 319 funding by HUC12: projects may span across multiple HUC12 watersheds. If this is the case, total funding for the project will be allocated equally across watersheds. b. States that put 319 funds in PPGs may not have project dollars fully captured in GRTS, leading to an underrepresentation of 319 funds spent. c. GRTS dollar amounts (appropriation dollars) are skewed by state allocation amounts. d. GRTS project locational data has had increasing quality over time. For example, the accuracy and consistency of GRTS locational data, and their HUC12 co-location, is substantially better over the previous few years versus 2010. 3. Assumption that dollars in a HUC12 watershed provide benefit to a disadvantaged community has high likelihood of being overly optimistic in this level analysis (as noted in Data/Methodology section). Additionally, depending on the types of practices and the pollutant(s) being addressed the work may or may not have positive impact on the overburdened/underserved community within a watershed. 4. Inherent Bias of 319 funds going towards HUC12 where known water quality issues exist, and are specifically NPS related impairments. If there is a lack of assessment data in an overburdened/underserved area, it is less likely 319 funds would have been allocated there. 5. 319 funding levels in urban, MS4 areas may be low. Program guidance prohibits using 319 funds to meet/comply with NPDES permit requirements. 319 funds may be used in MS4 areas if the ------- projects are unassociated with or going above and beyond permit requirements. (Include link to guidance document on spending 319 in urban areas). Future Analysis/Engagement Process Due to the complexity of this type of analysis, geographic variability in demographic and water quality issues, and the desire for state-specific input that was expressed by the group, we have developed a two-phase analysis approach. This methodology includes setting a broad, national baseline in Phase 1 so we may achieve a course understanding of how the program has historically been working in potentially overburdened/underserved communities, as well as a plan to conduct more in-depth, state-specific analyses. The goal of this Phase 2 state-specific analysis is to address issues of geographic scale (identified previously in the report), incorporate state/local/Tribal level data in identifying DACs, consider and understand ongoing work already occurring in this space at the state/local/Tribal level, and incorporate both water quality and social data in identifying areas of interest for potential future work. Phase 1 - National Analysis at HUC12 scale (completed June 2022) Phase one: Feb - August 2022. This first phase sets a coarse, national screening threshold to identify HUC12 watersheds that cover potentially overburdened/underserved communities. In Phase one, HUC12 watersheds were selected if they met or exceed the 80th percentile (assessing nationally) of at least two of the Watershed Index Online (WSIO) Social Indicators that are bolded below (those not in bold were not included in Phase 1). WSIO Social Indicators: • Low income % • Minority % • Linguistically isolated % • Vulnerable population % • Less than HS education % • Count of mobile home parks per watershed After identifying watersheds that met the Phase 1 criteria, they were compared to Section 319 state project funding data to determine: • Number and percent of HUC12 watersheds that meet or exceed the 80th percentile for WSIO Social Indicators and have received Section 319 funding. • Sum of funds and percentage of 319 funds geospatially located in HUC12 watersheds that meet or exceed the 80th percentile for WSIO Social Indicators There are several caveats to be aware of in examining Phase 1 results. These topics were discussed in with the baseline analysis workgroup: A more detailed description of Phase 1 analysis is found in the workgroup report: (link to Baseline workgroup doc) ------- Phase 2 - Fine Tuning and In-Depth Analysis at State-Level Phase 2 of this analysis will include more complex state-specific water quality and demographic variables. Beginning in FY23 with 5-10 states, EPA will work with interested states to further examine the watersheds identified in Phase 1 using the Recovery Potential Screening (RPS) tool, which includes both environmental and socioeconomic factors. Applicable state/local/Tribal water quality data (including data on NPS priority areas) can also be included to sharpen the screening approach to watersheds with identified NPS concerns. This information will then be examined at a sub watershed scale to better understand where DACs are located within watersheds (potentially using EJScreen or state/local/Tribal socioeconomic data). HQ will work closely with the state to determine data sources. The results and lessons from the Phase 2 analysis will be applied to the Phase 1 results to refine the list of screened DAC areas and will allow for the consideration and exploration of both water quality and socioeconomic/demographic data. Phase 2 methodology may be adjusted based on findings from the pilot projects. States interested in participating in the Phase 2 analysis should contact Ellie Flaherty at Flaherty.Ellie@epa.gov ------- |