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Recovery Potential Screening

Social Indicators

Social Indicator logoThis web page describes example indicators for the RPS Social Indicators category. A brief summary of each indicator provides the general name, example metrics used, relevance to the management of watershed condition and basic information about data sources and measurement. Several indicator summaries are hyperlinked to indicator-specific reference sheets with more detailed information including literature excerpts. Many of these example indicators have been compiled for the conterminous US on HUC12 watershed units and are either already embedded in the data tables of state-specific RPS Tools or publicly available through the Watershed Index Online (WSIO) Indicator Data Library.

Social Indicators are generally data-limited and harder to measure consistently on a nationwide basis than Ecological or Stressor Indicators. Some Social Indicators that weren't compiled nationally are often available at state or local scales, and these can and should be added to the RPS Tool by the user where they may support their screening objectives. When adding new Social Indicators, note that the appropriate directionality of some indicator values (i.e., whether higher value is better or worse) may vary depending on the specific purpose of the screening; in such cases the inverse of the indicator can also be added so that either option is available.

On this page:

Local Organizational Engagement 

  • Description: The number of groups active in water quality restoration and protection in the watershed, or the magnitude of activity of such groups. See Reference Sheet.
  • Example metrics: Count of Active Watershed Groups
  • Why relevant: Organizations at the level of the specific watershed have been shown to have a key influence on restoration success through building legitimacy through local representation, fostering conflict resolution and clarifying understanding of multiple interests and ideas in the community. Some sources of restoration assistance will not generally fund or implement restoration efforts without active groups that indicate community support and interest. Other related metrics associated with restoration success include organizational persistence, existence of a funded watershed leadership position and individual group or group leader performance.
  • Data sources and measurement: Often measured as the number of watershed groups located within each watershed. If the level of activity of all groups is documented, this metric can be modified to recognize different levels of critical mass, activity or expertise among different groups.

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Watershed Collaboration 

  • Description: The level of collaboration among stakeholder organizations in the watershed. See Reference Sheet.
  • Example metrics: Watershed Collaboration Rating (Case-specific)
  • Why relevant: Collaboration is related to local organizational presence but goes beyond by providing a measure of involvement and cooperation among the active organizations. As conflicting interests commonly are responsible for watershed restoration failures, successful bridging across differing interest groups can be a positive indicator of prospects for success. Collaboration can be in the form of one multi-interest organization that has broad and inclusive membership and inclusive procedural rules in place. Jointly authored or sponsored plans and activities can also demonstrate more favorable conditions for this metric.
  • Data sources and measurement: Although some spatial data on watershed and landowner organizations may be available, details about current collaboration are unlikely. This metric may be most simply scored as presence/absence of a multi-interest organization and/or process. If evaluation involves a small number of watersheds or the watersheds are all well-known, it may be possible for a group process such as expert elicitation to rank each as high/medium/low.

Government Agency Involvement 

  • Description: The level of government agency involvement in watershed restoration and/or protection projects in the watershed. See Reference Sheet.
  • Example metrics: Section 319 Nonpoint Control Projects Count; State or Federal Conservation Projects Count; Count of Agencies in Plan Development
  • Why relevant: Government agency support in the form of funding, recognition, added expertise, regulatory backing or an organizing/facilitating influence is cited as having a favorable effect on community and stakeholder buy-in on restoration efforts. Specifically in restoration efforts, stakeholders have appeared less likely to participate and commit to restoration if government agencies aren't also participating actively in support.
  • Data sources and measurement: Examples of agency involvement often perceived as a positive effect by other stakeholders include watershed or restoration planning, research projects that may inform actions that can improve condition, recognition programs (e.g., wild, scenic and recreational rivers) and agency conservation funding incentives. One source is the EPA Grants Reporting and Tracking System, which contains information on nonpoint source control projects. One or more forms of this indicator has been measured at the HUC12 scale for all lower 48 states and data are available from Watershed Index Online (WSIO).

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Participation in Land Conservation Programs 

  • Description: The level of participation in land conservation programs in the watershed. Typically, these programs are designed to offer landowners a monetary incentive to promote better land stewardship practices on their land. A common example is a program in which a land owner is offered payment to convert agricultural uses on sensitive land to a non-agricultural land use (e.g. wetlands or forest). Land conservation programs commonly include Natural Resources Conservation Service (NRCS) programs but can also include other state, region, county, or city administered programs.
  • Example metrics: USDA Conservation Reserve Program Area in Watershed; USDA Grassland Reserve Program in Watershed; USDA Healthy Forest Reserve Program in Watershed; USDA Wetlands Reserve Program in Watershed
  • Why relevant: Landowners engaging in restoration activities tend to motivate other landowners to take part. This may be due to observation of the positive results from the projects or from the demonstration that participation is possible and available. Incentive-based agricultural conservation programs not only address common sources of pollutants but also are a possibility for financial gain to participants.
  • Data sources and measurement: Information on participation rates may exist on a mapped basis or be attributable to generalized watershed locations. State conservationistsExit provide a state-specific source of this information concerning United States Department of Agriculture (USDA) conservation programs. Some states may have set up Conservation Cooperator Agreements with USDA that enables them to share information on restoration project involvement. If such information is used in Recovery Potential Screening projects, the user should take special precautions never to violate any provisions about data sensitivity or confidentiality. It may be possible to transform sensitive data (e.g., involved landowner names) to non-sensitive, more generalized metrics (e.g., percent of watershed participating in projects).

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Large Watershed Management Potential 

  • Description: A measure of the potential benefit or value of including a watershed unit in a larger-scale watershed planning effort. See Reference Sheet.
  • Example metrics: Count of Impaired Segments in HUC8; large-scale modeling efforts underway
  • Why relevant: State impaired waters programs are increasingly developing watershed plans and Total Maximum Daily Loads (TMDLs) for large watersheds that contain multiple impaired waters, rather than individual plans for specific impaired segments alone. EPA also promotes these 'watershed TMDLs' as an effective approach that employs many efficiencies and a 'critical mass' of effort. Frequently, watersheds at the 10- or 12-digit HUC scale contain several different impaired reaches or tributaries that are addressed in a single watershed plan or TMDL document. Moderate to large watersheds at the 8-digit HUC scale or larger have been successfully used to develop TMDLs and implement controls for 100 or more impaired segments. The approach has several procedural advantages for potential recovery. Primarily, there are efficiencies in modeling one larger system rather than constructing numerous models for smaller segments. Also regarding communications, one larger, coordinated effort can provide more consistent messages and thorough outreach to establish community support. Further, the interrelationship of numerous impaired segments in the same watershed through downstream effects, and indirectly through watershed protection decisions that may shift land use pressures to different subwatersheds, argues for some restoration planning to be done at a broader watershed context.
  • Data sources and measurement: This metric may be used with state impaired waters geospatial datasets to identify larger watersheds with multiple impaired segments and TMDLs within them. Individual, impaired segments are most easily compared on the basis of their co-location with other impaired waters within a standardized watershed unit (e.g. HUC12, HUC10, HUC8). The score can be based on the total count of impaired waters or use a threshold (e.g. 5 or more impaired waters) for defining watersheds with high potential for large-scale watershed planning. This metric may also be used to target less dense clusters that still offer the efficiencies of a watershed-based approach with greater likelihood that valuable ecological features remain and restoration can be achieved.

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University Proximity 

  • Description: The proximity of universities to the watershed that might be a source of scientific expertise and student labor on restoration projects. See Reference Sheet.
  • Example metrics: Count of Universities within X Miles; Nearest University Distance from Centroid
  • Why relevant: Universities provide persons with specialized knowledge that may advance a restoration effort in numerous ways. Experts from universities may be able to fill information gaps or lead technically advanced modeling or calculations essential to complex restoration plans. They also may be less polarizing sources of key information for reconciling stakeholder conflicts than corporate or agency experts. Students from universities may provide low-cost labor through the learning experience of restoration projects managed and overseen by professionals. As students and faculty are typically busy and seldom highly paid, proximity to an impaired water very likely influences the likelihood that they will become involved.
  • Data sources and measurement: Statewide coverage of universities can be developed from online sources such as UnivSourceExit; the entries can be further refined by including only those colleges with environmental, hydrology or civil engineering programs. Proximity can be estimated by buffering a selected distance (e.g., 50 miles) around the universities, then identifying the number of 'proximate' universities for each watershed.

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Decision-Maker Support 

  • Description: The level of leadership official support for watershed restoration in the watershed. See Reference Sheet.
  • Example metrics: Case-Specific Rating needed
  • Why relevant: The support for specific actions or programs that carry out restoration can be an influence on likelihood of restoration success. This support can be demonstrated in public opinion, in public leaders' positions, or both. Frequently the degree of community support and political support are in alignment. Thus decision-maker support for restoration actions can be an effective metric representing not only general likelihood of community backing but also the existence of influential backing from community leaders.
  • Data sources and measurement: Sources of this information are likely to vary from state to state and locality to locality. Suitability of this indicator for use in screening is a highly project-specific decision.

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% Protected Land 

  • Description: The extent of protected lands within the watershed, such as nature or wilderness reserves; national, state, or local parks; wildlife habitat protection areas; or conservation easements. Indicators can quantify the total extent of protected lands or focus on a specific protection status. The type and degree of protection varies among indicators. See Reference Sheet.
  • Example metrics: % Any IUCN Status; % Protected Land, IUCN Status II; % Protected Land, IUCN Status III; % Protected Land, IUCN Status IV; % GAP Status 1, 2, and 3
  • Why relevant: Depending on the protections afforded among categories of protected land, this factor provides an indicator of the prospects for a given proportion of total watershed land area to remain in conditions desirable for water quality restoration and protection. Although this factor may not be relevant for sorting relative recovery potential among watersheds at low levels (e.g., less than 25% watershed area), impaired waters with a high proportion of protected drainage area arguably have more ecological functions remaining intact, or may take less effort to reestablish degraded functions.
  • Data sources and measurement: The Gap Analysis Program (GAP) of the US Fish and Wildlife Service has worked in most states to compile geospatial data on statewide land and water protection status for combination with species range datasets. The Protected Areas DatabaseExit contains the spatial information for GAP. Other forms of land protection may be available at the state level. One or more forms of this indicator has been measured at the HUC12 scale for all lower 48 states and data are available from Watershed Index Online (WSIO).

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Applicable Regulation 

  • Description: The presence of regulatory requirements for sources of pollution in the watershed. See Reference Sheet.
  • Example metrics: Regulated Source Presence in Watershed; Point Source Impairments Presence in Watershed; Riparian Zone Protections in Watershed; Stormwater Regulations in Watershed; Agricultural Regulations in Watershed
  • Why relevant: Because many restoration mechanisms are voluntary, particularly for nonpoint source management, the presence of regulatory requirements for the pollutant sources in a watershed adds greater certainty that restoration actions will partially or fully restore an impaired waterway to meeting standards. Formal enforceable regulations not only improve the likelihood of pollution reduction directly but also may encourage restoration partners and other restoration efforts affecting the same waterbody, in the knowledge that at least some progress may be made. One easily assessed example is point source permitting but several other federal, state, and local regulations may be relevant for the watersheds and pollutants of interest.
  • Data sources and measurement: Data availability varies according to the regulation and pollutant source. Enforceable point source regulations is one well documented example. The EPA Assessment TMDL Tracking and Implementation System (ATTAINS) contains data on impaired waters by state and by semi-annual reporting cycle. Impaired waters and waters with completed TMDLs are identified as affected by point sources only, nonpoint sources only or mixed. Quantifying this metric in a very basic way could be done by distinguishing impaired waters that are nonpoint only from waters with some or all point sources. States, counties, or municipalities may have other regulations (e.g. riparian zone protections, conservation zoning) that may be directly mapped or can be extracted through mapping. For further regulatory information, the EPA has compiled a list of regulations by environmental topic.

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Certainty of Causal Linkages 

  • Description: The level of certainty in the specific pollutant(s) causing water quality impairments in the watershed. For 303(d) listed waters, some impairment causes are reported as 'Cause Unknown' (usually biological impairments) when the pollutant is not identifiable from available monitoring data. Other causes are reported as low dissolved oxygen, degraded habitat, toxicity, or other terms not specific to a controllable pollutant.  See Reference Sheet.
  • Example metrics: Unknown Impairment Cause Presence in Watershed; % Impaired Streamlength with Unknown Cause; % Impaired Waterbody Area with Unknown Cause
  • Why relevant: Some uncertainty in restoration projects is common, but a truly unknown cause of water quality impairment is a major obstacle to restoration. Restoration prospects depend heavily on understanding the impairment, the stressors to which the system is exposed, and the sources and pathways along which exposure occurs. Together these elements make up a causal pathway that, if uncertain, jeopardizes the progress of restoration. Action taken despite causal uncertainty can lead to targeting the wrong stressor or source, funding or requiring inappropriate control actions, under- or over-estimating controls needed and related development of significant stakeholder conflicts or legal actions.
  • Data sources and measurement: One measurement approach is to sort waters using this metric by simple presence/absence of 'cause unknown' or similar impairment listings. Another option is to measure the percent of waters with unknown causes of impairment out of the total length or area of impaired waters within each watershed. Cause information occurs in attribute tables that are linked to 303(d) shapefiles of each state's impaired waters. Data is available through the EPA Assessment TMDL Tracking and Implementation System (ATTAINS) or state-specific program tracking information.

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% Identified Stressor Sources 

  • Description: Percent of waters with water quality impairments that have specific sources of impairment identified. For 303(d) listed waters, sources of impairment are often reported in the impairment listing. Example sources include discharges from wastewater treatment facilities, agricultural or urban runoff, forestry activity, and resource extraction.
  • Example metrics: % Impaired Stream Length with Known Impairment Source; % Impaired Waterbody Area with Known Impairment Source
  • Why relevant: Acting to restore an impaired waterbody not only requires understanding the pollutants impacting it but also the sources of those pollutants. Action taken despite uncertainty in impairment sources can lead to targeting the wrong source, funding or requiring inappropriate control actions, under- or over-estimating controls needed and related development of significant stakeholder conflicts or legal actions.
  • Data sources and measurement: Can be measured as the percent of waters with impairment sources identified out of the total length or area of impaired waters within each watershed. Impairment sources may exist as attributes in the EPA Assessment TMDL Tracking and Implementation System (ATTAINS). Other state resources may be available or watershed models may allow for estimates of probable sources.

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Certainty of Restoration Practices 

  • Description: The level of certainty that specific restoration practices are known to be applicable and effective for addressing water quality impairments in watershed. See Reference Sheet.
  • Example metrics: Certainty of Restoration Practices Rating (Case-specific)
  • Why relevant: Our understanding of restoration techniques and their range of applicability is still incomplete and continually evolving. As track records are still being developed for many techniques among varied settings, uncertainty about techniques is still common. Waters whose restoration can be accomplished by known, tested techniques are stronger prospects for recovery potential than those facing uncertainty about technique applicability or effectiveness. Extensive familiarity with restoration techniques and their applicability is needed for applying this metric.
  • Data sources and measurement: One approach for measurement is to have local experts estimate their certainty of the applicability and likely effectiveness of restoration techniques for specific impairments using the following scoring: 0 = no restoration technique applicable; 1 = technique applicability uncertain; 2 = technique moderately applicable and effective; 3 = technique highly applicable and effective. Quantifying this metric will likely rely on expert judgment of whether routine techniques for addressing specific impairments and settings are known.

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TMDL or Watershed Plan 

  • Description: Indicators of the presence of Total Maximum Daily Loads (TMDLs) or other watershed plans in the watershed. See Reference Sheet.
  • Example metrics: % Stream Length with TMDLs; % Waterbody Area with TMDLs; Segments with Nutrient TMDLs Count;  Segments with Sediment TMDLs Count
  • Why relevant: Many different types of studies have observed that a completed and approved TMDL or watershed plan often has a positive influence on community understanding and acceptance of restoration efforts, despite the potential for conflict about a plan's contents. Studies of success stories have noted that a sound watershed plan was a major driving factor. A technical plan such as a TMDL provides a quantitative, scientific basis for guiding actions. Existing plans can also clarify misconceptions, increase recognition of common interests, indicate government support and service and provide a basis for further collaborative planning or action.
  • Data sources and measurement: Measured as the percent of total stream length or waterbody area in the watershed with a TMDL or watershed plan. Alternatively, the count of segments in the watershed with a TMDL or watershed plan. Indicators can measure all TMDLs or focus on TMDLs for individual pollutants of interest.  A national mapped dataset of waters with completed and approved TMDLs has been developed by EPA and is available through the Assessment TMDL Tracking and Implementation System (ATTAINS). Information on the presence of other restoration or management plans may be available from state-specific data sources. One or more forms of this indicator has been measured at the HUC12 scale for all lower 48 states and data are available from Watershed Index Online (WSIO).

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Ratio #TMDLs/#Impairments 

  • Description: Ratio of the number of Total Maximum Daily Loads (TMDLs) to the total number of water quality impairments in the watershed.
  • Example metrics: Ratio TMDLs to Impairments
  • Why relevant: This metric indicates how much restoration planning progress has been made relative to the known and reported amount of impairments overall. On the basis of this factor, watersheds ranking more highly are better documented and prepared for more rapid implementation of restoration practices and recovery.
  • Data sources and measurement: The calculation involves comparing the number of TMDLs (i.e., individual water body segment/pollutant combinations) developed in the watershed with the number of impairments (i.e., also individual water body segment/pollutant combinations) in the watershed. Both are available from EPA as geospatial data online through the EPA Assessment TMDL Tracking and Implementation System (ATTAINS). One or more forms of this indicator has been measured at the HUC12 scale for all lower 48 states and data are available from Watershed Index Online (WSIO).

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% of Stream Length Assessed 

  • Description: The percent or length of streams in the watershed unit that have been assessed for attainment of water quality standards under Section 305(b) of the Clean Water Act.
  • Example metrics: % Streamlength Assessed; Streamlength Assessed
  • Why relevant: This metric provides one measure of how thoroughly each watershed has been assessed for water quality impairments. Unknown factors that may inhibit recovery are less likely to occur in watersheds with a higher percentage of assessed waters. A higher percentage of assessed waters also points to greater availability of water quality monitoring data to inform detailed watershed planning.
  • Data sources and measurement: Measured as the percentage of total stream miles in the watershed that have been assessed for attainment of water quality standards under Section 305(b) of the Clean Water Act. A national geospatial dataset of assessed waters is available online through the EPA Assessment TMDL Tracking and Implementation System (ATTAINS). State datasets with more recent data may also be available. One or more forms of this indicator has been measured at the HUC12 scale for all lower 48 states and data are available from Watershed Index Online (WSIO).

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% of Water Body Area Assessed 

  • Description: The percent or area of lakes, reservoirs, and other open waters in the watershed that have been assessed for attainment of water quality standards under Section 305(b) of the Clean Water Act.
  • Example metrics: % Waterbody Area Assessed; Waterbody Area Assessed
  • Why relevant: This metric provides one measure of how thoroughly each watershed has been assessed for water quality impairments. Unknown factors that may inhibit recovery are less likely to occur in watersheds with a higher percentage of assessed waters. A higher percentage of assessed waters also points to greater availability of water quality monitoring data to inform detailed watershed planning.
  • Data sources and measurement: Measured as the percentage of total waterbody acres in the watershed that have been assessed for attainment of water quality standards under Section 305(b) of the Clean Water Act. A national geospatial dataset of assessed waters is available online through the EPA Assessment TMDL Tracking and Implementation System (ATTAINS). State datasets with more recent data may also be available. One or more forms of this indicator has been measured at the HUC12 scale for all lower 48 states and data are available from Watershed Index Online (WSIO).

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Estimated Restoration Cost 

  • Description: The estimated costs for addressing water quality restoration and remediation needs in the watershed. See Reference Sheet.
  • Example metrics: Estimated Cost of Restoration in Watershed
  • Why relevant: The expense of restoration due to the number of impaired waters and the complexity of restoration and remediation techniques is a major factor influencing the likelihood of restoration success. Extreme expense may halt progress on a single restoration effort, either directly due to the unwanted financial burden or due to inability to compete with other, less expensive restoration sites as priorities are set. Prioritization often depends as much on economic issues as ecological concerns.
  • Data sources and measurement: Detailed estimates of restoration costs are not likely to be available for all watersheds of interest, but this factor may play an important role in statewide strategies when available. Expert judgment based on impairment type/number and system type/size may be used to assign “high”, “medium”, or “low” expense categories to waters of interest. After measurement, indicator values should be directionally aligned so that greater cost-effectiveness corresponds to higher scores in the social index of RPS.

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Jurisdictional Complexity 

  • Description: Inverse of the number of political jurisdictions (states, counties, and/or cities) in a watershed. See Reference Sheet.
  • Example metrics: Single State in HUC12 Flag; Count of States, Cities and Counties partly within Watershed Unit.
  • Why relevant: A large number of political jurisdictions within a watershed can negatively influence the speed and effectiveness of logistics and agreements in restoration activities. Watersheds with multiple political jurisdictions often require the establishment of a separate group to facilitate planning and consensus-building for environmental initiatives. Single-jurisdiction watersheds are usually less complicated in watershed planning interactions.
  • Data sources and measurement: Can be measured as total number of cities, counties, or states wholly or partially within a watershed. Jurisdiction counts should be inverted so that fewer jurisdictions correspond to higher score in the social index of RPS. Alternatively this can be measured as a yes/no flag for whether the watershed only contains a single state, county, or city. Geospatial datasets of state, county, and city boundaries are available from the US Census Bureau TIGERExit website. If available, other jurisdictions may be added if they typically become involved in land use decisions and restoration actions.

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Landownership Complexity 

  • Description: Inverse measure of the complexity of landownership in the watershed. Within a given watershed, the diversity of landownership may include federal agencies, state agencies, local agencies, private individuals, or multiple-party private groups, and may also vary as to grain size of the ownership parcels. See Reference Sheet.
  • Example metrics: % Public Land in Watershed; % Public Land Area in Riparian Zone; Count of Unique Landowners in Watershed; Count of Unique Landowners in Riparian Zone
  • Why relevant: High numbers of private landowners in a watershed or stream corridor are likely to complicate efforts to restore an impaired water; fewer owners simply means fewer interactions. Negotiating management practices, easements or land purchases becomes complicated in fragmented ownership. Large tracts of public lands often are the site of many restoration projects as a result. Single owner-dominated watersheds, particularly where public land ownership is common, may have greater likelihood of restoration success.
  • Data sources and measurement: Can be measured as the percentage of watershed or riparian zone area in public ownership. The USGS Protected Areas DatabaseExit provides a geospatial database of public lands with protections in place to maintain natural ecosystems. If available, land parcel or other ownership data can be summarized to calculate the number of unique landowners in the watershed or riparian zone. A reasonable surrogate for the number of landowners in some areas is the number of low, medium and high-density urban land cover patches per unit of area in the watershed. After measurement, indicator values should be directionally aligned so that greater values correspond to greater restoration potential in the social index of RPS.

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% Owner-Occupied Residential  

  • Description: The amount of owner-occupied residential land along stream channels and lake shores.
  • Example metrics: % Owner-Occupied Land in Riparian Zone
  • Why relevant: The degree of owner occupancy along stream or lake frontage can influence the prospects of restoration in numerous ways, including positive and negative influences. As property owners and as residents, they may be motivated by the fact that restoration often improves property values and beneficial uses as well as neighborhoods. In contrast, sensitivity about property rights and engaging in waterfront uses that contribute to impairment or interfere with restoration may lead some owners to oppose restoration efforts. In all cases, these landowners are important stakeholders whose views are capable of influencing local support for restoration efforts and the prospects of recovery.
  • Data sources and measurement: Data on ownership might be gathered at the local level but may not contain actual occupancy information; it may be possible to generalize this metric into high/medium/low categories where sufficient information can be compiled.

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Recovery Time Frame 

  • Description: The estimated amount of time needed for a watershed to recover from water quality impairments or other watershed degradation issues.
  • Example metrics: Recovery Time Rating in Watershed (case-specific)
  • Why relevant: Although the time frame needed for recovery may not always directly relate to the potential for recovery, longer recovery times typically require sustained public and technical support over prolonged periods. Impairments with longer recovery times may be unable to demonstrate short-term evidence of success, an added social burden beyond the usual technical complexity of developing and implementing long-term recovery strategies.
  • Data sources and measurement: Existing data to specifically estimate recovery times is not common but several easily measured traits generally translate to longer recoveries. On the basic premise that larger ecosystems are more complex and slower to degrade and to recover, watershed size or waterbody length/size can be used as a surrogate for assumptions about recovery time frame. The number of upstream watersheds can factored in to estimate the implications of watershed size on recovery. Expert knowledge of how different types of impairments vary in recovery time can also be used to assign recovery time ratings (e.g., short, medium, long) to watersheds. After measurement, indicator values should be directionally aligned so that greater values correspond to higher scores in the social index of RPS.

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Environmental Justice Area of Concern 

  • Description: Indicators of the presence/absence or extent of Environment Justice (EJ) areas in the watershed.
  • Example metrics: % Environmental Justice Area in Watershed; specific EJ parameters for rural or urban EJ settings
  • Why relevant: Environmental Justice (EJ) areas and characteristics do not align consistently with positive or negative effects on prospects for restorability and if used they should be considered in a case-specific manner. Nevertheless, EJ attributes can be very important factors to consider when ensuring that comparisons or decisions are not systematically unfair to low income areas. A wide range of restoration-relevant EJ circumstances may exist in any given area.
  • Data sources and measurement: Development and use of EJ-related metrics is project-specific. It may not even be feasible to develop an EJ metric that is directionally consistent in all cases. One option for using EJ information in recovery potential screening is to screen a subset consisting only of EJ watersheds, in order to compare EJ areas only to one another on the basis of multiple restorability factors.

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Local Socio-Economic Stress 

  • Description: Indicators of socio-economic stress in the watershed. Indicators can focus on a single socio-economic factor such as long-term employment change, unemployment rate or housing affordability in the watershed, or combine multiple socio-economic factors into a single index value. See Reference Sheet.
  • Example metrics: Average Per Capita Income in Watershed; Aggregated Socio-Economic Index in Watershed (see below)
  • Why relevant: A community's socio-economic well-being or lack thereof can have mixed effects on community views about the prospects for restoration. A distressed rural area may be inclined to see restoration negatively if additional restrictions, expenses or loss of economic options are assumed. In contrast, restorations that may increase property value, provide restoration project jobs and an improved recreational economy may be welcomed. Generally, whereas perceptions in distressed areas provide an obstacle, the ultimate effects of a restoration effort often can provide a welcome improvement. This metric can be used as a negative input to the overall social context score if it is based on perceptions of distressed communities, or as a positive input to the score if based on the potential economic benefits to distressed areas. A choice of directionality (positive or negative) is case-specific before each screening use.
  • Data sources and measurement: This set of indicators was adapted from measures developed by the Sonoran Institute. Nine measures of socio-economic stress were originally published. These included high-distress interpretations of: long-term employment change; unemployment rate; per capita income; families living under poverty; educational attainment; housing affordability; short-term employment change; population change; and natural disaster risk. The nine measures can be aggregated into a single index value. The primary data sources for the nine component metrics used by the Sonoran Institute study are all nationally available geospatial datasets, available from the US Department of Commerce Bureau of Economic AnalysisExit (long and short term employment change, per capita income, housing affordability), Bureau of Labor StatisticsExit (unemployment rate, natural disaster risk), and Census BureauExit (population change, families living under poverty, educational attainment). Generally these are county-aggregated datasets although finer, census-tract data are available for the Census Bureau elements. NOAA has also developed spatial trends in socioeconomics for coastal areas (see https://coast.noaa.gov/digitalcoast/tools/qrt.html)Exit. ArcGIS online offers a number of compiled map services on socio-economic data (see http://www.arcgis.com/home/gallery.html)Exit.

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Population 

  • Description: Human population count or density in the watershed or within specific regions of the watershed (e.g. riparian zone, hydrologically connected zone, etc.).
  • Example metrics: Population in Watershed, Population Density in Watershed, Population in Riparian Zone; % Population in Riparian Zone; Housing Unit Density in Watershed
  • Why relevant Population density has many implications for recovery potential but they differ in directionality. A more dense population is generally associated with multiple stressors of higher magnitude that are more difficult and expensive to remediate. On the other hand, higher populations are associated with better information flow and education, which are credited as contextual reasons why more highly populous areas often support restoration with greater interest. Project-specific consideration is recommended before using this metric.
  • Data sources and measurement: US Census Bureau population dataExit can be adapted to measure human population in the watershed, riparian zone, or other region of interest by proportionally distributing census tract or county-level population statistics. One or more forms of this indicator has been measured at the HUC12 scale for all lower 48 states and data are available from Watershed Index Online (WSIO).

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Recreational Resource 

  • Description: Indicators of specific recreational uses of value in the watershed. See Reference Sheet.
  • Example metrics: Freshwater Fishing Demand in Watershed
  • Why relevant: Public support of restoration funding is often strongly tied to expectations of access and outdoor recreational benefit from the restoration investment. In contrast, inaccessible and privately owned waters with water quality impairments may struggle for restoration funding from public sources due to limited community support. An observable pattern of restoration projects frequently occurring on public and recreationally accessible lands is attributable largely to this factor. As such, documented recreational use data can be used to identify desirable watersheds for those users.
  • Data sources and measurement: Scoring is based on the level of recreational use in the watershed. Data sources may include surveys of recreational usership that can be summarized by watershed or statewide geospatial data for recreational lands. Statewide geospatial data may include State Conservation Areas, State Forests, State Fish and Wildlife Areas, and State Parks, and other recreational land types where available. The USGS Protected Areas DatabaseExit contains nationwide information on recreation areas. One or more forms of this indicator has been measured at the HUC12 scale for all lower 48 states and data are available from Watershed Index Online (WSIO).

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Drinking Water Intakes 

  • Description: Count of drinking water intakes in the watershed.
  • Example metrics: Drinking Surface Water Intake Count; Drinking Groundwater Well Count
  • Why relevant: Association with public drinking water is one of the most powerful traits a watershed can have concerning the need to demonstrate public support for restoration. This metric can provide a count of surface water and groundwater resources in use for drinking water.
  • Data sources and measurement: Exact locations of most drinking water intakes are not publicly available for security reasons, but can usually be obtained as more generalized information on a small watershed basis. One or more forms of this indicator has been measured at the HUC12 scale for all lower 48 states and data are available from Watershed Index Online (WSIO).

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% Source Water Protection Area 

  • Description: Percent of the watershed that is classified as a source water protection area (SWPA) for one or more public water system (PWS) drinking water sources.
  • Example metrics: % Drinking Water Source Protection Area (Surface Water, Groundwater)
  • Why relevant: Association with public drinking water is one of the most powerful traits a watershed can have concerning the need to demonstrate public support for restoration. This metric can provide an area measurement associated with surface water and groundwater resources in use for drinking water.
  • Data sources and measurement: Exact SWPA locations not be publicly available for security reasons but generalized areas associated with drinking water sources can be obtained. One or more forms of this indicator has been measured at the HUC12 scale for all lower 48 states and data are available from Watershed Index Online (WSIO).

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Drinking Water Population Served 

  • Description: The human population count served by drinking water sources that are located within the watershed. Drinking water sources can include groundwater and/or surface water sources.
  • Example metrics: Drinking Groundwater Population Served; Drinking Surface Water Population Served
  • Why relevant: The protection of drinking water sources can be very important to many different types of stakeholders in a watershed, and potential threats to drinking water sources may motivate stakeholders to have increased involvement in projects in watersheds with drinking water sources. Specifically in restoration efforts, stakeholders have appeared more likely to participate and commit to restoration if drinking water sources may be impacted.
  • Data sources and measurement: The EPA Safe Drinking Water Information System (SDWIS) contains data with service populations for drinking water sources. State specific drinking water databases may also contain information on sources and populations. One or more forms of this indicator has been measured at the HUC12 scale for all lower 48 states and data are available from Watershed Index Online (WSIO).

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Valued Ecological Attribute 

  • Description: Indicators of specific ecological features that are widely recognized as of value in the watershed. See Reference Sheet.
  • Example metrics: Presence of Natural Heritage Sites in Watershed; Presence of Class A Fisheries in Watershed; Presence of Wild and Scenic Rivers in Watershed
  • Why relevant: Community support for restoration is motivated by widely-shared recognition of a site's value, often in the form of natural aesthetics, biodiversity, rarity, charismatic species, outdoor sports such as fishing, or ecological goods and services. Formalized designation of a valued site not only reflects those original beliefs in the worth of an area but also reinforces the perception of its value with others, thereby strengthening the prospects for public support of its restoration.
  • Data sources and measurement: Can be calculated from datasets depicting the location of sites with formal recognition and designation by programs that are generally aligned with protecting biodiversity, aesthetics, recreational sport, or other uses. Can be scored as a basic presence/absence metric, percentage of the watershed that the site comprises, or high/medium/low/none rankings can be defined according to the available data.

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Funding Eligibility 

  • Description: Indicators of the eligibility of water quality impairments in the watershed for funding programs that provide financial assistance for restoration. See Reference Sheet.
  • Example metrics: Clean Water Act Funding Eligibility in Watershed; USDA Funding Eligibility in Watershed
  • Why relevant: Adequate funding is widely recognized as a major driver of restoration success. Eligibility for sources of restoration funding is therefore an important social indicator for recovery potential. Waters that are ineligible for restoration funding may have very limited opportunities for success especially if facing an expensive restoration effort. A major amount of restoration takes place through relatively few funding sources, thus eligibility for those sources can be crucial. Some major federal sources with limited eligibility include Clean Water Act Section 319 nonpoint source funds and State Revolving Funds, USDA agricultural programs and abandoned minelands remediation funds.
  • Data sources and measurement: Measurement is based on eligibility criteria for various federal and state funding programs along with watershed attributes related to those criteria (e.g. agricultural activities, abandoned minelands). Alternatively, eligibility can be assumed for watersheds if a funded project is already underway or recently completed. Scoring can be done by presence/absence of eligibility for individual or any funding sources, or by total counts of eligible programs by watershed.

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Human Health and Safety 

  • Description: Indicators of the risks of a water quality impairment to human health or safety in the watershed. See Reference Sheet.
  • Example metrics: Density Toxic Release Inventory Sites in Watershed; Density Superfund Sites in Watershed
  • Why relevant: Among decision-makers and communities alike, human health or safety has always been among the most powerful criteria for determining the importance of a restoration activity. Some environmental restorations are needed in part because of health and safety hazards that accompany environmental degradation (for example, many abandoned mine settings and hazardous waste remediation activities). When human health and safety risks are involved, the degree of support for a restoration effort is boosted above the support for environmental benefits alone, and the positive social context for recovery potential is increased.
  • Data sources and measurement: This metric generally relies upon site-specific monitoring data to verify the risk. Such data are available from hazardous waste, mining or other programs. Scoring may be performed as simple presence/absence of risk or assigned a severity scale, depending on available data and its consistency. Some example sources include searchable data as part of the Toxics Release Inventory and hazardous waste geographical queries through the Resource Conservation and Recovery Act. One or more forms of this indicator has been measured at the HUC12 scale for all lower 48 states and data are available from Watershed Index Online (WSIO).

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Iconic Value of Resource 

  • Description: Indicators of watershed attributes that are part of local identity of  the community. Iconic value or resource value can arise because the watershed contains a well-known water body that the community identifies heavily with in their local culture, history, and/or economy. See Reference Sheet.
  • Example metrics: Iconic Resource Presence in Watershed; Iconic Resource Rating in Watershed
  • Why relevant: In situations where the best-known and important water body has become impaired, this information can motivate communities very strongly to support restoration.
  • Data sources and measurement: There is no standard dataset or measurement for how communities identify with specific water bodies, but it is easily recognized at local scales. Measurement can consider tributaries that can impact the iconic water body (such as, tributaries in the Chesapeake Bay drainage versus ones that are not) to raise their recovery potential scores.

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303(d) Schedule Priority 

  • Description: The priority level for Section 303(d) listed waters in the watershed set by the state. For pollutant-impaired waters that will undergo development of Total Maximum Daily Loads (TMDLs), Clean Water Act (CWA) regulations require states to prioritize the current 303(d) listed waters for TMDL development in a schedule.
  • Example metrics: 303(d) Priority Category in Watershed; 303(d) vision state priority for restoration or protection.
  • Why relevant: High priority waters on the 303(d) list have the best chance of accelerated action toward their recovery. Faster, earlier restoration may also decrease the likelihood that continuing degradation will progress further and lead to greater losses of ecological function and beneficial uses.
  • Data sources and measurement: High, medium and low priority categories are assigned by states to the 303(d) listed waters in each listing cycle, indicating relative priority for TMDL development. If the recovery potential screening involves only listed waters without TMDLs (e.g. the most recent listing cycle only), this metric is appropriate for use. The metric is inappropriate for non-303(d) listed waters, for screening waters that already have TMDLs or watershed plans, or where the recovery potential screening is intended to provide the basis for 303(d) schedule priority-setting. Since 2013, state 303(d) Vision priority waters have been reported to EPA and constitute areas with generally greater investment in restoration and protection planning.

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Neutral Variable (Social) 

  • Description: The neutral variable indicator is equal to 0.5 for all watersheds in the RPS Tool. This is a “dummy” indicator used when you wish to omit the Social category from a screening.
  • Example metrics: Neutral Variable, Social Category
  • Why relevant: Users may want to run a RPS screening without including the Social indicator category to observe watershed comparisons based only on ecological and stressor attributes. There must be at least one indicator in all three categories for the RPS Tool to run. Selecting only the Neutral Variable in the Social category will allow the RPS Tool to run without errors and provide results that focus on just the Ecological and Stressor indicator categories.
  • Data sources and measurement: The neutral variable indicator is set to 0.5 for all watersheds; no measurement is necessary.

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