Appendix II
EPA Recovery Potential Screening (RPS) Tool:
Potential Applications for Watershed Analysis and
Water Equity Mapping
Prepared for:
Office of Wetlands, Oceans and
Watersheds, US EPA
March 2022
Prepared by:
Industrial Economics, Incorporated
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Table of Contents
Water Equity Mapping Approach 1
Introduction 1
The Recovery Potential Screening (RPS) Tool 1
Data Selection: RPS Indicators 2
Water Access 2
Watershed Health 3
Water Resilience 4
Water Equity Mapping 5
The San Antonio Watershed 5
Water Access 5
Watershed Health 10
Water Resilience 11
The Verde, Salt and Gila River Basins 14
Water Access 15
Watershed Health 17
Water Resilience 19
Water Equity Mapping using the RPS Tool: Lessons Learned 22
Attachment 1. Visualizations Generated Using the EPA RPS Tool 23
Attachment 2. Indicator Summary and Source Information 25
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Water Equity Mapping Approach
Introduction
A primary goal of the Water Reuse Action Plan is to identify more effective methods of water reuse and
to identify barriers to this goal.1 We sought to develop a methodology and identify tools that would help
the EPA consider the broad range of local factors that impact water reuse in a particular area. This
project sought to apply the Environmental Protection Agency (EPA) Recovery Potential Screening Tool
(RPS), which is a tool designed to compare the condition and restoration potential of watersheds within
a given region. By comparing social, environmental, and stressor data available through RPS at the
subwatershed level, we developed visualizations to help local and national stakeholders understand and
identify vulnerability hotspots in the San Antonio River and Verde River Watersheds. The maps
presented in this report are meant to offer the
reader a broad and integrated understanding of
water equity, which refers to a populations' access
to adequate and safe water for sustaining
livelihoods, human well-being, and socioeconomic
development.2 National and local datasetsthat
profile anthropogenic and environmental threats to
water security and sustainability can help to inform
water equity priorities within these watersheds. The
indicators selected from the 284 indicators stored in
the RPS Tool were designed to capture elements of
water equity and to create a foundation on which
the EPA and other stakeholders can make informed
decisions about water management.
The Recovery Potential
Screening (RPS) Tool
The RPS Tool was originally developed to help states, territories and tribes identify priority areas for
watershed restoration and support.3 The RPS Tool is an Excel spreadsheet that calculates index scores at
the watershed and subwatershed level using data for a series of social, environmental, and stressor
indicators. As of 2021, the tool contains 284 unique indicators from many national database sources,
including the National Hydrography Dataset, the US Census Bureau, and National Land Cover Database.
Data are stored by 12-digit Hydrologic Unit Codes (HUC12 regions), which are watershed boundaries
1 For more information, see the Water Reuse Action Plan.
2 For more information, see the U.S. Water Alliance National Briefing Paper
3 Overview of Recovery Potential Screening (RPS). EPA.
Primary Elements of Water Equity
Water Access: A populations' access to
adequate quantities of acceptable quality
water for sustaining livelihoods, human well-
being, and socioeconomic development.
Watershed Health: Quality of the water in a
watershed to ensure an adequate, reliable,
and continual supply of clean water for human
uses and ecosystems.
Water Resilience: the capacity of a water
supply to adapt to or recover from the effects
of rapid hydrologic change or a natural
disaster.
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that divide a region at the local, subwatershed level.4 It is possible to combine multiple indicators to
produce a single comparative index score for each of the HUC12 regions in a particular state or sub-state
area. See Attachment 1 for more information about the calculations in the RPS Tool. The EPA completed
RPS updates for the lower 48 states in November 2021.
HYDROLOGIC UNIT CODE DIVISIONS
Hydrologic Unit Codes (HUCs): The Watershed Boundary Dataset maps the entire U.S. surface level drainage
using a series of hydrologic units that nest within one another. This enables users to better visualize the broader
watershed or smaller units that comprise the given area. Each hydrologic unit in the Watershed Boundary
Dataset is assigned a Hydrologic Unit Code (HUC) and the hydrologic units are therefore referred to as HUCs.
Watershed levels include:
HUC4: Divides areas at the subregion level and delineates large river basins.
HUC6: Divides a watershed at the basin level.
HUC8: Divides the watershed at the subbasin level and delineates medium-sized river basins.
HUC12: The finest level of watershed granularity, HUC12 regions are divided at the local, subwatershed level and
delineate tributary systems. The continental U.S. is comprised of about 90,000 HUC12 regions.
Modifications include updating older indicators with more recent data where possible and adding over
30 new indicators into the tool, which include a series of indicators that could be relevant to
Environmental Justice (EJ) initiatives. This report includes data and results from Texas and Arizona RPS
Tools that include the 2021 updates. Most indicators in the updated tools are comprised of data
collected between 2016 and 2020.
Data Selection: RPS Indicators
To better understand the environmental, social, and economic demands on water supplies, we selected
a subset of indicators designed to identify areas across the whole watershed that would benefit the
most from development of water reuse plans. The final selection of indicators was informed by
Consensus Building Institute's stakeholder engagement process for the WRAP pilot where partners
decided on water equity considerations to be factored into the RPS mapping. We selected a total of 21
indicators from the RPS Tool to illustrate social equity, watershed health, and climate vulnerabilities
across three elements - water access, watershed health and water resilience. See Attachment 2 for
more detailed descriptions of each indicator.
Water Access
Water access includes societal factors that impact a population's sustainable access to water for
socioeconomic development and human wellbeing. The indicators chosen to demonstrate water access
across the watershed display factors that impact whether people have access to clean, safe water. They
also capture a number of stressors that influence which groups of the population may be most
4 Hydrologic Unit Maps. USGS.
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underserved across the watershed. Although additional factors beyond those indicators listed below can
influence water security, these indicators offer insights to help stakeholders identify hotspots within the
region that may be worth investigating further. In order to characterize vulnerability associated with
water access, we selected eight indicators from the 284 available in the RPS Tool to depict the most
vulnerable areas in the watershed with respect to water access. We split these eight indicators into two
sub-categories: social vulnerability, which identifies socially vulnerable communities, and human land
and water use, which illustrates the current regional demand on water.
Social Vulnerability
1. % Low-Income Population in Watershed
2. % Minority Population in Watershed
3. % Linguistically Isolated Population in Watershed
4. % < High School Educated Population in Watershed
5. % Vulnerable Age Group Population in Watershed
Human Land and Water Use
1. Population Density in Watershed
2. Domestic, Agricultural and Industrial Water Demand in Watershed
3. Groundwater Source Protection Areas in Watershed
Watershed Health
Watershed health reflects the health of the watershed and the ability to supply sufficient clean water to
the population. Water quality, ground, and surface water supply, and natural landcover are important
indicators for watershed health. Indicators selected to visualize watershed health include:
Watershed Health
1. % Natural Land Cover (N-lndexl) in Watershed5
2. Soil Stability, Mean in Watershed
3. Preliminary Healthy Watershed Analysis (PHWA) Watershed Health Index, State6
5The % Natural Land Cover is included in this analysis as a standalone indicator. It also factored into the PHWA, and therefore,
may have a somewhat greater influence on the Watershed Health index scores.
6 The Preliminary Healthy Watershed Analysis (PHWA) Watershed Health Index is an index based on the EPA's Healthy
Watersheds Assessment Framework. It integrates data from the following sub-indices: landscape condition, habitat, hydrology,
geomorphology, water quality and biological condition data. For more information about the PHWA Watershed Health Index,
see the EPA PHWA overview report.
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4. Change in % N-lndexl in Watershed (2001-16).7
Toxics Load
1. Toxic Release and Exposure Potential in WS
2. Hazardous Waste Management Sites, Count in WS
3. Risk Management Plan Sites, Count in WS
Water Resilience
Water Resilience captures the capacity of a watershed to withstand or adapt to or recover from rapid or
significant changes in the water system, including natural disasters. We selected the following six
indicators to illustrate the climate vulnerabilities within the watershed and inform considerations for
water resilience:
Present Vulnerability
1. % 100-Year Flood Zone in Watershed
2. PHWA Watershed Vulnerability Index, State
3. Wildfire Hazard Potential, Mean in WS (2018)
Projected Vulnerability
1. Projected Change in Annual Temperature
2. % Projected Change in Annual Precipitation, Inverse
3. % Projected Change in Annual Evaporative Deficit
All indicators were standardized on a percentile scale according to the range of values within the
mapping area to generate the maps in this report. The projected change in annual temperature and %
projected change in annual precipitation have relatively small ranges across both the San Antonio
Watershed and the Verde, Salt and Gila River Basins. The projected change in annual temperature, for
example, varies by just less than one degree Fahrenheit across the San Antonio region. While the maps
in the following section indicate "hotspots," these are all based on relative values across the watershed
and general projected trends. To view the full dataset for each indicator, see the RPS Tool the EPA RPS
Website.
7 The N-lndexl indicates land classified as natural land cover, according to the CDL-NLCD Hybrid Land Cover dataset. This
indicator was compared alongside the other indicators included in the Watershed Health index and was not incorporated into
the index itself.
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Water Equity Mapping
The San Antonio Watershed
While many of the stakeholders involved in this project are based in the central San Antonio area, both
federal and local stakeholders expressed interest in expanding the water equity data visualization
beyond the immediate watershed to the larger surrounding basin, including regions upstream and
downstream of the City of San Antonio. We selected the San Antonio Basin (HUC6:121003), shown in
Exhibit 1, to broaden the scope of the water equity mapping around the San Antonio urban center. This
basin extends from Kerr and Bandera counties, downstream to Victoria and Refugio counties, with the
San Antonio River at its center. It is comprised of 107 HUC12 regions, including 31 that fall within the
San Antonio city boundary.
Water Access
Social equity and human access to natural and manmade resources are essential to Integrated
Watershed Resource Management (IWRM). In order to identify the most socially vulnerable areas in the
San Antonio River Basin, we selected five indicators that equally contribute to a broad social
vulnerability index: the percent of the population identified as low-income, the percent minority (non-
white), percent linguistically isolated, percent with less than a high-school education, and the percent
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vulnerable age group (below 5 and above 64). See Attachment 2 for more information about the source
data and other details for each of these indicators.
A particular consideration, both within the city and throughout the surrounding watershed, are socially
vulnerable populations who may be disproportionately affected by water mismanagement. Exhibits 2
and 3 present heatmaps that divide the index scores by decile for the full basin and Bexar County,
respectively. The lowest scores (first decile, depicted in light red) indicate the least socially vulnerable
HUC12 regions, while the highest scores (tenth decile, depicted in dark red) show the HUC12 regions
with the highest social vulnerability index scores across the watershed,
portion of the city of San Antonio and the HUC12 regions south of the city along the Medina River and directly
south of the intersection between the San Antonio and Medina Rivers. Other socially vulnerable regions include
the Hondo Creek region of Karnes County and central Goliad County along the San Antonio River, both
downstream of the City of San Antonio.
The RPS Tool is a valuable resource for regions with little local data concerning water equity and reuse.
In the case of San Antonio, the City has invested in the collection of local data and the development of a
visualization tool called the Equity Atlas. The RPS Tool can be used to supplement or broaden this type
of local tool, or to compare national datasets with local data. Exhibit 3 compares the Equity Atlas map
for low income and minority populations (divided by census tract) and the RPS map that captures broad
social vulnerability by HUC12 region. The map trends overlap, and both local and national mapping tools
indicate that central and Southern Bexar County are home to some of the most vulnerable populations.
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Combined Score
The scores that range from 2 to 10 are
a combined score of the race and
income tabs, indicating that the higher
the number, the higher the
concentration of both people of color
and low income households in that
census tract. Click on a census tract to
see the overall combined score that it
received and the total population for
t hat tract.
Exhibit 3. The map on the right shows Bexar County social vulnerability based on RPS data: dark maroon regions
have the greatest socially vulnerable populations of the 107 HUC12 regions in the basin. Scores are based on the
five indicators included in the index (percent low-income, minority, linguistically isolated, less than high school
education and vulnerable age). The San Antonio Equity Atlas map on the left displays a combined low income
and minority population score. Higher values indicate a larger socially vulnerable population. The granularity of
the Equity Atlas map is finer and more clearly illustrates the population divisions within the city boundaries. The
RPS map includes more indicators to generate the final score (percent linguistically isolated and percent
vulnerable age group in addition to percent low income and percent minority). The RPS map also includes ail
HUC12 regions with a majority area in Bexar County, rather than only regions within the San Antonio city
boundary. The map trends overlap, and both indicate that central and Southern Bexar County are home to some
of the most vulnerable populations. See Attachment 2 for more details about individual indicators.
All HUC12 regions with the highest social vulnerability scores fall along or just south of the San Antonio
and Medina Rivers. Areas with high social vulnerability (Shown in Exhibit 3) face the greatest potential
impacts of inadequate access to green space, water management issues and old infrastructure, and
polluted or unhealthy local waterways. Identification of these social vulnerability hotspots can inform
future water management plans and strategies to improve underserved community access to clean,
safe, and affordable water services.
In addition to social vulnerabilities, water access must take into account water use patterns and water
protection areas. San Antonio, the second most populated city in Texas, is home to just over 1.5 million
people.8 The San Antonio water Systems, or SAWS, began a water conservation program in 1982 to
8 https://www.census.gov/quickfacts/sanantoniocitvtexas
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incentivize sustainable water management practices. Water use over the past three decades has
increased by about 20% compared to the 80% growth in population over the same period,9
The San Antonio River and Medina River upstream of the city are directly affected by the higher water
demand in the city. The central city region of San Antonio has the highest water demand after
combining agricultural, industrial, and domestic water use data (Exhibit 4). In central San Antonio in
Bexar County, water demand is primarily domestic and industrial, while regions in central eastern
Medina County use water primarily for agricultural purposes.
JC Comal
Kendall
Caldwell
San Anionic
Guadalupe
Gonzales
Lavaca
Wilson
DeWitt
Victoria
Goliad
Fayette
de Medina
Humand Land and Water
Use
1st Decie
I I 2nd Decile
3rd Decile
^2 4thDeoie
II _j 5th Deole
| 6tn Deole
T| 7th Deole
| 6th Deals
^ _J 9th Deole
| | 10th Decie
Atascosa
0 5 10 20 30 Miles Karnes
Exhibit 4. Dark red regions indicate the greatest water and land use [10th decile]. Regions of greatest water use
were calculated by combining domestic, agricultural, and industrial water demand, and groundwater source
protection areas in the watershed. Hotspots include areas of the city of San Antonio and areas of Bexar County
along the Medina River. The index includes agricultural, industrial, and domestic water demand.
Exhibit 5 illustrates the top decile crossover between the greatest water demand in the watershed and
areas with the lowest groundwater source protection areas. Commercial activity and industrial
production grew over the last decade. The city is home to three Air Force bases and one army post.
Biomedical and medical industries account for a significant portion of the city's economy.10 These
industries, along with the high population density in the area, accounts for a significant portion of the
industrial and domestic water demand in the watershed. Regions south and west of Bexar County have
greater agricultural water demand than the rest of the watershed, particularly in the eastern portion of
9 https://texasiivingwaters.org/water-conservation/how-san-antonio-reduced-its-dailv-water-use-bv-85-gaiions-per-person/
10 https://www.citv-data.com/us-cities/The-South/San-Antonio-Economv.html
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Medina County. Exhibit 5 shows the crossover between regions with the highest water demand and
those with the fewest source protection areas.
Exhibit 5. The pink HUC12 regions indicate those with the lowest proportion of groundwater source protection
areas in the watershed (lowest decile). Purple regions indicate those with the highest domestic, industrial, and
agricultural water demand within the watershed.
The red areas illustrate the lowest decile of percent drinking water source protection areas - specifically
groundwater. These regions have the smallest percent of source protection areas in the basin.
Groundwater is the primary water supply source in the San Antonio River Basin and the main source is
the Edwards Aquifer which the City of San Antonio sits on. While it is important to protect regions that
have the highest water usage - especially as the majority of the population sits on the region's primary
aquifer and demand is projected to grow as population increases - the headwater regions of the Medina
River may also be important to protect in the future.
Unprotected regions will also be severely impacted by a reduction in or the mismanagement of water
distribution and access. There is no current overlap between HUC12 regions with the lowest source
protection areas and highest water demand. However, source protection areas are scarcest southeast of
the city of San Antonio along the river, with the exception of the cluster of HUC12 regions at the head of
the Medina River. Increases in population density or water demand in these regions will likely impact
groundwater distribution needs and water access and increase the need for source protection areas
near these communities.11
11 https://www.mvsoutex.com/karnes countvwide/news/water-is-there-enoush-for-evervone/article 869edb3e-7e22-lle7-
Sfb5-2ba6cce62ba4.html
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Watershed Health
Watershed health captures the watershed's ability to supply sufficient clean water to its population to
maintain socioeconomic and general wellbeing. This category includes the overall ecological health of
the watershed. Exhibit 6 presents the watershed health vulnerability index scores for each HUC12 region
were generated using the RPS Tool by combining three indicators: the % Natural Land Cover (N-lndexl)
in Watershed (2016); the mean Soil Stability in the Watershed (by HUC12); and the Preliminary Healthy
Watershed Analysis (PHWA) Watershed Health Index, State (2016).12
The darkest areas in the watershed indicate the lowest overall watershed health indices, or the areas of
highest watershed health vulnerability. Areas in central and northern San Antonio and central Wilson
County suffer from the lowest watershed health in the San Antonio Basin. Additional areas of low
watershed health include the HUC12 regions in the southern region of Karnes County.
Fayette
Kendall
guao,
tomal
Caldwell
Guadalijpe
[San Anton ia
Jvalde
Medina
Watershed Health
Wilson
Vulnerability Index
1st Decile
~] 2nd Decile
DeWitt
3rd Decile
Karnes
lava la
Victoria
9th Decile
Exhibit 6. The darkest colors in the watershed health vulnerability heatmap indicate the HUC12 regions with the
lowest index scores by decile. Watershed vulnerability trends loosely follow the broad social vulnerability
hotspots.
Exhibit 7 overlays these poor watershed health areas with the previous analysis of socially vulnerable
populations (Exhibit 2), showing that many of the HUC12 regions with the most socially vulnerable
populations lie in close proximity to those with the greatest watershed health vulnerability.
12
The PHWA Health Index is comprised of water quality, landscape condition, habitat, hydrology, geomorphology, and
biological condition sub-indices. For more information see the EPA page here.
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Guadalupe
'£ RIVER,
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the basin (10th decile) include portions of upper San Antonio and southern HUC12 regions along the
border of Bexar County and Atascosa County. Additional regions that experience current environmental
stress include the HUC12 regions south of the Guadalupe River in western Guadalupe county, and
central Bandera County along the Medina River.
Caldwell
GOA?^
San Antonio
DeWitt
Victofia,
0 5 10 20 30 Miles
Refugio
Exhibit 8. Present climate vulnerability index scores include three indicators: %100-year flood zone in
watershed, PHWA watershed vulnerability index, and mean wildfire hazard potential in watershed. HUC12
Regions with greatest vulnerability fall in the lowest deciles (dark red).
Present Climate Vulnerability
1st Decile
2nd Decile
3rd Decile
4th Decile
5th Decile
6th Decile
7th Decile
8th Decile
9th Decile
10th Decile
Fayette
aide
Medina
Projected climate vulnerability will be impacted by many changing factors, including the projected
change in annual rainfall, increase in temperature and increase in annual runoff. Exhibit 9 captures the
projected increase in these values between 2061 and 2090 based on relative and historical conditions.
Areas with the greatest vulnerability are found toward the northern border of the San Antonio River
Basin, particularly north of the city of San Antonio. Regions in Bandera county along the Medina river fall
within the highest deciles for present climate vulnerability and projected climate vulnerability. Southern
Kendall, Comal and Guadalupe counties are also projected to have the greatest climate vulnerability
within the region in the second half of the century. For more information about climate vulnerability
indicators, see Attachment 2.
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Kendall
Caldwell
GUAO^
Fayette
San Antonio
Gonzales
Medina
Projected Climate Vulnerability
DeWltt
3rd Decile
Victoria,
6th Decile
0 5 10 20 30 Miles
Refugio
10th Decile
Exhibit 9. Projected Climate Vulnerability. Northern regions of the greater San Antonio watershed face greatest
environmental threats when considering projected temperature change, evaporative deficit, and projected
annual precipitation change (inverse). Annual precipitation change is projected to be negative (reflecting a
decrease in annual precipitation totals) in the 2061-2100 period.
A comparison of water resilience to water access and watershed health reveals that the areas of present
climate vulnerability show significant overlap with areas of watershed health and social vulnerability
throughout the central portions of the San Antonio Watershed. Projections suggest that the degree of
overlap in these vulnerabilities may decrease as the areas of highest climate vulnerability shift to the
north in the second half of the 21st century.
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The Verde, Salt and Gila River Basins
Although stakeholder conversations for the WRAP project primarily focused on the Upper Verde River
Basin, the water equity mapping was designed to visualize the broader basin area comprised of the
Verde, Salt and Gila Rivers (see Exhibit 10).
HAVASUPAI
NAVAJO NATION
Mohave
Coconino
HUALAPAI
HOPI
Navajo
Apache
-YAVAPAI-APACHE NATION
YAVAPAI-P RE SCOTT
Yavapai'
TONTO APACHE
Lake Pleasant
FORTAPACHE
Bartlett Dam
SALT RIVER
FORT MCDOWELL YAVAPAI NATION
JKJ
I J Phoenix
SALT RIVER
SAN CARLOS
GILA RIVER
Maricopa
MARICOPA (AK^CHIN)
Graham
Yuma
80 Miles
Exhibit 10. Verde River arid Surrounding Watersheds. The Verde, Salt and Gila Rivers converge just north of
Phoenix, and each is a part of one or more watersheds that comprise the central and southern regions of
Arizona. This area includes the Verde River Basin to the North (HUC6 150602} the Salt Basin to the West (HUC6
150601) and the Lower Gila-Agua Fria Basin to the Southeast (HUC6 150701). This entire area includes 634
distinct HUC12 regions.
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Water Access
The heatrriap in Exhibit 11 includes the three major watershed regions. The darkest colors indicate areas
with the highest social vulnerability index scores based on five social indicators: the percent low-income,
the percent minority (non-white), percent linguistically isolated, percent with less than a high-school
education, and the percent vulnerable age group (below 5 and above 64). Particularly high values for
social vulnerability occur north of the Salt River around the Fort Apache-White Mountain Reservation
(Exhibit 11). Additional vulnerability hotspots fall within the central and southern boundaries of the city
of Phoenix, as well as the western half of Maricopa County along the Gila River. Some additional areas of
vulnerability include northwestern Maricopa County and in the upper reaches of the Verde River
watershed. Water access is important to consider in remote regions of the state that have higher
proportions of native and minority populations and low-income communities, many of whom rely on
the land through farming.
Coconino
Hualapai
Social Vulnerability
Index
1st Decile
2nd Decile
Navajol
Apache
3rd Decile
4th Decile
5th Decile
6th Decile
7th Decile
8th Decile
Yavapai
Yavapai-Prescott
9th Decile
10th Decile
Tonto Apache
IjortjApache
W&ivek
black^
Fort McDowell Yavapai Nation,
I ' i ' ¦
Phoenix
San Carlos
Gila River
Greenlee
Maricopa
^/VER
Maricopa (Ak Chin)
Graham
Yuma
Exhibit 11. This heatmap displays the broad social vulnerability index across the Verde, Salt and Lower Gila
watersheds, by decile. These scores integrate data from five indicators: the population identified as low-income,
the percent minority (non-white), percent linguistically isolated, percent with less than a high-school education,
and the percent vulnerable age group (below 5 and above 64).
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Exhibit 12 illustrates human land and water use. The areas with the greatest population and domestic,
industrial, and agricultural water use include the central Phoenix area and Peoria just west of the city
border. Additional regions along the Gila River feeding into the city, as well as those extending beyond
the city to the Southwest have among the highest use of land and water resources. The southwest
portion of the Gila River in Maricopa County has particularly high levels of agricultural water demand
compared to other HUC12 regions, while areas of highest industrial water demand include central
Phoenix and Glendale/Peoria to the west of the city. Because water demand and population are highest
in the Phoenix area, regions downstream along the southern Gila River may be affected if the city
experiences water shortages. Arizona already has a management plan that controls water access in and
around Phoenix, but by broadening understanding of water demand across multiple connected
watersheds and subwatersheds, stakeholders and policymakers may better understand the relationships
between central city water use and demand in more remote regions of the state.
Coconino
Human Land
and Water Use
Navajo
1st Decile
2nd Decile
3rd Decile
4th Decile
5th Decile
6th Decile
Yavapai
7th Decile
8th Decile
9th Decile
10th Decile
Ri I,.
fiLACKR^l
Phoenix
a^\ver
Maricopa
80 Miles
Graham
Yuma
Exhibit 12. Dark red regions indicate the greatest water and land use [10th decile] within the Verde, Salt and Gila
River Basins. Regions of greatest water use were calculated by combining domestic, agricultural, and industrial
water demand, and groundwater source protection areas in the watershed. Hotspots include areas of central
and western Phoenix above and along the Gila River as well as those just south of the Gila River to the east of
the city border, and regions surrounding Flagstaff, Prescott, and Sedona near the Upper Verde River.
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Watershed Health
Regions with the greatest watershed health vulnerability in the Salt, Gila and Verde River watersheds
include the series of HUC12 regions along and north of the Gila River, ranging from Phoenix through
central Maricopa County, the Middle Verde subwatershed and parts of the Salt River (see Exhibit 13).
Watershed Health
Vulnerability
Mohave
Coconino
2nd Decile
3rd Decile
4th Decile
5th Decile
6th Decile
7th Decile
8th Decile
Phoenix
Greenlee
Maricopa
Graham
Yuma
Exhibit 13. This map displays the watershed health vulnerability index, which was generated by combining
three environmental indicators: the % natural land cover (N-lndexl) in watershed, Soil stability mean in
watershed, and Preliminary Healthy Watershed Analysis (PHWA) Watershed Health Index, State. The top decile
(darker colors) indicates areas with the highest vulnerability, or the lowest scores for these combined indicators.
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Maricopa county is the most populous county in Arizona, with over four million inhabitants, most of
whom reside within and surrounding the city borders of Phoenix. In August 2021, 86% of Maricopa
County was classified as a severe drought region by the National Oceanic and Atmospheric
Administration.14 Water management practices in the Upper Verde River and along the Salt River
ultimately impact the water flowing downstream towards Maricopa County via the Gila River. This water
is needed to support the substantial agricultural land use in Maricopa and in Pinal County to the west.
The Central Arizona Project (CAP) supplies water to nearly 80% of the state's population and significantly
benefits Pinal County and to a lesser extent the population of Phoenix.15 This said, regions within and
just outside of the northern Phoenix city boundary (through which the CAP canal system runs) fall into
the top decile of most vulnerable areas for watershed health based on natural land cover, soil stability
and the PHWA Watershed Health Index. Although these regions have access to water via the canal
system, the health of these subwatersheds is worthy of consideration in future water management
planning. Subwatersheds outside of the Phoenix area with greater watershed vulnerability include those
around Cottonwood near the border between Yavapai and Coconino counties extending to the west and
East from the upper Verde River. Additional watersheds with high vulnerability include the HUC12
regions surrounding Roosevelt Lake, the largest visible lake along the Salt River in the watershed health.
Exhibit 14 shows the top deciles for both watershed health vulnerability and social vulnerability. The two
indices are closely correlated across the map - areas of high social vulnerability along the Gila River
south of Phoenix and the Salt River east of the city also have high watershed health vulnerability index
scores. The highest areas of social vulnerability fall along and above the Salt River in Navajo, Gila, and
Graham counties. Additional regions of high watershed health vulnerability occur in Maricopa County
and Western Regions of Navajo county. Areas with the highest watershed health vulnerability scores
include the regions along the Upper Verde River subwatershed and areas upstream along the Salt River
(e.g., the northern section of Graham County and the southern regions of Navajo County). These areas
fall within the San Carlos and White Mountain Apache Tribal lands. It will be of particular importance
when developing water reuse action plans to consider tribal communities, especially those that are not
served by the CAP system. Policy and management changes in hotspot areas that focus on human equity
are likely to support surrounding ecosystem health and vice versa. Additionally, the environmental
stresses that occur in portions of the Verde River watershed are likely to adversely impact areas
downstream of vulnerable subwatersheds.
14
Historical Conditions for Maricopa County, Drought.gov
15
https://www.cap-az.com/water/cap-svstem/water-operations/svstem-map/
18
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Yuma
0 20 40 80 Miles Graham
1 I 1 I I 1 I I I
Social and Watershed Vulnerability Crossover
Social Vulnerability Top Decile
Watershed Health Vulnerability Top Decile
Top Decile Crossover
Cochise
Exhibit 14. Top decile crossover between socially vulnerable HUC12 regions and those with the lowest
watershed health illustrated in Exhibit 12. Striped HUC12 regions indicate areas of crossover between the
HUC12 regions within the top decile for both indices.
Water Resilience
The RPS contains datasets that, when combined to form a single index, indicate regions facing high
environmental stress levels - Present Climate Vulnerability Index. Stressor indicators included in this
index are the % 100-year flood zone (high-risk flood zone areas), the wildfire hazard potential, and the
PHWA watershed vulnerability index score (which has implications for future degradation of watershed
processes and aquatic system health).15 As shown in Exhibit 15, the eastern border of these watersheds
generally experiences the greatest present climate vulnerability, specifically the band of HUC12 regions
reaching from the border between Yavapai and Coconino counties down into northern Pinal county and
northern Graham county. The high vulnerability HUC12 regions roughly follow the expanse of the
1 For more information, see the EPA site on the Healthy Watersheds Analysis: https://www.epa.eov/hwp/download-
preliminarv-healthv-watersheds-assessments
19
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Coconino National Forest, which includes 1.8 million acres of wilderness and recreation areas.17 Wildfire
risk is a significant contributor to the present vulnerability scores of these regions.
Coconino
Present Climate Vulnerability
1st Decile
2nd Decile
3rd Decile
4th Decile
5th Decile
6th Decile
7th Decile
8th Decile
Yavapai
9th Decile
10th Decile
SLACK R;!
Phoenix
A^tVER
'Maricopa,
80 Miles
Graham
Yuma
Exhibit 15. Present climate vulnerability based on the combination of three indicators: % 100-year flood zone,
PHWA watershed vulnerability index, and wildfire hazard potential, Mean in watershed. Dark colors indicate
areas of greatest vulnerability.
Exhibit 16 presents projected vulnerability index scores that were generated by integrating the following
stressor indicators into a single index score: the projected change in annual temperature, the %
projected change in annual precipitation (inverse), and the % projected change in annual evaporative
deficit. The change in annual precipitation reflects average model projections from 2061-2090 relative
to historical 1971-2000 conditions.18 These indicators can be used to identify regions that are
particularly sensitive to climate change and will likely be impacted the most in the coming century. The
western border of the watersheds included in this analysis demonstrate the greatest vulnerability or
lowest projected resilience. Given that the western portion of the watershed is presently vulnerable (as
shown in Exhibit 15), immediate action to develop or strengthen long-term water reuse action plans wiil
be of particular importance. Additionally, because vulnerable populations such as tribes own a
significant portion of the land along the western Salt and Black Rivers, it will be important for the federal
17
https://www.fs.usda.gov/coconino
18
See the EPA RPS Mapping tool for indicator explanations and sources.
20
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government to prioritize action in these regions to increase land and watershed resiliency in the face of
climate change.
Coconino
Projected Climate
Vulnerability
1st Decile
Navajo
2nd Decile
3rd Decile
4th Decile
5th Decile
6th Decile
7th Decile
Yavapai
8th Decile
9th Decile
10th Decile
Cjj^LT R/u
Phoenix
Maricopa
Graham
Yuma
Exhibit 16. Projected climate vulnerability (2061 -2100). Darker maroon regions indicate greater vulnerability
based on three indicators: projected change in annual temperature, the % projected change in annual
precipitation (Inverse), and the % projected change in annual evaporative deficit.
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Water Equity Mapping using the RPS Tool:
Lessons Learned
The RPS Tool is extremely valuable as a public repository of data for over 200 social, environmental and
stressor indicators. Given this, it has great potential to supplement IWRM and efforts such as this
project, as it can help to jumpstart the visualization process to improve the understanding of social and
environmental dynamics that impact water equity within and across watersheds. The tool is also
accessible to the public and downloadable directly from the EPA RPS website.19 Lessons learned through
this project about using the RPS Tool to visualize water equity at the watershed level are outlined below.
• RPS is a comparative tool, meaning that index scores are based on the raw data for the
specific watershed region chosen by the user. The index scores provide valuable insights into
water equity within the selected region.
• The tool's visualization display capabilities are limited in producing clear visualizations of a
given watershed. The tool has a user-friendly map function that is useful for quickly visualizing
indicators. These maps are low resolution and cannot be used for water equity visualization.
Fortunately, RPS data and results can be readily integrated into ArcGIS to produce higher-
resolution maps that can be used effectively to convey water equity at the watershed and
subwatershed levels.
• Combining too many indicators to generate an index can lead to a significant amount of
"noise." The RPS Tool allows users to incorporate as many social, stressor and environmental
indicators as they choose. However, selecting too many indicators may obscure the relative
contribution of any indicator(s) to each HUC12 index score.
• Data stored in RPS may not be as recent or as granular as the most recent data collected
locally. Much of the data in RPS is from 2016 to 2019, while some indicators use even older
data. Local agencies or communities may have more recent data that will better represent their
communities and watershed as a whole.20
• Using the techniques developed through the course of this project, the RPS Tool could be
applied at any of the other UWFP locations. The data in RPS is easily exportable and can be
used with other software tools such as GIS to create visuals that could range in geographic scale
from the full state to a handful of HUC12 regions. The modular nature of the RPS Tool allows the
user to easily select the region of interest and to identify data-driven hotspots within it. The
tool, updated in August of 2021 to include a number of EJ social indicators, provides data from
national data sources. For regions with little local data, RPS may serve as a first step toward
identifying disadvantaged areas and areas that would benefit most from IWRM.
19
Find state specific RPS Tools at: https://www.epa.gov/rps/downloadable-rps-tools-comparing-watersheds
20 The RPS Tool is regularly updated, with another update and release anticipated for 2022.
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Attachment 1. Visualizations Generated Using
the EPA RPS Tool
The RPS Tool is extremely valuable as a repository of data for over 200 indicators in three major
categories - social, environmental and stressor. The RPS Tool also includes 31 base indicators. These
include reference metrics such as the HUC 6, HUC 8 and HUC 12 regional watershed boundaries,
watershed size, and other geographical information. For more information about the three major
categories of indicators and associated sub-categories, see the EPA RPS Indicator Overview website.21
The RPS Tool can be customized to evaluate an area as large as an entire state or as small as a handful of
HUCs at the 12-digit level, or HUC 12. Once HUC 12 regions of interest are selected, the tool uses the
data for each of these HUC12 regions to calculate index and RPI scores, both of which are generated
using comparative formulas that identify the most highly influenced HUC12 regions based on the social,
environmental and stressor indicators of interest. The tool is unique because it applies a watershed-
based approached to evaluating multiple data elements at the level of HUCs, which allows the user to
better understand the relationships among these data in these hydrologic regions. The tool allows users
to apply custom weighting for indicators when generating the index, which is valuable if the user wishes
to emphasize the impacts of certain indicators in a particular RPS data visualization.
Calculations
Index Scores: The RPS Tool categorizes all data as either base, ecological, stressor, or social indicators.
To effectively combine and compare indicators from multiple datasets that may be in different units of
measurement, the RPS Tool normalizes the data within a range of 0 to 1, then transforms the data into
an index with values ranging from 0 to 100. If combining multiple indicators into the index value (e.g., %
Wetlands Remaining in the watershed and % Forest Remaining in the watershed), the user is able to
assign weights to each indicator, if desired. The tool generates index scores by calculating the relative
value of each score within the subset of HUC12 regions selected for the analysis. The Index score
calculations are generated using the formula below:
IndNorm = Weight * (/ndi - Ind-\Miri) _j_ Weight * (7nd? - Ind?Miri)
{Ind^Max — Ind-iMiri) (Ind2Max — Ind2Min)
In tlx
Where IndNorm is the normalized index score for one of the categories (either ecological, stressor, or
environmental, depending on the indicators used), IndiMax is the maximum value within the HUC 12
regions selected for indicator l's dataset, IndiMin is the minimum value in the set for indicator 1. Indx
represents the total number of indicators (e.g., two in the example above). The social, stressor, and
environmental indices are calculated in the same way.
21
https://www.epa.gov/rps/overview-selecting-and-using-recoverv-potential-indicators
23
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Recovery Potential Index Score: The Recovery Potential Index (RPI) score is calculated from the
ecological, stressor and social index scores. In this way, the tool is able to generate a value for each
HUC12 region based on indicators from multiple categories. The rank ordered RPS score is designed to
support the user in identifying areas with the greatest "recovery potential/' or areas that have the
lowest stressor index scores and highest social and ecological index scores. Each RPS score is calculated
from the following formula:
RPI Score = [Ecological Index + Social Index + (100 - Stressor Index)]
3
Recovery Potential Index scores are relative in that the watersheds' scoring range and distribution is
based only on the gradient of scores for the watersheds screened. The tool does not account for or
incorporate any cutoff values (e.g., healthy or unhealthy, impaired or unimpaired), as such thresholds
are highly case-specific.22
For each of the categories identified in this report, we generated a normalized index that groups the
selected indicators into relevant categories (see the list on page 3 of this report). These values, which
range from 1 - 100, were then extracted, analyzed, and mapped using ArcGIS. Due to recent RPS Tool
updates and the goals of this project, we did not generate maps displaying the RPI scores of our two
major watershed regions. This choice was made to avoid directionality issues with the selected
indicators. For certain environmental and social indicators, high scores represent positive watershed
qualities, while for others high scores represent negative watershed qualities. We chose to illustrate the
watershed using indexes to avoid conflating index scores or combining contrasting data into one score.
22 For more information about calculations, see the RPS User Guide: https://www.epa.gov/sites/default/files/2020-
08/documents/181001 rpstool userguide508.pdf
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Attachment 2. Indicator Summary and Source
Information
The following table summarizes the data included in each of the indicators referenced in this report and
their sources. Indicators that comprise the population vulnerability and toxics load index categories are
social indicators, indicators in the watershed health category are ecological indicators, and indicators
within present and projected climate vulnerability and land and water use are categorized as stressor
indicators.
POPULATION VULNERABILITY
% Low-Income
Population in WS
Percent of total population in the HUC12 living in a household with low-income. Low-income is
defined as a household income that is less than or equal to twice the federal poverty level.
Source data was a map layer of low-income population count by census block group from the
US Census Bureau American Community Survey 2013-2017 Five-Year Summary, prepared by
EPA for the EJSCREEN mapping tool (2018 update; https://www.epa.gov/ejscreen). Low-
income populations were assumed to follow the same pattern of distribution as the total
population within a census block group. Calculated for each HUC12 as: Population in Low-
Income Households in HUC12 / Total Population in HUC12 * 100.
% Minority Population in
WS
Percent of total population in the HUC12 that is in a minority group. Minority groups include
individuals who define their race as other than white alone and/or list their ethnicity as
Hispanic or Latino. That is, all people other than non-Hispanic white-alone individuals. Source
data was a map layer of minority population count by census block group from the US Census
Bureau American Community Survey 2013-2017 Five-Year Summary, prepared by EPA for the
EJSCREEN mapping tool (2018 update; https://www.epa.gov/ejscreen). Census block groups
are the smallest geographic units used by the US Census Bureau to report demographic data.
Minority populations were assumed to follow the same pattern of distribution as the total
population within a census block group. Calculated for each HUC12 as: Minority Population in
HUC12/Total Population in HUC12 * 100.
% < High School Educated
Population in WS
Percent of the age 25 and over population in the HUC12 with less than a high school degree.
Source data was a map layer of population counts with less than high school education by
census block group from the US Census Bureau American Community Survey 2013-2017 Five-
Year Summary, prepared by EPA for the EJSCREEN mapping tool (2018 update;
https://www.epa.gov/ejscreen). Populations with less than high school education were
assumed to follow the same pattern of distribution as the total population within a census
block group. Calculated for each HUC12 as: Population with Less Than High School Education in
HUC12 / Age 25 and Over Population in HUC12 * 100.
% Linguistically Isolated
Population in WS
Percent of households in the HUC12 that are linguistically isolated. Households in which all
members age 14 years and over speak a non-English language and also speak English less than
'very well' are considered linguistically isolated. Source data was a map layer of linguistically
isolated household counts by census block group from the US Census Bureau American
Community Survey 2013-2017 Five-Year Summary, prepared by EPA for the EJSCREEN mapping
tool (2018 update; https://www.epa.gov/ejscreen). Populations living in linguistically isolated
households were assumed to follow the same pattern of distribution as the total population
within a census block group. Calculated for each HUC12 as: Linguistically Isolated Household
Count in HUC12 / Total Household Count in HUC12 * 100.
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POPULATION VULNERABILITY
% Vulnerable Age Group
Population in WS
Percent of total population in the HUC12 that is under age 5 or over 64 years old. Source data
were map layers of under age 5 and over age 64 population counts by census block group from
the US Census Bureau American Community Survey 2013-2017 Five-Year Summary, prepared
by EPA for the EJSCREEN mapping tool (2018 update; https://www.epa.gov/ejscreen).
Vulnerable age group populations were assumed to follow the same pattern of distribution as
the total population within a census block group. Calculated for each HUC12 as: (Population
Under Age 5 in HUC12 + Population Over Age 64 in HUC12) / Total Population in HUC12 * 100.
TOXICS LOAD
Risk Management Plan
Sites, Count in WS
Number of sites in the HUC12 that are in the EPA Toxics Release Inventory (TRI) database. The
TRI stores information on certain facilities that handle toxic chemicals in amounts above
established levels, including on-site or off-site land, air, or water disposal, recycling, energy
recovery, or treatment. There are 770 individually listed chemicals and 33 chemical categories
covered by the TRI Program. Source data was a map layer of TRI facilities in the EPA Facility
Registry Service (FRS): Facility Interests Dataset (December 2020 version;
https://www.epa.gov/frs/geospatial-data-download-service).
Hazardous Waste
Management Sites, Count
in WS
Count of Hazardous Waste Treatment, Storage, or Disposal (TSD) facilities in the HUC12. TSD
facilities are regulated under the Resource Conservation and Recovery Act (RCRA) and either
hold hazardous waste (storage) or change the physical, chemical, or biological characteristics of
waste to minimize its environmental threat (treatment and disposal). Source data was the US
EPA Facility Registry Service (FRS; December 2020 version:
httDs://www.eDa.sov/frs/seosDatial-data-download-service.
Calculated using latitude and longitude coordinates in the FRS as the count of TSD facilities
located in the HUC12. Facilities with missing coordinates in the FRS are not included in HUC12
counts.
Toxic Release and
Exposure Potential in WS
The relative potential for toxic chemical release and human exposure in the HUC12. Higher
values correspond to greater potential relative to other HUC12s for toxic release and exposure
due to a combination of: the magnitude of chemical releases, the size of exposed populations,
and the estimated dose of chemicals at points of human exposure. Quantified from 2015 to
2019 Risk-Screening Environmental Indicators (RSEI) Scores calculated by EPA for facilities that
release toxic chemicals through air emissions or wastewater discharge. RSEI scores for all
facilities nationwide were downloaded from the EasyRSEI database dashboard in December
2020; https://edap.epa.gov/public/extensions/EasyRSEI/EasyRSEI.html). RSEI scores were
assigned to HUC12s using mapped locations of Toxics Release Inventory (TRI) facilities in the
EPA Facility Registry Service (FRS): Facility Interests Dataset (December 2020 version;
https://www.epa.gov/frs/geospatial-data-download-service). Calculated as the sum of 2015-
2019 RSEI Scores for TRI facilities in each HUC12.
WATERSHED HEALTH
% N-lndexl in WS (2016)
Percent of the HUC12 classified as natural land cover (including barren land) by the 2016 CDL-
NLCD Hybrid Land Cover dataset. Natural land cover classes in the N-lndexl include barren,
forest, wetlands, shrubland, and grassland; codes 131,141 through 143,152,171,190, and 195
in the 2016 CDL-NLCD Hybrid Land Cover dataset. Equation used: N-lndexl Area / HUC12 Area
* 100. See also 2016 CDL-NLCD Hybrid Land Cover glossary definition.
Soil Stability, Mean in WS
Mean soil stability in the HUC12. Soil stability is the inverse of soil erodibility. Source data was
a 100-meter resolution grid of soil map units and attributes in the Natural Resources
Conservation Service (NRCS) Soil Survey Geographic (STATSG02) database, acquired from the
US Geological Survey in July 2013. Mean soil erodibility was calculated as the average of
erodibility grid values per HUC12. Mean soil stability was calculated as 1 - Mean soil erodibility.
PHWA Watershed Health
Index, State
The statewide Watershed Health Index score for the HUC12 from the 2021 EPA Preliminary
Healthy Watersheds Assessment (PHWA). The Watershed Health Index is an integrated
measure of watershed condition that combines Landscape Condition, Hydrologic,
Geomorphology, Habitat, Water Quality, and Biological Condition Sub-Index scores. Higher
scores correspond to greater potential for a watershed to have the structure and function in
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POPULATION VULNERABILITY
place to support healthy aquatic ecosystems. Source data were statewide Watershed Health
Index scores for HUC12s developed as part of the 2021 EPA Preliminary Healthy Watersheds
Assessment (August 8, 2021 version). NOTE: PHWA scores/percentiles are not suitable for
comparing HUC12s that occur in different states to one another. Scoring of a given HUC12
reflects its condition relative to all other HUC12s within the same state only. See also PHWA
glossary definition.
% N-lndexl Change in WS
(2001-16)
The change in the percentage of the HUC12 with natural cover (including barren land) from
2001 to 2016. Calculated from the National Land Cover Database 2016 (NLCD 2016) 2001 and
2016 Land Cover Datasets (January 2019 version). Natural cover classes included in the N-
Indexl are 'Barren Land (Rock/Sand/Clay)', 'Deciduous Forest', 'Evergreen Forest', 'Mixed
Forest', 'Shrub/Scrub', 'Grassland/Herbaceous', 'Woody Wetlands', and 'Herbaceous Wetlands'
cover classes; codes 31, 41, 42, 43, 52, 71, 90, and 95 in the 2001 and 2016 Land Cover
datasets. Positive values denote an increase in N-lndexl; negative values denote a decrease in
N-lndexl. Equation used: (Area Changing to N-lndexl-Area Changing From N-lndexl)/(HUC12
Area) * 100.
PRESENT CLIMATE VULNERABILITY
Wildfire Hazard Potential,
Mean in WS (2018)
The mean wildfire hazard potential in the HUC12. Wildfire hazard potential ranges from 1 (very
low risk of wildfire) to 5 (very high risk of wildfire) and depict the relative potential for the
occurrence of wildfire that would be difficult for suppression resources to contain. Calculated
from the 2018 USDA Forest Service Wildfire Hazard Potential geospatial grid dataset.
Calculated as the average of wildfire hazard potential for grid pixels in the HUC12. Areas not
assigned a Wildfire Hazard Potential value (non-burnable lands and water) were excluded from
the mean calculation.
% 100-Year Flood Zone in
WS
Percent of the HUC12 that is in the 100-year flood zone. The term 100-year flood is used to
describe a flood magnitude that has a 1% chance of occurring in a given year. The 100-year
flood zone is the area that is at-risk for flooding during a 100-year flood and is used for flood
risk mapping under the National Flood Insurance Program. Source data were 100-year flood
zone map layers maintained in the FEMA Flood Insurance Rate Maps National Flood Hazard
Layer (acquired February 2021; https://www.fema.gov/flood-maps/national-flood-hazard-
layer). For HUC12 analysis, portions of the 100-year flood zone were removed if they
overlapped surface waters such as rivers and lakes or wetlands.
PHWA Watershed
Vulnerability Index, State
The statewide Watershed Vulnerability Index score for the HUC12 from the 2021 EPA
Preliminary Healthy Watersheds Assessment (PHWA). The Watershed Vulnerability Index
characterizes the vulnerability of aquatic ecosystems in a watershed to future alteration based
on Land Use Change, Water Use Change, and Wildfire Vulnerability Sub-Index scores. Higher
scores correspond to greater potential vulnerability of aquatic ecosystems to future
degradation. Source data were statewide Watershed Vulnerability Index scores for HUC12s
developed as part of the 2021 EPA Preliminary Healthy Watersheds Assessment (August 8,
2021 version). NOTE: PHWA scores/percentiles are not suitable for comparing HUC12s that
occur in different states to one another. Scoring of a given HUC12 reflects its condition relative
to all other HUC12s within the same state only. See also PHWA glossary definition.
PROJECTED CLIMATE VULNERABILITY
% Projected Change in
Annual Precipitation,
inverse
Projected percent change in annual precipitation in the HUC12. Positive values indicate a
projected increase in average annual precipitation during 2061-2090 relative to historical 1971-
2000 conditions; negative values indicate a projected decrease. Annual precipitation during the
future and historical periods is calculated from results of 30 climate models summarized by the
USGS National Climate Change Viewer program
(https://www2.usgs.gov/landresources/lcs/nccv.asp). Projected future conditions reflect a high
greenhouse gas emission scenario, with continued increases in emissions through 2100 (the
Representative Concentration Pathway 8.5 emission scenario). Calculated for each HUC12 as:
(Projected Future Annual Precipitation - Historical Annual Precipitation) / Historical Annual
Precipitation x 100. See also the Climate Projection Data glossary definition.
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POPULATION VULNERABILITY
Projected Change in
Annual Temperature
Projected change in annual temperature in the HUC12 (degrees Celsius). Annual temperature is
the average of daily highs across a calendar year. Positive values indicate a projected increase
in average annual temperature during 2061-2090 relative to historical 1971-2000 conditions;
negative values indicate a projected decrease. Average annual temperature during the future
and historical periods is calculated from results of 30 climate models summarized by the USGS
National Climate Change Viewer program
(https://www2.usgs.gov/landresources/lcs/nccv.asp). Projected future conditions reflect a high
greenhouse gas emission scenario, with continued increases in emissions through 2100 (the
Representative Concentration Pathway 8.5 emission scenario). Calculated for each HUC12 as:
(Projected Future Annual Temperature - Historical Annual Temperature. See also the Climate
Projection Data glossary definition.
% Projected Change in
Annual Evaporative
Deficit
Projected percent change in annual evaporative deficit in the HUC12. Evaporative deficit is a
measure of atmospheric water shortage and is defined as the difference between potential
evapotranspiration and actual evapotranspiration. Positive values indicate a projected increase
in average annual evaporative deficit during 2061-2090 (i.e., drier conditions) relative to
historical 1971-2000 conditions. Annual evaporative deficit during the future and historical
periods is calculated from water balance models that simulate the hydrologic response to 30
climate models. The water balance model simulates the combined effects of precipitation and
temperature changes independent of land use and vegetation cover. Analysis of climate model
results and water balance modeling was completed by the USGS National Climate Change
Viewer program (https://www2.usgs.gov/landresources/lcs/nccv.asp). Projected future
conditions reflect a high greenhouse gas emission scenario, with continued increases in
emissions through 2100.23
HUMAN LAND AND WATER USE
Population Density in WS
Human population density in the land area of the HUC12 (persons per square kilometer).
Source data used was the EPA EnviroAtlas 'Dasymetric Population for the Conterminous United
States' raster (February 2015 version:
https://enviroatlas.epa.gov/enviroatlas/DataFactSheets/pdf/Supplemental/DasymetricAllocati
onofPopulation.pdf). The dasymetric population raster is derived from 2010 US Census Bureau
census block populations using a geospatial technique called dasymetric mapping. Dasymetric
mapping uses information on land cover and slope to distribute populations to grid pixels
within each census block.
Domestic Water Demand
in WS
Daily domestic water use in the HUC12 (million gallons per day). Domestic water use includes
indoor and outdoor household uses, such as drinking, bathing, cleaning, landscaping, and
pools. Domestic water can include surface or groundwater that is self-supplied by households
or publicly supplied. Water used in a HUC12 may originate from within or outside the HUC12.
Calculated by downscaling county water use estimates for 2005 reported by US Geological
Survey ('Estimated Use of Water in the United States County-Level Data for 2005') using the
2006 National Land Cover Database (2006 NLCD) Land Cover dataset and 2010 US Census
population estimates from the US Census Bureau. This indicator was calculated for EPA
EnviroAtlas.
23 These indicators were recalculated after the completion of this report and offer different projections of climate and
hydrology. The most recent version of the EPA EJSCREEN tools are available on the EPA website:
https://www.epa.gov/rps/downloadable-rps-tools-comparing-watersheds.
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POPULATION VULNERABILITY
Agricultural Water
Demand in WS
Daily agricultural water use in the HUC12 (million gallons per day). Agricultural water use
includes surface and groundwater that is self-supplied by agricultural producers or supplied by
water providers (governments, private companies, or other organizations). Water used in a
HUC12 may originate from within or outside the HUC12. Calculated by downscaling county
water use estimates for 2005 reported by US Geological Survey ('Estimated Use of Water in the
United States County-Level Data for 2005') using the 2006 National Land Cover Database (2006
NLCD) Land Cover dataset, the 2010 Cropland Data Layer, and a custom geospatial dataset of
irrigated area locations. Counties with zero reported water use were assigned a state-level
average value to address issues with water use reporting. This indicator was calculated for EPA
EnviroAtlas.
Industrial Water Demand
in WS
Daily industrial water use in the HUC12 (million gallons per day). Industrial water use includes
water used for chemical, food, paper, wood, and metal production. Only includes self-supplied
surface water or groundwater by private wells or reservoirs. Industrial water supplied by public
water utilities is not counted. Water used in a HUC12 may originate from within or outside the
HUC12. Calculated by downscaling county water use estimates for 2005 reported by US
Geological Survey ('Estimated Use of Water in the United States County-Level Data for 2005')
using a geospatial dataset on the location of industrial facilities as of 2009/10. Water use by
industrial facilities in counties that were reported to have zero industrial water use in the USGS
dataset was estimated from values for nearby facilities. This indicator was calculated for EPA
EnviroAtlas.
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