Summary Report:
Recovery Potential Screening of Kansas Watersheds
in Support of Nutrient Management
INTRODUCTION
The US Environmental Protection Agency's (EPA's) Total Maximum Daily Loads (TMDL) Program, in cooperation with
state water quality programs, released a long-term TMDL Vision document in December 2013. Part of the TMDL Vision
involves increasing states' identification of priority watersheds for restoration and protection efforts over a several-year
time frame, and better linkage of TMDLs to these priorities. Previously, a 2011 Office of Water policy memorandum on
nutrients had also recommended systematic watershed analysis, comparison and priority setting to obtain better
results.
EPA's TMDL program has provided watershed data, comparative assessment tools and state technical assistance for the
past ten years through the Recovery Potential Screening (RPS) approach and tools (see Attachment 1). In support of
state requests for assistance in nutrient-related prioritization, the TMDL program has partnered with several states,
including Kansas, to jointly carry out RPS assessments and develop results to help states consider their watershed
nutrient management options systematically with consistent data. These RPS assessments were designed to address
primary nutrient-related issues identified by each state using state-specific indicators and data relevant for watershed
comparison. This report summarizes the approach and findings of the Kansas project completed from 2015 to 2017, and
identifies multiple additional products (e.g., RPS Tools and data files) that were developed along with this overview
document.
Background
Recovery Potential Screening (RPS) is a systematic, comparative method for identifying differences among watersheds
that may influence their relative likelihood to be successfully restored or protected. The RPS approach involves
identifying a group of watersheds to be compared and a specific purpose for comparison, selecting appropriate
indicators in three categories (Ecological, Stressor, Social), calculating index values for the watersheds, and applying the
results in strategic planning and prioritization. EPA developed RPS to provide state water programs and other planners
with a systematic, user-customizable, flexible tool that could help them compare watershed differences in terms of key
environmental and social factors affecting prospects for prioritization and restoration success in a designated geographic
area of interest. The RPS Tool is a custom-coded Excel spreadsheet that performs all RPS calculations and generates RPS
outputs (rank-ordered index tables, graphs and maps). It was developed in 2010 to help users calculate Ecological,
Stressor, Social, and Recovery Potential Integrated index scores for comparing up to thousands of watersheds in a
desktop environment using widely available and familiar software. EPA's RPS Tools are embedded with indicator data
and available for all states and territories.
Kansas Department of Health and Environment (KDHE) requested assistance from EPA in 2014 to further the State's
efforts in prioritizing watersheds for nutrient TMDL development and nonpoint source watershed planning. An RPS
assessment project has been jointly undertaken by EPA's TMDL program, Tetra Tech (EPA contractor), and KDHE. Forty-
six (HUC8) and 241 (HUC12) base, ecological, stressor, and social indicators were measured from national and state data
sources and compiled in a Kansas statewide RPS tool (Excel file). The assessment findings and most figures in this
document are generated by the Kansas RPS Tool.
1
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APPROACH
As a starting point, each state RPS nutrient project was designed to apply recommendations from the EPA Office of
Water 2011 nutrient policy memorandum, which reads in part:
Prioritize watersheds on a statewide basis for nitrogen and phosphorus loading reductions
A. Use best available information to estimate Nitrogen (N) and Phosphorus (P) loadings delivered
to rivers, streams, lakes, reservoirs, etc. in all major watersheds across the state on a Hydrologic
Unit Code (HUC) 8 watershed scale or smaller watershed (or a comparable basis.)
B. Identify major watersheds that individually or collectively account for a substantial portion of
loads (e .g. 80 percent) delivered from urban and/or agriculture sources to waters in a state or
directly delivered to multi-jurisdictional waters.
C. Within each major watershed that has been identified as accounting for the substantial portion of
the load, identify targeted/priority sub-watersheds on a HUC 12 or similar scale to implement
targeted N and P load reduction activities. Prioritization of sub-watersheds should reflect an
evaluation of receiving water problems, public and private drinking water supply impacts, N and P
loadings, opportunity to address high-risk N and P problems, or other related factors.
The two-stage approach implicit in the text above fits well with the RPS Tool, which easily supports comparing HUC8s in
an initial targeting stage and then focuses on screening and comparing HUC12s in a second, implementation-oriented
stage, as illustrated in Figure 1. All of the RPS
nutrient projects utilize the same general two
stage approach (HUC8 or similar larger-scale unit in
Stage 1, HUC12 in Stage2), while encouraging
state-specific customization of the approach in
identifying stage 1 Scenarios, establishing state
approaches for priority watershed identification,
and selection and weighting of the most nutrient-
relevant indicators for use in both stages. In this
project, the data sources and indicators compiled
in the RPS tool, the selections of indicators, choice
of demonstration watersheds, and weighting of
indicators in the nutrient-related screening runs ali
took place collaboratively among KDHE, EPA and
its contractor. Nevertheless, this technical project's
findings and outputs are not meant to represent
decisions or policies of KDHE, EPA, or any other
entity.
Stage 1 Methodology: Defining and Analyzing Nutrient Scenarios
The RPS Tool is most effective in comparing groups of watersheds that have something in common, such as generally
similar landscapes, nutrient sources, impacts and possible management options; for this reason, Stage 1 begins by
engaging the state in defining specific types or groups of watersheds with something in common regarding their primary
nutrient management challenges. The term "Scenario" is used here to describe these sets of shared characteristics that
provide a basis for groups of similar watersheds to be compared and contrasted with one another effectively. Nutrient
management challenges in any given state can be complex and involve multiple Scenarios. Breaking down a large group
of watersheds statewide into smaller, more similar groups and focusing on Scenarios most relevant to each group
enables a narrower focus on nutrient issues and possible solutions.
For Kansas, three Stage 1 Scenarios of interest were initially selected during a series of conference calls between EPA,
KDHE, and Tetra Tech:
2
iffw• RPS Targeting stage 1: priority HUC8s in scenario
(moderate-high loads, good RP prospects)
r
SIH * Implementing stage 2: HUC12s in HUC8
(where to take action within priority 8's)
Tj
i
Rccowry Paternal Socertng fa HjBmns. 9/2014
«•*§
Figure 1. Two-stage conceptual approach utilized in RPS projects for supporting
state nutrient management
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• Scenario 1 - Nutrient TMDLs - Watersheds where nutrients directly impact public water supplies or
downstream waters for nutrient TMDL development
• Scenario 2 - Nonpoint Sources — Watersheds with opportunities to significantly reduce nonpoint source
nutrient loads
• Scenario 3 - Point Sources -- Watersheds for nutrient TMDL development and restoration that are significantly
influenced by NPDES permitted dischargers
Each of these Scenarios are assessed in Stage 1 at a HUC8 watershed scale (Figure 2); continued evaluation occurs in
Stage 2 at the smaller, HUC12 subwatershed scale within selected individual HUC8s.
10250002
02500^df~v ^ 10250003
r ji
^10260001 0260005
.10260004
I
10260012
10260011
15260013 10260014
10260009
-:10265007
10260003
11030007
A10240008
To^TTMi?- 1 "-1O240OO|
,10240005
10250017
,1026001?
1.11
•10260010
0260006
.10270205
1'027-010'i 10270102
10300101,
7 11020009
J
11030005 ,
(11030006 A ^>30004"
_11030008
) 11030005
11030001
1104?005 jVpJl103000
11040007
11040008
^,11060002 ,
11050001 \ L-Jf j
J
Figure 2. Kansas HUC8 watersheds
10270104
1070201 10290101
— , ^ ^ -
,11030002 \ iimnnn7 ) Vry~'10260008
•-< 1,107020,1
1>103001<) -W, s
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11070202;
1031)010 / r-
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m40003^-^^ S J ~~ >11060003xv "i1Q30016 (i 03001
11040002* ~_£? 11040006 C11040008 J \ i \ 1lB300t3\ /'J 11070104
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02
11100102
, 1106000^
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,10290104!,
\T107020^L ,
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11070206
Selection of Stage 1 Indicators
Watersheds within each Scenario are compared to one another with Scenario-specific indicator selections since each
Scenario differs in nutrient source types and exposure pathways. Indicators for Stage 1 need only to be sufficient for
generally comparing watersheds across the state, identifying which watersheds to include in each Scenario, and
revealing major differences in condition and estimated nutrient loading magnitude. Using the RPSTool, Scenario-specific
selections of recovery potential indicators are used to compare Kansas HUC8 watersheds within each Scenario.
Interpreting the Stage 1 Screening Results
Several products are produced by the RPS Tool through the screening runs for each Scenario. Each watershed in a
Scenario screening run receives an Ecological, Stressor, and Social index score and rank. There is also an aggregate
Recovery Potential Integrated (RPI) score and rank for each watershed. Ecological, stressor, and social index values have
a range from 0 to 100. They are each calculated by summing weight-adjusted, normalized indicator values, dividing by
the total weight, and multiplying by 100. RPI Scores are calculated as: [Ecological Index + Social Index + (100 - Stressor
Index)] / 3, and also range from 0 to 100. All four indices are equally important primary products of RPS screening, and
3
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the RPI score as an integrated score should not detract from use of the other three indices when they each provide
unique insights on watershed comparisons.
Among the Ecological, Social and RPI index values, a higher score implies a watershed may be better suited for
restoration. A higher Stressor Index score means higher stressors and thus implies lower relative recovery potential. In
the case of rank order, all four indices (ecological, stressor, social and RPI) are rank ordered so that #1 is always the
'best' rank (i.e., best-suited for recovery).
Although screening data can be exported to GIS for more complex map development, simple maps illustrating the
watersheds in the screening run are also generated within the RPS Tool. These maps can be customized to display a
range of values as color gradients for the watersheds based on any single index or indicator.
Bubble plots are also produced for each screening run. At a glance, these provide a visual tool for comparing the relative
values of ecological, stressor and social indices across all watersheds in the screening run. Individual watersheds can be
labeled or color coded by any single indicator or index for specific display purposes. The bubble plots position
watersheds relative to axes representing the median stressor and ecological scores for every screening run. These axes
split the plots into four quadrants. For example, watersheds in the upper left quadrant have high ecological scores and
low stressor scores. The size of the symbol indicates the social score.
The scores of any watershed in a screening run provide relative information for supporting the discussion on recovery
potential and nutrient management strategies and alternatives. Whereas screening results make no claim of predicting
the actual recovery potential or protection outlook for a watershed (e.g., a restorable/unrestorable threshold),
considering watersheds' relative scores may help guide restoration decisions or actions by revealing either better
candidates for recovery, or watersheds that would require much more effort than others. The most common approach
to applying RPS results in Stage 1 is to focus on those watersheds that have moderate to high pollutant loading or other
impact, but still score well on ecological or social indexes related to better recovery prospects.
STAGE 1 ANALYSIS AND RESULTS
Although the three Scenarios represent distinctly different settings of how nutrient issues affect Kansas watersheds, the
Scenarios are not mutually exclusive. An individual watershed may in fact be included in all three Scenarios if it has the
appropriate qualifying characteristics. In such a case, that watershed may be part of multiple strategic planning
approaches tailored to each Scenario's traits and needs. Many of Kansas' 90 HUC8s are included in more than one of the
three Scenarios. Scenario 1 includes 71 HUC8s and Scenario 3 includes 57 of the State's 90 HUC8s. Scenario 2 includes
every HUC8 in the state. In all Scenarios, different sets of indicators specific to the Scenario, its nutrient sources and
impacts are used in the screenings, and small numbers of high-scoring HUC8s per Scenario are identified from the
analysis.
Scenario 1 - Nutrient TMDLs -- Watersheds where nutrients may directly impact public water supplies or downstream
waters for nutrient TMDL development
Watersheds in this Scenario either have nutrient impairments and/or have a public drinking water supply that is
potentially impacted by nutrients. KDHE has indicated that generally the State's nutrient impairments are primarily
driven by phosphorus loading, therefore stressors in these watersheds include wastewater discharges, population, and
phosphorus yield. Watersheds with nutrient impairments or potential public water supply effects include 71 of 90 HUC8
watersheds in the state.
Scenario 1-specific indicators are provided in Table 11; Attachment 2 includes indicator descriptions. Ecological
indicators focus on watershed and stream assimilative capacity measured as flow and biotic integrity. Stressor indicators
primarily represent nutrient sources. Social indicators focus on watersheds that serve as public water supplies and
consider the distance to the state boundary. A copy of the RPS Tool populated with this Scenario's screening results is
among project deliverables, and the primary findings are summarized below.
4
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Table 1. Stage 1 HPS indicator selections and weights (wt) for screening and comparing HUC8 watersheds for Scenario 1. See Attachment 2 for
indicator definitions. Those indicators with a * are derived from state-specific datasets.
Ecological Indicators
wt
Stressor Indicators
wt
Social Indicators
wt
% natural cover in watershed (N-
Index2)
1
% agriculture (2006) in watershed
1
Nutrient TMDL count
1
% natural cover in hydrologically
connected zone (N-lndex2)
1
% urban (2006) in watershed
1
Distance to outlet of the state inverse*
1
National Fish Habitat Partnership
Habitat Condition Index
1
% population growth in watershed (2000-
2010)*
1
Total public drinking water system
(PWS) project score*
1
Flow (cfs) generated in watershed*
1
Phosphorus yield (SPARROW incremental)
1
Critical watershed class score*
1
IBI Indicator (weighted average IBI
score)*
1
Median TP concentration for streams in
watershed*
1
% watershed streamlength 303d-listed
nutrients
1
% watershed waterbody area 303d-listed
nutrients
1
Recovery Potential Integrated (RPI) scores for Scenario 1 are displayed in map form in Figure 3, showing the relative
geographic distribution of the Scenario. Higher ranking watersheds are found in the southern and eastern parts of the
state; the highest ranking watersheds include Neosho Headwaters (11070201), Kaw Lake (11060001), and Fall (11070102).
These and other high ranking watersheds also correspond with the Flint Hills ecoregion (Figure 4), which notably contains
the largest remaining intact tallgrass prairie in the Great Plains:
• Lower Walnut River (11030018)
• Kaw Lake (11060001)
• Upper Verdigris (11070101)
• Fall (11070102)
• Elk (11070104)
• Caney(11070106)
• Neosho Headwaters (11070201)
• Lower Cottonwood (11070203)
Although these areas are ecologically higher-scoring, there are also nutrient impairments in all of the watersheds with
the exception of Upper Verdigris and Fall (Figure 5), although both of these watersheds are part of a public drinking
water system project area.
5
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Figure 3. Scenario 1 watershed ranking by RPI score (darker blue implies better for restoration)
Legend
RPI Score
35.73 -
42.72
42.73 -
45.55
45.56 -
47.54
47.55 -
50.54
50.55 -
53.84
53.85 -
57.20
57.21 -
59.62
59.63 -
62.35
62.36 -
66.35
66.36 -
71.73
Not Analyzed / No Data
/ il . i'.'lil l's
Great Plain-
I WW I
itfiwesl Table
Central Oklahoma/ Ozark
Texas Plains Plateau
Figure 4. Kansas ecoregions
fcOMC
* " j'WiW
IMpaail IfcaA*
» J
JB* 0 V *3 ¦•KOji aa
6
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Nutrient Impaired Segment Count For HUC8 Watersheds
Legend
Nutrient Impaired Segment Count
0.00 - 0.01
0.02 - 5.00
5.01 - 10.00
10.01 - 20.00
20.01 - 70.00
Not Analyzed / No Data
Figure 5. Number of nutrient impairments per HUC8. Yellow-outlined HUCs have nutrient impaired segment counts but also scored among the top
three deciles of RPI score; darker green HUCs with yellow outlines may be good candidates for addressing significant nutrient impairments in
v
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Neosho Headwaters
Lower Salt Fork Arkansas
Lower Cottonwood
so \
Kaw Lake-i
Upper Cimarron -A
70 \\
Fall -v \
Upper Verdigris-
¦K 50
Upper Marais Des Cygnes
Lower Walnut River
Median Stream TP
Concentration in WS (INSTATE)
I I 0.03-0.09
CH 0.1-0,15
I 0.16-0.22
I 0.23 - 0.56
~ No Data
40 50 60 70 80 90 100
Stressor Index
Note: Circle size increases with Social Index score
Figure 6. Bubble plot for Kansas Scenario 1 watersheds color-sorted by median phosphorus concentration; watersheds that rank in the top 10 by RPI
score are labeled. Axes are set to median Ecological Index and Stressor Index scores.
Maps of Ecological and Stressor index scores for Scenario 1 are displayed in Figure 7 and Figure 8. The Ecological Index
map shows that high Ecological Index scores are mostly found in the eastern part of the state, which corresponds to
watersheds with higher amounts of natural areas and tend to be located in and near the Flint Hills ecoregion (Figure 4).
Lower Stressor Index scores are also found in the southeastern part of the state, also corresponding with the Flint Hills
ecoregion. HUC8s with higher Stressor Index scores correspond to developed areas in the northeast near Kansas City
and Topeka and in the south central near Wichita. Note that color intensity of these different indices is always 'the
darker blue the better.'
Table3 contains Ecological, Stressor, Social, and RPI scores for all HUC8 watersheds, in order of descending RPI score and
color-coded by quartile per RPI score. This tabular format is another option for presentation of Stage 1 results that can
be used to compare and contrast HUC8 watersheds. In interpreting this table, preferred HUC8 watersheds for nutrient
management do not necessarily have to be those with the highest RPI scores but instead could consider one or more of
the component index scores. For example, a watershed such as the Upper Walnut River (11030017) with poor Stressor
Index scores may be a good restoration priority candidate because of high its Ecological Index score and moderate Social
Index score; this would not be revealed by examining the RPI score alone.
8
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I
Legend
Ecological Index
17.58 - 24.28
24.29 - 28.30
28.31 - 30.70
30.71 - 33.58
33.59 - 35.80
35.81 - 39.74
39.75 - 43.58
43.59 - 50.70
50.71 - 56.04
56.05 - 66.70
Not Analyzed / No Data
Figure 7. Ecological ranking (darker blue implies better for restoration)
Legend
Stressor Index
313 - 7.36
7 37 - 11.97
11.98 - 16.19
15.20 - 17.14
17.15 - 19.31
19.32 - 22.33
22.34 - 24.62
24.63 - 28.16
28.17 - 31.14
31.15 - 49.46
Not Analyzed / No Data
Figure 8. Stressor ranking (darker blue implies better for restoration)
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Table 3. Index and RPI scores for Scenario 1. HUC8 watersheds are ordered by RPI score. Cells in each column are shaded by quartile according to
rank for each of the four indices (black = 76 -100th percentile; dark gray = 51-75th percentile; light gray = 26-50th percentile; white = 0-25th
percentile).
Social
Index
Social
Rank
60.03
18
54.10
24
54.20
23
Watershed
ID
Ecological
Index
Ecological
Rank
Stressor
Index
Watershed Name
Neosho Headwaters
11070201
Kaw Lake
11060001
11070102
Upper Marais Des Cygnes
10290101
Lower Wa nut River
11030018
Upper Verdigris
11070101
11040002
Upper Cimarron
11070106
Lower Cottonwood
11070203
Lower Sa t Fork Arkansas
11060004
11070104
10270104
Lower Kansas, Kansas
34.12
Upper Cimarron-Bluff
11040008
10290102
Lower Marais Des Cygnes
30.86
25.67
Midd e Kansas
10270102
22.61
56.83
10270101
Upper Kansas
22.16
50.47
Middle Neosho
11070205
40.26
23.76
61.66
10290104
Marmaton
30.50
17.57
61.49
North Fork Ninnescah
11030014
13.80
60.87
Lower Big Blue
10270205
45.36
26.90
64.00 12
60.82
Upper Walnut River
11030017
31.49
58.23
60.35
Medicine Lodge
11060003
43.58
41.97
59.63
South Fork Big Nemaha
10240007
31.64
20.51
59.30
Spring
11070207
43.24
31.14
65.53 10
59.21
Middle Verdigris
11070103
39.74
15.31
52.97
59.13
Independence-Sugar
10240011
28.46
20.89
59.04
Upper Cottonwood
11070202
32.10
58.86
Lower Little Blue
10270207
34.26
23.67
62.85 13
62.58 14
57.81
Tarkio-Wo f
10240005
28.66
19.63
57.20
Lower Smoky Hill
10260008
40.30
17.86
48.80
57.08
Chikaskia
11060005
38.34
19.31
56.71
Little Osage
10290103
30.98
29.59
65.50 11
55.63
Upper Republican
10250004
34.73
39.23
55.20
Upper Neosho
11070204
43.38
21.53
43.13
54.99
Upper Cimarron-Liberal
11040006
47.00
29.49
44.97
54.16
Ratt esnake
11030009
44.64
30.47
53.84
Smoky Hill Headwaters
10260001
48.54
17.33
52.84
Midd e Arkansas-S ate
11030013
35.24
49.46
52.83
Big Nemaha
10240008
18.88
27.26
65.58 8
61.70 15
52.40
Lower Republican
10250017
33.44
38.61
52.18
Ninnescah
11030016
28.68
22.59
49.23
51.78
South Fork Ninnescah
11030015
40.34
15.49
29.63
51.50
10
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Watershed
ID
Watershed Name
Ecological
Index
Ecological
Rank
Stressor
Index
Stressor
Rank
Social
Index
Social
Rank
RPI
Score
RPI
Rank
10250016
Middle Republican
36.62
34
19.16
34
34.17
45
50.54
43
10270103
Delaware
20.84
69
27.31
56
57.38
20
50.30
44
10260006
Middle Smoky Hill
33.58
43
13.73
19
30.03
50
49.96
45
11040007
Crooked
26.34
60
17.14
29
40.33
42
49.84
46
10260003
Upper Smoky Hill
37.02
33
9.26
11
17.33
65
48.36
47
11030012
Little Arkansas
35.34
37
44.67
70
52.85
26
47.84
48
10260004
Ladder
38.08
31
16.88
27
21.63
58
47.61
49
11030010
Gar-Peace
35.80
36
22.24
42
29.07
52
47.54
50
10260007
Big
27.14
58
30.41
61
44.93
37
47.22
51
10260013
Upper South Fork Solomon
40.64
25
8.93
10
8.53
71
46.75
52
11040003
North Fork Cimarron
28.30
57
18.95
32
30.70
48
46.68
53
10250015
Prairie Dog
24.18
65
35.04
66
50.60
30
46.58
54
10260015
Solomon
29.94
53
24.49
49
32.77
46
46.07
55
11030001
Middle Arkansas-Lake McKinney
31.08
47
16.86
26
23.67
56
45.96
56
10260002
North Fork Smoky Hill
30.36
52
12.73
16
19.03
63
45.55
57
10260014
Lower South Fork Solomon
30.70
50
15.19
22
20.28
60
45.26
58
10250011
Lower Sappa
23.52
66
27.30
55
38.70
44
44.97
59
11030004
Coon-Pickerel
31.20
46
22.33
43
23.00
57
43.96
60
10260010
Lower Saline
36.34
35
16.94
28
12.07
69
43.82
61
10260011
Upper North Fork Solomon
34.82
39
19.31
35
13.98
67
43.16
62
10250010
Upper Sappa
20.90
68
18.98
33
27.03
53
42.98
63
11030006
Buckner
26.82
59
25.43
51
26.77
54
42.72
64
10260009
Upper Saline
37.20
32
23.36
46
13.73
68
42.53
65
10260012
Lower North Fork Solomon
24.94
62
28.16
57
19.10
61
38.63
66
11030005
Pawnee
22.58
67
30.16
60
21.20
59
37.87
67
11030003
Arkansas-Dodge City
17.58
71
24.62
50
19.07
62
37.34
68
11030011
Cow
24.40
63
37.00
68
24.30
55
37.23
69
11030008
Lower Walnut Creek
24.28
64
30.81
63
18.13
64
37.20
70
10260005
Hackberry
26.10
61
30.51
62
11.63
70
35.74
71
Scenario 2 - Nonpoint Sources - Watersheds with opportunities to significantly reduce nonpoint source nutrient loads
This Scenario includes HUC8 watersheds that are of higher interest for nonpoint source nutrient management efforts.
The analysis will screen and compare nonpoint source-impacted HUC8 watersheds that could be targeted for
phosphorus reductions from nonpoint sources. Agricultural land uses, animal agriculture activities, erosion, and septic
systems are potential stressors in these watersheds. All of Kansas' HUC8 watersheds are screened for this Scenario.
Scenario-specific indicators are provided in Table 2; Attachment 2 includes indicator descriptions.
11
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Table 2. Stage 1 RPS indicator selections and weights (wt) for screening and comparing HUC8 watersheds for Scenario 2. See Attachment 2 for
indicator definitions. Those indicators with a * are derived from state-specific datasets.
Ecological Indicators
wt
Stressor Indicators
wt
Social Indicators
wt
% natural cover in watershed (N-
Index2)
1
% agriculture (2006) in watershed
1
Nutrient TMDL count
1
% natural cover in hydrologicaily
Distance to outlet of the state
connected zone (N-index2)
1
Number of dams in watershed
1
inverse*
1
National Fish Habitat Partnership
Total public drinking water system
Habitat Condition Index
1
Watershed mean soil erodibility
1
(PWS) project score*
1
Hydrologicaily connected zone mean soil
Flow (cfs) generated in watershed*
1
erodibility
1
Critical watershed class score*
1
IBI Indicator (weighted average IBI
score)*
1
Phosphorus yield (SPARROW incremental)
1
Median TP concentration for streams in
watershed*
1
% watershed streamlength 303d-!isted
nutrients
1
% watershed waterbody area 303d-listed
nutrients
1
RPI scores for Scenario 2 are displayed in map format in Figure 9. North Fork Republican (10250002), Neosho
Headwaters (11070201), Lower Cimarron-Eagle Chief (11050001), Upper Cimarron (11040002), and Lower Salt Fork
Arkansas (11060004) HUC8 watersheds are the highest ranked watersheds for recovery potential based on RPI score.
Distribution of the higher-scoring Scenario 2 watersheds around the state roughly resembles that of Scenario 1, despite
their different themes and indicators selected.
Legend
RPI Score
30.49 - 36.49
36.50 - 39.37
39.38 - 41.32
41.33 - 45.84
45.85 - 49.98
49.99 - 52.94
52.95 - 55.29
55.30 - 59.07
59.08 - 61.27
61.28 - 65.49
Not Analyzed/No Data
The bubble plot for Scenario 2 (Figure 10) reflects the relative value differences among HUC8 watersheds in Ecological,
Stressor and Social index scores by each bubble's size and position on the graph, also showing how these compare to
region-wide Ecological and Stressor index medians (the horizontal and vertical median lines respectively). Figure 11 color
sorts the bubble plot to show number of nutrient impairments in each watershed. Four of the top ten highest RPI ranked
watersheds do not have any identified nutrient impairments (North Fork Republican, Lower Cimarron-Eagle Chief, Fall,
and Lower Salt Fork Arkansas); these may be of less interest for nutrient management, but could be candidates for
protection strategies. Maps of Ecological and Stressor Index scores for Scenario 2 are displayed in Figure 12 and Figure 13.
HUC8 watersheds with high Ecological Index scores are in the east-central part of the state; low Stressor Index scores are
found in the southern part of the state.
12
-------
¦
a-9.9
~
9.91-18.8
~
18.81-27.7
~
27.71- 36.6
~
36.61-45.5
u
45.51-54.4
~
54.41-63.3
n
63.31-72.2
~
72.21-81.1
~
81.11-90
40 so
Stressor Index
Note: Circle size increases with Social Index score
Figure 10. Bubble plot for Scenario 2 HUC8 watersheds color-coded by RPI rank. Axes are set to median Ecological and Stressor Index scores.
Neosho Headwaters
Lower Walnut River
Upper Marais Des Cygries
Kaw Lake
Upper Cimarron
\
Caney -x
Nutrient Impaired Segment
Count
¦
0-0
~
0.01 -1
~
1.01-10
~
10.01-25
~
25.01-70
Stressor Index
Note: Circle size increases with Social Index score
Figure 11. Bubble plot for Scenario 2 HUC8 watersheds. This plot color-sorts the watersheds by number of nutrient impairments; labeled watersheds
have top ranking RPI scores and at least some nutrient impairments. Axes are set to median Ecological and Stressor Index scores.
13
-------
Figure 12. Scenario 2 Ecological Index (darker blue implies better for restoration)
Legend
Ecological Index
9.07 - 22.97
22.98 - 25.64
25.65 - 28.72
28.73 - 31.50
31.51 - 34.35
34.36 - 38.30
38.31 - 42.21
42.22 - 48.50
48.51 - 52.25
52.26 - 74.85
Not Analyzed / No Data
Figure 13. Scenario 2 Stressor Index (darker blue implies better for restoration)
Legend
Stressor Index
9.21 - 19.22
19.23 - 24.59
24.60 - 28.65
28.66 - 31.17
31.18 - 34.21
34.22 - 36.64
36.65 - 39.52
39.53 - 42.96
42.97 - 46.37
46.38 - 52.68
Not Analyzed / No Data
Table 3 contains Ecological, Stressor, Social, and RPI scores for Scenario 2, in order of descending RPI score and color-
coded by quartile per RPI score. This tabular format is another option for presentation of Stage 1 results that can be
used to compare and identify HUC8 watersheds for Scenario 2 nutrient management efforts. Of interest, Lower Kansas,
Kansas has a much higher Stressor Index score, however it also ranks very high for Social Index, which generates an
overall high RPI. Conversely, Upper Arkansas-John Martin Reservoir is ranked highest for Ecological Index and has a good
Stressor Index score, however a very low Social Index score moderates the overall RPI ranking for this watershed (ranked
24 out of 90).
14
-------
Table 3. Index and RPI scores for Scenario 2. HUC8 watersheds are ordered by RPI score. Cells in each column are shaded by quartile according to
rank for each of the four indices (black = 76 -100th percentile; dark gray = 51-75th percentile; light gray = 26-50th percentile; white = 0-25th
percentile).
Ecological
Index
Ecological
Rank
Social
Index
Social
Rank
Stressor
Index
Higher Index is
Better
Lower Index is
Better
Higher Index is
Better
Higher Score is
Better
Watershed ID
Watershed Name
North Fork Republican
10250002
Neosho Headwaters
11070201
Lower Cimarron-Eagle Chief
11050001
11040002
Upper Cimarron
Lower Salt Fork Arkansas
11060004
Upper Marais Des Cygnes
10290101
11070102
54.37
Kaw Lake
11060001
54.33
Lower Walnut River
11030018
11070106
10270104
Lower Kansas, Kansas
33.92
47.88
Lower Marais Des Cygnes
10290102
30.52
33.99
Upper Cimarron-Bluff
11040008
50.57
Upper Verdigris
11070101
51.80
Upper Salt Fork Arkansas
11060002
43.87
North Fork Ninnescah
11030014
46.90
Midd e Beaver
11100102
50.63
11070104
51.17
10270101
Upper Kansas
27.56
50.63
Arikaree
10250001
41.74
28.43
Midd e Kansas
10270102
34.41
57.00
57.83
Middle Neosho
11070205
39.70
36.19
57.47
Upper Walnut River
11030017
37.61
57.36
Upper Arkansas-John Martin
Reservoir
11020009
18.97
57.15
Lower Cottonwood
11070203
30.90
41.10
56.74
10290104
Marmaton
29.92
33.85
55.94
Spring
11070207
43.22
41.86
55.69
Middle Verdigris
11070103
38.90
27.24
53.70
55.12
Midd e Arkansas-S ate
11030013
34.48
42.78
54.89
Medicine Lodge
11060003
41.10
42.87
54.80
Upper Cimarron-Liberal
11040006
43.60
45.87
54.36
Lower Big Blue
10270205
43.62
45.76
53.99
Upper Cottonwood
11070202
32.67
53.73
Chikaskia
11060005
37.34
51.77
53.72
Rattlesnake
11030009
41.82
31.37
53.56
South Fork Big Nemaha
10240007
30.52
53.32
South Fork Republican
10250003
38.10
43.23
52.69
Independence-Sugar
10240011
27.96
39.78
52.65
Lake 0 The Cherokees
11070206
26.78
34.69
52.62
15
-------
Ecological
Index
Ecological
Rank
Stressor
Index
Stressor
Rank
Social
Index
Social
Rank
RPI
Score
RPI
Rank
Watershed ID
Watershed Name
Higher Index is
Better
Lower Index is
Better
Higher Index is
Better
Higher Score is
Better
10260008
Lower Smoky Hill
38.72
35
30.46
34
49.50
41
52.59
40
10270207
Lower Little Blue
33.06
51
40.20
67
62.88
15
51.91
41
10240005
Tarkio-Wolf
28.02
65
36.95
56
62.85
16
51.31
42
10290103
Little Osage
30.26
58
42.71
70
65.67
13
51.07
43
11070204
Upper Neosho
42.08
28
32.85
40
43.43
47
50.89
44
11030015
South Fork Ninnescah
38.60
36
18.23
9
30.67
62
50.35
45
11030016
Ninnescah
28.06
64
28.95
31
49.73
40
49.61
46
11030010
Gar-Peace
34.04
47
20.34
12
30.13
64
47.95
47
10250009
Harlan County Reservoir
42.50
27
46.03
80
47.35
42
47.94
48
10250004
Upper Republican
31.88
54
28.74
28
40.20
54
47.78
49
11030012
Little Arkansas
34.22
46
44.98
76
53.45
30
47.57
50
10300101
Lower Missouri-Crooked
17.64
87
43.38
75
68.20
7
47.49
51
10250017
Lower Republican
32.50
52
52.21
89
62.03
17
47.44
52
10240008
Big Nemaha
18.94
86
43.29
74
65.73
11
47.13
53
10250014
Beaver
33.88
49
34.36
47
39.20
56
46.24
54
11040007
Crooked
25.68
72
31.39
38
41.40
51
45.23
55
10260001
Smoky Hill Headwaters
44.88
23
28.93
30
17.80
82
44.59
56
10250016
Middle Republican
35.10
42
38.95
61
34.67
57
43.61
57
10260006
Middle Smoky Hill
32.28
53
34.41
48
30.58
63
42.81
58
10270103
Delaware
21.12
84
51.00
88
57.43
23
42.52
59
11040004
Sand Arroyo
30.93
55
33.00
41
28.90
66
42.28
60
11030004
Coon-Pickerel
29.84
60
28.15
26
23.90
72
41.86
61
10260007
Big
26.20
70
46.36
81
45.03
45
41.62
62
11030001
Middle Arkansas-Lake
McKinney
29.38
61
29.51
32
24.53
71
41.47
63
10270206
Upper Little Blue
9.08
90
37.04
57
50.90
36
40.98
64
11040003
North Fork Cimarron
26.03
71
35.24
52
31.60
60
40.79
65
10250015
Prairie Dog
23.20
80
52.68
90
51.48
33
40.67
66
10260003
Upper Smoky Hill
34.74
43
31.35
37
17.88
81
40.42
67
10290108
South Grand
10.88
89
32.79
39
42.47
50
40.19
68
10260013
Upper South Fork Solomon
38.94
33
28.90
29
9.67
89
39.90
69
10250012
South Fork Beaver
24.88
76
34.16
45
28.30
67
39.67
70
10260004
Ladder
36.18
39
39.67
64
22.03
74
39.51
71
10250013
Little Beaver
23.08
81
34.59
50
30.00
65
39.50
72
10260015
Solomon
29.00
63
45.86
79
33.53
58
38.89
73
11040005
Bear
36.17
40
36.67
55
15.40
83
38.30
74
10250011
Lower Sappa
22.00
82
47.53
84
39.70
55
38.06
75
11030003
Arkansas-Dodge City
17.06
88
24.04
18
20.10
76
37.71
76
10260002
North Fork Smoky Hill
27.76
67
34.26
46
19.50
78
37.67
77
10260010
Lower Saline
34.64
44
36.61
54
13.10
86
37.04
78
10260014
Lower South Fork Solomon
29.32
62
39.35
62
20.90
75
36.96
79
11030006
Buckner
25.50
73
42.91
72
27.63
69
36.74
80
16
-------
Watershed ID
Watershed Name
Ecological
Index
Ecological
Rank
Stressor
Index
Stressor
Rank
Social
Index
Social
Rank
RPI
Score
RPI
Rank
Higher Index is
Better
Lower Index is
Better
Higher Index is
Better
Higher Score is
Better
10250010
Upper Sappa
19.53
85
38.04
60
28.07
68
36.52
81
10260011
Upper North Fork Solomon
33.50
50
39.45
63
14.65
85
36.23
82
10260009
Upper Saline
35.30
41
43.16
73
14.70
84
35.61
83
11030011
Cow
23.80
78
46.44
82
25.43
70
34.27
84
11030002
Whitewoman
25.48
74
41.09
68
11.87
88
32.09
85
11030008
Lower Walnut Creek
23.28
79
47.21
83
19.33
79
31.80
86
11030007
Upper Walnut Creek
27.00
68
39.89
66
7.40
90
31.50
87
10260012
Lower North Fork Solomon
24.18
77
49.88
86
19.78
77
31.36
88
11030005
Pawnee
21.50
83
50.28
87
22.17
73
31.13
89
10260005
Hackberry
24.94
75
45.76
77
12.30
87
30.49
90
Delaware and Little Arkansas are of particular interest to the State, thus a summary of the rankings for these watersheds
is provided in Table 4. Both of these watersheds have high levels of stressors, but also rank very well in the Social Index.
Little Arkansas ranks much better than Delaware for Ecological Index. Figure 14 shows where on the bubble plot these
watersheds plot.
Table 4. Rankings for two watersheds of interest in Kansas
Ecological
Index
Ecological
Rank
Stressor
Index
Stressor
Rank
Social
Index
Social
Rank
RPI Score
RPI Rank
Watershed ID
Watershed Name
Higher Index is
Better
Lower Index is
Better
Higher Index is
Better
Higher Score is Better
11030012
Little Arkansas
34.22
46
44.98
76
53.45
30
47.57
50
10270103
Delaware
21.12
84
51.00
88
57.43
23
42.52
59
17
-------
100
90
Stressor Index
Note; Circle size increases with Social Index score
Figure 14. Bubble plot for Scenario 2 HUC8 watersheds. This plot highlights the location of Little Arkansas and Delaware watersheds. Axes are set to
median Ecological and Stressor Index scores
Scenario 3 - Point Sources - Watersheds for nutrient TMDL development and restoration that are significantly
influenced by NPDES permitted dischargers
Watersheds in this Scenario contain point sources (wastewater, stormwater, or animal feeding operations) and are
screened and compared for targeted nutrient TMDL development and restoration. These watersheds include
wastewater facilities discharging greater than 0.5 million gallons per day (MGD), at least one regulated MS4, and/or
contain at least 23 animal feeding operations (the statewide median number of animal feeding operations per HUC8). A
copy of the RPS Tool populated with this Scenario's screening results is among project deliverables.
The goal of this analysis is to rank watersheds that are impacted by moderate to high point source loadings. In this case,
the focus is on phosphorus reduction. The following 57 of Kansas' 90 HUC8 watersheds are part of this Scenario:
Tarkio-Wolf
South Fork Big Nemaha
Big Nemaha
Independence-Sugar
Prairie Dog
Lower Republican
Ladder
Middle Smoky Hill
Big
Lower Smoky Hill
Upper Saline
Lower Saline
Delaware
Lower Kansas, Kansas
Lower Big Blue
Lower Little Blue
Upper Marais Des Cygnes
Lower Marais Des Cygnes
Marmaton
Lower Missouri-Crooked
Middle Arkansas-Lake
McKinney
Whitewoman
Arkansas-Dodge City
Coon-Pickerel
Pawnee
North Fork Ninnescah
South Fork Ninnescah
Ninnescah
Upper Walnut River
Lower Walnut River
North Fork Cimarron
Upper Cimarron-Liberal
Crooked
Kaw Lake
Chikaskia
Upper Verdigris
Middle Verdigris
18
Little Arkansas
Delaware
-------
• Upper North Fork Solomon
• Lower North Fork Solomon
• Upper South Fork Solomon
• Lower South Fork Solomon
• Solomon
• Upper Kansas
• Middle Kansas
• Buckner
• Lower Walnut Creek
• Rattlesnake
• Gar-Peace
• Cow
• Little Arkansas
• Middle Arkansas-Slate
• Neosho Headwaters
• Upper Cottonwood
• Lower Cottonwood
• Upper Neosho
• Middle Neosho
• Spring
Scenario-specific indictors are provided in Table 5; Attachment 2 includes indicator descriptions. Ecological indicators
focus on the assimilative capacity of the watershed represented by higher average flows and the presence of biota that
indicate good water quality. Stressor indicators focus on urban area, population growth indicating increases in wastewater
loads, wastewater discharges, and watershed nutrient loads. Social indicators focus on regulated areas such as MS4s.
Table 5. Stage 1 HPS indicator selections and weights for screening and comparing HUC8 watersheds for Scenario 3. See Attachment 2 for indicator
definitions. Those indicators with a * are derived from state-specific datasets
Ecological Indicators
wt
Stressor Indicators
wt
Social Indicators
wt
% natural cover in watershed (N-
% urban (2006) in hydrologically connected
Index2)
1
zone
1
Nutrient TMDL count
1
% natural cover in hydrologically
connected zone (N-lndex2)
1
% urban (2006) in watershed
1
% MS4 in watershed*
1
National Fish Habitat Partnership
Count of animal feeding operations in
Habitat Condition Index
1
watershed*
1
% population growth in watershed (2000-
Flow (cfs) generated in watershed*
1
2010)*
1
IBI Indicator (weighted average IBI
score)*
1
Phosphorus yield (SPARROW incremental)
1
Cumulative design flow discharge in MGD of
major and mid minor plants in watershed*
1
% watershed streamlength 303d-listed
nutrients
% watershed waterbody area 303d-listed
nutrients
RPI scores for Scenario 3 are displayed in map format in Figure 15. RPI scores are a composite of scores for the Ecological,
Stressor, and Social Indices based on the Scenario's indicator selection and weighting. The highest ranking watersheds
include Neosho Headwaters (11070201), Upper Marais Des Cygnes (10290101), Upper Verdigris (11070101), Middle
Neosho (11070205) and Lower Walnut River (11030018).
19
-------
I
Legend
RPI Score
35.58 - 39.36
39.37 - 41.64
41.65 - 42.76
42.77 - 43.56
43.57 - 45.88
45.89 - 47.08
47.09 - 48.91
48.92 - 50.12
50.13 - 52.75
52.76 - 60.34
Not Analyzed / No Data
Figure 15. Scenario 3 RPI scores (darker blue implies better for restoration)
The bubble plot in Figure 16 displays the relative value differences among HUC8 watersheds in Ecological, Stressor and
Social Index scores by each bubble's size and position on the graph, also showing how these compare to medians (the
horizontal and vertical median lines). Further, this figure presents the highest RPI-scoring watersheds in the state. It is
unusual to see very good and very poor index scores occurring in the same watershed, but that is evident in several cases.
Notably, one of the highest Social Index watersheds also has one of the poorest Stressor Index scores (Lower Kansas,
Kansas). Figure 17 sorts all of the Scenario 3 watersheds by median total phosphorus concentration. Of the highest overall
ranking watersheds, Lower Kansas, Kansas has a very high median concentration of phosphorus and is ranked the second
highest for Social Index. Despite scoring poorly on the Stressor Index, watersheds with mixed traits often deserve
consideration for management efforts because their more positive ecological setting or social context may enable more
progress in loading reduction than other watersheds that may have scored poorly on all indices.
20
-------
100
Kaw Lake
Neosho Headwaters
w
Upper Verdigris
r Lower Cottonwood
Lower Walnut River
North Fork Ninnescah
Upper Marais Des Cygnes
Rattlesnake
X
4i
"O
C
- Lower Kansas, Kansas
Middle Neosho
UJ
SO
0
10
20
30
40
60
70
80
90
100
Stressor Index
Note: Circle size increases with Social Index score
Figure 16. Bubble plot for Scenario 3 watersheds. This plot highlights the top 10 watersheds based on RP! scores (green bubbles with labels). Axes
are set to median Ecological and Stressor Index scores.
Median Stream TP
Concentration in WS (INSTATE)
EH 0.05-0.1
CD 0.11-0.14
I] 0.15-0.16
I 0.17-0.21
1 0,22-0.33
I 0.34 -0.56
m
o
1 i No Data
o
O
C
3 O
#
0V3
•
O
• 0
1
^0
•
©
• ©
•
0 10 20 30 40 50 60 70 80 90 100
Stressor Index
Note: Circle size increases with Social Index score
Figure 17. Bubble plot for Scenario 3 watersheds with color-coding based on median total phosphorus concentration in watershed
21
-------
Maps of Ecological and Stressor Index scores for Scenario 3 are displayed in Figure 18 and Figure 19. HUC8 watersheds
with high Ecological Index scores are focused in the eastern part of the State; watersheds with high Stressor Index scores
are found in the central and northeastern part of the state. A series of maps showing select single indicator values are also
provided (Figure 20, Figure 21, and Figure 22). Viewing indicators individually in map or bubble plot form is easily done in
the RPS Tool without changing the screening parameters, and images of these single indicator maps or plots can be saved
for later use. Upper Kansas (10270101) presents an interesting example of a watershed that has a moderate overall RPI
ranking (ranked 16 out of 57), but with a very high Ecological Index score and a very high Stressor Index score. This
watershed tends to stand out in the indicator specific maps, showing a very high percentage of natural cover and a high
percentage of population growth.
Table 6 contains Ecological, Stressor, Social, and RPI scores for Scenario 3, in order of descending RPI score and color-
coded by quartile per RPI score. This tabular format is another option for presentation of Stage 1 results that can be
used to compare and identify HUC8 watersheds for Scenario 3 nutrient management efforts. The tabular format is
especially effective at revealing where HUCs with otherwise 'middle of the pack' overall scores may have very positive
Ecological or Social Index scores, and where otherwise high scoring HUCs may have very poor Stressor or other index
scores that may present a greater challenge.
Legend
Ecological Index
14.32 - 21.58
21.59 - 26.29
26.30 - 29.70
29.71 - 32.10
32.11 - 34.40
34.41 - 37.91
37.92 - 41.56
41.57 - 46.92
46.93 - 56.68
56.69 - 68.10
Not Analyzed / No Data
Figure 18. Scenario 3 Ecological Index (darker blue implies better for restoration)
22
-------
I
Figure 19. Scenario 3 Stressor Index (darker blue implies better for restoration)
Legend
Stressor Index
2.00 - 4.51
4.52 - 6.56
6.57 - 7.89
7.90 - 9.04
9.05 - 12.11
12.12 - 12.86
12.87 - 15.22
15.23 - 17.06
17.07 - 26.44
26.45 - 43.74
Not Analyzed / No Data
Legend
Weighted-Average IBI Score (INSTATE)
3Z| 50 86 - 61.07
61.08 - 67.34
67.35 - 68.57
68.58 - 71.16
71.17 - 74 46
74.47 - 76.43
B 76.44 - 80.05
80.06 - 84.30
84.31 - 86.35
86.36 - 94.65
Not Analyzed / No Data
23
-------
Legend
% Natural Cover, N-index2 (2006) in
Watershed
10.58 - 18.76
18.77 - 22.58
22.59 - 26.23
26.24 - 28.20
28.21 - 36.96
36.97 - 42.09
42.10 - 46.76
46.77 - 51.94
51.95 - 60.61
60.62 - 80.14
Not Analyzed / No Data
Figure 20. Select ecological indicators (IBI and natural cover)
Legend
Count of Animal Feeding Operations in
WS (INSTATE)
3.00 - 11.40
11.41 - 23.00
23.01 - 26.00
26.01 - 30.40
30.41 - 36.00
36.01 - 41.20
8 41.21 - 50.20
50.21 - 66.40
66.41 - 94.60
94.61 - 186.00
Not Analyzed / No Data
Legend
% Population Growth in WS (2000-2010)
(INSTATE)
0.00 - 5.10
5.11 - 10.20
10.21 - 15.30
15.31 - 20.41
Not Analyzed / No Data
24
-------
Legend
Design Flow of Major/Minor Plants in
(INSTATE)
0.00 - 18.59
18.60 - 37.18
37.19 - 55.77
55.78 - 74.37
Not Analyzed / No Data
Figure 21. Select stressor indicators (count of animal feeding operations, population growth, and wastewater flows)
Legend
% MS4 in Watershed
0.00 - 0.00
0.01 - 5.00
5.01 - 15.00
15.01 - 30.00
30.01 - 50.00
50.01 - 64.83
Not Analyzed / No Data
Figure 22. Select social indicator (% MS4)
Table 6. Index and RPI scores for Scenario 3. HUC8 watersheds are ordered by RPI score. Cells in each column are shaded by quartile according to
rank for each of the four indices (black = 76 -100th percentile; dark gray = 51-75th percentile; light gray = 26-50th percentile; white = 0-25th
percentile).
Watershed
ID
11070201
10290101
11070205
11070101
11030018
11070203
11060001
10270104
Watershed Name
Neosho Headwaters
Upper Marais Des Cygnes
Middle Neosho
Upper Verdigris
Lower Walnut River
Lower Cottonwood
Kaw Lake
Lower Kansas, Kansas
41.32
Ecological
Rank
32.64
32
Stressor
Index
Stressor
Rank
7.30
16
10.90
26
8.18
20
36.20
10.00
Social
Rank
20
13
6
25
9
5
50
7
5
11.21
28
13.45
20
8.00
18
0.55
53
11030009
Rattlesnake
45.74
13
4.49
6
10.00
26
11030014
North Fork Ninnescah
52.40
11
6.51
12
5.00
43
10270102
Middle Kansas
53.62
9
26.24
51
23.15 12
11070202
Upper Cottonwood
58.24
6
12.85
34
5.00
43
RPI Rank
33
1
42
2
55
3
25
-------
Watershed
ID
Watershed Name
Ecological
Index
Ecological
Rank
Stressor
Index
Stressor
Rank
Social
Index
Social
Rank
RPI Score
RPI Rank
10290104
Marmaton
30.06
39
4.75
25.00
11
50.10
13
10290102
Lower Marais Des Cygnes
30.38
37
10.85
30.30
8
49.94
14
10260008
Lower Smoky Hill
39.50
21
21.16
50
30.60
6
49.65
15
10270101
Upper Kansas
58.88 4
16.93
45
6.95
37
49.64
16
10260013
Upper South Fork
Solomon
41.52
18
3
10.00
26
49.43
17
11070103
Middle Verdigris
41.72
17
11
10.95
22
48.78
18
11030012
Little Arkansas
36.28
24
28.33
53
37.60
4
48.52
19
10240011
Independence-Sugar
27.60
45
15.10
40
32.50
5
48.33
20
11070204
Upper Neosho
43.80
15
8.90
23
10.00
26
48.30
21
11030017
Upper Walnut River
54.70 8
26.74
52
15.70
17
47.89
22
10260011
Upper North Fork
Solomon
34.54
28
8.20
21
15.00
19
47.11
23
11040006
Upper Cimarron-Liberal
47.22
12
11.11
27
5.00
43
47.04
24
11070207
Spring
43.44
16
16.15
42
12.15
21
46.48
25
10300101
Lower Missouri-Crooked
15.48
56
36.25
56
1
46.41
26
11030015
South Fork Ninnescah
41.04
20
6.96
15
5.00
43
46.36
27
10260004
Ladder
39.00
23
10
5.00
43
46.16
28
11060005
Chikaskia
39.38
22
14
5.00
43
45.88
29
10270205
Lower Big Blue
43.84
14
16.90
44
10.40
23
45.78
30
10240005
Tarkio-Wolf
28.44
43
2.95
2
10.00
26
45.16
31
10260006
Middle Smoky Hill
32.40
33
7.43
17
10.00
26
44.99
32
10250015
Prairie Dog
21.34
52
16.51
43
30.00
10
44.94
33
10260015
Solomon
28.04
44
17.09
46
20.00
15
43.65
34
10260014
Lower South Fork
Solomon
28.56
42
8.05
19
10.00
26
43.50
35
10270207
Lower Little Blue
33.28
30
12.80
33
10.00
26
43.49
36
11030013
Middle Arkansas-Slate
34.40
29
43.74
57
39.65
3
43.44
37
11030010
Gar-Peace
35.66
26
12.11
29
5.95
39
43.17
38
10260007
Big
25.70
47
12.46
30
15.70
17
42.98
39
11040003
North Fork Cimarron
32.68
31
4.19
5
0.00
55
42.83
40
11030002
Whitewoman
31.98
35
4.53
7
0.00
55
42.48
41
11030001
Middle Arkansas-Lake
McKinney
29.86
40
13.39
36
10.30
24
42.26
42
10240007
South Fork Big Nemaha
30.08
38
13.60
37
10.00
26
42.16
43
11040007
Crooked
25.96
46
5.26
9
5.00
43
41.90
44
10270103
Delaware
18.86
54
13.83
38
20.00
15
41.68
45
11030016
Ninnescah
29.08
41
9.25
24
5.05
42
41.63
46
10260010
Lower Saline
34.94
27
12.78
32
0.60
52
40.92
47
10260009
Upper Saline
35.84
25
18.13
48
5.00
43
40.91
48
11030006
Buckner
24.34
48
12.70
31
10.25
25
40.63
49
10250017
Lower Republican
32.30
34
33.01
54
20.15
14
39.81
50
11030004
Coon-Pickerel
30.84
36
12.86
35
0.35
54
39.44
51
11030005
Pawnee
19.46
53
6.74
13
5.00
43
39.24
52
10260012
Lower North Fork
Solomon
22.38
50
15.69
41
10.00
26
38.90
53
11030011
Cow
23.36
49
14.81
39
6.05
38
38.20
54
11030003
Arkansas-Dodge City
14.32
57
8.79
22
5.40
41
36.98
55
11030008
Lower Walnut Creek
21.74
51
17.33
47
5.65
40
36.69
56
10240008
Big Nemaha
17.14
55
20.38
49
10.00
26
35.59
57
26
-------
STAGE 2 ANALYSIS AND RESULTS
As described in the Approach section of this report, the Stage 2 analysis compares HLJC12 subwatersheds to one another
for the purpose of identifying priority HUC12s for actions to reduce nutrient loads. A much more extensive array of RPS
indicators is available at the HUC12 scale (compared to HUC8), enabling specific targeting of indicators relevant to the
implementation of nutrient management activities.
Stage 2 indicators and weights were selected by EPA and used in the Stage 2 screenings carried out by EPA. The three
Stage 2 scenarios formulated by EPA and KDHE were:
• Scenario 1 - HUC12s that are candidates for nutrient TMDL development where nutrients may impact public
water supplies;
• Scenario 2 - HUC12s with opportunities to significantly reduce nonpoint source nutrient loads;
• Scenario 3 - HUC12s that are candidates for nutrient TMDL development that are significantly influenced by
NPDES permitted dischargers.
Stage 2 screenings were completed for HUC12s within a single HUCS (Lower Big Blue) for scenario 1 and statewide for all
HUC12s in scenarios 2 and 3. The Stage 2 screening results are briefly summarized below. As with the Stage 1 screenings,
a separate copy of the RPS Tool for each of the demonstration scenarios has been archived for delivery to KDHE with
other products.
Results of Stage 2-Scenario 1
Scenario 1 focused on evaluating HUC12 subwatersheds within a single HIJC8 that are: (a) candidates for nutrient TMDL
development and; (b) have public drinking water supplies that are potentially impacted by nutrients. To begin the
analysis, EPA reviewed characteristics of HUC8s that contain nutrient impairments and drinking water supplies. Stage 1
analysis found that 71 of 90 HUCSs in Kansas have nutrient impairments and drinking water supplies. These 71 HUCSs
vary in the number of nutrient impairment listings, the size of public water systems, and relative HUCS condition.
Together, EPA and KDHE determined that the Lower Big Blue watershed (Figure 1) was the best candidate for
demonstrating Scenario 1. The Lower Big Blue watershed is a known priority for drinking water supplies and has over 20
nutrient impairment listings.
Figure 23. Map of Kansas HUC8s with the Lower Big Blue HUC8 highlighted (left) and HUC12s within the Lower Big Blue HUC8 (right).
27
-------
The Lower Big Blue watershed contains 35 HUC12s that were compared in two screenings that separately focused on
agricultural and urban sources of nutrients. Indicators selections for the two screenings are listed in Table 1 (indicator
descriptions can be found in Attachment 1). Both screenings use the same ecological and social indicators but differ in
the stressor indicators selected to reflect agricultural versus urban nutrient sources.
Table /. Indicator selections for the Stage 2-Scenario 1 screenings.
Ecological Indicators
Stressor Indicators
(Agricultural)
Stressor Indicators
(Urban)
Social Indicators
PHWA Watershed Health
Index, State (2016)
% Agriculture in WS (2011)
% Urban in RZ (2011)
USDA Conservation Reserve
Program Area in WS
PHWA Watershed Health
Index, ER (2016)
% Cultivated Crops in RZ (2011)
% Urban Change in WS (2001-
11)
% Streamlength Assessed
(2015)
% Pasture/Hay in RZ (2011)
% Developed, Open Space in WS
(2011)
Nonpoint Control Projects
Count
Agricultural Water
Demand in WS
% Developed, Medium Intensity
in RZ (2011)
Nutrients Nonpoint Control
Projects Presence
Manure Application in WS
% Developed, Low Intensity in
RZ (2011)
Critical Watershed Class Score
(Instate)
Synthetic N Fertilizer Application
in WS
% Waters Near >= 5%
Impervious Cover (2011)
Count (2011-2014)
Conservation Practices
(Instate)
303(d)-Listed Segments
Count (2015)
Population Density in RZ
303(d) Vision Restoration
Priority 2017
% Streamlength 303(d)-Listed
Nutrients (2015)
303(d)-Listed Segments Count
(2015)
WRAPS 2018 Priority for
Cropland
Number of Animals (USDA
County) in WS (Instate)
Segment-Cause Impairment
Combinations Count (2015)
WRAPS 2018 Priority for
Livestock
Count of Animal Feeding
Operations in WS (Instate)
Nutrients 303(d)-Listed
Segments Count (2015)
WRAPS 2018 Priority for
Steambank
% Streamlength 303(d)-Listed
Nutrients (2015)
WRAPS 2018 Priority Sum
Number of Septic Systems in WS
(INSTATE)
28
-------
Bubble plots displaying Ecological, Stressor, arid Social index scores for the Scenario 1 agricultural and urban screenings
are displayed in Figure 2. The RPS Tool is able to generate two separate bubble plots for any screening: a "subset"
version and a "statewide" version. The subset version displays index scores exactly as calculated with user-supplied
screening settings (watersheds, indicators, and weights). The statewide version displays scores that are based on the
same indicators and weights but considers all watersheds in the state for index score calculation. The statewide bubble
plot provides a broader context for evaluating the screening results so that users can understand how the highest and
lowest index scores for their selected watersheds compare to statewide values.
Figure 2 displays both the subset and statewide bubble plots for the agricultural and urban screenings. Key observations
include:
• In the statewide bubble plots, HUC12s are generally condensed within a smaller range of index scores compared
to the subset plots. This is a typical result. Index scores in the statewide plots consider a larger group of HUC12s
with a wider range of indicator values, which serve as the basis of index scoring. Relative differences among
HUC12s in indicator values are, therefore, less pronounced in the statewide plots.
• In the statewide bubble plots, the HUC12s selected for screening have Ecological Index scores that extend above
and below the horizontal axis. Since the horizontal axis is set to the statewide median Ecological Index score, this
points to a wide variety of ecological conditions within the Lower Big Blue HUC12s above and below what is
typical for the state.
• Similarly, Stressor Index scores in the statewide bubble plot for the agricultural screening extend across both
sides of the vertical axis (the statewide median Stressor Index). This indicates a wide range of stressor exposure
within the Lower Big Blue HUC12s.
• The median Stressor Index (vertical axis) for the urban screening is near zero in the statewide bubble plot. This
commonly occurs when the stressor indicators selected for a screening measure attributes that are relatively
uncommon across the entire state and cluster at zero or near-zero values. In this case, the finding of a near-zero
Stressor Index for the urban screening reflects the rural setting of most Kansas HUC12s.
• In both the agricultural and urban scenarios, Social Index scores vary widely among the subset of watersheds
selected for screening (i.e., a wide range of bubble sizes is apparent). The statewide and subset plots do not
show major differences in Social Index scores, indicating that social indicator values in the watershed subsets are
representative of statewide conditions.
(LBB HUC8 only)
o (
(LBB HUC8 only)
°oO
» •'
Q «
r
(Statewide)
statewide version
(Statewide)
Figure 24. Bubble plots for Stage 2-Scenario 1 screenings. For each screening, a "subset" version and a "statewide" version of the bubble plot are
displayed.
29
-------
The agricultural and urban RPS screenings were used to evaluate potential priority HUC12s in the Lower Big Blue
watershed for TMDL development and implementation. The evaluation of potential priorities was organized around the
following questions:
1. Which HUC12s have programmatic attributes that support nutrient TMDL development?
a. Not fully supporting domestic water supply designated uses
b. 303(d) listed for nutrients
c. Limited presence of existing nutrient TMDLs
d. Prior designation as a priority by the Kansas Watershed Restoration and Protection Strategy (WRAPS)
program or Kansas 303(d) program
2. How do index scores compare among potential priority HUC12s for nutrient TMDL development?
3. What nutrient management actions might be needed in potential priority HUC12s?
Which HUC12s have programmatic attributes that support nutrient TMDL development?
Question 1 focuses on identifying HUC12s with attributes relevant to 303(d) and other clean water programs that
support their designation as priorities for nutrient TMDL development. These attributes include: (a) the presence of
waters that are not supporting designated uses for domestic water supply; (b) the presence of waters that are 303(d)
listed for nutrients; (c) limited presence of existing nutrient TMDLs; (d) and the presence of waters that were previously
designated as a WRAPS or 303(d) program priority. These four factors indicate that nutrient TMDLs are needed, that
drinking water supplies may be at risk from excess nutrient loading, and that support for prioritization has been
previously established.
Question 1 was evaluated using indicator data presented on the "HUC12 Data" tab of the RPS Tool (Table 2). Out of 35
total HUC12s in the Lower Big Blue watershed, 12 were not fully supporting their domestic water supply designated
uses, 22 had nutrient 303(d) listings, 2 had existing nutrient TMDLS, and 23 were state-defined WRAPS or 303(d) priority
waters. Eight HUC12s combined all four attributes:
• Alcove Spring-Big Blue River (102702050502)
• Cedar Creek-Big Blue River (102702050705)
• Cedar Creek-Black Vermillion River (102702050405)
• Corndodger Creek-Black Vermillion River (102702050406)
• Deer Creek-Big Blue River (102702050204)
• Irish Creek (102702050305)
• Outlet North Fork Black Vermillion River (102702050302)
• Outlet Robidoux Creek (102702050403)
These eight HUC12s are of particular interest for this scenario and are highlighted in the following discussion of
additional screening questions.
30
-------
Table 8. HUC12s in the Lower Big Blue watershed with information on domestic water supply designated use attainment, nutrient impairments,
nutrient TMDLs, and 303(d) program or WRAPS priority designations.
Not Attaining Drinking
Nutrient
Nutrient
2017 303(d)
Count of
Name HUC12 Watershed
Water Supply
Impaired
TMDL
Vision
2018 WRAPS
Designated Use
Segment Count
Count
Priority Flag
Priorities
Deer Creek-Big Blue River
X
4
0
X
4
Outlet North Fork Black Vermillion River
X
2
0
X
3
Irish Creek
X
2
0
X
1
Outlet Robidoux Creek
X
4
0
X
3
Cedar Creek-Black Vermillion River
X
5
0
X
1
Corndodger Creek-Black Vermillion
1
0
X
1
River
X
Alcove Spring-Big Blue River
X
5
0
X
1
Carter Creek-West Fancy Creek
X
0
0
0
Deadman Creek-West Fancy Creek
X
0
0
0
North Fork Fancy Creek-West Fancy
0
0
0
Creek
X
Otter Creek-Fancy Creek
X
0
0
0
Cedar Creek-Big Blue River
X
3
0
X
1
Mission Creek
2
0
X
1
Big Blue River
1
0
X
1
North Elm Creek-Big Blue River
4
0
X
4
Headwaters Horseshoe Creek
2
0
X
1
Outlet Horseshoe Creek
4
0
X
1
Headwaters North Fork Black Vermillion
0
X
River
Town of Centralia-Black Vermillion River
2
1
X
1
Town of Vermillion-Black Vermillion
0
X
River
Little Timber Creek-Black Vermillion
0
X
River
Headwaters Robidoux Creek
1
0
X
3
Snipe Creek
0
0
2
Clear Fork
2
0
X
1
Marysville Country Club Dam-Spring
3
0
X
3
Creek
Elm Creek-Big Blue River
4
0
X
1
Bluff Creek
0
0
0
Game Fork-Big Blue River
0
0
X
1
Swede Creek-Tuttle Creek Lake
0
0
0
North Otter Creek
0
0
0
Walnut Creek-Fancy Creek
0
0
0
Booth Creek-Tuttle Creek Lake
0
0
0
Mill Creek-Tuttle Creek Lake
0
0
0
Big Blue River-Tuttle Creek Lake
0
0
0
Tuttle Creek Dam
1
1
0
31
-------
How do index scores compare among potential priority HUC12s for nutrient TMDL development?
Question 2 can be evaluated with bubble plots displaying RPS screening results by reviewing the position of the eight
HUC12s identified from question 1, Figure 3 displays bubble plots for the agricultural and urban screenings with labels
added to the eight HUC12s of interest.
In both screenings, the eight HUC12s of interest cover a wide range of Ecological and Stressor Index scores. Four of these
(Alcove Spring-Big Blue River; Cedar Creek-Black Vermillion River; Irish Creek; Outlet Robidoux Creek) have above-
median Ecological Index scores and also have Stressor Index scores that are near or above the median for the screening.
These four HUC12s could be prioritized for nutrient TMDL development because they appear to have moderate levels of
agricultural and urban stressors, but stiii maintain positive ecological traits that can facilitate improvement in aquatic
ecosystems within the HUC12 and might lead to full restoration .
Conversely, HUC12s with higher Stressor Index scores but lower Ecological Index scores (e.g., Outlet North Fork Black
Vermillion River, Deer Creek-Big Blue River, Cedar Creek-Big Blue River) may be of greater interest for efforts targeting
HUC12s with the highest nutrient loads to reduce downstream impacts.
100
90
80
70
S a
TJ
C
* 50
u
'5b
o 40
o
o
LU
30
20
10
0
0 10 70 30 40 50 GO 70 80 90 100
Stressor Index
100
90
80
70
£ 60
TJ
c
15 50
u
'5b
O 40
o
Q
LU
30
30
10
0
O
0
c
-*
t <
3
r Cedar Creek-Btack Vermillion River
)
rish Creek
•
D
/I /-Aicove bpring
, - - - Outlet
-big blue mver
Robidoux Creek
r
i
Corndodger Creek-
o
Black Vermillion River
1
!
k.
)
n
3
Outlet North Fork Black
zz
Deer Creek-Big
Blue River
o
cr"
Vermillion River
Cedar Creek-Big Blue
tfver
•
0
Urban
screening
O o
o o
Q
) Irish Creek
Bk
Black Verm
m
O
/•/
/ uuuei KODiuoux vre
Cedar Creek
illion River
0
•0
u
er
Alcove Sprtng-Big Blue Rive
0
o
n
Corndodger Creek-
c8
y
8
Q
Deer Creek-B
g Blue Rive
Black Vermillion
River
o
d
>
G,
Cedar Creek-Big Blue
River
(
5
Outlet North Fork Black
Vermillion River
0 10 20 30 40 50 50 70 80 90 100
Stressor Index
Figure 25. Bubble plots for the Stage 2-Scenario 1 screenings. The labeled HUC12s are potential priorities for nutrient TMDL development because
they contain waters that are not supporting domestic water supply designated uses, waters that are 303(d) listed for nutrients, and waters
previously designated as a WRAPS or 303(d) program priority.
32
-------
What nutrient management actions might be needed in potential priority HUC12s?
Although the RPS Tool is primarily a screening-level resource for comparing relative conditions within a group of
watersheds, it can also be used for initial evaluations of specific water quality restoration needs in one or more
watersheds. Figure 4 displays bubble plots for the agricultural screening with bubbles shaded according to three
indicators that are relevant to nutrient reduction planning;
(a) Percentage of the HUC12 with cultivated crops
in the riparian zone (defined as the 100-meter
buffer around surface waters). Figure 4a shows that
potential priority HUC12s have between 5% and 9%
of their area covered by cultivated crops in the
riparian zone, equating to approximately 1,250
acres to 3,700 acres of riparian zone in the HUC12s
of interest. These HUC12s appear to have sufficient
crop cover in their riparian zone to benefit from
efforts to promote the establishment and
expansion of vegetated buffers to filter agricultural
runoff.
(b) Average rate of synthetic nitrogen fertilizer
application in the HUC12. In Figure 4b, five of the
potential priority HUC12s appear to have moderate
to high rates of synthetic fertilizer application
compared to other HUC12s (Alcove Spring-Big Blue
River, Cedar Creek-Black Vermillion River, Deer
Creek-Big Blue River, Outlet North Fork Black
Vermillion River, and Outlet Robidoux Creek). Annual
application rates for the five HUC12s range from 36
to 58 kilograms of nitrogen per hectare, all of which
are above the statewide average of approximately 26
kilograms of nitrogen per hectare. These five FIUC12s
may therefore be good candidates to implement
programs that aim to reduce over-application of
fertilizers on agricultural lands.
(c) The number of animal feeding operations (AFOs)
in the HUC12. Figure 4c displays AFO counts in each
HUC12 in the Lower Big Blue watershed. All of the
potential priorities for TMDL development have at
least one AFO, with the highest count (6 AFOs) in the
Outlet North Fork Black Vermillion River and the
Cedar Creek-Big Blue River HUC12s. Efforts to
encourage best practices for animal manure
management may help to reduce nutrient loading in
these HUC12s.
S ®
TJ
C
— 50
% Cultivated Crops in RZ
o
|_J 0-2.4
9%
9%
9%
° J
o
o*
_
/
edar Creek-Black
Vermillion River
~ 2.5-4
O
Alcove Spring-Big Blue
~ 5-7.4
?
3
River
- Outlet Robidoux
y 7.5-10.3%
Corndodger Creek-.
Y
«•
i
<
4
•
n
i
Black
/•
Deer Creek-Bi
®
•
Vermillion River
Cedar Creek-Big Blue Riv<
r
•
Stressor Index
I o_
o J O
Q>
O
Corndodger Creek-.
Irish Creek -fr )
O
Cedar Creek-Big Blue Riv<
Cedar Creek-Black
Vermillion River
Alcove Spring-Big Blue
River
Outlet Robidoux Creek
Synthetic N Fertilizer
Application in WS (kg/ha/yr)
O 2.27 -14.99
~ 15-29.99
~ 30-44.99
H 45 -66.15
Deer Creek-Big
Blue River
Outlet North Fork Black
Vermillion River
Stressor Index
(c)
O
Count of Animal Feeding
Operations in WS (INSTATE;
fin
0 J
0
c*"M
/
Cedar Creek-Black
Vermillion River
~
1-4
5-8
9-12
O
r
cove Spring-Big Blue
River
U
~
* O,
Corndodger Creek-.
I
-So
$
D
Deer Creek-Bi
0
m'
Vermillion River
Cedar Creek-Big Blue Rlv<
r
•
Stressor Index
Figure 26. Bubble plots for the Stage 2-Scenario 1 agricultural screening
with labels applied to potential priority HUC12sfor nutrient TMDL
development. The bubbles in each plot are shaded according to different
indicators of agricultural nutrient sources.
33
-------
A similar review can be completed for the urban screening. Figure 5 displays bubble plots for the urban screening with
bubbles shaded according to three indicators that are relevant to management of urban nutrient sources:
(a) Percent of the HUC12 with urban cover in the
riparian zone (defined as the 100-meter buffer
around surface waters). Figure 5a shows that
most of the priority HUC12s have less than 1% of
their area classified as urban land cover in the
riparian zone. The exceptions are the Deer
Creek-Big Blue River HUC12 (1.2%) and the Cedar
Creek-Big Blue River HUC12 (4.2%). Results
suggest that the Cedar Creek-Big Blue River
HUC12 may be a prime candidate to significantly
benefit from efforts to promote the
establishment and expansion of vegetated
buffers to filter urban runoff.
(b) Percent impervious cover in the HUC12. Figure 5b
also reflects the limited extent of urban
development in the Lower Big Blue watershed, as
only the Deer Creek-Big Blue River HUC12 (1.4%)
and the Cedar Creek-Big Blue River HUC12 (4.7%)
have impervious cover percentages greater than
1%. This reinforces the designation of the Cedar
Creek-Big Blue River FIUC12 as a better candidate
for actions to reduce nutrient loading from urban
lands, such as the installation of retention basins,
rain gardens, and other stormwater best
management practices (BMPs).
(c) Number of septic systems in the HUC12. Figure 5c
displays septic system counts for each HUC12 in
the Lower Big Blue watershed. All of the
potential priorities for TMDL development have
some septic systems present, however, the Deer
Creek-Big Blue River HUC12 and Cedar Creek-Big
Blue River HUC12 again stand out with 196 and
886 septic systems, respectively. These two
HUC12s appear to be best-suited for efforts to
inventory and upgrade septic systems and
expand centralized sewer services.
(a)
% Urban in RZ (2011)
~ 0.4%-1%
~ 1%- 2%
~ 2%- 3%
0
O ©
Of
; Irish Creek „ „ ^ „
1 3% - 4%
O
-it
/ G"
I Alcove Spring-Big Blue
—frv-r^ River —
—£
—
¦ft
n
Corndodger Creek-
Black Vermillion
A
v. J v > Deer Creek-E
ig Blue River
O
>
Cedar Creek-Big Blue River
c
Outlet North Fork Black
Vermillion River
Stressor Index
(b)
o
O o .
I qQ 1 On Irish Creek
O-
oc
r Outlet Robidoux Creek
I J jo
/ O j _ .— Cedar Creek-Black Vermillion River
' Qr
_ ^? i Alcove Spring-Big Blue
—^7 Wver —
% Imperviousness,
Mean in WS (2011)
~ 1%- 2.5%
~ 2.5% - 4.7%
Corndodger Creek-
Black Vermillion
River
<9a
~ o
o
Outlet North Fork Black
Vermillion River
- Cedar Creek-Big Blue River
(C)
o
c
<
w
O o .
qO Oq Irish Creek
Corndodger Creek-
Black Vermillion...
o°_
~rQ~
'J
Stressor Index
- Outlet Robidoux Creek
— Cedar Creek-Black Vermillion River
©"
Alcove Sprlng-BIg Blue
m.
Number of Septic
Systems in WS (INSTATE)
D10-49
~ 50-149
D150-249
~ 250-886
r
Deer Creek-Big Blue River
GT
k \ Outlet North Fork Black
™ Vermillion River
- Cedar Creek-Big Blue River
Stressor Index
Figure 27. Bubble plots for the Stage 2-Scenario 1 urban screening with
labels applied to potential priority HUCHsfor nutrient TMDL
development. The bubbles in each plot are shaded according to
different indicators of urban nutrient sources.
34
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Results of Stage 2-Scenario 2
Scenario 2 consisted of an exploratory analysis of HUC12 subwatersheds across the state to evaluate opportunities to
reduce nutrient loading from nonpoint source pollution. The analysis focused on HUC12s that were already identified as
priorities through the Kansas Watershed Restoration and Protection Strategy (WRAPS) framework. Included in the
Kansas RPS tool are social indicators that describe whether each HUC12 in the state has been designated as a high,
medium, or low priority under the WRAPS program in different categories (e.g., urban stormwater, cropland,
streambank erosion, TMDL development). For each category, indicators are scored as 1.0 for high priority, 0.67 for
medium priority, and 0.33 for low priority within the RPS tool. As of March 2018, a total of 340 HUC12s in Kansas were
assigned WRAPS priority status in at least one category. Figure 6 illustrates the sum of WRAPS priority scores in each
HUC12. The HUC12s with the highest WRAPS priority totals are shaded dark blue in Figure 6 and were designated as high
priority in at least three categories. These HUC12s generally cluster in the eastern portion of the state.
"H:
WRAPS 2018 PRIORITY SUM
0.66 - 0.99
1.00 - 1.99
2.00 - 2.99
3.00 - 3.34
| Not Analyzed/No Data
Figure 28. Sum of WRAPS priority scores for Kansas HUC12s. Summed values reflect the total of individual priority scores for various categories (e.g.,
urban stormwater, cropland, streambank erosion, TMDL development).
The exploratory analysis completed for scenario 2 did not include a formal RPS screening run. Instead, indicator data for
HUC12s with WRAPS priorities were reviewed using the RPS tool's mapping functionality. The scenario 2 analysis was
organized around the following questions for HUC12s with WRAPS priorities:
1. Which HUC12s contain nutrient impaired waters?
2. In which HUC12s are urban and agricultural nonpoint sources of nutrients prevalent?
3. What additional impairments are present in the HUC12s?
4. Which HUC12s might be considered for actions to protect water quality from future degradation?
Which HUC12s contain nutrient impaired waters?
Of the 340 HUC12s with WRAPS priority status, 178 contain at least one nutrient impaired waterbody segment. Figure 7
displays the extent of nutrient impairments in each HUC12, Impairment extent is mapped as the number of waterbody
segments with nutrient impairments (top), the percentage of HUC12 streamlength with nutrient impairments (middle),
and the percentage of HUC12 lake or reservoir area with nutrient impairments (bottom). The maps show a wide range in
the extent of nutrient impairment within the HUC12s, For example the percentage of impaired streamlength ranges
from 1% to 91% in HUC12s with at least one nutrient impaired segment. This variety offers planners an opportunity to
determine whether nonpoint source management resources should be directed towards HUC12s with widespread issues
versus HUC12s with isolated nutrient impairments.
35
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•Hp x
Nutrients 303d-Listed Segments Count
(2015)
0
1
2 - 4
5 - 8
Not Analyzed / No Data
% Streamlength 303d-Listed
Nutrients (2015)
0
1 - 25
25 - 50
50 - 91
Not Analyzed / No Data
% Waterbody Area 303d-Listed
Nutrients (2015)
0
1 - 10
B10 - 50
50 - 94
Not Analyzed / No Data
Figure 29. Nutrient impaired waters in HUC12s with WRAPS priority status. Impairments are mapped as: the count of waterbody segments with
nutrient impairments (top), the percentage of streamlength with nutrient impairments (middle), and the percentage of waterbody area with
nutrient impairments (bottom).
36
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In which HUC12s are urban and agricultural nonpoint sources of nutrients prevalent?
Watershed priorities can be further refined by identifying likely sources of nutrients within HUC12s. Figure 8 through
Figure 10 display indicators of the potential for nonpoint source pollution from urban stormwater and agricultural
runoff. Figure 8 shows that most HUC12s with WRAPS priorities have a relatively low amount of impervious cover (less
than 5% of the HUC12). While urban stormwater issues may be present these HUC12s, they are likely to be site- or
reach-specific and not prevalent throughout the HUC12 area. Three HUC12s in the vicinity of Wichita (Cadillac Lake-
Cowskin Creek; Wichita Floodway; Wichita VC Floodway-Arkansas River) have more than 10% impervious cover and are
at greater risk for widespread urban stormwater pollution.
The percentage of cropland in each HUC12 is mapped in Figure 9. Reflective of Kansas' character as an important
agricultural state, a large number of HUC12s have cropland cover across at least 50% of their area. While this group of
HUC12s could be considered priorities for implementing agricultural BMPs, a review of additional indicators can pinpoint
watersheds in greater need of specific management actions. For example, Figure 10 shows estimated annual rates of
phosphorus application to cropland from chemical fertilizer. HUC12s in Figure 10 are shaded according to their
percentile rank for phosphorus application. Those within the top ten percentile (highest phosphorus application; shaded
dark blue) are concentrated in the northeast and east-central part of the state. These HUC12s could be higher priorities
for BMPs that reduce nutrient concentrations in agricultural runoff or outreach efforts to producers on preventing over-
application of fertilizer.
% Imperviousness, Mean in WS
(2011)
<1
1 - 4
B5 - 9
10 - 36
Not Analyzed / No Data
Figure 30. Percentage of impervious cover in HUC12s with WRAPS priority status.
37
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% Cultivated Crops in WS (2011)
Not Analyzed / No Data
Figure 31. Percentage of cultivated cropland in HUC12s with WRAPS priority status.
Inorganic P Fertilizer Application
WS (kilograms /hectare/yr)
0.36 - 1.67
1.68 - 2.74
2.75 - 3.77
3.78 - 4.60
4.61 - 5.68
5.69 - 6.67
6.68 - 7.93
8 7.94 - 8.80
8.81 - 10.80
10.81 - 17.07
Not Analyzed / No Data
Figure 32. Estimated rates of agricultural phosphorus application from chemical fertilizer in HUC12s with WRAPS priority status.
What additional impairments are present in the HUC12s?
The goals of a rioripoint source management plan could include restoration of degraded biological communities or de-
listing of impaired waterbody segments. To achieve such goals, an understanding of the complete group of pollutants of
concern within a watershed is needed. The Kansas 303(d) list of impaired waters serves as a resource for identifying
pollutants of concern that are causing designated use impairments. Figure 11 displays the number of impairment causes
within each HUC12 as reported on the Kansas 303(d) list Impairment causes can include nutrients, pathogens,
temperature, metals, pesticides, salinity, sediment, impaired biota, etc. Figure 11 can be compared with the number of
nutrient impaired segments (Figure 7; top) to identify HUC12s in which nutrients are the only cause of impairment (i.e.,
HUC12s with one cause of impairment and at least one nutrient-impaired segment). These HUC12s might be priorities
for nonpoint source management because they could be de-listed with reduced nutrient loading and their biological
communities may show greater recovery following nutrient reductions relative to ecosystems that are subject to excess
levels of metals, pesticides, etc.
38
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Unique Impairment Causes Count
(2015)
Not Analyzed / No Data
Figure 33. Number of impairment causes reported on the Kansas 303(d) list in HUC12s with WRAPS priority status.
Which HUC12s might be considered for actions to protect water quality from future degradation?
Although degraded watersheds with water quality impairments are often the focus of nonpoint source management
resources, proactive actions in unimpaired watersheds can prevent future impairments and avoid the need for costly
restoration measures. Activities to prevent or minimize pollutant loading from future development can also be paired
with restoration actions in impaired watersheds to support long-term water quality protection. For example, restoration
of degraded riparian buffers can be paired with easement acquisition to ensure long-term protection of the restored
buffers. One indicator in the RPS tool that can guide the prioritization of watersheds for protection is the Preliminary
Healthy Watersheds Assessment (PHWA) statewide Watershed Health Index (https://www.epa.gov/hwp/download-
2017-preliminarv-healthv-watersheds-assessments). This indicator scores HUC12s according to their potential for
supporting healthy, functioning aquatic ecosystems by combing subindices of landscape, hydrologic, geomorphology,
habitat, water quality, and biological condition. Figure 12 maps Watershed Health Index scores as a percentile relative to
all other HUC12s in the state. HUC12s in the top ten percentile could be prioritized for protection since they are most
likely to support functioning aquatic ecosystems. HUC12s in the second grouping (75th-89th percentile) could also be
prioritized for protection since they may be more vulnerable to degradation from future increases in pollutant loading.
PHWA Watershed Health Index, State
Percentile (2016)
1 - 74
75 - 89
H90 - 99
Not Analyzed I No Data
Figure 34. Watershed Health Index scores for HUC12s with WRAPS priority status. HUC12s are divided into three groups for mapping based on
Watershed Health Index scores: top ten percentile, 75th to 89th percentile, and below 75th percentile.
39
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Results of Stage 2-Scenario 3
Scenario 3 investigated HUC12s that are suitable for nutrient TMDL development and may be significantly influenced by
NPDES permitted dischargers. The exploratory analysis completed for scenario 3 did not include a formal RPS screening
run. Instead, this scenario demonstrates the "subset" function of the RPS tool. The subset function allows the user to
define a condition or combination of conditions based on indicators in the tool to select a group of watersheds. In order
to identify an initial group of HUC12s that could be suitable for TMDL development and affected by point source loading
from NPDES permitted dischargers, the following subset conditions were applied:
• 303(d)-Listed Segments Count greater than zero; and
• NPDES Permit Count greater than zero.
The above query creates a subset of 276 HUC12s statewide that could be candidates for nutrient TMDL development.
Figure 7 displays a map of these 276 HUC12s shaded by the number of waterbody segments that are listed as impaired
due to nutrients. Additional subset conditions could be further applied to identify HUC12s that may require less complex
TMDLs and show greater reductions in nutrient concentrations with improved point source management. Example
subset conditions could include:
Nutrients 303d-Listed
Segments Count (2015)
1
2 - 3
4 - 5
6 - 7
8 - 10
Not Analyzed
Figure 35. HUC12s that contain 303(d) listed waters with nutrient impairments and NPDES-permitted dischargers.
• The "Headwater HUC12 Flag" or "Upstream HUC Count" indicators could be used to focus on headwater HUC12s
or those with relatively few additional upstream HUC12s. This group is less likely to be subject to nutrient
pollution from sources beyond their upstream boundary. The HUC12s could also require lower-complexity
TMDLs if additional upstream sources are insignificant;
• The "Watershed Unique 303(d)-Listed Causes Count" indicator to identify HUC12s with relatively few causes of
impairment reported on the state 303(d) list. In addition to nutrients, impairment causes could include
pathogens, temperature, metals, pesticides, salinity, sediment, etc. HUC12s with a lower number of impairment
causes may also require lower-complexity TMDLs.
Other subset conditions could be further applied to identify HUC12s with aquatic ecosystems that may be more
responsive to recovery with reduced nutrient loads. For example, the PHWA Watershed Health Index could be used to
identify HUC12s that received higher watershed health scores under the EPA Preliminary Watershed Health Assessment.
40
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SUMMARY AND RECOMMENDATIONS
This document summarizes the usage of Recovery Potential Screening (RPS) to compare watersheds at two scales (HUC8
and HUC12) for purposes of informing possible watershed management options and priorities for nutrient management.
Utilizing georeferenced data provided primarily by KDHE, EPA and additional sources, this project compiled indicators
(base, ecological, stressor and social) at one or both watershed scales that were used to screen and compare watersheds
in a two-stage process. In the first stage, Kansas's HUC8s were screened with two separately developed sets of
indicators selected to identify and rank watersheds. Based on these first stage screenings and other criteria, one
watershed was selected as a demonstration HUC8 for further analysis in the second stage (Little Arkansas).
Stage two screening was performed on the demonstration HUC8 that scored and compared HUC12s using a more
detailed sets of indicators that drew from HUC12-scale metrics. Whereas the purpose of Stage 1 was to compare and
recognize like groups of watersheds at the larger scale, Stage 2's purpose was to examine and reveal potential
opportunities for nutrient management action at the more localized HUC12 scale. As a demonstration of how the RPS
Tool could be applied to support decision-making (rather than a true analysis of priority watersheds), no priorities
among HUC12s were selected in this project but numerous alternatives and analytical techniques were presented.
Products include this summary report, a master RPS Tool file, and separate screening files that archived the results from
the Stage 1 and Stage 2 screenings. Opportunities for KDHE and other users from this point forward may include:
Become adept at RPS Tool desktop use. Despite the extensive amount of data stored within the RPS Tool and the wide
variety of comparisons among watersheds that these data can support, the RPS Tool is actually a fairly simple
spreadsheet tool. This tool allows for simple but useful forms of spatial data analysis, systematic comparisons among
watersheds, and a variety of visualization tools - on users' own desktops. A wide circle of users will be able to perform
quick 'what-if' screenings to compare watersheds and gain insights on what may be worth a greater investment of time
and effort with more technical analytical tools.
Apply the RPS Tool to other screening topics. Although this effort focused on a nutrients application of RPS, the Kansas
dataset could support numerous other screening themes and purposes that can be explored in long-term restoration
and protection priority setting. Other screening applications might include sediment, metals, pathogens, or any other
prominent cause of impairment. Or in contrast, screenings might focus on a valued resource/use such as watersheds
with coldwater fisheries, or drinking water sources, or major outdoor recreational sites. The RPS Tool might be used to
develop a first-cut identification of healthy watersheds for protection, or rank likely eligibility for specific types of
pollution control incentives. With both the TMDL Program and the Non-Point Source Control Program promoting
watershed priority-setting, the range of opportunities is extensive.
Refine the available data and selection of indicators. Even within this nutrient application of RPS, opportunities exist to
add more relevant data or refine previous screenings as new insights are gained. The RPS Tool is structured to accept
additional indicator data from a user that can be incorporated into future screenings. New data does not need to be
available statewide, and a local user may still use the tool after adding data for a limited set of their local
subwatersheds. Further, previous analyses can be refined by structured group processes to assign consensus weights to
indicators, or by correlation analyses designed to narrow down indicator selections and better differentiate between
watersheds. For example, expanding Kansas' available HUC8 indicators and re-screening could allow for considering
nutrient delivery to the Gulf of Mexico.
Galvanize state/local restoration and protection dialogue and partnering. RPS offers a mechanism for state-local
collaboration. Features of the RPS Tool, such as the option to add new or updated indicator data or the ability to quickly
adjust screening settings, allow an analysis to be tailored to reflect the environmental and social settings of a specific
locale. Watershed groups, academic researchers and local governments can provide data or other refinements to
develop a customized watershed screening within the versatile RPS Tool. Further, if local organizations do engage with
KDHE and enhance their RPS Tool copies, they may provide valuable dialogue on addressing local as well as statewide
interests in watershed priority-setting and improved nutrient management.
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ATTACHMENT 1
RECOVERY POTENTIAL
SCREENING: SUMMARY
• Recovery Potential Screening (RPS) is a systematic,
comparative method for identifying differences among
watersheds that may influence their relative likelihood to
be successfully restored or protected. The EPA Office of
Wetlands, Oceans and Watersheds (OWOW) created RPS
jointly with the EPA Office of Research and Development
(ORD) in 2004 to help states and others use limited
restoration resources wisely, with an easy to use tool
that is customizable for any geographic area of interest
and a variety of comparison and prioritization purposes.
• The main programmatic basis for RPS includes the TMDL Program (e.g., prioritized schedule for listed waters; where
best to implement TMDLs; Integrated Reporting of Priority waters under the TMDL Vision) and the Nonpoint Source
Program (e.g., annual program strategies; prioritization to aid project funding decisions; collaboration with Healthy
Watersheds), but several other affiliations also exist.
• Since 2005, several hundred RPS indicators have been incrementally compiled through literature review, identifying
states' indicator needs and preferences, and collaboration with others (ORD EnviroAtlas, Region 4 Watershed Index).
Most have been applied in a series of statewide RPS projects. In 2009, an RPS paper was published in the refereed
journal Environmental Management. The one-stop RPS Website hosts a library of indicators, RPS tools, case studies
and step by step RPS instructions.
• As of 2017. RPS projects and statewide databases have been either initiated or completed in 28 states (see figure).
Approximately that many additional states have expressed interest in RPS usage, but limited EPA resources have not
yet been able to support all requests.
• The RPS Tool is key to RPS' ease of use, widespread applicability and speed. This tool is an Excel spreadsheet that
contains all watershed indicators, auto-calculates key indices, and generates rank-ordered tables, bubble plot
graphics and maps that can be user-customized. Any novice Excel user can become fiuent in using the RPS Tool.
• Statewide RPS Tools and data are available; for each of the states and territories. These generally contain 285
indicators measured for every HUC12, and enable customizable desktop screening, rank ordering, graphics plotting
and mapping without advanced software or training. Individual, state-specific RPS Tools were distributed in 2014,
2016, and 2017 and are publicly available online.
• RPS is playing/may soon play a pivotal role in each of the following:
Prioritizing watersheds for nutrient management (projects in 9 states)
Identifying state priority watersheds for TMDL Vision/Integrated Reporting 2016-2022
Improving state/local interactions in states with RPS projects
Enabling Tribes to screen and compare their watersheds for purposes similar to states
Helping the Healthy Watersheds program by providing a national Preliminary Healthy Watersheds Assessment
(PHWA; https://www.epa.gov/hwp/download-2017-preliminary-healthy-watersheds-assessments)
Jointly (OW and EPA Region 4) creating the Watershed Index Online (WSIO) interactive tool
(https://www.epa.gov/wsio/download-and-use-wsio-tool)
• Contact: Miranda Chien-Hale, WB/WRAPD/OWOW at chien hale.miranda@epa.gov or 202-566-0401.
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ATTACHMENT 2
KANSAS STAGE 1 (HUC8) SCENARIO INDICATOR DESCRIPTIONS
Green denotes ecological indicators, red are stressor indicators, and blue are social indicators. All Kansas-specific
indicators are denoted with (INSTATE).
HUC8 INDICATOR
DESCRIPTION
Weighted-Average !Bi Score
(INSTATE)
The area-weighted average Index of Biological Integrity (IBI) score for each HUC8, derived
from HUC12 data provided by the state of Kansas. IBI scores are based on data from 1994-
2014. Source data used was received via personal communication with Andrew Lyon (State of
Kansas) in April 2015. "(INSTATE)" denotes that the indicator was only calculated for HUC
areas within Kansas state boundaries.
Flow (cfs) Generated in
Watershed |IM5TA1 E)
Flow in cubic feet per second (cfs) generated within the HUC8. HUC8 scale data was provided
by the state of Kansas. Source data used was received via personal communication with Tom
Stiles (State of Kansas) in May 2015. "(INSTATE)" denotes that the indicator was only
calculated for HUC areas within Kansas state boundaries.
tat Condition index WS
(2015)
Mean Habitat Condition Index (HCI) score for the HUC12 from the National Fish Habitat
Partnership (NFHP) 2015 National Assessment. Scores range from 1 (high likelihood of aquatic
habitat degradation) to 5 (low likelihood of aquatic habitat degradation) based on land use,
population density, roads, dams, mines, and point-source pollution sites. Source data were
NFHP 2015 National Assessment Local Catchment HCI scores for NHDPIus Version 1
catchments (acquired via personal communication with NFHP in March 2016). NHDPIus
Version 1 catchments are local drainage area delineations for surface water features in the
NHDPIus Version 1 database. Catchment HCI scores were aggregated to HUC12 scores by
calculating the area-weighted mean of HCI scores for catchments that intersect the HUC12.
See http://ecosystems.usgs.gov/fishhabitat/nfhap_download.jsp for more information on the
NFHP National Assessment.
% N-lndex2 in WS (2011) (%
natural cower in the watershed)
Percent of the HUC12 classified as natural land cover (excluding barren land) by the 2011 CDL-
NLCD Hybrid Land Cover dataset. Natural land cover classes in the N-lndex2 include forest,
wetlands, shrubland, and grassland; codes 141 through 143,152,171,190, and 195 in the
2011CDL-NLCD Hybrid Land Cover dataset. Equation used: N-lndex2 Area / HUC12 Area * 100.
(See also 2011 CDL-NLCD Hybrid Land Cover glossary definition).
% N-lndex2 in HCZ (2011) (%
natural cower in the HCZ)
Percent of the HUC12 that is in the Hydrologically Connected Zone (HCZ) and classified as
natural land cover (excluding barren land) by the 2011 CDL-NLCD Hybrid Land Cover dataset.
Natural land cover classes in the N-lndex2 include forest, wetlands, shrubland, and grassland;
codes 141 through 143,152,171,190, and 195 in the 2011 CDL-NLCD Hybrid Land Cover
dataset. Equation used: Area of N-lndex2 in HCZ / HUC12 Area * 100. (See also 2011 CDL-NLCD
Hybrid Land Cover and Hydrologically Connected Zone glossary definitions).
% Urban in WS (2011)
Percent of the HUC12 classified as urban cover by the 2011 CDL-NLCD Hybrid Land Cover
dataset. Urban cover classes include 'Developed, Open Space1 (code 121), 'Developed, Low
Intensity' (code 122), 'Developed, Medium Intensity' (code 123), 'Developed, High Intensity'
(code 124) in the 2011 CDL-NLCD Hybrid Land Cover dataset. Calculated as urban area divided
by HUC12 area, multiplied by 100. (See also 2011 CDL-NLCD Hybrid Land Cover glossary
definition).
% Urban in HCZ (2011)
Percent of the HUC12 that is in the Hydrologically Connected Zone and classified as urban
cover by the 2011 CDL-NLCD Hybrid Land Cover dataset. Urban cover classes include
'Developed, Open Space' (code 121), 'Developed, Low Intensity' (code 122), 'Developed,
Medium Intensity' (code 123), 'Developed, High Intensity' (code 124) in the 2011 CDL-NLCD
Hybrid Land Cover dataset. Calculated as urban area in the Hydrologically Connected Zone
divided by HUC12 area, multiplied by 100. (See also 2011 CDL-NLCD Hybrid Land Cover and
Hydrologically Connected Zone glossary definitions).
% Agriculture in WS (2011)
Percent of the HUC12 classified as agriculture cover by the 2011 CDL-NLCD Hybrid Land Cover
dataset. Agriculture cover classes includes cropland and pasture; codes 1 through 92,181,
182, and 204 through 254 in the 2011 CDL-NLCD Hybrid Land Cover dataset. Calculated as
43
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agriculture area in the HUC12 divided by HUC12 area, multiplied by 100. (See also 2011 CDL-
NLCD Hybrid Land Cover glossary definition).
Count of Animal Feeding
Operations in WS (INSTATE)
The count of Animal Feeding Operations in the watershed, within the state of Kansas. HUC8
indicator data was derived from HUC12 data provided by the state of Kansas. Source data used
was received via personal communication with Tom Stiles (State of Kansas) in May 2015.
"(INSTATE)" denotes that the indicator was only calculated for HUC areas within Kansas state
boundaries.
Median Stream TP
Concentration in WS (INSTATE)
The median total phosphorus concentration within the watershed, within the state of Kansas.
HUC8 scale total phosphorus concentration data was provided by the state of Kansas. Source
data used was received via personal communication with Tom Stiles (State of Kansas) in May
2015. "(INSTATE)" denotes that the indicator was only calculated for HUC areas within Kansas
state boundaries.
Design Flow of Major/Minor
Plants in WS (INSTATE)
The total discharge from the sum of all design flow discharges from "Mid Major" and "Major"
NPDES permitted dischargers with a design flow greater than 0.5 Million Gallons per Day
(MGD) within each HUC8, within the state. HUC8 scale NPDES data was provided by the state
of Kansas. Source data used was received via personal communication with Tom Stiles (State
of Kansas) in May 2015. "(INSTATE)" denotes that the indicator was only calculated for HUC
areas within Kansas state boundaries.
% Population Growth in WS
(2000-2010) (INSTATE)
The percent of population growth in watershed (2000-2010) based on census data (positive
values only). County scale data was processed using a weighted average according to county
size. Watersheds with negative growth were changed to no growth (zero change). Source data
used were the Intercensal Estimates of Resident Population for Counties: April 1, 2000 to July
1, 2010 (https://www.census.gov/popest/data/intercensal/county/CO-EST00INT-01.html).
"(INSTATE)" denotes that the indicator was only calculated for HUC areas within Kansas state
boundaries.
SPARROW Predicted
Incremental P Yield
Incremental total phosphorus yield from HUC8 predicted by SPARROW water quality model.
% Streamlength 303d-Listed
Nutrients (2015)
Percent of streamlength in the HUC12 listed as impaired due to nutrient-related causes and
requiring a TMDL under Section 303(d) of the Clean Water Act. Source data for calculating the
length of stream features that are 303(d) listed was the EPA Office of Water 303(d) Listed
Waters geospatial dataset. Only includes the length of stream features with "Nutrients",
"Organic Enrichment/Oxygen Depletion", "Algal Growth", or "Noxious Aquatic Plants" listed as
a parent cause of impairment. The denominator used for percentage calculations (total
streamlength) is the length of NHDPIus2 NHD Snapshot stream features plus any additional
custom-added streams in the 303(d) Listed Waters dataset. (See also 303(d) Listed Waters and
NHD Snapshot glossary definitions).
% Waterbody Area 303d-Listed
Nutrients (2015)
Percent of the area of lakes, estuaries, and other areal water features in the HUC12 listed as
impaired due to nutrient-related causes and requiring a TMDL under Section 303(d) of the
Clean Water Act. Source data for calculating the area of waterbody features that are 303(d)
listed was the EPA Office of Water 303(d) Listed Waters geospatial dataset. Only includes area
of waterbodies with "Nutrients", "Organic Enrichment/Oxygen Depletion", "Algal Growth", or
"Noxious Aquatic Plants" listed as a parent cause of impairment. The denominator used for
percentage calculations is the area of NHDPIus2 NHD Snapshot waterbodies in the HUC12 plus
any additional custom-mapped waterbodies in the 303(d) Listed Waters dataset. (See also
303(d) Listed Waters and NHD Snapshot glossary definitions).
Soil Erodibility, Mean in WS
Average soil erodibility (K) factor in the HUC12. 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.
Calculated as the mean of soil erodibility values in the HUC12.
Soil Erodibility, Mean in HCZ
Average soil erodibility (K) factor in the Hydrologically Connected Zone (HCZ) of the HUC12.
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. Calculated as the mean of soil erodibility values in
the Hydrologically Connected Zone of the HUC12. (See also Hydrologically Connected Zone
glossary definition).
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HUC8_Number of dams WS
Number of dams within each HUC provided by EnviroAtlas that uses the National Inventory of
Dams maintained by the US Army Corps of Engineers.
Segments with Nutrient TMDLs
Count (2015)
Count of surface water segments with a nutrient-related TMDL in the HUC12. Calculated as
the number of unique state-assigned surface water segment IDs in the HUC12 from the EPA
Office of Water TMDL Waters geospatial dataset with "Nutrients", "Organic
Enrichment/Oxygen Depletion", "Algal Growth", or "Noxious Aquatic Plants" listed as a parent
TMDL pollutant. (See also TMDL Waters glossary definition).
Critical Watershed Class Score
(INSTATE)
Mean watershed priority value on a scale from one to five, from lowest priority (1) to highest
priority (5). HUC8 and HUC12 scale data was provided by Jaime Gaggero (state of Kansas) in
April 2015. "(INSTATE)" denotes that the indicator was only calculated for HUC areas within
Kansas state boundaries.
% MS4 in Watershed
Percent of the HUC12 that is in Municipal Separate Storm Sewer Systems (MS4s). An MS4 is a
drainage system that collects and conveys stormwater from developed lands. Includes MS4s
that are regulated under the EPA National Pollutant Discharge Elimination System (NPDES)
stormwater program; non-regulated MS4s are not counted. Source data was a geospatial
dataset of MS4 boundaries developed circa-2010 by EPA Office of Waste Management
(acquired via personal communication). The MS4 boundary dataset was created from a list of
regulated MS4s, jurisdictional boundaries for municipalities and counties with regulated MS4s,
and urbanized area boundaries from the US Census Bureau. Equation used: MS4 Area / HUC12
Area * 100.
Distance to Outlet of the State
Inverse (INSTATE)
A spatial analysis was performed using a 30-meter resolution DEM to estimate average flow
lengths from each HUC8 outlet to the receiving HUC8 intersecting the state boundary. Outlet
HUC8s were scored as 10. A Jenks Method to identify natural statistical breaks was used to
rank those HUC-8 watersheds not already identified as outlet HUC-8s, with scores ranging
from 9 to 1. "(INSTATE)" denotes that the indicator was only calculated for HUC areas within
Kansas state boundaries.
Public Drinking Water System
(PWS) Score (INSTATE)
The total project score applied to the watershed contained within a Public Water Supply (PWS)
reservoir project area, as scored under the State Interest Priority Scoring Tool (SIPS). SIPS
considers 4 major metrics: percent of Water Assurance District population served, total
population to be served that participates in a Water Assurance District, the volume of
reservoir water that is in the Kansas Water Marketing Program, and number of interstate
watersheds draining to a PWS outside of state boundaries. "(INSTATE)" denotes that the
indicator was only calculated for HUC areas within Kansas state boundaries.
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Attachment 3: Kansas Stage 2 (HUC12) Screening Indicator Descriptions
Green denotes ecological indicators, red are stressor indicators, and blue are social indicators. All Kansas-specific
indicators are denoted with (INSTATE). These indicators are based on data that end at the state-line, therefore
watersheds were clipped to the state line and all metrics were calculated based on this area.
HUC12 INDICATOR
DESCRIPTION
Watershed Health index
(Statewide)
The statewide Watershed Health Index score for the HUC12 from the 2016 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
place to support healthy aquatic ecosystems. Source data were statewide Watershed Health
Index scores for HUC12s developed as part of the 2016 EPA Preliminary Healthy Watersheds
Assessment (February 8, 2017 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.
Watershed Health Index
(Eco regional)
The ecoregional Watershed Health Index score for the HUC12 from the 2016 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
place to support healthy aquatic ecosystems. Source data were ecoregional Watershed Health
Index scores for HUC12s developed as part of the 2016 EPA Preliminary Healthy Watersheds
Assessment (February 8, 2017 version). NOTE: PHWA scores/percentiles are not suitable for
comparing HUC12s that occur in different ecoregions to one another. Scoring of a given
HUC12 reflects its condition relative to all other HUC12s within the same ecoregion only.
Soil Stability, Mean in HCZ
Mean soil stability in the Hydrologically Connected Zone (HCZ) of 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 in the HCZ was calculated as the average of erodibility grid values in the HCZ per
HUC12. Mean soil stability was calculated as 1 - Mean soil erodibility. (See also Hydrologically
Connected Zone glossary definition).
% Urban in WS (2011)
Percent of the HUC12 classified as urban cover by the 2011 CDL-NLCD Hybrid Land Cover
dataset. Urban cover classes include 'Developed, Open Space1 (code 121), 'Developed, Low
Intensity' (code 122), 'Developed, Medium Intensity' (code 123), 'Developed, High Intensity'
(code 124) in the 2011 CDL-NLCD Hybrid Land Cover dataset. Calculated as urban area divided
by HUC12 area, multiplied by 100. (See also 2011 CDL-NLCD Hybrid Land Cover glossary
definition).
% Agriculture in WS (2011)
Percent of the HUC12 classified as agriculture cover by the 2011 CDL-NLCD Hybrid Land Cover
dataset. Agriculture cover classes includes cropland and pasture; codes 1 through 92,181,
182, and 204 through 254 in the 2011 CDL-NLCD Hybrid Land Cover dataset. Calculated as
agriculture area in the HUC12 divided by HUC12 area, multiplied by 100. (See also 2011 CDL-
NLCD Hybrid Land Cover glossary definition).
% Agriculture in HCZ (2011)
Percent of the HUC12 that is in the Hydrologically Connected Zone and classified as agriculture
cover by the 2011 CDL-NLCD Hybrid Land Cover dataset. Agriculture cover classes include
cropland and pasture; codes 1 through 92,181,182, and 204 through 254 in the 2011 CDL-
NLCD Hybrid Land Cover dataset. Calculated as agriculture area in the Hydrologically
Connected Zone divided by HUC12 area, multiplied by 100. (See also 2011 CDL-NLCD Hybrid
Land Cover and Hydrologically Connected Zone glossary definitions).
% Streamlength 303d-Listed
Nutrients (2015)
Percent of streamlength in the HUC12 listed as impaired due to nutrient-related causes and
requiring a TMDL under Section 303(d) of the Clean Water Act. Source data for calculating the
length of stream features that are 303(d) listed was the EPA Office of Water 303(d) Listed
Waters geospatial dataset. Only includes the length of stream features with "Nutrients",
"Organic Enrichment/Oxygen Depletion", "Algal Growth", or "Noxious Aquatic Plants" listed as
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HUC12 INDICATOR
DESCRIPTION
a parent cause of impairment. The denominator used for percentage calculations (total
streamlength) is the length of NHDPIus2 NHD Snapshot stream features plus any additional
custom-added streams in the 303(d) Listed Waters dataset. (See also 303(d) Listed Waters and
NHD Snapshot glossary definitions).
% Waterbody Area 303d-Listed
Nutrients (2015)
Percent of the area of lakes, estuaries, and other areal water features in the HUC12 listed as
impaired due to nutrient-related causes and requiring a TMDL under Section 303(d) of the
Clean Water Act. Source data for calculating the area of waterbody features that are 303(d)
listed was the EPA Office of Water 303(d) Listed Waters geospatial dataset. Only includes area
of waterbodies with "Nutrients", "Organic Enrichment/Oxygen Depletion", "Algal Growth", or
"Noxious Aquatic Plants" listed as a parent cause of impairment. The denominator used for
percentage calculations is the area of NHDPIus2 NHD Snapshot waterbodies in the HUC12 plus
any additional custom-mapped waterbodies in the 303(d) Listed Waters dataset. (See also
303(d) Listed Waters and NHD Snapshot glossary definitions).
Number of Animals (USDA
County) in WS (INSTATE)
The total number of animal units within each watershed, within the state. Animal unit data
was derived using a county size weighted average of the USDA Census of Agriculture 2012
county-scale data. "(INSTATE)" denotes that the indicator was only calculated for HUC areas
within Kansas state boundaries.
Number of Septic Systems in WS
(INSTATE)
The total number of septic systems within each watershed, within the state. HUC12 septic
system data was obtained from the EPA STEPL model input database (http://it.tetratech-
ffx.com/steplweb/models$docs.htm). "(INSTATE)" denotes that the indicator was only
calculated for HUC areas within Kansas state boundaries.
Segments with Nutrient TMDLs
Count (2015)
Count of surface water segments with a nutrient-related TMDL in the HUC12. Calculated as
the number of unique state-assigned surface water segment IDs in the HUC12 from the EPA
Office of Water TMDL Waters geospatial dataset with "Nutrients", "Organic
Enrichment/Oxygen Depletion", "Algal Growth", or "Noxious Aquatic Plants" listed as a parent
TMDL pollutant. (See also TMDL Waters glossary definition).
Critical Watershed Class Score
(INSTATE)
Mean watershed priority value on a scale from one to five, from lowest priority (1) to highest
priority (5). HUC8 and HUC12 scale data was provided by Jaime Gaggero (state of Kansas) in
April 2015. "(INSTATE)" denotes that the indicator was only calculated for HUC areas within
Kansas state boundaries.
Count (2011-2014) Conservation
Practices (INSTATE)
The count of conservation practices funded by NRCS, the Kansas Department of Agriculture
Division of Conservation (Conservation Districts), and Kansas 319 program - Watershed
Restoration And Protection Strategy (WRAPS) within the HUC12 over the 2011-2014 time
period. Source data was provided by Andrew Lyon (state of Kansas) in April 2015. "(INSTATE)"
denotes that the indicator was only calculated for HUC areas within Kansas state boundaries.
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Attachment 4: Kansas RPS Tool file names and contents
The following are RPS Tool files completed during this project and delivered to Kansas for statewide and watershed-
specific use. Except for KS RPS-Scoring-Tool-052416_BASE, all these files contain archived results for each geographic
area and Scenario as named. Other than differences in their screening results, these files are otherwise identical to the
master file.
RPS Tool File Name
Content
KS RPS-Scoring-Tool-052416_BASE
Kansas RPS Tool with all HUC8 and HUC12 data, no
screening content saved (master copy for all new
screening statewide or on HUC subsets)
KS RPS-Scoring-Tool-052416_SCENARIOl
Kansas RPS Tool with screening results for Scenario 1
KS RPS-Scoring-Tool-052416_SCENARIO2
Kansas RPS Tool with screening results for Scenario 2
KS RPS-Scoring-Tool-052416_SCENARIO3
Kansas RPS Tool with screening results for Scenario 3
KS RPS-Scoring-Tool-052416_LittleArkansas
Kansas RPS Tool with Stage 2 results for HUC12
screening of Little Arkansas HUC8
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