United States
Environmental Protection
Agency
Environmental Research
Laboratory
CorvaJIis, OR 97333
EPA/eoaG-90072
August 199o
and Development
4>EPA APPLICATION OF THE SYNOPTIC APPROACH
TO WETLAND DESIGNATION:
A CASE STUDY IN WASHINGTON
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DISCLAIMER
The research described in this report has been funded wholly or in part by the United
States Environmental Protection Agency under Contract #68-C8-0006 to NSI Technology
Services Corporation. Mention of trade names or commercial products does not constitute
endorsement or recommendation for use.
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ABSTRACT
The synoptic approach is a rapid assessment method designed to provide a context for
evaluating landscape sensitivity to cumulative wetland loss and to complement site specific
information used in reviewing permit applications to alter wetlands. The objectives of this
study were to: 1. test the utility of the synoptic approach in prioritizing wetland "functional
uses" (including State surface water designated uses) within the state of Washington; 2.
demonstrate and improve this method's ability to identify wetland resources that are
ecologically important or sensitive to change; 3. investigate the applicability of the synoptic
approach in the landscape assessment of a relatively small watershed; and 4. implement
the transfer of the research products to State wetland managers. Readily available data
were compiled for Washington into a set of map overlays. The overlays were synthesized
to produce indices of landscape input and wetland capacity for hydrologic, water quality,
and life support functions, cumulative impacts and future wetland losses for watersheds
within the State. The synoptic approach identifies wetland functions not included in
Washington's designated uses of surface waters. The approach is appropriate for a state
with a generalized set of water quality standards such as Washington's, i.e., one that has
no specific designated uses relative to wetland hydrologic and water quality improvement
functions. The products of this assessment will be useful in regional planning and in the
development of State wetland conservation plans.
u
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TABLE OF CONTENTS
DISCLAIMER i
ABSTRACT .-. ii
LIST OF TABLES v
LIST OF FIGURES vi
ACKNOWLEDGEMENTS vii
INTRODUCTION 1
OBJECTIVES 3
OVERVIEW OF THE SYNOPTIC APPROACH 4
ANALYSIS OF WASHINGTON DATA 8
DATA COLLECTION 8
MAP DEVELOPMENT 8
Hydrologic Input 8
Water Quality Input 11
Life Support Input 12
Wetland Capacity 12
Cumulative Impacts 15
Designated Uses of Surface Waters 15
TECHNICAL INFORMATION TRANSFER '. 16
FINAL PRODUCTS 22
DISCUSSION 23
CONCLUSION 26
LITERATURE CITED 28
m
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APPENDIX I. Maps of overlay components used for deriving synoptic
indices 31
APPENDIX II. Human population1 (1970 and 1980), agricultural acreage2 (1974
and 1982), and (RTE) by county : 44
APPENDIX III. Hydrologic unit composition of counties. Total area is given
for each county, along with the partial area for each component
hydrologic unit (a hydrologic unit need not be entirely contained
within one county, but may cross several). The percent is the
proportion of total county area found in that hydrologic unit. . 46
APPENDIX IV. Derived index maps 54
APPENDIX V. Rankings of hydrologic units for hydrology, water quality, and
life support cumulative effects 72
APPENDIX VI. A synoptic approach to wetland planning in small watersheds:
Mill Creek feasibility analysis 74
IV
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LIST OF TABLES
TABLE 1. Summary of measures used to estimate landscape indices 6
TABLE 2. Curve number (percent runoff) for pairwise combinations of hydrologic
soil groups and land uses (adapted from Rawls et al. 1981) 13
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LIST OF FIGURES
Figure 1. Water Resource Inventory Areas 9
Figure 2. Hydrologic Input 10
Figure 3. Water Quality Input (non-normalized) 14
Figure 4. Life Support Input 17
Figure 5. Wetland Capacity 18
Figure 6. Cumulative Impacts (non-normalized) 19
Figure 7. Future Loss : 20
Figure 8. Washington Designated Uses of Surface Waters 21
VI
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ACKNOWLEDGEMENTS
This report was submitted in fulfillment of contract #68-C8-0006 by NSI Technology
Services Corporation under the sponsorship of the U.S. Environmental Protection Agency.
This report covers a period from July, 1989 to August, 1990; work was completed August,
1990. We wish to thank Dr. Eric M. Preston for his support as Wetlands Team Leader.
We acknowledge the cooperation of staff members of the state agencies who provided
data and review of the pilot study. Robert Hippie, Daren Moore and Donna Frostholm
assisted in the collection of data. Jeff Irish designed and produced the maps. Kristina
Heike edited the final document. Finally, we wish to think Dr. Sam Williamson, Dr.
Spence Peterson, Dr. Naomi Detenbeck, Ann Hairston and Lisa Ellingson for their helpful
suggestions and comments in reviewing this document.
vu
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INTRODUCTION
Wetland protection under Section 404 of the Clean Water Act has typically taken
a traditional approach to impact assessment. Under this approach, a permit for placement
of dredged and fill material is issued if significant impact will not occur to waters of the
United States. When considered together, however, the aggregate impact of individually
permitted activities could cause significant degradation and damage to the environment.
The quantification of these impacts, pursuant to the Clean Water Act, has been hampered
by the lack of a standardized approach to cumulative impact assessment. The goal of
cumulative impact assessment is to evaluate the cumulative effects of these individual
impacts occurring over the entire landscape and through time (Bedford and Preston 1988;
Gosselink and Lee 1989).
Compliance with the National Environmental Policy Act requires cumulative impacts
to be considered. However, few cumulative impact assessment (CIA) tools are currently
available. Dickert and Tuttle (1985) applied a CIA method to a small watershed that
emphasizes field measurements and interpretation of land use changes over the past 50
years to develop a model land use planning system appropriate for California coastal
watersheds. Walker et al. (1987) used maps of historical changes in Prudhoe Bay, Alaska,
to assess the indirect effects of oil field developments. Johnston et al. (1988) analyzed
land use and water quality data from different years with a Geographic Information System
and statistical methods to identify empirical relationships between resource loss and
environmental degradation. While these approaches yield valuable information on
landscape function, they do not provide an easily executed, standardized method for
assessing landscape sensitivity to wetland loss. All of the above mentioned approaches rely
on data that may not be available in many parts of the country or would be prohibitively
expensive or time consuming to collect for broad scale studies. The Wetlands Research
Program (WRP) of the U.S. Environmental Protection Agency (EPA) has ongoing research
to examine the environmental effects of cumulative wetlands loss. As part of this effort,
a method is being developed that assembles generally available data into a scientific
framework that ranks watersheds according to the relative importance of wetland function
and wetland loss. This method provides a landscape perspective and is referred to as the
synoptic approach (Abbruzzese et al. 1990a submitted). The approach is being developed
as a rapid and inexpensive assessment technique for use in routine 404 permit requests.
To further development of the synoptic approach, WRP sought opportunities to
conduct statewide pilot applications. Coincident with this, EPA's Office of Wetlands
Protection (OWP) expressed interest in determining whether the synoptic approach could
be used in the development of state wetland water quality standards. The federal Clean
Water Act grants to the states broad authority for developing standards that protect their
water resources. By extending these water quality standards to include wetlands, the states
can exert direct control over projects in or affecting wetlands (U.S. EPA 1989). This
application of state standards requires that specific classes of wetland be assigned
1
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appropriate "designated uses."
A synoptic case study could offer insight on how a landscape perspective may
influence the assignment of designated uses to wetlands. EPA Region 10 selected
Washington for this pilot study, through its Regional Applied Research Effort Program
(RARE), to support a major program initiative of Region 10 and OWP involving the
development of water quality standards for wetlands. Also, EPA presumed that data
generated by the study could be used to help design new regulatory strategies for
protecting the State's remaining wetlands. A similar case study was conducted in the State
of Louisiana (Abbruzzese, et al. 1990b).
The study described in this document was conducted to determine whether the
synoptic approach could be used in the development of state water quality standards.
Development of the synoptic approach is not complete; an explicit goal of this pilot project
was to improve the method. The results of the synoptic analysis are not meant to be final
or conclusive, and should only be taken to illustrate the utility of this method in developing
state water quality standards.
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OBJECTIVES
The primary objective of this research was to test the utility of the synoptic approach
in prioritizing wetland "functional uses" (including State surface water designated uses) at
the watershed scale. The second objective was to demonstrate and improve this method's
ability to identify wetland resources that are ecologically important or sensitive to change.
A third, and ancillary, objective was to investigate the applicability of the synoptic
approach in the landscape assessment of a relatively small watershed for wetland planning
activities i.e., Millcreek, Appendix VI. A fourth objective was to interactively implement
the transfer of the research products to state wetland managers. The specific approach
was to:
1. Evaluate and comparatively rank wetland landscapes (i.e., watersheds) based
on their functional attributes and sensitivity to change;
2. Identify potential wetland functions and values from maps depicting the
ranked wetland landscapes;
3. Compare the potential wetland functions and values with existing adjacent
or contiguous surface water use designations;
4. Identify ecologically important wetlands or those sensitive to change based
on the comparative rankings;
5. Develop a workplan for the analysis of wetland landscape data on a selected
small watershed (Appendix VI); and
6. Transfer to appropriate EPA Regional and Washington State natural
resource management staff the ongoing status and technical results of the
pilot project.
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OVERVIEW OF THE SYNOPTIC APPROACH
The synoptic approach is a rapid, inexpensive method for assessing the cumulative
effects of wetland loss on landscape function. The method was designed for use in routine
wetland evaluation and management work. It should serve to complement existing
management practices, including the assessment of local value and function, by providing
an anticipatory approach to wetland protection.
The approach can be applied to a variety of geographic scales and regulatory issues,
including: 1. the identification of priority areas for research and wetland protection at the
national scale; 2. providing a context for wetland permitting and advance wetland planning
at the regional or state scale; and 3. identification of sites where wetland restoration and
creation efforts could be beneficial at the watershed scale.
. The approach uses generally available maps and data to derive relative rankings of
watersheds within a study area using indices of the ecological function wetlands perform
(Preston and Bedford 1988; Leibowitz and Preston, pers. comm.). The functions are
grouped into three general categories, including: 1. hydrology~the ability of wetlands to
attenuate peak hydrologic flow, desynchronize floods, and stabilize shorelines; 2. water
quality~the capability of wetlands to retain, remove, or detoxify pollutants; and 3. life
support-the ability of wetlands to supply the required habitat and food chain support of
wetland dependent biota.
The assessment indices were developed as part of a conceptual landscape model
(Leibowitz and Preston, pers. comm.). They provide relative measures of the functions
wetlands contribute to the landscape, the risk of loss of landscape function from wetland
loss or alteration, and the social significance of such loss.
The first four indices (primary indices) are based on data we have collected and
interpreted. Three additional derived indices (secondary indices) are based on the primary
indices and are addressed in the Discussion section of this report. The primary indices
are:
1. Landscape Input-materials produced by the landscape which can potentially be
processed or supported by wetlands; thus, an index of the opportunity for wetlands
to contribute to landscape function within a cumulative impact area (watershed).
2. Wetland Capacity-the potential ability of wetlands to promote landscape function
through processing or support of landscape inputs.
3. Cumulative Impacts-wetland losses that have occurred historically.
4. Future Loss-wetland impacts that are likely to occur in the future.
4
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Since data are not generally available to summarize the relationships characterized
by these indices, surrogate measures of the indices were chosen. For example, to
calculate landscape input for hydology (i.e., hydrologic input), measures of watershed area,
precipitation, runoff potential, slope and channel length were used. The following
approach summarizes how the relative rankings of watersheds were produced: 1. selection
of the appropriate surrogate measure for each index (Table 1); 2. collection of mapped
and tabular data; 3. analysis of the data to derive primary data layers; and 4. combination
of the data layers to produce the relative watershed rankings.
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TABLE l. Summary of measures used to estimate landscape indices.
Landscape Index Definition
Hydrologic Input Precipitation x area x runoff x fl+slope)
Length
Precip (cm) = precipitation contours digitized from Cummans et al. (1975)
prorated to watershed boundaries
Area (ha) = area of water resource inventory areas from Washington
Department of Water Resources (1969)
Runoff (percent) = runoff curve number as illustrated in Table 2
Slope (m/m) = slope calculated from USGS 1:250,000 topographic maps,
by subtracting the elevation
Length (m) = length of the main channel planimetered from 1:250,000 USGS
topographic maps
Water Quality Input Length of Polluted Streams
Length of Polluted Streams (km) = length of streams listed as "partially
supporting" or "nonsupporting" of designated
uses in State 304(1) Report.
Life Support Rare, Threatened & Endangered Species
Rare Threatened 6
Endangered Species (number) = total number of rare, threatened, and endangered
species per WRIA from Washington Department of
Wildlife (1990) and Washington Department of
Natural Resources (1990)
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TABLE 1. (cont.)
Landscape Index Definition
Wetland Capacity Wetland Area
Wetland area (ha) = proportion of wetland area derived from dot grid samples
of 1:250,000 USGS Land Use/Land Cover maps
Cumulative Impacts Hydric Area-Current Wetland Area
Hydric Area-
Current Wetland Area (ha) = Area of hydric soils from county soil surveys
and SCS hydric soils list (Hydric Soils
Committee 1987) prorated to WRIA using dot grid
samples. Current wetland area as above
Future Loss Risk x Wetland Area
Risk = agricultural growth x 87/95 + population growth x 8/95
agricultural growth = Agr 84 - Agr 72
Agr 72 Agricultural land
8 (US Bureau of the Census 1974, 1982a)
prorated by Appendix II.
population growth = pop 80 - pop 70
pop 70 Human Population
10 (US Bureau of the Census, 1972, 1982b)
prorated by Appendix II.
wetland area = see above
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ANALYSIS OF WASHINGTON DATA
DATA COLLECTION
Sixty two watersheds (Figure 1) were delimited using Washington Department of
Ecology's (DOE) "water resource inventory areas" (WRIA) (Washington Department of
Water Resources 1969).
Data for calculating the four primary indices for each watershed were collected from
a variety of federal and State agencies, including the U.S. Geological Survey, U.S. Bureau
of the Census, DOE, Washington Wildlife and Natural Resources and Washington State
University. In addition, existing State surface water use designations were mapped for
comparison with synoptic watershed rankings. Other agencies were contacted for
information, including the Department of State Parks and Washington Nature Conservancy.
The quality assurance of the data was assessed in terms of its: 1. level of general
availability (nationwide) and comparability with data sets for other states; 2. scale of
resolution; 3. the degree of replication of techniques employed in obtaining the data. A
5% quality control check was performed on areal, linear and elevation measurements taken
from maps and data recorded from other sources. An error level less than 5% was the
target. A person, other than the original data collector, replicated every twentieth
measurement to check for accuracy. The result of the check was that the 5% accuracy
criterion for measurements taken from maps was always met. This accuracy only applies
to primary data measurements, and not the final combined maps.
MAP DEVELOPMENT
To produce a map for a particular index, it was first necessary to produce maps of the
index components (Appendix I). Several of the maps, e.g. cumulative impacts, are
presented in both the non-normalized and normalized forms to illustrate potential
applications to particular management questions, i.e., absolute loss vs. percent loss.
Following is a brief description of the components and data sources for these maps (maps
produced using the ARC/INFO Geographic Information System):
Hydrologic Input
The estimate of hydrologic input (peak discharge) has both a spatial and temporal
dimension; it is calculated as the product of precipitation, watershed area, runoff potential,
and stream channel slope divided by channel length (Figure 2).
8
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Figure 1
Canada
Water Resource
Inventory Areas
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HYDROLOGIC INPUT
Canada
- egon
Figure 2
91 - filer ieitirce Iiteilor; irti
Precip. x Area I Runoff
x (1+Slope) / Length
|| 35 90
111 90 190
1 90 - 410
4 10
1070
i -
7 -
IS -
II -
25 -
31 -
37 -
43 -
49 -
55 -
61 -
401
5(1
101
871
(58
42
U7
51
111
102
87
2 -
I -
14 -
20 -
2! -
32 -
31 -
44 -
50 -
5« -
12 -
40S
174
491
600
(08
75
257
73
II
6S
164
3 -
I -
15 -
21 -
27 -
33 -
39 -
45 -
51 -
57 -
197
145
588
713
420
37
240
331
39
108
4 -
10 -
16 -
22 -
21 -
34 -
40 -
46 -
52 -
56 -
1066
260
575
592
303
94
167
1 19
67
109
5 -
II -
17 -
23 -
29 -
35 -
41 -
47 -
53 -
59 -
[later Resource Inventory Area]
245
183
341
266
471
108
62
216
40
If
6 -
12 -
II -
24 -
SO -
36 -
42 -
41 -
54 -
60 -
395
219
491
701
171
104
35
242
51
224
Prtpirfd bj DSIPA lelliidi Icieireh Progrim. USIPA Ii>ironnciIiI teitirch lib. Coritllii. Orej»i
10
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Mean annual precipitation contours (Cummans et. al. 1975) were digitized and
then pro-rated to watershed units. An estimate of the volume of water entering the system
is obtained by multiplying precipitation by drainage area for each watershed.
Runoff potential is derived from a modification of the Soil Conservation Service's
(SCS) curve number (Rawls et al. 1981; SCS 1986). The percent runoff for a drainage unit
is calculated as the weighted average of the runoff value for each pairwise combination of
hydrologic soil group and land use. Proportions of land uses and hydrologic soil groups
were estimated from dot grid samples of 1:250,000 scale U.S. Geological Survey (USGS)
Land Use/Land Cover maps and a State soil map (Loomis et. al. 1985), respectively.
Runoff values for these combinations (Table 2) were adapted from Rawls et al. (1981);
the joint percentage of the soil and land use areas is used as weights. Thus, runoff is given
by:
Runofftotai = Z Z Runoffy x Weighty
i J
= Z Z Runoffij x Area;/Areatotal x Areaj/Areatotal
i J
where i is an index for the four soil groups and j is an index for the six land uses. As an
example, assume a drainage unit with half of all soils belonging to group A and the other
half to group C, and with agriculture representing 25% of total land use and the remaining
75% in forest. Using Table 2 to obtain the pairwise runoff values, percent runoff for that
unit would then be (63 x [0.5 x 0.25]) + (43 x [0.5 x 0.75]) + (77 x [0.5 x 0.25]) + (75 x
[0.5 x 0.75]) = 61.75.
Total discharge is obtained by multiplying the volume of precipitation by percent
runoff. To estimate the temporal distribution, total discharge was multiplied by channel
slope and divided by channel length, since peak discharge for a given event increases with
slope and shorter channel lengths. Slope was calculated by subtracting the elevation at
10% of the channel length from elevation at 85% of the channel length, then dividing the
difference by 75% of the total channel length (Cummans et al. 1985). Length of the main
channel was measured using an electronic planimeter. It should be emphasized here that
this method provides an estimate. The units of measurement were arbitrarily chosen.
Also, since we do not currently have a method for calculating water retention by upstream
wetlands, the estimate does not include the import of water from upstream units.
Water Quality Input
Water quality input (Figure 3), or the degree of point and nonpoint source
pollution, was estimated from State water quality data, since data on pollutant loading rates
are not readily available. Input was calculated as the length of streams inventoried that
11
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were listed as "partially supporting" or "nonsupporting" of State and federal designated uses
(such as "swimmable" or "fishable") in the State's 304(1) Report (Washington Department
of Ecology 1989). No data were recorded in the State 304(1) Report for twelve of the
Sixty-two WRIA's, suggesting that streams were not sampled in those units. Those units
were assigned a "no data" value and a rank of 1 to indicate a probable low degree of
pollution (Figure 3).
Waterbodies located in multiple WRIA's, i.e., portions of the Columbia River, were
omitted from the study to avoid double counting of stream reaches. Length of polluted
streams is the surrogate used; however we do not know what proportion of all streams this
represents, since the intensity of stream sampling is not known.
Life Support Input
We used the number of rare, threatened or endangered wetland dependent species
present as a surrogate for life support input (Figure 4) (Washington Department of
Wildlife 1990; Washington Department of Natural Resources 1990). This is based on the
assumption that these species represent the portion of wetland biota that are most sensitive
to habitat destruction.
Wetland Capacity
Wetland capacity (Figure 5) is a measure of the ability of wetlands to attenuate
peak hydrologic flow, process pollutants and provide habitat. These complex relationships
are difficult to evaluate because of a lack of existing data; therefore, wetland area derived
from USGS Land Use/Land Cover maps, as described above, is used as a surrogate for
wetland capacity. Note that twenty three of the WRIA's show a zero value for wetland
area (Figure 5). This is probably due to the scale of the analysis, rather than an absolute
absence of wetlands in the watersheds. Either the map scale (1:250,000) is too small to
depict small wetlands present on the ground or the dot grid used was too widely spaced
to count a small percentage of wetlands present on the map.
12
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TABLE 2. Curve number (percent runoff) for pairwise combinations of hydrologjc sofl
groups and land uses (adapted from Rawls et aL 1981).
Land Use
Agricultural
Land
Hydrologic Soil
A B
63 69
Group
C
77
D
82
Forest Land 43 64 75 81
Miscellaneous/ 68 78 84 86
Barren Land
Urban or 55 71 83 88
Built-up Land
Water 100 100 100 100
Wetland 45 66 77 83
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WATER QUALITY INPUT (NON-NORMALIZED)
Canada
egon
39 - liter Kcitircc lucilor; irti
Length of Polluted Streams (km)
0-0
Figure 3
0 - 73
73 - 120
120 - 470
1 - 417
7 - 230
13 - 58
19 - 88
25 - 105
31 - MO DATA
J7 - 202
43 - NO DATA
4« - 171
55 - 78
II - NO DATA
2
I
1 4
20
28
32
38
< <
50
II
1,2
0
235
70
0
151
158
0
HO DAM
NO DATA
If
115
I
9
15
21
27
33
3t
45
51
5V
12
153
45
76
70
113
103
44
NO DATA
39
4
I 0
18
22
28
34
40
4C
52
58
0
227
41
230
1 10
236
NO DATA
44
104
DO DATA
5
1 1
17
23
29
35
41
<7
53
59
228
71
0
253
21
171
74
0
NO DATA
65
[later Resource Inventory Area]
6 - o
12 - NO DATA
16 - 0
24 - 14
30 - 73
36 - NO DATA
NO DATA
0
11
53
42
II
II
Prewired bj USKPA 11 U « n d s teseirck Projnn. USEPA En T i r onmt n 11 I letetrch Lib, Cornllii. 0 r e ( o l
14
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Cumulative Impacts
Wetland impacts that have occurred in the past were estimated as the amount of
original wetland area lost (Figure 6). Area of hydric soils was used as a surrogate for
historic wetland area, using county soil surveys and the SCS hydric soils list (Hydric Soils
Committee 1987). County soil data were prorated to WRIA's using dot grid samples from
the WRIA map overlaid on a Washington State map, with county boundaries, at the same
scale. Many lands in federal ownership in Washington have no county soil surveys or other
soils data available from which to estimate area of hydric soils, i.e.: Makah and Quinalt
Indian Reservations; Mt. Rainier, Olympic and North Cascades National Parks; Ft. Lewis
and Bremerton Military Reservations; and Okanogan, Mt. Baker-Snoqualmie, Gifford
Pinchot, Kaniksu and Umatilla National Forests. In these areas estimates were derived
from a state soil association map (Loomis et. al. 1988) and averaged with estimates from
neighboring counties. Current wetland area was obtained as described above. It should be
noted that some areas, especially around lakes and estuaries, show a net wetland gain using
this method. This is probably an error caused by inconsistencies in the classification of
wetlands and open water in county soil surveys and the U.S. Geological Survey land
use/land cover maps. However, there may be net wetland gains in some watersheds in the
Columbia Basin area of the State, e.g., WRIA's numbers 39, 44 and 45, associated with
increases in irrigated agriculture (Office of Technology Assessment 1984).
Future Loss
Agricultural conversion and urban expansion have historically accounted for 85 and
10% of national wetland loss, respectively (Tiner 1984). Thus, risk of future wetland loss
was based on recent trends in agricultural and population growth. We derived a risk factor
by using a weighted average of the annual rate of agricultural growth between 1974 and
1982 (U.S. Bureau of the Census 1974, 1982a) and population growth between 1970 and
1980 (U.S. Bureau of the Census 1972, 1982b) (Appendix II). Since these data are
reported by county, the county data were prorated to the watershed units using the
weighting factors in Appendix III. The proportions of wetland loss reported by Tiner
(1984) were used as weights. The risk factor was multiplied by current wetland area to
derive future loss (Figure 7).
Designated Uses of Surface Waters
Four use categories were derived from State wetland water quality standards
(Washington Code Reviser 1988): 1. Class AA (extraordinary); 2. Class A (excellent); 3.
Class B (good); 4. Class C (fair). Streams assigned to the above uses were mapped
(Figure 8) according to their water body identification number (Washington Department
of Ecology 1989). No streams were listed as Class C.
15
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TECHNICAL INFORMATION TRANSFER
Information transfer to EPA Region 10 and Washington resource agency staff was
accomplished through technical seminars. Fundamental to this strategy was the
participation of EPA and State technical staff in the preparation and review of map
products and narrative reports. Two technical seminars were attended by EPA regional
staff and representatives from Washington's DOE. The objectives of these seminars were
to: 1. introduce the synoptic approach (July, 1989); and 2. present preliminary results of
the Washington analysis (April, 1990). As a result of discussions at the July, 1989 meeting,
an amendment was made to the study design to include a summary of how the synoptic
approach could be used in wetland planning for a small watershed. Questions and
concerns about the approach and its applications, raised at the April, 1990 meeting, were
addressed in subsequent phone conversations and correspondence. A third seminar will
be scheduled in fall of 1990 to present final results.
16
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LIFE SUPPORT INPUT
Canada
egon
31 - liter Rcioirec Inteitorj iret
Rare, Threatened 4 Endangered
Species ( number )
0.0 4.7
Figure 4
[HJ 4.7 6.5
pli!] 6.5- 9.0
9.0 - 12.0
i
7
19
19
25
31
37
43
49
55
ft!
11.0
12.0
1.0
5.0
1.0
9.0
90
to
12.0
5.0
I.I
2
I
14
20
26
32
38
44
50
58
t,2
I
10
4
I
II
7
7
5
7
0
8
3
9
15
21
27
33
31
45
51
57
.
2.0
11.0
6.0
3 .0
30
4
10
It
22
21
34
40
46
52
56
6 .0
10.0
7.0
11.0
10.0
7.0
to
2.0
5
II
17
2:>
29
36
41
47
53
:, s
[later Resource Inventory Area]
I
1C
4
I
10
6
10
I
3
4
I
II
II
24
II
II
42
4fl
54
SO
4 . 0
6.0
5.0
110
10.0
9.0
8.0
9.0
3.0
7 .0
Prtpirtd bj 1ISEPA Itlllldi tticirek Pro|rim, USEPi In i i r onmt i t i I teieircb Lib. Corilllil, Ortjoi
17
-------
IfETLAND CAPACITY
Canada
Oregon
38 - liter Kcioirce Uicntorj Arei
fetltnd Area ( b a )
0 - 0
Figure 5
0 - 560
560 - 1975
1975 - 10845
1 - 2321
7 - 2448
13 - 411
II - 286
25 - 0
31 - 4»7
37 - 10841
43 - 0
41 - 4874
55 - 521
81 - 0
2 -
8 -
14 -
20 -
26 -
32 -
38 -
44 -
50 -
58 -
62 -
0
891
1088
1934
1568
500
539
566
51 1
0
0
3 -
9 -
15 -
21 -
27 -
33 -
39 -
45 -
51 -
57 -
7227
0
449
6771
0
0
2620
2110
0
0
4 -
10 -
16 -
22 -
26 -
34 -
40 -
46 -
52 -
56 -
525
0
1387
4450
2551
1050
0
0
545
1200
5 -
11 -
17 -
23 -
29 -
35 -
41 -
47 -
53 -
59 -
2051
1425
0
1628
49!
0
7846
0
0
0
[later Resource Inventory Area]
6 -
12 -
16 -
24 -
30 -
36 -
42 -
48 -
54 -
80 -
1206
0
348
3510
527
6
1518
0
1092
Prtpirti bj USEPJ tetliiii leltirck Projrim, OSIPt ID T i r o nmt n t i I leltirch Lib. Cirnllil. Orejol
18
-------
CUMULATIVE IMPACTS (NON-NORMALIZED)
Canada
egon
39 - liter Eetoiree liitilery Irei
Hydric Area -
Current lelland Area (ha)
I 1 -1055 - 1640
1640
3025
Figure 6
3025 - 6625
6625 - 22605
1 - 11617
7 - 21931
13 -
19 -
25 -
SI -
37 -
43 -
t9 -
55 -
81 -
4204
(441
3)02
3556
5051
3412
5173
2702
1499
2 -
» -
14 -
20 -
26 -
32 -
31 -
44 -
50 -
5» -
62 -
2278
(688
2675
8493
4902
850
331
-238
-2
2593
2601
3 - 4254
9 - 4615
15 - 9216
21 - 10737
27 - 234«
33 - 316
39 - -955
45 - -1054
51 - 14(2
57 - 1612
4 - 15464
10 - 9023
932
itii
-163
7186
1723
3)2
5754
4436
16 -
22 -
28 -
34 -
40 -
46 -
52 -
58 -
5 - 8753
11 - 8420
17 - 6155
23 - 13822
29 -
35 -
41 -
47 -
53 -
59 -
844
5171
(40
819
18)9
2656
[later Resource Inventory Area]
12 -
18 -
24 -
30 -
3S -
42 -
48 -
54 -
(0 -
2944
2049
8414
9716
2069
245)
2S97
22603
2872
3106
Prtpirtd k; DSIPl Ictlndt Rxcireh Projnm. USKPI En» i r onme n 1 > 1 teteirch Lib, Cortillii. Origin
19
-------
FUTURE LOSS
Canada
31 - lit
egon
tionret Inicnlorj ll
Risk i !e t 1 an d Area
-29.3 - -0.1
Figure 7
-0.1 0.0
0.0 - 6.4
6.4 - 72.4
7
II
19
25
31
37
41
II
61
-2.s
58.6
3.7
-1.0
0.0
-15
-199
I.I
4 .7
-3.7
0 .0
B
1 I
20
28
44
50
58
0.0
140
5.7
4 . 4
4 . 1
-i .a
-12
2.5
2 . 0
0 .0
o o
I
9
15
2 I
27
33
31
45
51
57
113
I.I
154
619
I.I
0.0
-29 3
72 4
0.0
00
4
10
16
22
2B
34
40
46
52
SB
2.3
0.0
12.4
I .0
17.0
2.5
0.0
0.0
2.6
9. I
5
1 1
1 V
23
29
3!,
< 1
II
53
It
later Resource Inventory Area]
28.9
ll.S
o.o
65
-2.7
0.0
25.2
0.0
0.0
0.0
6 -
It -
24 -
30 -
36 -
48 -
60 -
7.4
0.0
0.3
45.0
0.0
3.2
0.0
2. 1
0.0
6.1
Prtpartd bj USUJ lellildt lit
rh Pro(nn
OSEPi En
20
-------
WASHINGTON DESIGNATED USES
OF SURFACE WATERS
Figure 8
Class AA (Extraordinary)
Class A (Excel lent)
Cl
B (Good)
Pr
-------
FINAL PRODUCTS
The final products of this pilot study are the following:
1. Maps, generated with the ARC/INFO Geographic Information System,
depicting rankings of Washington's "water resource inventory areas" according
to the synoptic indices and the component data layers for each index,
including:
o Hydrologic input
—mean annual precipitation
-total drainage area
-potential runoff
—stream channel slope
—channel length
o Water quality input
-nonpoint water quality input
o Life support input
o Wetland capacity
o Cumulative impacts
o Future risk
-agricultural growth (1974-1982)
-human population growth (1970-1980)
o Future loss
2. Map of Washington's "designated uses" of surface waters
3. Floppy diskette with all data collected for the study
4. ARC/INFO data tapes (for use with Geographic Information System)
22
-------
DISCUSSION
The derived (secondary) indices, mentioned in the "Overview of the Synoptic
Approach" section of this report, can be discussed in terms of wetland functions and
sensitivity to change. The concepts incorporated in the indices are central to the synoptic
approach, although methods to measure the indices are still in the developmental stage.
The derived indices are defined here and some of the maps generated for them (Appendix
IV) are used for illustrative purposes:
Landscape Sensitivity-landscape input into wetlands divided by wetland capacity.
This is an index of the potential "loading" of wetlands by landscaping inputs.
Sensitivity = Input/Capacity
Since sensitivity is the input divided by capacity, the twenty three units with zero
wetland capacity (Figure 5) were assigned an "undefined" value for sensitivity and
a rank of 4 to reflect "infinite" sensitivity (Figure IV.1-IV.3). Units, such as unit 12
with no water quality input data and zero wetland capacity were assigned a "no
data" value for water quality sensitivity and a rank of 1 (Figure IV.2). The same
logic was applied to cumulative effects (Figure IV.7-IV.14) and wetland significance
(Figure IV.15-IV.17).
Cumulative Effects-fthe likelihood of changes in landscape function caused by
wetland impacts, estimated as the product of sensitivity and impacts (historic and
future).
Cumulative Effects = Sensitivity x Cumulative Impacts
Wetland Significance-the significance of wetland loss to potential beneficiaries of
wetland function, calculated by multiplying cumulative effects by some specific use
(i.e., a population of interest or area of some land use).
Wetland Significance = Cumulative Effects x 1980 population
The identification of relative wetland function can be achieved by comparing landscape
inputs with wetland capacity for a given function. Several of the WRIA's surrounding the
Puget Sound can be used to illustrate the concept. For example, compare values for
hydrologic inputs in units 1 (Nooksack), 3 (Lower Skagit-Samish) and 5 (Stillaguamish) east
of the Sound with values in units, 15 (Kitsap), 16 (Skokomish-Dosewallips) and 18 (Elwha-
Dungeness) west of the sound (Figure 2). Hydrologic inputs in units 1, 3 and 5 are
relatively low compared to inputs in units 15, 16, and 18. On the other hand, wetland
capacity in units 1, 3 and 5 (Figure 5) is relatively high, compared to wetland capacity in
units 15, 16 and 18. This suggests that units 15, 16 and 18 are relatively more sensitive
23
-------
than units 1, 3 and 5 to the hydrologic effects of wetland loss, as illustrated by the
"hydrologic sensitivity" map (Appendix IV).
The addition of the cumulative impacts component to the indices for wetland function
provides a tool for identifying landscapes that have potentially suffered from wetland loss.
Cumulative impacts for units 15 and 18 (Figure 6) are relatively high compared to those
for unit 3; high sensitivity and high impacts suggests greater likelihood of loss of landscape
function as illustrated by the map for "hydrologic effects" (Appendix IV). In addition, the
relatively high human population density in the units surrounding the Sound implies that
such loss of the hydrologic function performed by wetlands could have high social
significance, as illustrated by the "hydrologic significance to humans" map (Appendix IV).
The products of the Washington statewide assessment can be used to identify
functions (or "uses") (U.S. EPA 1990) and areas sensitive to impacts, at the regional or
watershed scale, not identified in existing surface water use designations. Washington's
Water Quality Standards (Washington Code Revisor 1988) list a suite of uses (such as
water supply, wildlife and navigation) and physical, chemical and biological criteria
according to each "criteria class" which range in value from "extraordinary" to "fair."
Wetlands are not mentioned in the definition of "surface waters of the State," and the
"water use" classes do not include any indicator of the hydrologic or water quality
improvement provided by wetlands. Therefore, a classification system is needed for
identifying wetland functions in Washington.
Additional protection for wetlands could be provided by designating watersheds for
"hydrologic use" where the relative hydrologic sensitivity is high. The same principle could
be applied to water quality and life support functions where existing "use" designations do
not appear to provide adequate protection for the wetland functions identified by the
synoptic maps. It should be emphasized that the synoptic approach is not intended to
make value judgements, or management decisions, with respect to which wetland functions
are most important to protect within a geographic area. The index or suite of indices used
for designating wetland "use" or assessing cumulative impacts must be determined by the
regulatory agencies involved.
Outstanding national resource waters are defined as waters and wetlands of
"exceptional ecological significance" (US. EPA 1990). To designate candidate wetlands and
wetland complexes for "Outstanding State Resource Waters," a protocol could be
developed by combining existing surface water designated uses with synoptic wetland
function identification or cumulative effects ranking. For example, Appendix V summarizes
the rankings of watersheds for hydrology, water quality and life support cumulative effects.
Those units with low rankings for a particular function, e.g., a rank of 1 through 10, are
likely to have a high potential for processing landscape inputs for that function and are
likely to be relatively unimpacted. Watersheds that have low cumulative effects rankings
for all functions, e.g., units 45, 28 and 39, might be considered to have wetlands of
24
-------
relatively high functional value and therefore identified for special protection as
"Outstanding State Resource Waters." The rankings could be further refined by weighting
the watersheds by wetland patch size, the existence of state wetland heritage sites or the
wetland rating system being developed by the Washington DOE.
25
-------
CONCLUSION
The synoptic approach is a framework for assessing the cumulative effects of
wetland loss on landscape function, designed to complement existing management practices.
The approach can be applied to a variety of spatial scales and regulatory issues and can
be modified according to the concerns of a particular regulatory agency. An assessment
can be completed in a matter of months at a relatively low cost, providing the capability
of rapidly ranking watersheds or regions according to their sensitivity to future Wetland
losses.
The synoptic approach does provide a landscape perspective on wetland function
and identifies wetland functions not included in Washington's designated uses of surface
waters. Additional protection could be afforded to Washington's wetlands by using the
synoptic approach to differentiate functions (uses) performed by wetlands, which may be
quite different from adjacent lakes and streams due to differences in hydrology and biotic
composition. In comparing the results of the Washington and Louisiana pilot studies
(Abbruzzese et. al. 1990b), we conclude that the approach may be more appropriate for
a state, such as Washington, with a generalized set of water quality standards than a state
such as Louisiana which has specific surface water use categories, such as "oyster
propagation", "public water supply", and "agriculture". However, the approach does not
supersede the need for site specific information on wetland value and function and does
not provide adequate information for decisions regarding a particular wetland site, due to
the broad scale of the study. Thus, the approach should not be used for site specific
decisions or for engineering purposes, e.g. locating sites for bridges, since the relative
location of different components of the ecosystem becomes critically important for such
decisions.
The need for greater precision in the approach, e.g., using higher resolution maps
where available, is accentuated in Washington because of the high spatial variability in
landforms, soil association and precipitation patterns, wetland density and availability of
data, compared to Louisiana. For example, wetland area in WRIA's with zero values for
wetland area (see Figure 5 and section on Wetland Capacity) should be calibrated by
comparison with a random sample of wetland area depicted on U.S. Fish and Wildlife
Service National Wetland Inventory maps. Also, the lack of soil surveys for a substantial
portion of the state made it difficult to compare, even in a relative sense, wetland losses
in different WRIA's. A cooperative effort to map soils on federal lands would alleviate
this problem and contribute, in general, to comprehensive planning in Washington.
The Washington pilot study can provide a "first cut" at identifying wetland
"designated uses" in the state and identify areas where additional study is needed. The
assessment may also be useful in regional planning and the development of State Wetlands
Conservation Plans in accordance with recommendations of the National Wetlands Policy
Forum (National Wetlands Policy Forum 1988), or as a tool for nonpoint source pollution
26
-------
assessment. Ultimately, the utility of the synoptic approach in providing information useful
to the development of wetland water quality standards and the strategy for wetland "use
designation" in the study area must be decided by resource management agencies.
The synoptic approach was developed to provide a tool, in addition to existing
management practices, for evaluating the cumulative effects of wetland loss in regulatory
decisions that must be made quickly and with limited resources. The approach is a
common sense logic structure based on many simplifying assumptions whose consequences
are not fully understood. These assumptions include the following: 1. precipitation based
processes determine hydrologic function; 2. data on polluted streams from state 305B
reports are valid indicators of pollutant loading rates; 3. number of rare, threatened and
endangered wetland dependant species present are representative of wetland biota most
sensitive to habitat destruction; 4. wetland area is proportional to wetland capacity to
process landscape inputs, regardless of location in the watershed; 5. hydric soils can be
used to estimate past wetland losses; and 6. recent trends in agricultural and population
growth can be used to predict future wetland losses.
The method is still developmental. For example, hydrologic input does not currently
include upstream imports, and therefore downstream input is underestimated. Also, we
currently have no way of quantifying the overall confidence level of the approach. Future
research strategies, including quantification of upstream import, validation of the above
mentioned assumptions, establishment of confidence levels for the surrogates, and
additional data will be incorporated as they are developed. The final product of the
Wetland Research Program's cumulative impacts research will be the completion of a
Cumulative Impact Assessment manual in 1991.
27
-------
LITERATURE CITED
Abbruzzese, B., S.G. Leibowitz, F.L. Morris, P.R. Adamus, C.B. Johnson, and E.M.
Preston. 1990a. A synoptic approach to the assessment of cumulative effects of
wetland loss on landscape function. Submitted to Environmental Management.
Abbruzzese, B., S.G. Leibowitz, and R. Sumner. 1990b. A synoptic approach to wetland
designation: A case study in Louisiana. U.S. Environmental Protection Agency,
Corvallis, Oregon. EPA/600/3-90/066.
Bedford, B.I., and E.M. Preston. 1988. Developing the scientific basis for assessing
cumulative effects of wetland loss and degradation on landscape functions: Status,
perspectives, and prospects. Environmental Management 12(5): 751-771.
Cummans, J.E., M.R. Ceilings, and E.G. Nassar. 1975. Magnitude and frequency of floods
in Washington. U.S. Geological Survey Open-File Report 74-336. U.S. Geological
Survey, Tacoma, Washington.
Dickert, T.G. and A.E. Tuttle. 1985. • Cumulative impact assessment in environmental
planning: a coastal wetland watershed example. Environmental Impact Assessment
Review 5:37-64.
Gosselink, J.G, and L.C. Lee. 1989. Cumulative impact assessment in bottomland
hardwood forests. Wetlands 9: 93-174.
Hydric Soils Committee. 1987. Hydric soils of the United States. USDA Soil Conservation
Service, Washington, D.C.
Johnston, C.A., N.E. Detenbeck, J.P. Bonde, and G.J. Niemi. 1988. Geographic
information systems for cumulative impact assessment. Photogrammetric Engineering
and Remote Sensing 54 (11): 1609-1615.
Leibowitz, S. G., and E.M. Preston, USEPA Environmental Research Laboratory, personal
communication, 1990.
Loomis, M.L, A.J. Busacca, and B.E. Frazier. 1988. General soil map of Washington.
Agricultural Research Center, Washington State University, Pullman, Washington.
National Wetlands Policy Forum. 1988.
Office of Technology Assessment. 1984. Wetlands: Their use and regulation. OTA-0-
206. U.S. Congress, OTA, Washington, D.C, 195 pp. + app.
28
-------
Preston, E.M., and B.L. Bedford. 1988. Evaluating cumulative effects on wetland
functions: A conceptual overview and generic framework. Environmental
Management 12 (5): 565-583.
Rawls, WJ., A. Shalaby, and R.H. MC Cuen. 1981 Evaluation of methods for
determining urban runoff curve numbers. Transactions of the ASAE 24(6): 1562-
1566.
Soil Conservation Service. 1986. Urban Hydrology for small watersheds. Technical
Release 55, 210-VI-TR-55. U.S. Government Printing Office, Washington, D.C.
Tiner, R.W., Jr. 1984. Wetlands of the United States: current status and recent trends.
U.S. Fish and Wildlife Service, National wetlands Inventory, U.S. Government
Printing Office, Washington, D.C. Table 1 pp. 1-5.
U.S. Bureau of the Census. 1972. Census of population and housing: 1970. Population
and land area of counties: 1970 and 1960, Washington. U.S. Government Printing
Office, Washington, D.C. Table 9, pp. 15.
U.S. Bureau of the Census. 1974. Census of agriculture. Vol.1, Part 47, Washington
state and county data. U.S. Government Printing Office, Washington, D.C.
U.S. Bureau of the Census. 1982a. Census of agriculture. Vol. 1, Part 47, Washington
state and county data. U.S. Government Printing Office, Washington, D.C.
U.S. Bureau of the Census. 1982b. Census of population and housing: 1980. Part 49,
summary characteristics for governmental units and standard metropolitan statistical
areas, Washington. U.S. Government Printing Office, Washington, D.C. Table 1,
pp. 1-4.
U.S. EPA, Office of Wetlands Protection. 1989. Wetlands and 401 certification:
opportunities and guidelines for states and eligible Indian tribes. U.S.
Environmental protection Agency, Washington, D.C.
U.S. EPA, Office of Wetlands Protection. 1990. National guidance: Water quality
standards for wetlands. U.S. Environmental Protection Agency, Washington D.C.
Walker, D.A., PJ. Webber, E.F. Binnian, KLR. Everett, N.D. Lederer, E.A. Nordstrand,
and M.D. Walker. 1987. Cumulative impacts of oil fields on northern Alaskan
landscapes. Science 238:757-761.
29
-------
Washington Code Revisor. 1988. Chapter 173-201 Washington Administrative Code:
Water quality standards for surface waters of the state of Washington. Washington
Code Revisor. Olympia, Washington.
Washington Department of Ecology. 1989. Clean water act section 304(1) technical
report, volume 1: lists of waterbodies required under section 304(1). Washington
State Department of Ecology, Olympia, Washington.
Washington Department of Natural Resources-Natural Heritage Information System.
1990. Wetland associated plant species of concern by priority by WRIA.
Unpublished data.
Washington Department of Water Resources. 1969. Water resource inventory areas.
Map (scale 1:1,900,800). Washington Department of Water Resources. Olympia,
Washington.
Washington Department of Wildlife-Non-Game Program. 1990. Number of wetland
associated species of concern by WRIA basin. Unpublished data.
30
-------
APPENDIX L Maps of overlay components used for deriving synoptic indices.
31
-------
MEAN ANNUAL PRECIPITATION
Canada
39 - liter Stiooret lifeitorj Irci
Precipitation (cm)
25 - 40
Figure 1.1
40 - 90
90 - 175
175
360
1 - 178
7 - 224
IS - 131
II - til
25 - 211
31 - 27
J7 - II
43 -
41 -
55 -
I! -
25
to
5<
87
2 - 74
I - 1)1
14 - III
II - 214
tl - 113
32 - 42
II - 133
44 - 25
51 - 25
51 -
12 -
52
93
I - 101
• - 112
15 - 127
21 - 391
27 - 242
33 - 28
31 - II
45 - 114
51 - 35
57 - II
4 - 2EI
10 - 1J4
II - 214
22 - 275
21 - 172
34 - 31
40 - 31
46 - 104
52 - 42
51 - 53
5 - 171
11 - 154
17 - 102
23 - 110
21 - 114
35 - 41
41 - 25
47 - 150
53 - 25
51 - 41
[later Resource Inventory Area]
I - 43
12 - 13
II - 215
24 - 231
30 -
31 -
42 -
41 -
54 -
10 -
II
25
25
81
29
55
k; BSIM Itlliilt itittrci f-ijr«». DS1P1 InTirOBBCItiI lutircb Lib. Ctrtillli. Ort|ei
32
-------
TOTAL DRAINAGE AREA
Canada
egon
31 - later Kcioirce livcDlor; irei
Drainage Area (he)
38160 - 142590
Figure 1,2
142590 - 251570
251570 - 357900
357900 - 749320
1
T
13
II
37
41
41
IS
II
315(24
4175(4
721(1
113573
moo
741313
413231
5431S6
175194
145079
2 -
I -
14 -
20 -
21 -
32 -
31 -
44 -
50 -
51 -
82 -
1(2316
1470?
211271
(4(IO(
3(0152
210140
307743
2252(2
111703
323152
S - 143506
I - 131145
15 - 1IIII3
21 - 2K472
27 - 135015
3J - 1BI10I
31 - 554tlt
45 - 357154
SI - 51117
57 - 7(577
4 - I3I53C
10 - 261720
It - ] 5J81 7
22 - 338700
28 - 113113
34 - 726031
40 - 224tll
46 - 126(71
S2 - 25(561
SI - 21(118
5 - 1(0072
1) - 200123
17-110072
13 - 334IIS
21 - 223378
35 - 583176
41 - (54525
47 - 273014
S] - 135523
SI - 2(3779
[liter Resource Inventory Aret]
I!
II
24
42
II
54
(t
54147
410(0
1(7(16
24(571
315514
4251(2
115730
54(412
231277
251717
D3IM telliidi Iticirek Prtfria. BSIPi lit I r innei 111 leinrch Ilk, Ctrnllii. Or<|ti
33
-------
POTENTIAL RUNOFF (CURVE NUMBER)
Canada
39 - liter leitirce livelier; Irei
Runoff (fraction)
| - 1 0.63 0.68
0.68 0.72
Figure 1,3
0.72-0.75
0.75 - 0.93
T -
IS -
II -
25 -
SI -
JT -
43 -
41 -
55 -
61 -
.IS
.77
74
.14
.(I
.74
73
.74
.(I
70
S3
i
«
'4
20
32
31
44
II
II
•2
093
0 63
0.77
70
17
(8
73
72
73
48
s -
» -
IS -
21 -
27 -
SS -
31 -
4S -
51 -
57 -
33
81
14
70
88
71
74
69
67
4
10
II
22
21
34
40
46
52
51
.7S
.74
.71
.It
.76
73
. 75
.16
.17
.11
5
11
17
23
2!
35
41
47
53
5S
[later Resource Inventory Area]
76
14
84
se
.67
.73
72
70
75
87
I
12
II
24
so
36
42
S4
80
- 0.91
- 0 66
•0.63
-0.72
- 0 69
- 071
-0.76
- 0 72
- 0 .61
-0.17
Frepirei bj ISIM ttllui'i Icieireb frojrtn, DSIPi tntiroineiti1 lettireb Lib. Cortillii, Or«|«l
34
-------
STREAM CHANNEL SLOPE
Canada
• egon
Slope (m/m)
| | 0 . OOE-3 1 . 17E-3
Figure 1.4
1. 17E-3 - 4 . 46E-3
4 . 46E-3 - 7 . 11E-3
7.1 1E-3 - 4 . 81E-2
i
ij
11
25
31
J7
41
49
55
81
.UI-2
.451-2
.4SI-2
.711-2
90E-2
.321-9
.12E-2
211-2
.151-3
251-2
001(0
2 - t .
t - 0.
14 - 0 .
20 - 0.
26 - 0
32 - 0
96 - 0
44-0
50-0
56 - 0
62-0
(81-1
1*1-2
361-2
6J«-2
.241-2
.561-2
.711-2
.521-2
.111-2
.461-2
.00140
3
15
21
27
33
59
45
51
57
- 0
O.OOE-tO
0 57E-2
0.791-2
0.54E-2
0.671-2
0.661-3
0.368-2
0.60B-2
391-1
- OI24E-2
4
10
16
22
26
14
40
46
52
56
541-2
651-2
.121-1
361-2
I 11-1
331-2
OOEtO
I6E-I
44E-2
OOEtO
5
I 1
17
23
29
35
41
47
53
59
(liter Resource Inventory Area]
.56E-2
751 2
.45E-1
.I3E-2
.191-1
451-3
561-3
411 2
.OOEtO
.61E-3
6
12
19
24
30
38
42
48
54
80
.741-2
.OtltO
.13E-I
.261-2
.101-1
.33E-2
.OOEtO
.64E-2
.I9E-2
.I9E-2
Pr«p«rH fcj USIPl Iclliiii leiiirek Pro(rim, D3EPI Ini I r t nmei 111 Icitircb lit. Conillii. Ort|
-------
CHANNEL LENGTH
Canada
39 - liter Beioirce lueitor; lrtl
Length (km)
|~~| 5470 61950
61950 - 99440
Figure 1.5
99440 - 126070
126070 - 204350
1 - 1 14561
7 - H44«l
IS -
It
Z5 -
74979
34272
36ZOJ
31 - 188862
17 - 170(7(
43 - 156395
49 - 125502
Si - 65325
II - 70791
2 - 6758
B - 105172
14 - 22526
20 - 102978
21 - 204343
32 - 140305
31 - 142978
44 - 70351
50 - 72405
50 - 70313
(2 - 111504
3 - S5969
9 - 127755
15 - 30732
21 - 104907
27 - 132512
33 - 92139
39 - 150120
45 - 122926
51 - 35559
57 - 33467
4 - 121319
10 - 124151
16 - 62107
22 - 107481
20 - 40270
34 - 172405
40 - 30410
40 - 71207
52 - II053I
5t - 92839
5 - 90(32
11 - 10)447
17 - 2(962
23 - 123571
29 - (1464
35 - 1(1495
41 - 145775
47 - 1325)2
53 - (5004
59 - 100241
[later Resource Inventory Area]
12
II
24
30
36
42
II
54
60
5471
1029)
(4(12
5(5(0
121(40
74(14
10(999
145454
17530
42471
Prepared b; DSIPl lelludi leieirek Projrm. USEP4 ID > i r o nine i 111 leieireh Lib, Cornllis. Orefii
36
-------
WATER QUALITY INPUT (NORMALIZED)
Canada
egon
31 - liter Btimret Ineitir) Irei
Length of Polluted S Ire urns /
Length of All Streams (km/km)
I—I o.oo-o.oo
Figure 1.6
0.00 - 0.65
0.65 - 0.99
0.99 - 1.00
i
7
13
19
25
31
57
43
-0.72
-066
-060
- I .00
-1.00
- NO DITi
- 1 .00
- DO Dili
- 1.00
-1.00
- NO DITI
14
20
21
32
36
4t
50
M
62
I .00
0 IS
050
0.10
1.10
1.10
o.to
10 DITi
10 Dili
1.10
I 00
I
IS
21
27
33
39
45
51
57
67
62
38
77
49
00
62
50
10 CHI
1.00
4
10
16
22
26
34
40
46
5:
56
00
oo
77
82
II
00
0 DITi
57
00
10 DITI
5
I I
17
23
It
15
41
47
53
59
[liter Resource Inventory Ares]
oo
00
00
00
16
00
00
00
10 DITi
I .00
f
12
I)
Z<
30
38
(J
(i
5<
60
1 .00
10 DITI
00
DC
00
0 DITi
0 DITI
II
00
00
Frtpirti by DSin lellndi Iticirck Projri«, USIPl In I r ointi 111 Itieircb Lib, Coriillii. Or«|ii
37
-------
NON-POINT fATER QUALITY INPUT (NON-NORMALIZED)
Canada
• egon
39 - liter Resource Initotorj Area
Length of Non-Point
Polluted Sir earns (km)
0 -
73
Figure 1.7
73 120
120 - 470
1 - 467
7 - 230
13 - 5!
It - «!
25 - 105
31 - NO D«Ti
37 - 202
43 - NO DAT*
49 - 171
55 - 78
81 - NO DAT*
2 - 0
6 - 235
14 - 70
20 -
21 -
n
> I
62 -
1 b 1
I b6
0
NO
KO
92
! I 5
Dirt
Din
3 - 82
J - 153
15 - 45
21 - 78
27 - 70
33 - 113
3» - 103
45 - 44
51 - HO DATA
57 - 39
4
10
16
22
21
34
40
48
52
58
0
227
48
230
I 10
236
HO DATA
44
104
HO DATA
I
II
17
23
El
35
4 1
4 7
it
it
228
71
0
2!, :t
21
I 1 I
74
0
NO OATA
85
later Resource Inventory Area
I
I :'
in
:.'<
II
II
Ii
IB
S4
II
0
10 DATA
0
64
73
HO DATA
HO DATA
0
83
53
Prepared bj USIPA lellands Research Program, USEPA Environmental Research Lab. Coriallis. Oregoi
38
-------
NON-POINT WATER QUALITY INPUT (NORMALIZED)
Canada
o<-
egon
39 - later Resource Uieitory tret
Length of Non-Pi. Polluted Streams /
Length of All Streams (km/km)
I—I o.oo - o.oo
Figure 1,8
0.00 - 0.65
0.65 - 0.99
0.99 - 1.00
i
7
13
!>
25
3]
37
43
49
55
81
0 72
0.16
I.II
I .00
I .00
NO DATA
1 .00
NO Dili
1 .00
1 .00
NO DATl
2 - 0.
1-0.
14-0.
20-0.
26-1
32-1
3> - 0.
44 - NO
50 - HO
56 - I .
62-1
00
15
50
00
01)
00
oo
Dili
DAIi
00
00
3
I
15
21
27
33
3»
45
51
57
.67
.62
.3D
.77
.41
.00
.12
0.50
NO DATA
1 .00
10
16
22
28
34
40
46
52
58
0.00
1 .00
0.77
0.62
I.II
1 .00
10 DATA
0 . 57
1 .00
NO Dili
5
11
n
23
29
35
41
41
53
59
[later Resource Inventory Area]
no
oo
oo
oo
in
oo
oo
00
NO DATA
1 .00
ti
12
I »
2t
30
:ie
(2
41
5t
60
0 .00
10 DATl
0 00
1 .00
I .00
NO DATA
NO DATA
0. 00
I .00
1 . 00
Prep«red by USSPi 11 I I 11 d s itsetrch Projrim, USEPA IDT IrointiI>1 Research Lib, Cortlllii. Oregon
39
-------
CUMULATIVE IMPACTS (NORMALIZED)
Canada
egon
Figure 1.9
39 - Inter Rcioarce Inveitorj irei
Zetland Loss /
11 y d r i c Area (fraction)
|| -1.00 0.63
pi] 0.63 0.86
0.86 - 0.99
0.99 - 1.00
i
7
13
19
25
31
37
43
49
55
II
0.9
0 9
1 .0
2 -
1 -
14 -
20 -
2» -
32 -
3« -
44 -
50 -
56 -
«2 -
3
9
15
21
27
33
39
45
51
57
0.4
1 .0
I .0
o.e
o
.0
-0.8
-1.0
I . 0
I .0
4
10
It
22
28
34
40
4 t
52
5B
1 0
i .0
0.4
0.7
-0.5
0.9
I .0
I .0
0.9
0.8
5
1 1
I?
23
29
35
4 1
47
53
59
[later Resource Inventory Area]
II
II
2(
10
II
(2
80 -
Prcpircd b; USEFA lellinds Rexircb Projrtm, DSEP1 E n t i r o nmt n t i 1 Rcieircb lib, Corilllil, Oregoi
40
-------
HUMAN POPULATION GROWTH (1970-1980)
Canada
39 - liter ItKirti lifiitiri Arei
egon
Annual Rate
Pop80-Pop70 ]/Pop70/lfl )
8 . 54E-3 - 1 .48E-2
1 . 48E-2 - 2 . 30E-2
Figure 1,10
2 . 30E-2 - 4 . 40E-2
4 . 40E-2 - 1 .03E-1
i
7
13
19
25
11
II
43
<9
55
81
- 0
0 30E-
0 ME
0.tlE-
0.49E-
0.121-
0 541-
0.30E-
0 IOE-
191-
0 20E
0 6(1-1
2
I
1 <
20
26
32
3B
50
51
62
. lOEt
101-
54E-
.49E-
. 19E-
.111-
. 1BE-
261-
291-
19E-
45E-
3
9
15
21
27
33
39
45
51
57
23E-I
.JBE-2
.40E-
21E-
.411-
23E-
«5E-
. 12E-
19E-
19J-
4
10
IS
22
2t
34
40
4t
52
SB
.278-
.171-
488-
. 151-
.501-
. 141-
36E-
'908-
.321-
.<3E-
5
11
17
23
29
35
41
47
53
59
29I-)
25E-1
491-1
44E-1
32E-1
I IE-1
I5E-I
131-1
971-2
66E-I
I
I 2
If)
21
:)0
II
II
(8
0
0. 631
0.III
0.491
0.99E
0.211
0.31E
0.III-
0 20E-
211
BO - 0 40E-
[later Resource Inventory Area
Prfpartd b, VSlfk letlllds
USEPI lit 1101BII111 Rotircb Lib, Conillis. Oregon
41
-------
AGRICULTURAL GROITH ( 1974-1982)
Canada
• egon
Figure 1.11
i
i»
19
II
II
37
<:i
49
5S
I]
-0.401-2
0.228-1
0.411-2
-0.818-2
0 4!E 2
-0.848-2
-0.478-2
-0.468-2
-0.651-3
-0.958-2
-0.298-2
2 - -0.
I - 0.
14 - 0.
20 - -0
21 - 0
32
38
14
50
M
-o
- 0
82
t
I)
0
131-1
218-1
Bil-3
208-2
111-2
501-2
428-2
231-2
1(8-2
938-2
348-2
3
I
IS
21
27
33
it
45
51
57
0
0
0
0
0
-0
-0
0
0
• 0
641-3
208-1
348-1
118-2
411-2
531-3
131-1
361-1
328-3
118-1
4
10
I S
22
ei
34
(0
(8
52
II
39 - Inter Resource Inieatorj irei
Annual Rate
(|Agrfl2-Agr74]/Agr74/8)
-1 . 33E-2 - -4 . 08E-3
-4 . 08E-3 1 . 01E-3
1 . 01E-3 4 . 72E-3
4 . 72E-3 - 5 . 36E-2
131-1
(91-2
121-1
168-2
661-2
418-3
228-2
431-1
401-2
311-2
I
i:
i n
24
II
II
42
4fl
S4
80
0.958-3
0 141-1
358-2
138-1
731-2
388-2
318-2
268-3
648-2
248-2
[later Resource Inventory Area
Prepared bj DSIPl leUinds Icstirek Progrin, OS8P1 In I I r onmt D11 1 leieircb Lib. Cornllil. Oregon
42
-------
FUTURE RISK
Canada
egon
39 - later Reioiree llftltlf} Area
Veighled Growth
(Agr*B7/95 + Pop«8/95)
I I -1.1 2E-2 - -1 . 96E-3
-1.96E-3 - 3 .OBE-3
Figure I .12
3.08E-3 - 7 . 75E-3
7.75E-3 - 4 . 98E-2
1 - -0.I2E-2
7
I 3
19
25
31
37
43
49
55
61
0
0
0
0
0
- 0
0
0
0
0
21E-1
B9E-2
338-2
548-2
318-2
KE-2
351-2
97E-3
70E-2
30E-2
2 - -0.35K-2
I
14
20
28
32
38
44
50
56
62
0 208-1
0.538-2
0 238-2
0.268-2
361-2
23E-2
448-2
398-2
(98-2
(98-3
3 - 0.258-2
9
15
21
27
33
39
45
51
57
19E-1
34E-1
9IE-2
72E-2
I4E-2
118-1
348-1
138-2
(48-2
4 - 0.448-2
10
16
22
20
34
40
46
52
58
0. 148-1
o! m-2
0.22E-3
0.((E-2
0.24E-2
0 5(8-2
0.50E-1
0.488-2
0.768-2
5 - 0.148-1
I I
17
23
29
35
41
47
53
59
[later Resource Inventory Area]
.798-2
.188-1
.528-2
.548-2
. 138-2
.328-2
408-1
-0.2(8-2
0.278-2
12
18
iM
30
36
(2
41
54
80
0.628-2
0.148-1
0.908-3
0.138-1
-0.418-2
0.828-2
0.438-2
0 148-2
-0.408-2
0.5(8-2
Prepared bj US8FA letlnds (eieireh Program, USEP1 En ? i r o nme 11 a 1 leseircb Lab, Conallis. Oregai
43
-------
APPENDIX IL
County
Human population1 (1970 and 1980), agricultural acreage2 (1974 and
1982), and (RTE) by county.
Population
1970 1980
Agricultural Acreage
1974 1982
Adams
Asotin
Benton
Chelan
Clallam
Clark
Columbia
Cowlitz
Douglas
Ferry
Franklin
Garfield
Grant
Grays Harbor
Island
Jefferson
King
Kitsap
Kittitas
Klickitat
Lewis
Lincoln
Mason
Okanogan
Pacific
Pend Oreille
Pierce
San Juan
Skagit
Skamania
Snohomish
Spokane
Stevens
Thurston
Wahkiakum
Walla Walla
Whatcom
12014
13799
67540
41355
34770
128454
4439
68616
16787
3655
25816
2911
41881
59553
27011
10661
1156633
101732
25039
12138
45467
9572
20918
25867
15796
6025
411027
3856
52381
5845
265236
287487
17405
76894
3592
42176
81950
13267
16823
109444
45061
51648
192227
4057
79548
22144
5811
35025
2468
48522
66314
44048
15965
1269749
147152
24877
15822
56025
9604
31184
30639
17237
8580
485643
7838
64138
7919
337720
341835
28979
124264
3832
47435
106701
1147185
277692
720930
94214
30300
99587
317312
38020
955630
778280
600959
361184
1081599
49581
20701
12563
51368
7788
457051
786736
137078
1469010
15441
1340031
34178
65845
62079
21113
108972
8330
78170
687162
593099
65211
15748
805948
132921
1155524
287052
676837
134619
28342
101660
338643
40809
970528
800517
632519
337134
1113170
49141
20853
15525
59813
10974
393516
725048
135531
1404250
15232
1332990
38515
63998
68936
18862
109834
8940
92820
626780
578060
67628
15915
755240
128371
44
-------
County Population Agricultural Acreage
1970 1980 1974 1982
Whitman 37900 40103 1365589 1400743
Yakima 144971 172508 1767297 1714809
Data Sources:
JU.S. Bureau of the Census 1972, 1982b.
2U.S. Bureau of the Census 1974, 1982a.
45
-------
APPENDIX m.
Hydrologic unit composition of counties. Total area is given for each
county, along with the partial area for each component hydrologic unit
(a hydrologic unit need not be entirely contained within one county,
but may cross several). The percent is the proportion of total county
area found in that hydrologic unit
County/Unit
Adams
34
36
41
43
Asotin
35
Benton
31
32
33
36
37
40
Chelan
4
39
40
44
45
46
47
48
50
Clallam
17
18
19
20
ea
4997.0
1514.8
1189.3
2132.5
160.3
1644.3
1644.3
4583.6
2134.7
7.4
4.9
114.9
1667.7
653.9
7814.4
19.0
0.6
276.1
209.2
3198.6
1271.2
2483.3
313.3
43.0
4550.3
289.5
1372.3
979.8
1908.7
Percent
100.00
30.32
23.80
42.68
3.21
100.00
100.00
100.00
46.57
0.16
0.11
2.51
36.38
14.27
100.00
0.24
0.01
3.53
2.68
40.93
16.27
31.78
4.01
0.55
100.00
6.36
30.16
21.53
41.95
46
-------
APPENDIX III. Continued.
County/Unit
Clark
27
28
Columbia
32
33
34
35
Cowlitz
23
25
26
27
Douglas
41
42
44
47
49
50
51
53
Ferry
51
52
53
54
58
59
60
61
ea
Percent
1706.2
851.5
854.6
2236.4
948.8
47.8
1.5
1238.3
2964.1
13.0
231.8
1757.1
962.2
4763.7
33.9
317.1
2704.4
14.2
11.7
1623.8
5.5
53.0
5898.1
29.5
1559.2
205.9
6.2
2248.7
13.9
1785.7
48.9
100.00
49.91
50.09
100.00
42.43
2.14
0.07
55.37
100.00
0.44
7.82
59.28
32.46
100.00
0.71
6.66
56.77
0.30
0.25
34.09
0.12
1.11
100.00
0.50
26.44
3.49
0.11
38.13
0.24
30.28
0.83
47
-------
APPENDIX III. Continued.
County/Unit
Franklin
33
34
36
Garfield
35
Grant
36
40
41
42
43
44
50
53
Grays Harbor
14
16
21
22
23
24
Island
5
6
Jefferson
16
17
18
20
21
22
Percent
3313.7
1015.6
97.6
2200.5
1817.0
1817.0
7207.4
622.9
16.1
4235.5
1586.1
495.1
222.8
0.1
29.0
4946.5
6.1
37.2
1062.7
2867.8
461.0
511.7
519.4
90.0
429.4
4631.9
688.0
857.2
468.8
905.6
1706.7
5.6
100.00
30.65
2.95
66.41
100.00
100.00
100.00
8.64
0.22
58.77
22.01
6.87
3.09
0.00
0.40
100.00
0.12
0.75
21.48
57.98
9.32
10.35
100.00
17.33
82.67
100.00
14.85
18.51
10.12
19.55
36.85
0.12
48
-------
APPENDIX III. Continued.
County/Unit
King
7
8
9
10
38
39
45
Kitsap
15
Kittitas
7
9
36
38
39
40
41
44
45
Klickitat
29
30
31
37
Lewis
11
13
23
24
25
26
30
38
Area
Percent
5670.5
2503.7
1335.7
1379.2
227.1
11.5
148.6
64.8
996.5
996.5
6034.6
0.2
1.4
12.5
208.9
4442.7
1077.2
133.5
2.5
155.8
5001.3
635.1
2162.3
1994.8
209.1
6407.6
520.6
. 82.3
1851.2
0.2
23.8
3816.3
33.4
79.8
100.00
44.15
23.56
24.32
4.00
0.20
2.62
1.14
100.00
100.00
100.00
0.00
0.02
0.21
3.46
73.62
17.85
2.21
0.04
2.58
100.00
12.70
43.24
39.89
4.18
100.00
8.13
1.29
28.89
0.00
0.37
59.56
0.52
1.24
49
-------
APPENDIX III. Continued.
County/Unit
Lincoln
34
41
42
43
53
54
Mason
14
15
16
21
22
Okanogan
4
47
48
49
50
51
52
53
60
Pacific
22
23
24
25
Pend Oreille
55
57
59
61
62
Area
Percent
6050.5
286.4
70.8
33.6
4069.1
920.6
669.9
2474.3
796.3
281.6
961.8
14.8
419.7
13675.6
3.0
19.1
5121.7
5528.1
625.8
543.0
973.5
137.0
724.4
2412.6
1.4
273.3
1855.5
282.5
3720.0
355.1
65.3
2.6
25.9
3271.2
100.00
4.73
1.17
0.56
67.25
15.22
11.07
100.00
32.18
11.38
38.87
0.60
16.96
100.00
0.02
0.14
37.45
40.42
4.58
3.97
7.12
1.00
5.30
100.00
0.06
11.33
76.91
11.71
100.00
9.55
1.76
0.07
0.70
87.93
50
-------
APPENDIX III. Continued.
County/Unit
Pierce
9
10
11
12
15
26
38
San Juan
2
Skagit
1
3
4
5
47
48
Skamania
26
27
28
29
30
Snohomish
3
4
5
6
7
8
. 45
47
Area
Percent
4299.8
4.4
2450.6
1049.3
337.1
250.0
136.0
72.4
431.1
431.1
4587.2
132.5
1305.4
2441.4
540.0
109.7
58.3
4369.8
700.0
1488.7
398.0
1781.2
1.8
5412.2
1.1
1457.0
1247.4
1.5
2313.8
210.5
130.1
50.8
100.00
0.10
56.99
24.40
7.84
5.81
3.16
1.68
100.00
100.00
100.00
2.89
28.46
53.22
11.77
2.39
1.27
100.00
16.02
34.07
9.11
40.76
0.04
100.00
0.02
26.92
23.05
0.03
42.75
3.89
2.40
0.94
51
-------
APPENDIX III. Continued.
Countv/Unit
Spokane
34
43
54
55
56
57
Stevens
54
55
58
59
60
61
62
Thurston
11
13
14
23
Wahkiakum
23
25
Walla Walla
31
32
33
34
35
Area
Percent
4627.1
880.8
89.0
630.0
1072.7
1129.9
824.7
6548.4
991.6
'353.7
619.6
2696.5
137.6
1482.4
267.0
1882.6
470.4
566.7
100.1
745.4
637.8
2.0
635.8
3340.7
2.4
2561.8
769.6
4.8
2.0
100.00
19.04
1.92
13.61
23.18
24.42
17.82
100.00
15.14
5.40
9.46
41.18
2.10
22.64
4.08
100.00
24.99
30.10
5.31
39.59
100.00
0.31
99.69
100.00
0.07
76.69
23.04
0.15
0.06
52
-------
APPENDIX III. Continued.
County/Unit
Whatcom
1
3
4
48
Whitman
34
35
56
Yakima
26
29
30
31
36
37
38
39
40
Area
Percent
5590.1
2870.3
94.8
2455.6
169.4
5666.5
4542.4
1030.9
93.2
11104.7
18.8
46.2
1501.8
266.5
37.5
5630.2
2439.7
965.9
198.1
100.00
51.35
1.70
43.93
3.03
100.00
80.16
18.19
1.64
100.00
0.17
0.42
13.52
2.40
0.34
50.70
21.97
8.70
1.78
53
-------
APPENDIX IV. Derived index maps.
54
-------
HYDROLOGIC SENSITIVITY
Canada
egon
39 - later Resource injector? Irei
Input / Capacity
I—| o.oo - o.oo
0.00 - 0.12
Figure IV.1
0.12 - 0.23
0.23 - 2.35
i
7
I]
II
It
Jl
37
43
41
45
ii
0.11
0 24
0.24
2.34
DIDtrillD
0.01
0.01
UIDirillD
O.Ot
0.20
uumiiD
2
I
14
21
21
32
31
44
SO
SI
12
outrun
li
41
31
21
IS
41
13
1 ]
outrun
outrun
3
i
IS
21
27
33
39
45
SI
57
0.03
mtiriitt
1.31
1.11
OUiriltt
0.01
C. 16
OUtrUID
OltlPlIID
4
10
II
22
21
34
40
41
52
SI
2.04
DIDEr UEt
41
13
12
09
. 12
.09
S
11
n
23
21
3S
41
47
S3
59
. II
0.9<
UiDtriltD
0.01
DIDirillD
DIDiriKU
DIDIF1IID
[liter Resource Inventory Art*]
c
12
II
24
30
3«
42
41
S4
1C
e 33
tmr nit
1.43
I 21
oiiiriiii
I 21
ouir nit
0 II
miiruiD
021
b; tSIfl lellilll Ititirck Pr«jr«». VSIPl l«» 11 e»t 1111 Itldrtk Lit. C«n«llii. Ort|
-------
IATER QUALITY SENSITIVITY (NON-NORMALIZED)
Canada
39 - liter Kcioircc liteilor; Irei
Input / Capacity
|~~] 0.00 0.00
0.00 - 0.04
Figure IV.2
0.04 - 0.11
0.11 - 0.34
1 - 020
7 - 0.09
13 - 0.13
19 - 0.23
2 -
I -
14 -
20 -
tt - Ullirilll 21
91 - 10 DIT1
37 - 0.02
43 - DO Din
49 - 0.04
Si - 0.15
II - DO DITi
32 -
36 -
34
0?
00
. 10
.32
.90
44 - 10 1)171
SO - 10 D171
SI -
12 -
3 - 0.01
9
li - 0.10
21 - 0.01
27 -
4 - 0.00
10 -
II - 0.03
22 - 9.05
21 - 0.04
13 - omnmt 14 - 0.22
19 - 9.94 40 - 10 1171
45 - 9.92 41 - OlDirill
SI - DO 1171 52 - 0.19
57 - Dltirilll it - 10 1171
5 - Oil
11 - 9 05
17 - DIDIMIID
23 - 9.11
29 - 9 04
( - O.tt
12 - 10 Mil
II - O.OC
24 - 0.02
30 - UitirillD
35 - BltlMIID 31 - 10 (171
41 - 9 01 42 - 10 HT1
47 - DIlirillD 41 - 0.01
53 - 10 1171 54 -
51 - II1IFIII1 10 - 0.0!
[liter Resource 1 D i e n t o r y Area]
frepirti hi IJIPl Itlluli Itscirck
. OSIPi III i r eimti I • 1 teittrck Lib. Corttllii. Orcfti
56
-------
IATER QUALITY SENSITIVITY (NORMALIZED)
Canada
39 - littr Icicirct litcitir; Irn
Input / Capacity
0 . OOE-4 - 0 OOE-4
Figure I V . 3
0 .OOE-4 - 3 . OOE-4
3 . OOE-4 - 8 . 50E-4
8.50E-4 - 3 . 48E-3
i
T
19
II
25
31
n
43
4J
55
tl
- 0.311-3
- 0 271-3
- 0. 141-2
- 0 J5I-2
DO BIT!
0 (21-4
KO 11T1
0811-3
8.UI-2
10 BlTl
I
I
14
20
21
32
31
44
S<
51
82
UIMMHSD
121-2
471-3
(08*0
• 413
201-2
101*0
10 eiTi
10 tin
outrun
3
I
15
21
27
33
31
45
51
57
0 .928-4
UNDEFHID
(.151-9
(.111-9
OIDIMIID
ommiD
(.141-3
t.241-3
10 tin
nitiriiiii
10
16
22
21
34
40
46
52
56
O.(0l4(
DIDIFIIIft
(.551-3
0. ltl-3
0.3(1-3
(.151-3
10 I1TI
(. 111-2
10 tin
5
I I
17
23
29
35
4 1
47
53
59
[later Resource Inventor; Arei]
411-3
701-3
821-3
351-3
- 0. 138-3
10 11T1
DIDIF IIIB
I
12
(I
2*
30
3E
42
48
54
80
0 8313
10 DJTt
0 OOI-l 0
0218-3
Dltir 1MB
10 nn
10 BlTl
0 00810
DIBIT nit
0 S28-3
I; IJIPt I>tln4i Icttirtk Pr»|ri«. OSIPi lit i r «>•
-------
NON-POINT IATER QUALITY SENSITIVITY (NON-NORUALIZED )
Canada
39 - liter Seitirce littitor; Irei
Input / Capacity
[—| o.oo o.oo
Figure IV.4
0.00 - 0.04
0.04 - 0.11
1 - 0 20
7 - 0.01
19 - 0.13
II - 02)
25 - DltiriUD
31 - 10 DlTl
IT - 0.02
49 - HO lit!
41 - 0.04
55 - 015
01 - 10 gut
2 - miring
I -
14 -
2« -
21 -
32 -
31 -
34
17
II
10
52
00
44 - 10 DITI
SO - 10 Dill
si - omrniD
12 - DIIIMIID
3 - 1.01
0.11 - 0.34
4 - 0.10
OHDirillt 10 - llljriltl
IS - 0.10
tt - 001
27 -
S3 -
31 - 0.04
44 - 0:02
SI - 10 DI7A
17 -
II - 0.13
22 - I IS
21 - 1.04
14 - 1.22
40 - 10 I1T1
41 - oiDiriii
52 - I. II
SI - 10 1171
S - Oil
II - 0 OS
17 - DIDIP1IID
23 - 0.11
21 - 0.04
35 - DIDIFIIID
41 - 0.01
47 - oiDIHIlD
S3 - 10 till
SI - DUIFIIID
I - 0.00
12 - DO H71
II - 0.00
24 - 002
30 - DIDirilll
31 - DO D171
42 - 10 01T1
41 - 0.00
S4 - DIDirillD
II - O.OS
[liter Resource InTtntory Area]
kj I3IPI Icllnis Ifitirek PrejriB. D3IF1 In I r •!»« 1111 tciiirch L«k. Ctriillit. Ort|ii
58
-------
NON-POINT IATER QUALITY SENSITIVITY (NORMALIZED)
Canada
0<-egor>
Figure I V . 5
1
13
It
23
37
43
55
II
0.311-3
0 271-3
0. 141-2
0 351-2
UIDirillD
DO DATA
0.921-4
DO Dili
8.211-3
0.l»I-t
*0 DATl
2
I
H
20
H
32
31
44
50
51
(2
outrun
0.121-2
0 47E-3
0.OOI-tO
0 641-3
0.201-2
OOUt
10 DATA
10 DATA
- 0
I
15
21
27
93
39
45
SI
57
0.921-4
UKDEFIIID
0.851-3
m DIM m
0.241-3
0 241-3
10 DATA
OIDIMIII
4
10
1C
22
28
14
40
46
52
51
Input / Capacity
0 . OOE-4 0.OOE-4
0 . OOE-4 3 . OOE-4
3 . OOE-4 8 . 50E-4
8 . 50E-4 - 3 . 48E-3
0.491-3
0.701-3
OIDir DID
O.I2E-3
0.351-3
DIDirillD
0. 138-3
IIDIFIIIB
10 1ATA
I
12
II
£1
30
36
42
41
54
60
0.001*0
ID DATA
O.OOItO
0.281-3
10 DATA
lit DATA
O.OOIlO
- 0.921-3
[later Resource Inventory Area]
kj DSIPI lelliiii Icieirek PrejriB. CSIfl IIT i r onuci t • I Itxircb Lit, Cirnllii. Or<|ii
59
-------
LIFE SUPPORT SENSITIVITY
Canada
eg°n
39 - liter Rcieirce liteitorj Irei
Input / Capacity
| 1 0 . OOE-3 0 . OOE-3
0 . OOE-3 - 3 . 80E-3
Figure IV.6
3 . 80E-3 - 9 . OOE-3
9.OOE-3 - 2 . 01E-2
i
7
13
II
25
31
37
43
41
55
I 1
471-2
.498-2
.iii-i
.171-1
IDIP11ID
.111-1
(SE-3
IDIPIHD
251-2
9(1-2
DIDmilD
2
t
14
20
2«
32
31
44
50
51
(2
oiiDtPiiiD
141-1
371-1
2(1-2
«4I-2
141-1
131-1
881-2
141-1
DIDEPIIID
DIDIPIIID
3
15
21
27
31
31
46
51
57
O.I3E-3
UIDIFIIED
0 I IE-1
0.191-3
UIDIFIICD
UIDIFIIID
0.42E-2
0 211-2
gitir HID
OIIDEPlKtD
- 0111-1
501-2
251-2
391-2
.(71-2
loir mi
• DIP III!
.731-2
5H-2
t.
1 1
17
83
29
35
4!
47
53
5S
0.241-2
0.701-2
OIDIPIIID
0 371-2
0.2*1-1
DIDIPIIID
0. 131-2
DICIPIIID
DIDIPIIID
DIDIPIIID
12
I !
24
30
38
42
4t
14
CO
0.331-2
DIDIPIIID
0 141-1
0.311-2
DIDIPIIID
0 171- 1
DIDIPIIID
0.591-2
DIDIPIIID
O.MI-2
[liter Resource Inventor; Area]
'7 DSIPI Ictli
ck Pr
D3IP1 InirODBtiti1 Itttircb Lik. C«rt«llii. Orc|oi
60
-------
HYDROLOGIC EFFECTS (NON-NORMALIZED)
Canada
egon
39 - liter Icioirce Uteitor; Irei
Sensitivity i Cumulative Impacts
-165 - 0
Figure IV.7
0 - 625
625 - 1300
1300 - 31495
1 - 2923
7 - 5247
13 - 1001
II - 15040
25 - UIDirillD
31 - 303
S7 - 59
43 - OIKIFIIIID
4» - lit
55 - 5Z7
II - UIOIMMD
14 -
20 -
21 -
32 -
31 -
44 -
50 -
51 -
Dimiui
1171
1322
2135
1277
127
151
-31
3 - 111
I - UIDEFHID
15 - 12071
21 - 1131
27 - OlDIFHIt
33 - OKIIFHIO
31 - -II
45 - -115
5i -
57 - UIIDIPIIID
4 - 31493
10 -
II - 311
22 - 1195
21 - -102
34 - (40
40 - DIDIFIItl
41 - OIDIFIII)
52 - 704
51 - 404
5 - 1044
11 - 1011
17 - DIDIFIIID
23 - 2447
21 - 112
35 - OUIFIIID
41 - 9
47 - D1IIFIIID
53 - DltlFIIID
59 - BIDIFIIID
C
12
II
14
30
31
42
41
54
II
Hi
IIIIFIIID
12(33
ISM
DIIIFlllt
413
DIIIFIII1
3113
OIIIFIIID
137
[liter Resource iDtentory Area]
frtp.nl k; tSIFi Itlliiit Iticirck Frg|riB. OSIFl In i rttaci 111 lettirct lib. Cert.lln. Orc|ii
61
-------
IATER QUALITY EFFECTS (NON-NORMALIZED)
Canada
- egon
39 - liter ttsonrct llititor; Irei
Sensitivity i Cumulative Impacts
I 1 -0.3- 0.0
Figure IV.8
0.0- 1.6
1.6- 5.7
5.7 - 22.4
1 - 5.1
7 - 5.1
IS - «.0
II - 22.4
25 - UNDIFHID
31 - NO DATA
J7 - 0.5
43 - 10 DATA
41 - 1.1
55 - 5.2
II - NO DATA
2 -
uiDtrimD
5.6
.4
1 4
20
21
32
31
44 - 10 DATA
SO - 10 DATA
SI - DI1EFHID
12 -
3 - 0.4
I - DRiEFHID
IS - 7.J
21 - 1.2
27 - DNDIFHID
33 - OIDIFKID
31 - -0.2
45 - -0.2
51 - 10 DATA
57 -
4 - 0.0
10 - DIDIFHID
II - O.S
22 - 1.7
21 - -0.3
14 - I.I
40 - 10 DATA
41 - OlDiriltl
52 - 10.1
SI - 10 I1T1
5 - 4.3
11 - i.i
17 - OIDIFKID
23 - 1.5
21 - 1.3
35 - OIDIFKID
41 - O.I
47 - DIDIFHID
S3 - 10 IATA
51 - tlDIFIIID
[later Resource I D i entory Area]
6 - 2.4
12 - 10 (ATA
II - 0.0
24 - 2.1
30 - OIDIFKID
31 - 10 DATA
42 - 10 DATA
41 - 0.0
54 - OIDIFKID
10 - 2.1
bf 03IPA Irlliid lestirek Fr«|riB. DSIPA lit i rem
-------
NON-POINT IATER QUALITY EFFECTS (NON-NORMALIZED)
Canada
egon
39 - littr Rtjoirct liictlorj Irci
Sensitivity i Cnmultlive Impact!
-0.3 0.0
Figure IV.9
0.0- 1.5
1.5- 5.6
5.6 - 22.4
7
19
II
25
31
J7
49
41
Si
II
S.I
S.I
10
22.4
UIOIMIID
10 Dili
1.1
*0 DJTi
1. 1
5.1
ID Dili
2
8
[4
20
26
32
36
44
SO
s«
62
- miriiiD
- s i
- i
i.o
•0 Dili
10 Dili
OIMMIID
3
i
15
II
27
S3
31
4S
SI
s;
t .4
7.9
1.2
oiiiniiD
-0.2
-0.2
10 11T1
omrniD
4
10
II
22
2B
34
40
41
52
SI
0.0
minis)
o.s
1 .7
-0.3
I.I
DO DITI
OlDirilll
10.(
10 »IT1
i
11
17
23
21
35
41
47
53
5S
4.3
I.I
i.s
DIDirillD
10 D1T1
DUIFlIIt
[later Rtaource ln»entory Arei]
6
12
It
24
31
36
42
41
54
80
O.t
10 lilt
0.0
2.1
10 IIT1
10 im
O.I
2.1
k; t SIP i Irtlnit Inctrck Pr«|n». D3IP1 In i r innei 111 Icieirct lit. Cert.llii. Ortfii
63
-------
LIFE SUPPORT EFFECTS ( NON-NORM AL I ZED)
Canada
egon
39 - liter teioircc littiUrj Irti
Sensitivity I Cumulative Impact:
|] -4.0 0.0
Figure IV. 10
0.0 20.0
20.0- 52.0
52 . 0
176.9
1 - 7(.«
7 - 117.5
13 - 1C.2
II - 112.0
zs -
JI - 14.4
J7 - 4.2
41 - DltlHIID
41 - 12.7
55 - 25.9
II -
2 - umriiiD
I - 17.5
14 - 10.
21 - 22.
21 - 31 .
32 - II.
3t - 4.
44 - -2.1
SI - 00
si - mtirniD
12 - omrniD
} - 3.5 4 - 171.1
I - OltirillD It - DIDEPIIIt
IS - 102.1
21 - IS
27 -
33 - UliirillD
31 - -41
45 - -3.1
si - gitirniD
57 -
16 - 4.7
22 - 22.2
28 - -3.4
34 - 47.1
40 - DIDIFIIII
41 - OIIIPIIII
52 - 42.3
51 - 25.)
5 - 213
11 - 51. I
17 - DIDIMIIID
23 - 510
21 - 17.0
35 - UIDirillB
41 - I.I
47 - UIOiriMD 41 - 134 I
53 - DIDirillD 54 - OlimilD
51 - DIDirillD II - II.I
12 - DIDirillD
It - 120 I
24 - 30.4
30 - guiriiiD
31 - 41.1
42 -
[Tiler Resource Inventory Area]
ttifinl t; ISIM lelluli Itstirek rrofriB. USIPi In i r ncti 111 leittrel Lit. Ctriilln. Or>|ii
64
-------
HYDROLOGIC EFFECTS (NORMALIZED)
Canada
egon
39 - later Bcicirce 11»e11 orj irei
SeDsilivity I Cumulative Impacts
| 1 -0.16 0.00
Figure IV.11
0.00 - 0.10
0.10 - 0.21
0.21 - 2.24
1 - 6.15
7 - 1.22
19 - I. II
It - 2.24
ti -
>1 - I. 07
37 - I. «0
41 -
.
54 - I. II
61 -
Prtpiri< k)
2 - DKBIMIID
t -
14 -
20 -
21 -
32 -
II -
44 - -
50 -
22
34
25
20
0!
It
3»
lit
si - miriiii
12 -
3 - 0.01
I - OltlMUD
15 - 1.25
21 - 0.01
27 - oitirimD
35 - ominut
91 - -0.05
45 - -0.II
51 - OIBiriKIl
57 - omrim
4 - 1.87
10 -
II - 0.17
22 - 0.09
21 - -0.01
14 - 0.01
41 - UKDIMIID
52 - 0.11
51 - 0.07
5 - 0.10
11 - 0.11
17 - OIOIMIID
29 - 0. II
29 - 0 II
35 - OIDUIIID
41 - 0.00
47 - OlDtrillD
53 - OlDtFIMD
59
I - 1.2]
12 - CIIIMIID
II - 137
24 - 115
31 - I. II
42 - BllirillD
41 - 115
54 - CltirillD
10 - 1.15
[later Resource Inttntory Area]
Itlliidi Iiitircb FregrtB. CSIPi In i r ODmt 1111 Icitirck Lib, Ccrtilln, Ore|
-------
IATER QUALITY EFFECTS (NORMALIZED)
Canada
egon
Figure IV.12
39 - l.i.r B.io.rce IneiUrj Irti
Sensitivity i Cumulative Impacts
| | -2 . 37E-4 0 . OOE-4
0 . OOE-6 2 . 33E-4
2 . 33E-4 - 7. 1 1E-4
i
7
13
II
25
11
57
4)
41
55
II
0.271-3
i m-3
0131-2
0.331-2
UIDIHIID
no DITI
t.2«I-4
DO DITi
I.111-9
0 1(1-2
»0 Dill
2
i
14
20
21
32
31
44
SO
SI
12
outrun)
.111-2
.941-3
.001*0
.411-3
. 111-2
.011*0
Dill
Dili
.
10
10
DUET KID
Ditiriiio
3
I
15
21
27
33
it
45
SI
57
C.341-4
OIUMIID
O.tlI-3
0.711-4
ouiriiiD
oiiirim
-e. MI-!
-0.241-3
10 I1T1
DIIIFIIII
4
10
II
22
21
14
40
41
52
91
7. 1 1E-4 - 3 .33E-3
0081*0
0.221-3
0. 121-3
-0.201-3
0 831-3
10 Dill
UKDlf lltt
0. 171-2
10 Bin
5
1 1
17
29
2«
IS
41
47
53
58
[later Resource Igventorj Area]
401-3
iei-3
0.551-3
C. 221-3
OIDIHIID
0. 121-4
OIDIFIIIID
10 1171
12
It
24
30
3t
42
41
54
to
I .511-3
10 Dill
I.IOI40
1.211-3
outrun
10 DITI
10 DITi
•001*0
I III-3
trtfutt kj ISIPl Ittliiii Itifirck trtfttm USIfl IK i f OIBCI 111 leitirek Lik, C«rt
-------
NON-POINT IATER QUALITY EFFECTS (NORMALIZED)
Canada
egon
39 - later Resource Inventor; Irei
Sensitivity i Cumulative Impacts
| 1 -2 . 37E-4 0 . OOE-4
0 . OOE-4 - 2 . 25E-4
Figure I V . 1 3
2 . 25E-4 -7.1 1E-4
1 - 0.271-3
7 - 0.241-3
13 - 0.131-2
II - 0.331-2
25 - DIDirlllD
31 - DO D1TI
37 - 0.291-4
43 - »0 DIT1
41 - 0.111-3
is - 0:111-2
II - DO Dill
2 - UlttrillD
I - 0.III-2
0.341-3
21 - 0 008*0
21 - 0.411-3
32 - 0.131-2
31 - 0 001*0
44 - DO DITt
SI - DO DITt
SI - D1DEHIID
<2 - DIDirillD
O.III-3
0.701-4
3 - 0.341-4
15 -
21 -
27 -
33 -
J» - -0.141-1
45 - -0.241-3
SI - 10 till
57 - D1IIPI1ID
4 - 0001*0
10 - 01D1PIIE1
It - 0.221-3
22 - 0.121-3
21 - -0.201-3
14 - 0 831-3
40 - 10 Bill
52 - 0.171-2
51 - 10 DITt
7. 1 1E-4 - 3 . 33E-3
0401-3
0.«OE-3
5 -
11 -
17 -
23 -
29 -
35 -
41 - 0.121-4
47 - OID1PIIID
S3 - 10 11TI
59 - OIDIPIUD
0.551-3
1.221-J
[later Resource Inventory Area]
I
12
II
24
30
31
42
41
54
(0
0001*0
DO DITt
0.00140
0.211-3
10 DITt
10 D1T1
0 . 001*0
DKDirlllD
0.111-3
trtfttti bj OSIfl letlnds teittrek PrtjriB, DSSPi In i roimei 111 leitirch Lib, Ctrtillii. Ort|ti
67
-------
LIFE SUPPORT EFFECTS (NORMALIZED)
Canada
egon
39 - later Resoiree lifeitorj iret
Sensitivity i Cumulative Impacts
| 1 -6 . 4 1E-3 0 . OOE-3
0. OOE-3 2.70E-3
Figure IV.14
2 . 70E-3 - 6 . 15E-3
6 . 15E-3 - 1 .73E-2
i
7
I]
II
Z5
31
37
4)
41
55
II
« .421-2
.448-2
.178-1
.171-1
v iirimg
. !(i-i
26E-S
.131-2
IOE-2
UIDIF HID
2
14
20
21
32
31
44
SI
SI
12
.111-1
.271-2
.211-2
.411-2
.BII-2
491-2
.141-2
.571-4
OHBEFIHD
3
I
IS
21
17
33
31
4*
51
57
0.311-3
DKtlFUID
0.111-1
O.S4E-3
UIBEFIIIEB
-0.241-2
-0.211-2
OIBEFIIIID
OIBEF1IEB
4
10
II
22
21
14
40
41
52
51
0.1II-I
DIDEPIII)
.201-2
.17E-2
- .201-2
.511-2
D DEFIIEl
D DEFIKIH
.«7E-2
4IE-2
5
11
17
23
29
35
41
47
S3
59
0.201-2
O.IOK-2
UKDEMHID
0.3SE-2
I. 13E-1
0 12E-3
CKDIf I»8D
DIDIHUB
DIDtFIIID
12
I
2*
30
36
42
41
54
to
1.241-2
DUEFIIID
I. 141-1
« 211-2
DIDirIIIB
0.14E-1
UIBBF1IEB
0 511-2
DIBIFIIEB
1.471-2
[liter Resource I n?eDtory Area]
kj 13IM (till
DSEP1 li i i r ODBC 1111 Icidrck Lib, Cirttllli. Or«|«i
68
-------
HYDROLOG1C SIGNIFICANCE TO HUMANS
Canada
egon
39 - liter Beioirct Ilititorj Irei
Effects I I960 Population
-6530 0
0 - 3200
Figure IV,15
3200 - 9000
9000 - 338870
1 - 8742
7 - 151730
11 - 8317
It - 24157
ts - OIDIFHID
91 - 45(5
S7 - 476
43 - UIDIFHID
41 - 156
i5 - 13341
II - UIDIMUD
2 -
14 -
20 -
21 -
32 -
31 -
44 -
51 -
SI -
62 - DIDIFHID
DIBIT HID
11(60
5605
6269
11237
3594
lilt
-1432
3 - 203
9 - UIDEFIIID
15 - 223471
21 - 1313
27 - DIDIFIIID
33 - OIDIFHID
31 - -9501
45 - -6529
51 - OIDIFHID
57 - DIDIFHID
4 - 336666
10 - OIDIPHID
16 - 24t8
£2 - 3(95
26 - -5641
34 - 79«B
40 - UIDIFHID
46 - OIDIFHID
52 - 416
58 - 355
5
11
17
23
29
35
41
47
53
59
6987
16915
OIOIFHID
11704
3609
DDDIFHID
35
OIOIFHID
DIDIFHID
OIDIFHIJ
[loter Resource Inventor; Area]
II
24
30
36
42
<«
5<
II
I486
DIDIFHIJ
2311!
2150
OIDIFHID
5494
OltlFHIC
2569
DIDIFHID
691
k; usifi Itllndi Ititirck Fr>|riB. 03IPI Int I ronti 111 Icitircb Lib, C«r?illn. Or<|ti
69
-------
IATER QUALITY SIGNIFICANCE TO HUMANS
Canada
39 - Itter teitirce luttUry Jrci
Effects i 1960 Population
-19.1 0.0
Figure IV. 16
[111 0.0 4.8
lili 4.8 - 45.0
45.0 - 336.4
1 - 15.3
7 - 171.2
13 - 41.6
II - 370
31
S7
49
41
55
II
MO DAT*
3.1
MO D1TI
1 .1
131.3
DO Dili
2
I
14
28
21
32
31
44
50
51
62
OIDEMHID
in. 4
5.1
41.2
e.o
no DIM
10 OITl
- niiiriiiD
3 - 1.7
I -
IS - 145.4
21 - 1.4
17 -
S3 -
31 -
45 -
51 -
57 -
-t.i
-i.i
10 DITi
4
10
16
22
21
34
40
4C
52
51
I.I
DIDIFI1K1
3.3
1.4
-II.I
15.4
10 6iTl
DUIFIIIl
(.2
10 till
5
1 1
17
25
29
J5
41
47
53
59
357
12.5
OIDIF1IID
40.7
I .3
DIDirillD
0.4
10 DITi
D1DIFIIID
[later Resource Inventory Area]
II
16
24
1C
31
42
41
54
(0
21.5
19 DITi
O.I
4.2
OltlFIIIl
10 till
10 I1T1
O.I
DIDIFIII1
2.7
tttftttt bj ISiri 1tlln4i Ititirck frojriB. DSIP1 IBT 1 r o met 111 leitircb Lib. Cttiillii. Or«|ti
70
-------
LIFE SUPPORT SIGNIFICANCE TO HUMANS
Canada
• egon
91 * liter Rtioiree liteitor; Irei
Effects i I960 Population
|| -195 - 0
Pill 0-50
Figure IV.17
50 - 280
1 - 238
T - 3101
13 -
It -
25 -
Jl -
J7 -
43 -
41 -
55 -
(i -
((I
IBS
977
34
18
151
2 - Illirilll
I - S135
14 -
20 -
28 -
32 -
31 -
44 -
50 -
SI -
82 -
41
52
472
337
848
-II
-1
3 - (
i - outer i HID
li - 1819
21 - 11
27 - OlttriHD
33 -
It - -110
45 - -118
57 -
4 - HO!
10 -
18 - 30
22 - 72
28 - -11J
34 - 598
40 - gitirillt
48 - UIDIHIU
52 - 25
58 - 23
[later Resource inyentory Area]
280 - 3935
5 - 184
11 - »25
I? - DIDIP1IID
ZJ - 244
29 - 71
35 - OIDIHIID
41 - 4
47 - OlDIPimD
S3 - tlDIPHID
59 -
8 - 88
12 - mtirilll
18 - 237
24 - 48
30 - OlDirillD
38 - 477
42 - UltirillD
41 - 91
54 - OIDIMIIO
10 - 19
b; USIFJ IMIilds Itltirek trtittm, DSIPi lit I r oinel t i I loeircb lib. Corttllli. Orc|
-------
APPENDIX V.
Rankings of hydrologjc units for hydrology, water quality, and life
support cumulative effects.
Rank Hydrology Water Quality
Unit Value Unit
Life Support
Value Unit
Value
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
45
28
39
44
50
41
37
3
49
32
38
31
16
58
36
55
60
34
52
29
6
13
5
11
21
8
22
26
14
24
23
20
1
48
7
18
15
-165.245
-102.264
-87.512
-30.715
-0.239
8.760
59.098
115.905
125.684
126.782
157.823
303.196
386.385
403.658
482.614
527.130
636.834
639.944
704.145
812.081
965.118
1008.363
1043.738
1080.582
1131.079
1178.487
1195.298
1276.895
1321.734
1939.189
2447.272
2634.612
2923.109
3603.318
5246.556
12033.100
12070.530
12
31
36
40
42
43
44
50
51
53
58
61
28
45
39
4
18
20
38
48
41
29
3
37
16
49
21
1.4
22
32
6
24
60
26
5
1
55
NO DATA
NO DATA
NO DATA
NO DATA
NO DATA
NO DATA
NO DATA
NO DATA
NO DATA
NO DATA
NO DATA
NO DATA
-0.333
-0.250
-0.228
0.000
0.000
0.000
0.000
0.000
0.107
0.298
0.392
0.466
0.515
1.061
1.220
1.359
1.655
1.699
2.441
2.768
2.845
3.130
4.268
5.121
5.184
39
28
45
44
50
41
3
37
38
16
21
6
14
32
49
29
60
5
20
22
58
55
24
26
36
52
34
23
11
31
8
1
13
15
7
19
18
-4.010
-3.371
-2.998
-2.103
-0.029
1.070
3.531
4.193
4.299
4.701
9.514
9.765
10.771
11.893
12.736
16.994
19.914
21.340
21.962
22.203
25.867
25.918
30.449
31.299
41.944
42.250
47.907
51.012
59.089
64.439
67.549
78.761
80.193
102.588
107.521
112.007
120.814
72
-------
APPENDIX V. Continued.
Rank Hydrology
Unit Value
Water Quality
Unit Value
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
19
4
2
9
10
12
17
25
27
30
33
35
40
42
43
46
47
51
53
54
56
57
59
61
62
15039.970 8
31492.910 11
UNDEFINED 7
UNDEFINED 13
UNDEFINED 34
UNDEFINED 15
UNDEFINED 23
UNDEFINED 52
UNDEFINED 19
UNDEFINED 2
UNDEFINED 9
UNDEFINED 10
UNDEFINED 17
UNDEFINED 25
UNDEFINED 27
UNDEFINED 30
UNDEFINED 33
'UNDEFINED 35
UNDEFINED 46
UNDEFINED 47
UNDEFINED 54
UNDEFINED 56
UNDEFINED 57
UNDEFINED 59
UNDEFINED 62
5.775
5.909
5.918
6.011
6.844
7.852
8.502
10.563
22.401
UNDEFINED
UNDEFINED
UNDEFINED
UNDEFINED
UNDEFINED
UNDEFINED
UNDEFINED
UNDEFINED
UNDEFINED
UNDEFINED
UNDEFINED
UNDEFINED
UNDEFINED
UNDEFINED
UNDEFINED
UNDEFINED
Life Support
Unit Value
48 134.006
4 176.851
2 UNDEFINED
9 UNDEFINED
10 UNDEFINED
12 UNDEFINED
17 UNDEFINED
25 UNDEFINED
27 UNDEFINED
30 UNDEFINED
33 UNDEFINED
35 UNDEFINED
40 UNDEFINED
42 UNDEFINED
43 UNDEFINED
46 UNDEFINED
47 UNDEFINED
51 UNDEFINED
53 UNDEFINED
54 UNDEFINED
56 UNDEFINED
57 UNDEFINED
59 UNDEFINED
61 UNDEFINED
62 UNDEFINED
73
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APPENDIX VL A synoptic approach to wetland planning in small watersheds: Mill
Creek feasibility analysis.
Representatives from the Wetlands Research Program at the Corvallis Environmental
Research Laboratory met with U.S. Environmental Protection Agency (EPA) Region 10
and the State of Washington's Department of Ecology (DOE) staff in July, 1989 to discuss
the application of the synoptic approach in the development of state water quality
standards protective of wetlands. Interest in using concepts from the approach to develop
more detailed analyses was expressed. The DOE wanted to identify the types of
information and procedures needed for a statewide wetland inventory. The Region's
interest was in developing a high resolution comprehensive approach for evaluating small
watersheds targeted as critical "clean up areas." This section of the Washington pilot study
addresses those interests.
The objective of this feasibility analysis was to examine the feasibility of using the
synoptic approach for wetland planning in a small watershed. Specifically, the goal was to
determine whether the approach could be used to develop an ecosystem management
strategy for protecting the hydrologic, water quality and life support functions of wetlands.
The Mill Creek Drainage Basin (Fig. VI. 1) in southern King County, Washington, was
chosen for this effort to complement concurrent planning studies in the basin funded, in
part, by EPA Region 10 (U.S. EPA 1989). Several government agencies (federal, state
and local) are participating in the study of Mill Creek because it is one of the more
pristine areas of southern King County, has a relatively high percentage of wetlands (ca.
21% of the land area), and is under great development pressure from surrounding
communities (Eric Stockdale, pers. comm.)
APPROACH
The approach to this analysis consisted of identifying the data requirements particular
to the scale of study, contacting the appropriate agencies for data sources and ongoing
studies of Mill Creek, and developing a plan for the analysis of wetland landscape data.
SCALE CONSIDERATIONS
The synoptic approach is based on the assumption that data can be organized and
summarized to characterize the extent of processes affecting landscape function (landscape
inputs), the contribution of wetlands to enhancing landscape function (wetland capacity),
and the extent of impacts to wetlands (cumulative impacts). The synoptic framework can
be applied at a variety of geographic scales and thus is independent of scale (Abbruzzese
et al. submitted). However, the type of data required is dependent on the scale of
analysis. The method assumes that the contribution of different ecosystems to landscape
function is independent of ecosystem location. For example, wetland capacity is estimated
74
-------
Figure VI. 1 Mill Creek Drainage Basin
Subcatchment Boundary y\i 8
Stream
OOS1 Tribuury Number
• 4104 Proposed Project
75
-------
using total wetland area alone, without considering location, since locational information
requires a greater level of analysis. This assumption will be valid as long as the watershed
is large enough so that site specific effects become negligible, or as long as any site specfic
effects are consistent between watershed units, allowing them to be ignored. At the
regional or watershed scale, these conditions should be met. At the subwatershed level,
however, the area of a unit may not be large enough to dampen site specific effects, and
thus spatially explicit data are necessary. For example, the effects of bridges, roads, and
sewer outfalls on local hydrology and water quality become critical at the local level. In
addition, since more detailed data sources may be available at the county or local scale
than at the state or national scale, these sources should be considered in selecting
surrogates for the indices of wetland function and impacts.
IDENTIFICATION OF DATA SOURCES
A variety of agencies were contacted to identify potential data to serve as surrogates
for the synoptic indices, including: EPA Region 10, the Corps of Engineers (COE)--Seattle
District, Washington DOE and Department of Natural Resources, Puget Area Council of
Governments, King County Planning and Surface Water Management Divisions, University
of Washington and the Municipality of Metropolitan Seattle. It appears that adequate data
exist, or are being generated, to characterize and develop management strategies for the
Mill Creek watershed. Coordination of the agencies managing Mill Creek and integration
of their research efforts is probably the most important need. Following is a list of data
sources identified for each synoptic index:
Hydrologic Input-
A Hydrologic data on discharge for sub-basins as it becomes available through the
COE for the Special Area Management planning process.
B. Runoff potential-Hydrologic soil groups from King County Soil Survey (U.S.
Department of Agriculture, Soil Conservation Service. Map scale 1:20,000). Land
use/Land Cover from King County land use maps. Map scale 1:2,000.
C. Slope and channel length~U.S. Geological Survey topographic maps. Map scale
1:24,000.
D. Hydrologic modifications-COE and Public Works departments of King County and
cities of Auburn and Kent.
Water Quality Input-
A Point and Non-point water quality data-Municipality of Metropolitan Seattle (range
of variables measured monthly or annually since 1970's at mouth of Mill Creek),
King County Surface Water Management Division (monitoring of Mullins Slough
and outfalls into Mill Creek), Green River Community College (monitoring of
physical, biological, and chemical variables at four points in Mill Creek watershed
since 1987).
76
-------
B. Locations of point and non-point pollutant source areas-King County Planning
Department (Wetland Inventory, Land Use maps, High Erosion Potential maps).
Life Support Input-
A. Observed plant and animal species-King County Wetland Inventory conducted in
accordance with Sensitive Areas Ordinance.
B. Rare, threatened or endangered species-Department of Natural Resources Heritage
Program and Department of Wildlife Non-game data system.
Wetland Capacity
A. Wetland area and type-U.S. Fish and Wildlife Service National Wetland Inventory
maps. Map scale 1;24,000.
C. . Storage capacity, water quality improvement capacity and habitat quality-ratings for
all wetlands, based on collected data, provided in King County Wetland Inventory.
D. Flood prone areas-King County Comprehensive Plan
Cumulative Impacts-
A. Current wetland area~as described under Wetland Capacity above.
B. Original wetland area-hydric soil area from King County soil survey.
Future Loss-
A. Population-Puget Sound Council of Governmnents-census tract data and population
projections for the next thirty years.
B. Land Use-Data on zoning and planned land use patterns and recent land use
trends, population growth-King County Planning Department Comprehensive Plan.
77
-------
PLAN FOR ANALYSIS OF WETLAND LANDSCAPE DATA
OBJECTIVE
The objective of the analysis is to develop an ecosystem management strategy to
protect wetland functions, specifically to:
1. Characterize the wetland population.
2. Lo&te wetlands providing hydrologic, water quality and life support functions.
3. Characterize threat to wetland function.
4. Identify areas where wetland creation would be most useful.
METHOD
1. Collect data and map, by sub-watershed, to characterize synoptic indices of
hydrologic, water quality, and life support inputs, wetland capacity, cumulative
impacts and future loss from data sources identified.
2. Create map overlays depicting range of values for each index, manually or
with a Geographic Information System.
3. Delineate areas, watersheds or other units, of relative homogeneity relative
to wetland function (e.g. areas with excess capacity, areas where capacity is
exceeded, areas sensitive to future loss).
4. Develop matrix with criteria for protection, wetland restoration and
enhancement, etc.
5, Comparatively rank subunits according to criteria developed.
78
-------
CONCLUSION
This feasibility analysis suggests that adequate data do exist for the Mill Creek
watershed to be used in a synoptic approach assessment for wetland planning. An
assessment at this scale would contribute information useful to fine tuning the synoptic
approach. It should be kept in mind, however, that in performing an analysis at the
subwatershed scale, particular attention will have to be focused on determining any site
specific factors that might be so important as to overwhelm the general trends described
by a synoptic approach.
79
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LITERATURE CITED
Abbruzzese, B., S.G. Leibowitz, F.L. Morris, P.R. Adamus, CB. Johnson, and E.M.
Preston. 1990. A synoptic approach to the assessment of cumulative effects of
wetland loss on landscape function. Submitted to Environmental Management.
Stockdale, Eric, King County, Washington, Planning and Community Development Division,
personal communication, 1990.
U.S. EPA Region 10 Management Division. 1989. Region 10 environmental indicators
FY 88 summary. U.S. Environmental Protection Agency, Seattle, Washington.
80
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