WRIA 6 Hydrographic Inventory and Modeling, Stream Water Typing,
and Watershed Inventory and Characterization.
The function and management of coastal streams and their associated watersheds have largely been
ignored in salmon recovery plans, shoreline master programs, and critical area ordinances. This is in
part due to the lack of information about the ecological functions of these stream systems both at the
site level and in the broader Puget Sound landscape context. There is a lack of accurate information
about fish use of these systems, and in some cases the documented existence of these streams. Recent
work by Beamer et al. 2013 has shown that coastal streams with watersheds with an approximate
minimum size of 111 acres in the Whidbey Basin are utilized by both ESA listed Chinook and other
salmon for rearing. Spawning of cutthroat trout, Coho, Chum salmon have also been documented in
small coastal streams throughout the Whidbey Basin and greater Puget Sound.
The efforts to better understand the ecological role of coastal streams at the site and landscape scale
are occurring at the same time that the environmental impacts of increasing development are being
observed in these systems. Research over the past decade has identified multiple impacts from the
development and urbanization of coastal streams including impacts to fish from urban runoff such as
pre-spawn mortality in Coho returning to coastal streams (Feist et al. 2011, Scholz et al. 2011), impacts
to salmon olfactory organs (Sandahl et al. 2007), impacts to macroinvertebrate assemblages and health
(Morely et al. 2002, DeGasperi et al. 2009, Alberti et al. 2007) and impacts to stream geomorphology
and hydrology (McBride et al. 2005, Booth et al 2001, Sergura et al. 2010).
An assessment tool is needed to identify ecologically important streams systems and assess their health
at the appropriate scale so that the proper protection, management, and restoration of these systems
can occur. The Puget Sound Watershed Characterization (PSWC) project was the first concerted effort
to look at watershed systems across the entire Puget Sound and try to assess their relative health and
necessary protection, management, and restoration actions needed. The PSWC results proved useful
for rivers systems and Puget lowland streams, however, details about watersheds classified into the
coastal group were lost when they were aggregated into analysis units (AU). The PSWC coastal group
was assembled based on similar landform, geologic and water flow characteristics into AU’s on average
of about one square mile (Stanely et al. 2009). The basis for this aggregation was theoretically sound but
in the case of Water Resource Inventory Area (WRIA) 6 the information did not provide detailed enough
information for use in Island County’s Fish and Wildlife CAO update. One of the goals of this project is to
help inform the process by which coastal group AU’s are generated and to help determine if the scale of
the PSWC is applicable to understanding and managing ecological function for the coastal group
watersheds.
Water Resource Inventory Area (WRIA) 6, is composed of Whidbey, Camano and other smaller Islands
(Smith, Minor, Deception, Strawberry, Ben Ure, and Baby Islands) and contains no large river system.
WRIA 6 is dominated by PSWC coastal group AU’s (96 out 118) with 22 AU’s classified as lowland
streams. WRIA 6 lies solely within the boundaries of Island County and is a predominately rural county
with limited resources for assessing conducting habitat assessments. In 2009 Island County began the
process of updating its Shoreline Master Program (SMP), fish and wildlife CAOs, and implementing
adaptive management for the WRIA 6 Salmon Recovery Plan (SRP) and a need was expressed by several
parties for more detailed information about ESA listed Chinook and fish use of streams in WRIA 6 as well
as means to assess and prioritize these streams for management, restoration, and protection efforts.
Three tasks were developed to address these needs:
1) WRIA 6 Hydrographic Inventory and Modeling: The goals for this task were to 1) conduct a
census of all drainage outfalls to fill data gaps in the existing hydrographic datasets 2)Model
surface water drainage to delineate watersheds based on confirmed areas of surface water
runoff
2) WRIA 6 Stream Water Typing: The goals for this task were to 1) conduct habitat surveys and fish
sampling for use in the development and calibration of fish presences models for coastal
streams. 2) Develop a predictive juvenile Chinook stream presence model. 3) Develop a model
to identify “Fish Use” stream characteristics from Washington Administrative Code (WAC) 22216-031 Interim Water Typing System.
3) WRIA 6 Watershed Inventory and Characterization: The goals for this task were to 1) collect all
available and applicable geospatial datasets and compile and summarize them into the WRIA 6
watershed inventory geodatabase. 2) Generate a high resolution land cover classification from
2014 National Agricultural Inventory Program (NAIP) 4-band aerial imagery and incorporate into
WRIA 6 watershed inventory geodatabase 3) Conduct a watershed characterization to assess
current watershed health and prioritize protection and restoration efforts for fish.
WRIA 6 Hydrographic Inventory and Modeling
Purpose
Island County lacks an accurate and complete inventory of the hydrography in the County. Previous
hydrographic modeling efforts by the County utilizing ESRI’s ArcHydro tool set in ArcGIS resulted in the
most accurate data layer to date. However, assessment of the accuracy of the data layer was limited to
verify water courses that could be distinguish from aerial imagery or which crossed public roads.
Without a better assessment of the accuracy of the County’s water course data layer an accurate layer
depicting the County’s hydrographic watersheds could not be produced and any watershed
characterization or water type modeling work would be inaccurate. A hydrographic dataset based on
confirmed surface drainage locations needed to be developed
The goals for this task were to
1) Conduct a census of all drainage outfalls to fill data gaps in the existing hydrographic datasets
2) Model surface water drainage to delineate watersheds based on confirmed areas of surface
water runoff
Methods
ESRI’s ArcHydro hydrographic modeling toolset was used to model WRIA 6 hydrography utilizing a 2002
LiDAR derived bare earth digital elevation model (DEM) acquired from the Puget Sound LiDAR
Consortium (PSLC). A standardized threshold drainage area for initiating the generation of a drainage
line did not exist for WRIA 6 and a range of different drainage line initiation efforts were run in
ArcHydro, e.g. 50, 100, & 200acres. Initial efforts resulted in an overestimation of streams e.g. drainage
areas of 25 and 50 acres. It was decided after reviewing the data results and known stream locations
that a minimum drainage size of 100 acres to initiate a drainage course would be used. Existing datasets
from the Puget Sound Nearshore Ecosystem Recovery Program (PSNERP) and Island County were
included in the final drainage outfall dataset to determine how well they represented actual surface
water drainages and locations.
Verification of drainage outfalls was initially conducted utilizing GIS and remote sensing methods. A
combination of high resolution aerial imagery (NAIP, Google Maps, Bing Maps), oblique photos (Dept of
Ecology Shoreline photos1 and Bing Maps Bird’s Eye view2 and LiDAR3 was utilized. Key identifying
features that were used to identify drainage outfalls were, the existence of a drainage channel, ravine to
marine waters, observable drainage, and/or piped outfall. Drainages that were easily observable or
known to exist from previous fieldwork were classified as being present. At locations where the
presence of a stream could not be confirmed remotely the drainage site was identified for field
verification. All drainage sites in the GIS data layer were visited by boat or field checked from land
where boat access was not possible. All drainage outfall locations were corrected in the field if
necessary, on ruggedized field computer with GPS and running ESRI’s ArcGIS 9.3. In Island County there
were 17 drainage outfalls that were not unable able to be located or determined to exist. This was due
either to an inability to access the site or because a surface water drainage outfall did not exist at that
location. In some cases the hydrology of certain areas was so highly modified that determining whether
there was any surface drainage was not possible. The majority of all potential stream sites were visited
and either confirmed or designated as not present. Potential drainage outfalls between Admiralty Head
at Fort Casey State Park north to Deception Pass were verified only from land. Sites falling within U.S.
Navy Property were identified with remotely sensed data in the office and could not be confirmed in the
field. Despite the effort to conduct a census of every surface drainage in Island County there still exists
the potential that some surface drainages in the WRIA 6 were missed.
Table 1. Summary of drainage outfall census
1
Results of Drainage Outfall Census
Number of confirmed surface drainage outfalls
114
Number of surface drainage outfalls that could not be found
Number of surface drainage outfalls whose status was unable to be determined
Total Number of Original Drainage Outfalls Generated for Field Verification
58
17
189
Washington Department of Ecology oblique shoreline photos can be viewed at
https://fortress.wa.gov/ecy/coastalatlas/tools/ShorePhotos.aspx
2
http://www.bing.com/maps/
3
LiDAR downloaded from Puget Sound LiDAR Consortium website, http://www.pugetsoundlidar.org/
Table 2 Results of drainage outfall census by data source
Number of Drainage Outfalls
Modelled or from Pre-Existing
Data Sets
Number of Drainage Outfalls
Confirmed
Number of
Drainages Not
Found
Number of Drainage
Outfalls
Undetermined
40
16
21
3
127
83
30
14
Number of Drainage Outfalls
Identified by the Tulalip Tribes
11
10
1
0
Number of Drainage Outfalls
Derived from Island County
Stream Layer
11
5
6
0
Totals
189
114
58
17
Data Source
Arc Hydro Drainage Generated
Utilizing 100 Acre Drainage
Area to Initiate Drainage
Number of Drainage Outfalls in
Island County Derived from
PSNERP Stream Mouth Data
Layer
A final GIS data layer was generated representing the locations of all of the confirmed drainage outfalls.
This data layer was used to select the pour points generated from the Flow Direction and Flow
Accumulation grids in ESRI’s ArcGIS utilizing the ArcHydro modelling tools and to generate drainage
courses. These grids were also used to generate the modelled extent of drainage area that would
contribute to the surface drainage outfall, pour point4. All of the watersheds and drainage courses were
reviewed for consistency and any errors in overlap or underrepresentation were corrected. Many of the
drainage courses needed editing due to issues with damming of drainage lines behind road grades.
LiDAR DEM data needs to be conditioned by burning road crossing culverts into the DEM, otherwise the
model treats the road as a dam and will reroute the drainage course until it hits a low point in the road
at which to continue the modeled flow down slope. In some cases the existing Island County stream
layer provided the best representation of the actual flow of water across the land. In low gradient areas
where either canopy cover obscured the stream channels the meandering drainage course generated by
the modelling was accepted as the best representation of the drainage. In low gradient areas where
narrow drainage ditch elevations were not consistently represented in the data existing stream course
data from Island County was used or the drainage ditch was digitized in from aerial imagery. Four
drainage outfalls were not used to generate watersheds due to the fact that the drainage areas were
dominated by stormwater pipes and ditches making interpretation of a surface water drainage area not
possible. One of the watersheds on Whidbey NAS is defined by the airstrip to the west. There is a
culvert that runs underneath the airfield but due to the relatively flat topography and an inability to
access the site which direction the water flowed under the airstrip could not be determined. A final
watershed data layer was developed and is the basis for the watershed characterization, Map 2.
4
Details on the use of ArcHydro and hydrographic modeling can be found at ESRI’s website at
http://resources.arcgis.com/en/communities/hydro/01vn00000010000000.htm and The University of Texas
Center for Research in Water Resources at http://www.crwr.utexas.edu/reports/2004/rpt04-6.shtml.
Map 1. Results of drainage outfall census
Map 2. Map of Verified Island County Watersheds
Data Limitations
The final hydrography data set that includes drainage outfalls, drainage courses, and watersheds is
intended to represent where surface water drains off of land into the marine waters of the Puget Sound.
The term drainage is used for all surface water runoff. The purpose of the hydrography modelling and
mapping effort was to identify where surface waters drained across the landscape not to classify what
type of water they were e.g. stream, ditch, stormwater outfall.
Modeled Hydrography Analysis and Assessment.
The final outputs from the WRIA 6 hydrography modeling were confirmed drainage outfalls, corrected
drainage course layer, and a watershed data layer for WRIA 6. A comparison between the Puget Sound
Watershed Characterization Assessment Units (AU), Island County’s original watershed data layer
(OICW) and the updated watershed data layer (UICW) was conducted for this report and is shown below
in Maps 3 and 4. The AU layer is not meant to solely represent surface hydrography and this is apparent
in Figure 3. The AUs also do not represent any watersheds less than 188 acres. The updated Island
County watersheds have 37 out of 109 watersheds which are less than 188 acres in area and the original
Island County watershed layer has 82 out of 190 watersheds that are less than 188 acres. The primary
difference between the OICW and UICW is that the UICW are based on confirmed surface water
drainage whereas many of the watersheds in the OICW are solely based off of modelled hydrography.
Figure 1. Comparison of watershed size distributions by source
Map 3. Comparison between the updated and original watershed layer for Island County.
Map 4. Comparison between the Puget Sound Watershed Characterization assessment units and the updated Island County
watersheds.
Results
The final outputs of the hydrographic modelling and mapping are the basis for the water typing of
streams and for developing a watershed characterization for Island County in the rest of this document
and are provided in the Watershed Inventory and Characterization geodatabase.
WRIA 6 Stream Water Typing
Purpose
Information about the use and location of fish in streams in WRIA 6 was limited to local knowledge, a
few reports and the Washington Department of Natural Resources (WDNR) hydrology GIS datalayer. The
primary data source in Washington State for locating streams that have fish presence in them is the
WDNR which maintains the GIS hydrology database which contains the water typing classifications for
the entire State of Washington. The WDNR identifies the “water type” of a stream as having “fish use”,
or “F-Type” streams, under the definitions and determinations given in Washington Administrative Code
(WAC) 222-16-031. Water typing was developed by WDNR as a process for regulating forest practice
activities that effect surface waters in Washington State. However, WDNR’s GIS database and water
typing classifications are commonly used by land use permitting agencies when reviewing critical areas
ordinance permits (CAO) to help them determine the required buffer setbacks from streams. The water
typing dataset that exists for WRIA 6 is primarily based on a logistical regression model that utilizes a
DEM with a resolution of 10 meters. This level of resolution works well for larger stream and river
systems but can under represent or not detect smaller streams with fish presence. The majority of
streams in WRIA 6 are relatively small and there has been limited use of the WDNR modeled water
typing data in WRIA 6 since it sometimes portrays stream that do not exist or does not portray streams
that do exist, and very little validation field work has been done to correct or calibrate the model in
WRIA 6. As a result there has been a lack of protection of small coastal streams with fish presence in
WRIA 6. Utilizing the updated and verified hydrography inventory for WRIA 6 a new effort at water
typing was conducted to fill this data gap.
The goals for this task were to:
1) Conduct habitat surveys and fish sampling for use in the development and calibration of fish
presences models for coastal streams.
2) Develop a predictive juvenile Chinook stream presence model.
3) Develop a model to identify “Fish Use” stream characteristics from Washington Administrative Code
(WAC) 222-16-031 Interim Water Typing System.
Methods
It is not feasible to sample or conduct habitat surveys on all of the streams in WRIA 6. Filling this data
gap requires that an updated fish presence model be developed for coastal streams in WRIA 6 based on
higher resolution LiDAR DEM data paired with measured stream characteristics and fish sampling data
to calibrate and validate the model.
The water typing modeling effort was nested within the larger effort of trying to identify key physical
features that can be modeled with existing geospatial datasets to identify small coastal streams utilized
by juvenile salmon for rearing. The study area encompassed all the marine areas in the Whidbey Basin.
The stream habitat surveys, fish sampling effort, and GIS modeling included portions of Snohomish
County from the City of Edmonds up to Warm Beach in Port Susan, all of WRIA 6, and Fidalgo Island in
Skagit County. The large geographic extent of the field and modeling effort was needed to ensure that
enough field data was collected for comparison with modeled data. Two models were developed, one
to identify WDNR water typing stream characteristics the other to predict the presence of juvenile
Chinook in coastal streams. The Potential Fish Presence (PFP) model or F-type model identified
potential fish use by looking at the connectivity of streams to marine waters for anadromous fish access
to the lower reaches of the stream using stream characteristics defined in WAC 222-16-031 criteria for
fish use. The PFP model was intended to only identify streams with characteristics defined in WAC 22216-031 to be considered streams with “fish use” and not to identify the upstream extent of fish
presences. The purpose of the model was to “flag” streams that have potential fish presence for further
investigation or consideration for permitting and planning. A data layer was generated to assist with
planning and watershed management efforts. The data layer identifies all stream segments with
gradients 16% or less that are continuously connected upstream from the mouth and is only intended to
identify anadromous habitat.
The predictive juvenile Chinook model was based on the juvenile Chinook salmon presence rate and
abundance to statistically test effects of landscape, stream, and stream mouth characteristics. The
predictive juvenile Chinook model was developed as part of another report, Juvenile Chinook Salmon
Rearing in Small Non-Natal Streams Draining into the Whidbey Basin, and is available online5. The
methods, analysis, and results of this model are not discussed in this report and you should refer to the
other report for details about the model. The results of the predictive model are used for analysis in the
watershed characterization portion of this report.
Habitat Surveys
Habitat surveys were conducted on 61 streams throughout the study area. Data was collected utilizing
protocols described in the quality assurance project plan (QAPP) for Predictive Modeling & Protection of
Coastal Streams in WRIA 6. Habitat surveys were conducted to identify unique stream reaches in each
stream based on slope, bankfull width, wetted width, and stream geomorphology. Each stream reach
was labeled in sequential order with the first reach, reach 1, always being the intertidal area of the
5
Skagit River System Cooperative documents website,
http://www.skagitcoop.org/documents/EB2752_Beamer%20et%20al_2013.pdf
stream and features such as culverts were also classified as reaches. An example of the habitat data
collected is shown in Table 3.
Table 3 example of habitat data collected by reach.
Site ID Reach #
BRBA07
BRBA07
BRBA07
BRBA07
BRBA07
BRBA07
BRBA07
BRBA07
1
2
3
4
5
6
7
8
Unit
Type
Intertidal
Stream
CUL
Stream
Stream
Stream
CUL
Stream
Reach Unit
Length
(meters)
15
12.4
43
24.9
69.9
22
37.2
Average
Average
Average Reach
Reach
Max Depths Wetted Width
Gradient % (meters)
(meters)
1.5%
2.02
1.5%
0.70
3.80
3.6%
6.0%
1.4%
7.0%
9.5%
0.49
Average Reach
Bankful Width
(meters)
4.60
2.07
1.28
1.94
3.30
3.36
3.48
2.64
4.08
Information about the intertidal reaches were recorded during each fish sampling event and only culvert
length was consistently collected. All of the reach units were marked with flagging in the field for
reference during fish sampling. Results of the habitat survey data were combined with the fish catch
results for analysis and were used to compare measured stream characteristics with modeled ones.
Fish Sampling
Fish sampling was conducted biweekly for at least 3 sampling events for each site February through
May. One pass electrofishing protocols described in the QAPP for Predictive Modeling & Protection of
Coastal Streams in WRIA 6 were employed. All fish sampling was conducted by reach so that reach
habitat attributes could be associated with the fish data. Culverts were not sampled except for one
exception in Japanese Gulch. Intertidal reaches were sampled when possible. The first 25 of each fish
species caught were measured to fork length, where applicable, with any additional fish identified to
species and counted. Fish sampling focused on the lower reaches of streams and was not designed to
identify the extent of fish presence upstream.
Potential Fish Presence (PFP) Modeling (F-type modeling)
The intent of the fish presence modeling was to identify streams that meet habitat criteria outlined in
WAC 22-16-031-3-i-A for classifying a stream as a F-Type, or stream used by fish, from physical
characteristics that states:
“(i) Waters having any of the following characteristics are presumed to have fish use:
(A) Stream segments having a defined channel of 2 feet or greater within the bankfull width in Western
Washington; or 3 feet or greater in width in Eastern Washington; and having a gradient of 16 percent or
less;”
The results of the fish sampling agree with the use of the 16% gradient as an indicator of for identifying
fish use Figure 5. Fish sampling results showed that most of the fish caught were located in stream
reaches that were 16% gradient or less. A potential bias exists in the data since only the lower 200
meters of streams were sampled. This tends to be the lower gradient areas of the streams, however
many of the streams sampled had steep increase in gradient within 200 meters of the shoreline.
Figure 2. Fish CPUE plotted by percent stream reach gradient
All of the streams that were sampled had a bankfull width of .61 meters, 2 feet, or greater so
determining if fish were present in streams with bankfull width channels of less than 2 feet was not
possible or available for comparison with modeled data.
Modeling Gradient
Using the confirmed surface drainage outfalls and ArcHydro hydrographic modeling from the previous
task 50, 100, 150, and 200 feet stream segments were generated from the derived Flow Accumulation
drainage lines and elevation values were extracted at each line segment intersection and the change in
elevation was calculated and then divided by the length of the line segment (up slope end segment
value - down slope segment end value/ segment distance) to calculate a gradient value for each stream
segment. The elevation data was extracted from LiDAR derived bare earth DEMs with a pixel resolution
of six feet with a calculated vertical accuracy of 30 centimeters or approximately 1 foot. An attempt was
made to derive the average slope for reaches by extracting and averaging slope values from a slope grid
derived from the LiDAR DEM using ArcGIS Spatial Analyst Slope tool but the resulting slope values were
abnormally high compared to measured values. Anomalies in the LiDAR data in low lying areas and in
steep sloped terrain areas negative values were calculated for some stream segments. The percent of
negative segments were calculated by dividing the total length of negative valued segments by the
entire sum of all the modeled stream segment lengths, Table 4, The 150 foot segments were chosen as
the best fit for calculating the modeled slope for streams.
Table 4. Negative slope value generated from deriving slope from LiDAR DEMs
Assessment of negative precent slope values by segement length
Sum of total length Sum of total length
Precent of modeled
Segement Length of modeled stream of negative slope stream slope segements
(ft)
segements (ft)
values (ft)
that have a negative value
50
620,595.9
108,882.3
17.5%
100
620,595.9
32,748.5
5.3%
150
620,595.9
17,236.8
2.8%
200
620,595.9
0.0%
The average modeled segment values were plotted against each measured reach gradient value which
showed that the models tend to overestimate actual gradient values. Looking at the error statistics,
Table 5, there does not appear to be a significant difference in the two methods except for the
maximum error associated with the 200ft segments.
Figure 3 plots of 150ft and 200ft modeled gradient against measured gradient values
Table 5
Modeled segment error calculated against measured
gradients
150 ft Segements
200 ft Segements
Mean
5.16%
4.92%
Standard Deviation
8.24%
9.67%
Max Value
17.74%
34.06%
Median Value
3.86%
2.27%
The catch per unit effort (CPUE) calculated from the fish sampling effort matched well with the modeled
reach values for the 150ft line segments, Figure 4, used to calculate gradient and appear to better
represent fish presence below 16% gradient than the 200ft segments Figure 5.
Figure 4
Figure 5
The modeled parameters were all analyzed using a Best Fit and Akiake Information Criteria (AIC) in
Primer-E Primer and Permanova v6 to determine what modeled characteristics, in sampled streams,
best explained the fish assemblages. The results showed that both the modeled 150ft and 200ft reach
slopes are significant and explain 4.14% and 3.34% of the variability but the AIC best overall solution
does not include the 200ft modeled slope values, Figure 7. The 150ft segments were chosen as the best
fit for deriving segment slope for identifying F-Type streams.
Primer PremAnova v6 Output
VARIABLES
1 Model watershed Acres
Trial
2 Modeled 150 avg slope % reach
Trial
3 Modeled 200 avg slope % by reach
Trial
4 Model MeanFetch (m)
Trial
5 Model Path Distance
(m)
Trial
6 Model Least Resistance Path Distance (m)
Trial
MARGINAL TESTS
Variable
SS(trace) Pseudo-F
Model watershed Acres
P
Prop.
1.40E+05
128.6
0.001
0.21376
Modeled 150 avg slope % reach
27036
20.407
0.001
4.14E-02
Modeled 200 avg slope % by reach
21852
16.359
0.001
3.34E-02
Model MeanFetch (m)
70786
57.439
0.001
0.10829
16155
11.986
0.001
2.47E-02
11820
8.7101
0.001
1.81E-02
Model Path Distance
(m)
Model Least Resistance Path Distance (m)
OVERALL BEST SOLUTIONS
AIC
R^2
RSS
No.Vars
3257.1
0.32652
4.4024E5
5
Selections
1,2,4-6
3258.2
0.32776
4.3944E5
6
All
3261.2
0.32073
4.4403E5
5
1,3-6
3264.2
0.31346
4.4878E5
4
1,2,4,5
3265.2
0.31206
4.497E5
4
1,4-6
3265.4
0.31466
4.48E5
5
1-5
3268.2
0.30761
4.5261E5
4
1,2,4,6
3268.4
0.30743
4.5273E5
4
1,3-5
3269.5
0.30866
4.5192E5
5
1-4,6
3272.1
0.30193
4.5632E5
4
1,3,4,6
Figure 6
Data Limitations
The potential fish presence model only identifies streams with potential anadromous fish use. The
modeling effort looks at fish accessibility from the mouth of the stream up. The study did not investigate
the extent upstream that fish can travel. However, it did classify all of the stream sections with gradients
of 16% or less and continuously connected to marine waters as potential fish presence. This data is
intended for use by Island County planners to identify stream reaches that need to be evaluated for fish
presence to ensure the proper planning and county ordinances are applied. The data layer does not
identify fish streams with upland sources such as ponds, lakes, or resident fish. The data only models
potential fish use stream segments and should not be used as a definitive classification.
The calculation of slope information included several sources of potential error. The elevation values
may not have accurately represent the actual elevations in the stream channel. Elevations were derived
from the Puget Sound LiDAR Consortium (PLSC) Island County LiDAR dataset and have a vertical accuracy
of 30 cm or less in flat open surface which could result in a vertical error of approximately two feet
when calculating the stream segment slope. Artifacts in the LIDAR such as road grades, bridges, or
vegetation could have resulted in inaccurate elevations and in some cases result in negative slopes when
derived. Some drainage ditches or low lying stream areas were not detected by the LiDAR due either to
the canopy cover being too dense, Figure 7 or the stream or drainage ditch feature being smaller than
the 6ft pixel values of the LiDAR can represent Figure 8. The result is that the modeled drainage line
does not follow the actual stream course. Fourth the derived slope segments do not pick up sudden
short vertical elevations such as small cascades or waterfalls. The slope data is a generalization of the
stream channel over 150ft and features that are considerably smaller than this can be lost. This is an
issue when there is a small waterfall or drop that could be considered a fish barrier that is not
detectable in the slope data such as examples shown in Figure 9.
Figure 7 Loss of defined channel in LiDAR due to canopy cover
The final modeled F-type streams identify modeled conditions that have been shown to have fish use
Figures 4 and 6. However, the only definitive means to verify that an upstream reach is an F-type is to
assess the stream in the field to determine if 1) the average gradient is 16% or less and 2) has a bankfull
width of 2 feet or more, and there are no natural barriers downstream from the site. Any streams with
a less than 16% gradient and bankfull width of 2ft or more above a manmade barriers such as culvers,
dams, and vaults is considered a fish use stream. For more information about water typing refer to WAC
222-16-031 and Forest Practices Board Manual Section 136.
6
http://www.dnr.wa.gov/BusinessPermits/Topics/ForestPracticesRules/Pages/fp_board_manual.aspx
Figure 8. Drainage line does not follow drainage ditch due to errors in the LiDAR data
Figure 9. Left, a 3 meter vertical cascading waterfall on a stream at Scatchet Head on Whidbey Island. Right, a 2 meter
waterfall at a stream near Point Demock on Camano Island.
Problems encountered
A major problem with the sampling data was the number of streams which had culverts on them which
directly affected fish presence in those streams. The presence of culverts at some of the streams
completely blocked fish access making the sampling results of those streams invalid as an indicator of
the stream being suitable for fish use. The use WAC 222-16-031 stream characteristics to identify
potential fish presence avoids the issue of having to really solely on the correlation between data
collected and stream habitat characteristics and as a result were used as the predictive parameters in
the PFP model.
Analysis and Assessment
The assessment of the different water typing methods was conducted qualitatively. The different
methods for determining fish use were compared by mapping all of the water typing methods employed
and comparing the number of water-typed values in tables to see how they differed.
Results
The results of the stream habitat surveys, fish sampling, and water type modeling show that fish use in
small coastal streams was widespread and that the potential fish presence mapping aligned somewhat
with the Washington Department of Natural Resources fish use modeling. However the WDNR layer has
more streams than the stream census found, Tables 6 and 7, and does not include some of the drainages
that were identified in the stream census, Map 5.
Table 6. Number of WDNR water typed streams in the study area and their water typing
Water Typing for WDNR Hydrology Datalayer
Fish Use
None Fish Use
No Data
Undetermined
Total
121
67
0
6
194
Table 7.Comparison of Fish Presences Modeling to WDNR Water Typing for Confirmed Streams
WDNR Water Typing Confirmed
Streams
Modeled Fish Presence
Fish Use
Fish Use Not Probable
No Data
Undetermined
Total
123
36
13
3
175
Fish Use
None Fish Use
No Data
Undetermined
Total
102
33
37
3
175
Map 5. WDNR streams compared to stream census results
The WDNR hydro layer only contains modeled fish use data and does not contain field verified data
according to the data layers attribute table. Twelve of the 31 streams sampled in WRIA 6 were
confirmed to have fish present in them. Across the entire study area, including WRIA’s 4,5,6,7 and8, 32
streams were confirmed to have fish present in them. 31 streams with culverts were sampled of which
17 did not have fish above the culvert. At 13 of the 17 culverted streams fish were found in the
intertidal channel below the culvert, suggesting that fish would have been present in the stream system
if not for the culverts blocking fish access, Map 6.
Table 8. Fish presence determined from fish sampling and habitat surveys for the study area
Fish Use Determined from Fish
Sampling
Fish Use in Stream
Fish Use Intertidal only
No Fish Observed
Not Samples
Total
32
15
23
105
175
Fish Use Determined from Habitat
Surveys
Fish Use
None Fish Use
No Data
30
1
144
Total
175
The location and types of salmon species encountered while sampling are shown in Map 7. The most
common species encountered were sculpin, Coho, Cutthroat, Chum, Chinook, three spine stickleback,
and steelhead. Coho, sculpin, chum, and Chinook dominated the intertidal catches while cutthroat,
Coho, and sculpin dominated the dominated the stream channel catches. Some of the difference in
values can be explained by the presence of culverts at the mouth resulting in different fish assemblages.
Coho were found in surprising numbers in the intertidal channels of streams and were prevalent
throughout the project area.
Table 9. Total catch by species for stream and intertidal reach types
# of
# of
Type
# of Chinook # of Coho # of Chum Cutthroat Steelhead
Intertidal
115
514
331
46
0
Stream
53
642
58
806
4
Totals
168
1156
389
852
4
# of
# of
Stickleback Sculpin
40
683
22
496
62
1179
Map 6. Comparison of different water typing results
Map 7. Salmon species encountered during sampling by site
Watershed Inventory and Characterization
Purpose
A comprehensive, accurate and detailed watershed characterization did not exist for WRIA 6. Previous
development of watersheds and watershed based assessment in WRIA 6 were either based on modeled
data with limited ground-truthing, e.g. DRAFT Water Quality Data Synthesis and Recommendations for a
Surface Freshwater Monitoring Program, or at a scale that was too coarse for local use, e.g. Puget Sound
Watershed Characterization Assessment Units. Recent monitoring and studies have highlighted the
importance of coastal stream systems as important habitat for juvenile Chinook and other salmon
(Beamer et al:2013) and water quality monitoring results have identified high bacteriological levels in
streams (Island County Environmental Health. 2012). An inventory of watershed based environmental
and conditions and pressures was needed to allow for better and more dynamic analysis of watershed
conditions and variables for use with planning, permit review, water quality assessments, and salmon
recovery planning. And watershed characterization assessing the condition and prioritizing protection
and restoration efforts for salmon recovery and fish protection was needed.
The goals for this task were to
1) Collect all available and applicable geospatial datasets and compile and summarize them into the
WRIA 6 watershed inventory geodatabase.
2) Generate a high resolution land cover classification from 2014 National Agricultural Inventory
Program (NAIP) 4-band aerial imagery and incorporate into WRIA 6 watershed inventory geodatabase
3) Conduct a watershed characterization to assess current watershed health and prioritize protection
and restoration efforts for fish.
Watershed Inventory
Land Cover Analysis
The land cover analysis was conducted to get a more accurate representation of land types in WRIA 6
for use in the watershed characterization. Analysis was conducted on 4-band imagery (red, green, blue,
and near infrared) from the 2014 National Agricultural Inventory Program (NAIP) aerial imagery. Training
pixels were carefully hand-selected to develop a spectral profile for each class (6 classes: mature forest,
young forest, agricultural/grassland, impervious surface, open water, and error/shadow class). The
original imagery (4-band) along with the spectral profile (also 4-band) were used as inputs in ESRI’s
Image Analysis Maximum Likelihood Classification Tool. A class for sensed vegetation was merged with
agricultural land. The water class was found to contain significant amounts of error, so was merged with
the error/shadow class. An Island County waterbodies class was then used to recreate the class. This
resulted in 5 land classes and 1 error/shadow class. ESRI’s Majority Filter tool was run multiple times
followed by ESRI’s Boundary Clean tool to remove isolated pixels and create more congruency in the
data. This raster data was then converted into polygon data so analysis of land cover by watershed could
be executed. Metadata was generated for the land cover and is included in the geodatabase. Attributes
for the land cover layer are:
Name: Unique identifier for each watershed
MEAN_Acre: Total area (in acres) of each watershed
SUM_Water_Acres: Acres of water as delineated in Island County’s “Lakes_and_Ponds” feature
class in each watershed.
SUM_Water_Pct: Percent of watershed classified as open water
SUM_MatureFO_Acres: Acres of mature forest in each watershed
SUM_MatureFO_Pct: Percent of watershed classified as mature forest
SUM_Ag_Acers: Acres of agricultural/grassland in each watershed
SUM_Ag_Pct: Percent of watershed classified as agricultural/grassland
SUM_Imperv_Acers: Acres of impervious surfaces in each watershed
SUM_Imperv_Pct: Percent of watershed identified as being covered by impervious surfaces
SUM_YoungFO_Acres: Acres of young forest in each watershed
SUM_YoungFO_Pct: Percent of watershed classified as young forest
SUM_Shadow_Acres: Acres of watershed unclassifiable due to shadowing and other errors
SUM_Shadow_Pct: Percent of watershed unclassifiable due to shadowing and other errors
Data Compilation
Island County Data
Island Count Planning and Community Development staff provided multiple GIS datalayers to
incorporate into the WRIA 6 watershed characterization. All of the layers provided were reviewed and
layers that we not useful in evaluating environmental conditions in the watersheds were omitted, e.g.
voting districts and fire districts. The layers selected for inclusion were intersected with the watersheds
layer developed for the project, then had attributes not deemed essential for the project removed.
These actions kept the datasets small and manageable. Metadata was then added to each layer to
describe what each attribute represented and how to link the data back to Island County's Dataset,
should a relevant attribute have been removed. Exceptions include the Geology, ParcelPoints, Precip,
Soils, and Watersheds feature classes. Attribute data as well as metadata are more complete for these
layers. The data layers and their descriptions and listed below. For more details on the datalayers refer
to the datalayer’s metadata in the geodatabase. Data layers incorporated in the watershed inventory
include:
AquiferRechargeAreas: Polygons of assessed aquifer recharge areas within the Island County
Catch_Basins: Points of the location of catch basins in Island County
City_Town: Polygons of the different cities areas, urban growth area, future growth planning
area, joint planning area, and non-municipal urban growth area.
Critical_Drainage_Areas: Polygons that identify areas of critical drainage.
Culverts: Points of the location of Island County maintained culverts
Culverts_WSDOT: Point of the location of culverts maintained by the Washington State
Department of Transportation
Dike_Drain_Districts: Polygons of the different diking districts in Island County
Eagle_Points_2006: Points of known eagle nesting sites (NOT FOR PUBLIC DISTRIBUTION)
Geology: Polygons of geologic map units defining extent, age, and lithology at a scale of
1:100,000 and 1:24,000 obtained from the Washington Division of Geology and Earth Resources,
Olympia WA. The 1:24,000 resolution mapping was available for most of the watersheds, but not
all. Therefore, the highest resolution data available for the entirety of each watershed is provided
in this geologic layer.
HOLI_region: Polygon of habitats of local interest
Lakes_and_Ponds: Polygon of lakes and pond in Island County
ParcelPoints: Centroids of parcels used to assess the parcel distribution and density within Island
County watersheds.
Parks: Polygons of lands designated as parks in Island County
Precipitation: The 30-year normal (1981 - 2010) for precipitation was obtained from the PRISM
Climate Group at www.prism.oregonstate.edu. A point feature class was then developed using
the centroids of each of the watersheds. Precipitation values were extracted by point from the
PRISM grid and appended to each of the watersheds.
Protected_Plants_and_Communities: Scientific and common name for the protected plant(s)
and/or community associated with the polygon feature in Island County.
Roads: Lines depicting the roads in Island County
Soils: Polygons of soil characteristics expected to impact water quantity, quality, and
hydroperiod. Data is obtained from the United States Department of Agriculture (USDA), Natural
Resources Conservation Service (NRCS) Soil Survey Program. Data was imported to ArcGIS
using the NRCS's Soil Data Viewer, available at http://www.nrcs.usda.gov/.
Trails: Inventory of trails in Island County, line file.
US_Navy_Property: Polygon of U.S. Navy properties in Island County
Watersheds: A polygon layer developed from LiDAR derived flow accumulation and flow directs
grids. Verified drainage outfalls were isolated to Whidbey and Camano islands for
characterization purposes. Topology was used with a 10 foot cluster tolerance to eliminate most
of the gaps and overlaps along the boundaries between the different watersheds. Larger gaps
and overlaps were reviewed and adjusted to best visually match the LiDAR DEM and Island
County's existing watersheds. Watersheds with multiple outlets were expanded to include all
drainage areas between the outlets.
Wells: Point locations of wells located within Island County
Wetlands: This dataset was composed in 2006 with the initiation of the Island County Critical Area
Update. During the process wetland information was complied from three main resources. The National
Wetland Inventory Dataset, digital wetland delineations performed by Pentec in 1998, and county
wetland files. Aproximity 750, 600, and 400 shapes respectively were merged together to form this
single dataset. Many of the same wetlands were found in each dataset thus when combined the total
number to wetlands was approximately 1000. Since the CAO Update began in 2006 the Planning Dept.
has followed a policy of regular updates of the Wetlands layer and will continue to do so in the future.
Other Data Sources
National Agricultural Imagery Program 2014 4 band (red, green, blue, and near infrared) aerial imagery
was acquired from the U.S. Department of Agriculture for more information visit the USDA’s website
http://www.fsa.usda.gov/FSA/apfoapp?area=home&subject=prog&topic=nai
National Land Cover Database: National Land Cover Database 2011 (NLCD 2011) is the most recent
national land cover product created by the Multi-Resolution Land Characteristics (MRLC) Consortium.
NLCD 2011 provides - for the first time - the capability to assess wall-to-wall, spatially explicit,
national land cover changes and trends across the United States from 2001 to 2011. As with two
previous NLCD land cover products NLCD 2011 keeps the same 16-class land cover classification
scheme that has been applied consistently across the United States at a spatial resolution of 30
meters.
Stream_points: A point layer developed by the Tulalip Tribes as part of this project. The datalayer
contains the modeled GIS stream characteristics used in the development of a predictive fish model for
juvenile salmon and the summary data from the stream habitat surveys and fish sampling in Island
County.
The watershed inventory geodatabase is available to all project participants and funding agencies. Upon
completion of this project maintenance of the watershed characterization geodatabase will be the
responsibility of the Island County Planning and Community Development Department
(ICPCD).Summary tables and maps of the data generated for the watershed inventory are located in
Appendix A.
Watershed Characterization
Watershed Condition Analysis
Indicators of watershed conditions and protection prioritization were generated and mapped against
four different fish presence scenarios, watersheds with known juvenile Chinook rearing, Map 8,
watersheds with WDNR designated fish type streams, Map 10, watersheds with modeled potential fish
use, Map 11, and watersheds identified to have juvenile Chinook in them from a predictive model, Map
9.
Map 8. Watershed with rearing juvenile Chinook
Map 9. Predicted Chinook presence model
Map 10. WDNR F-Type watersheds
Map 11. Modeled potential fish presence (PFP)
The assessment of current watershed conditions in WRIA 6 was conducted using a combination of
percent impervious surface land cover class derived from NAIP imagery and road density for each
watershed.
Percent impervious surface was generated from the land cover classification of the 2014 NAIP imagery.
One of the difficulties with interpreting the land cover classifications was the prevalence of shaded areas
where there was not a clear spectral signature as a result there were some error in the land cover
classification percentage cover estimates. Map 12 shows the percentage values for each watershed
when only impervious surface percentage is calculated. Map 13 shows percentage values for each
watershed when the impervious surface and shadow classification are combined.
Map 12
This comparison is to point out the potential error in the land cover classification. Percentage of
impervious land cover for each watershed was binned into six different zones adopted from Birch Bay
Watershed Characterizations and Watershed Planning Pilot Study, Table 10, to classify the relative
health of each watershed. Initial analysis of the percentage of impervious surface for each watershed
showed that only two watersheds throughout WRIA 6 have impervious land cover greater than 10%
over their watershed, (SKBA12 at 16.9% and PTSU03 at 11.9%) Map 12. These two watersheds are not
identified as having fish habitat except in the case of the predictive Chinook presence model, Map 9. The
analysis of watershed health by percent impervious surface cover does not identify any significantly
impacted watersheds. This is not overly surprising given that WRIA 6 is dominated by a rural landscape
and watersheds dominated by anthropogenic modification were not included in the analysis.
Map 13
Table 10
Watershed Impervious Cover Impacts
% impervious
cover
Watershed
Conditions
Stream Quality
0-6%
6-10%
10 -25%
25-30%
30-60%
Sensitive
Transitional
Respons Zone
Impacted
Transitional
Respons Zone
NonSupporting
Poor
Good
Fair
The results of the impervious surface analysis did not allow for discerning or differentiating the health of
the watersheds in WRIA 6. A readily available data set that has been used to assess watershed health
beyond impervious surface cover has been road density7. NOAA Fisheries defined road densities of less
than 2 miles per square mile with no valley bottom roads as "properly functioning". Densities between 2
and 3 miles per square mile with some valley bottom roads are designated as "at risk" and densities over
3 miles per square mile with many valley bottom roads are considered "not properly functioning" (NOAA
Fisheries Habitat Matrix: 1996). Richard et al:1998 noted that increased peak flows may be evident at
road densities of 2-3km/km^2. Increased peak flows have been shown to effect stream ecosystem
(DeGasperi et al. 2009). Review of the road densities in WRIA 6 watershed using the NOAA condition
classification proved overly sensitive, Maps 14, with the majority of watershed being classified as “nonfunctioning”.
A solution was to combine both metrics into a matrix to increase the number of assessment levels and
retain the relevance of the classification systems, Table 11, to effectively assess each watershed’s
health.
Table 11
Road Density Assessed Condition
Road Density
Condition
Classifications
7
Not Properly
Functioning
At Risk
Properly
Functioning
Road densities
greater than 3 miles
of road per square
Road densities
between 2 to 3
miles of road per
square mile
Road densities of
less than 2 miles of
roads per Square
Mile
% impervious cover
# of Watersheds
69
11
2
18
1
No Values
9
No Values
No Values
0-6%
good
6-10%
10 -25%
Good - Fair
Fair
Impervious Assessed Condition
USFS Watershed Condition Classification (Potyondy and Geier 2011),
Intensively Monitored Landscape Classification & Human Disturbance Characteristics (Whittier et al.
2011), National Fish Habitat Assessment (National Fish Habitat Board 2010),Northwest Forest Plan
(Gallo et al. 2005), NOAA Fisheries Matrix of Pathways and Indicators (National Marine Fisheries Service
Environmental and Technical Services Division Habitat Conservation Branch 1996)
Map 14
The results of the matrix were mapped by watershed with the different fish presence scenarios added,
Maps 15 and 16.
Map 15
Map 16
Watershed Action Prioritization
The purpose of the watershed action prioritization characterization was to identify and rank priority
actions for each watershed based on their current ecological integrity and level of development.
Watersheds that have fish use and ESA listed Chinook salmon use, are highlighted in the maps so that
the appropriate prioritized actions can implement for these ecologically important watersheds. The
protection prioritization characterization on WRIA 6 watersheds used two metric that best represent
current intact habitat conditions and potential/existing level of development. The two metrics used
were percent total forest land cover (mature forest cover plus young forest cover) and parcel density in
each watershed. The forest cover dataset is the closest assessment to identifying intact ecological
systems and parcel density is a good indicator of potential and existing build out scenarios. Results of
this characterization show areas with 50-100% forest cover as being priority action watersheds for
protection and conservation. Only three of the watershed had high parcel densities greater than 1.5
parcels per acre so they were incorporated into the protection and conservation classification. Areas
with 0-50% forested cover and parcels densities between 0-1 parcels per acre are priority action areas
for restoration. Areas with 0-50% forest cover and parcel densities between 1-2 parcels per acre are
priority action watersheds of enhancement, Table 12.
The results of the priority watershed action characterization are mapped with the different fish
presences scenarios in Maps 17 and 18. The expectation is the action prioritization ranking will useful for
Chinook salmon recovery planning and prioritizing.
Table 12
Legend Key
Percent Total Forest Cover
75-100%
a
EcologicaWatershed with / Priority is Protection and Conservation
50-75%
b
25-50%
c
Impacted Watershed with low density
development/ Priority is Restoration
0-25%
Impacted Watershed with high density
development/ Priority is Enhancement
d
Class
1
0 to 0.5
2
3
0.5 to 1
1 to 1.5
Parcels Per Acre
4
1.5 to 2
Map 17
Map 18
Larger version of the watershed characterization maps area located in Appendix D.
A copy of the geodatabase can be obtained from Island County Planning and Community Development
Department, PO Box 5000, Coupeville, WA 98239. (360) 679-7339
References
Alberti, M., Booth, D., Hill, K., Coburn, B., Avolio, C., Coe, S., & Spirandelli, D. (2007). The impact of urban patterns on aquatic
ecosystems: An empirical analysis in Puget lowland sub-basins. Landscape and Urban Planning, 80(4), 345–361.
doi:10.1016/j.landurbplan.2006.08.001
Beamer, E.M., W.T. Zackey, D. Marks, D. Teel, D. Kuligowski, and R. Henderson. 2013. Juvenile Chinook salmon rearing in small
non-natal streams draining into the Whidbey Basin. Skagit River System Cooperative, LaConner, WA.
Booth, D. B. and Henshaw, P. C. (2001) Rates of Channel Erosion in Small Urban Streams, in Land Use and Watersheds: Human
Influence on Hydrology and Geomorphology in Urban and Forest Areas (eds M. S. Wigmosta and S. J. Burges), American
Geophysical Union, Washington, D. C.. doi: 10.1029/WS002p0017
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(JAWRA) 43(2):414-426. DOI: 10.1111 ⁄j.1752-1688.2007.00032.x
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Appendix A: WRIA 6 Watershed Inventory Maps
See pdf file W6_WIM_Appendix_A.pdf
Appendix B: WRIA 6 Watershed Land Cover Maps
See pdf file W6_WLCM_Appendix_B.pdf
Appendix C: WRIA 6 Fish Presence and Comparison Maps
See pdf file W6_FPCM_Appendix_C.pdf
Appendix D: Watershed Characterization Maps
See pdf file W6_WCM_Appendix_D.pdf
Appendix E: Watershed Inventory Summary Data Tables
See pdf file W6_WISDT_Appendix_E.pdf