COASTAL GEOLOGIC SERVICES, INC.

Interim Results Analysis Feeder Bluff Restoration Assessment for Island and East Jefferson Counties

Prepared for: Northwest Straits Foundation, Joan Drinkwin Prepared by: Coastal Geologic Services, Inc. Preparer: Andrea MacLennan, MS, and Jim Johannessen, LEG, MS

December 19, 2014

Introduction and Purpose The objective this project is to develop a portfolio of feeder bluff restoration projects for Island and east Jefferson Counties, with willing landowners and conceptual restoration designs that are ready to refine and implement. To reach these goals, the project is delineated into ten tasks, the first five of which comprise a detailed feasibility and benefits assessment conducted using GIS. The assessment is focused only on parcels within the study area that encompass armored feeder bluffs. Armored bluffs are those in which a shore defense structure reduces bluff toe erosion, such as a bulkhead, seawall, riprap or other similar structure. The potential benefit of armor removal is assessed by analyzing nearshore conditions within each parcel and the net shore‐drift cell in which it is found. The feasibility of armor removal is assessed at a coarse scale using GIS. Outreach efforts will target locations where feasible, high‐benefit potential armor removal parcels are in abundance. Outreach efforts will include landowner workshops and individual site assessments. Site assessments and higher resolution analyses will affirm that armor can be removed without resulting in unnecessary threat to improvements on the subject property. Restoration designs will be developed for high‐benefit, feasible sites in which landowner willingness have been obtained. Bulkhead removal feasibility is informed by the background erosion rates of bluffs (bluff recession rates) within the study area that are subject to variable wave energy due to differing fetch, shore orientation, and geology. The focus of this memo is the provide a summary of the preliminary results of the bluff recession rates observed across the study area, which will be used to extrapolate future shoreline positions and where bulkheads can be safely removed without imposing the threat of erosion on existing improvements such as houses.

Methods Overview Bulkhead removal feasibility is assessed by applying a series of GIS steps, some of which require considerable analyses. The general concept is to measure structure setback distances (from the bluff crest) for each parcel in the study area, in which there is an armored feeder bluff. Next, bluff recession

1711 Ellis St. Suite 103, Bellingham, WA 98225 (360) 647-1845 www.coastalgeo.com Interim Results Analysis NWSF Feeder Bluff Restoration Assessment of Island and Jefferson Cty, Page 2 COASTAL GEOLOGIC SERVICES, INC. rates were measured from a stratified sample of unarmored bluffs in the study area. Bluff recession measures were made from bluffs with various combinations of exposure, shore orientation, and bluff geology. The bluff recession data are then analyzed against the different variables of potential influence. Based on the influence of these variables, all armored bluffs would be assigned to the stratification category that shoreline conditions resemble, to which a range of measured bluff recession rates can be extrapolated. The bluff recession rates for each category will be projected forward 75‐years and a safe setback distance will be identified for each bluff category. All parcels that either have no structures or structures that are setback adequately from the bluff crest (e.g. setback beyond the defined “safe setback distance”) will be identified as feasible for armor removal. The safe setback distance will also address the historical occurrence of large landslides at or near the site. The methods employed to identify each of the bluffs from which recession rates were measured, and the precise methods applied to measure bluff recession rates are described below. Shore Change Analysis The first step in conducting the shore change analysis element of this study was to identify unarmored feeder bluffs with variable levels of exposure, shore orientation, and geology. The stratified structure of the feeder bluff sample required that equal portions of the feeder bluffs were exposed to low, medium and high fetch categories. Roughly one‐third of the sampled bluffs were oriented to the northern quadrants and the remaining orientated to the south. The surface geology and availability of stratigraphy were then investigated for each bluff in the preliminary sample. High resolution aerial photography with visible shoreline conditions were an additional required component of bluff selection. Peer reviewed research was reviewed to identify techniques to reduce sources of uncertainty and calculate cumulative error in this type of analysis (Moore 2000, Ruggerio and List 2009, Fletcher et al. 2003, Ruggerio et al. 2003, Morton et al. 2004). Measures to reduce unnecessary error and uncertainty of analysis included:  Use of the largest scale vertical aerial photos (1:12,000)  Using the most reliable shoreline proxy (bluff crest or bluff toe)  Used a single digitizer at a consistent scale to reduce error associated with interpretation  Use of DSAS to reduce error associated with change measures  Alongshore averaging of change rates were applied within each shoretype to nullify localized trends within a given shoretype  Careful selection of sampled shoretypes to avoid potential sources of interference to a basic background shoreline change rate such as: bedrock promontories, rock outcrops directly off‐ shore, dramatic sediment supply loss in the drift cell, and shore armor within the subject shoreform The largest scale historic, vertical aerial photos were acquired and compiled in ArcGIS throughout the study area. Many historic air photos required georeferencing, which was conducted to achieve the highest local accuracy and minimal error (less than 5 RMS). For example, control points were placed waterward and landward of the bluff to assure local accuracy of the shoreline. Some of the bluffs identified for Interim Results Analysis NWSF Feeder Bluff Restoration Assessment of Island and Jefferson Cty, Page 3 COASTAL GEOLOGIC SERVICES, INC. analysis did not have adequate aerial photography, meaning that there were not adequate control points for accurate georeferencing or the bluff was shaded to the degree that features could not be interpreted with adequate certainty. In most cases, these bluffs were replaced with another site that met the stratification criteria. In total 39 bluffs were identified for analysis. A geodatabase was created to house all the bluff crest digitizing and perform the change analysis. An additional point layer was created to house summary and supporting data for the bluffs. The bluff crests from the historic vertical aerial photos were then digitized. Heads‐up digitizing was conducted at 1:700 – 1:1,000 scale. Breaks in the line were drawn in areas where the shore was too heavily forested to discern the location of the bluff crest. The bluff toe was delineated in some locations where the bluff crest position was not reliable. However, typically the most landward shoreline proxy was selected, as more landward features can be interpreted with greater accuracy (Ruggerio et al. 2003). The shoreline proxy that was delineated was noted in the attribute table as well as the year that feature represented. Different historical aerial photos were used for different areas, based on availability and the ability to clearly view the subject feature with a high level of confidence. Photos were typically 1: 12,000‐scale and ranged from 1956 to 1969. Current features were digitized from the most recent vertical aerial photographs of high resolution (Jefferson 2009, Island County 2013) or more commonly from LIDAR imagery (Island County 2002, Jefferson County 2004). Figure 1 provides an example of the digitization process from both historical and LIDAR imagery.

Figure 1. Bluff crest digitizing example from 1956 historic vertical image (top) and 2002 LIDAR slope change imagery of bluff (shoreform ID) 2754 on southwest Camano Island. Interim Results Analysis NWSF Feeder Bluff Restoration Assessment of Island and Jefferson Cty, Page 4 COASTAL GEOLOGIC SERVICES, INC.

Supporting data was populated in the attribute table. The shoreform ID from the Puget Sound Feeder Bluff mapping geodatabase (MacLennan et al. 2013) was used to identify each bluff. The type of bluff mapped along that shore reach was also noted (feeder bluff or feeder bluff exceptional). The maximum measured fetch was measured by hand by measuring the distance from the subject bluff as far as possible to the greatest distant land across the sea. These results will be compared with other methods of measuring fetch, such as those compiled in the ShoreZone Database, in the final draft of the report. Shore orientation quadrant was recorded, as was local geology (high resolution; 1:24,000), and whether or not bluff stratigraphy data were available for the site. All of the original feature digitizing was completed by a single, well‐qualified staff member (MacLennan) to assure consistency in feature interpretation, and preclude unnecessary bias associated with multiple analysts. All digitizing was QA/QC’d by senior coastal geologist Jim Johannessen to ensure accuracy. After quality assurance revisions were applied the data were ready for digital analyses. A secondary QA/QC step was applied after the erosion rates were calculated to identify and resolve potential problem areas. Each bluff where erosion rates were measured are displayed in Figure 2. DSAS and Statistical Analysis The Digital Shoreline Analysis System (DSAS) is a free software application that was developed by the Environmental Systems Research Institute (ESRI) and USGS (DSAS 2013). DSAS computes rate of change statistics for a time series of shoreline vector data. DSAS automates the shore change process allowing for greater efficiency and reduces the opportunity for error. Prior to running the software, baselines were created from which transects would be drawn perpendicular to the shoreline. Baselines were created by exporting sample shoreform reaches of the WDNR Shorezone shoreline (WDNR 2001) and buffering those reaches landward of the feature digitizing. Cumulatively over 910 transects were placed at 82‐foot (25‐ meter) intervals across the sampled bluffs. DSAS then calculated the distance between each shoreline feature from each transect and calculated an end point rate (EPR), which equates to the measured distance between the two features divided by the number of years between those features (e.g. 1957 and 2009). The EPR measures were then analyzed within each individual feeder bluff and across exposure and orientation categories. Compile Existing Erosion Rates Raulph Keuler, geologist with USGS, measured and compiled historic erosion rates from a number of sites throughout Island and Jefferson Counties (Keuler 1988). These measures were also compiled to augment new CGS bluff recession data (Figure 2). Keuler measured the distance between the bluff crest and known survey monuments at sites with earlier matching data from 17 bluffs in the study area. Supporting data on fetch, exposure, and shoreline geology were compiled for each of the Keuler bluffs, similar to the newly measured shore change bluffs.

Results Erosion Rates Erosion rates were measured using historic aerial photography and DSAS software and compiled with existing erosion rates measured by Keuler (1988). The results of each approach will be described below Interim Results Analysis NWSF Feeder Bluff Restoration Assessment of Island and Jefferson Cty, Page 5 COASTAL GEOLOGIC SERVICES, INC. both separately and together. These results will together help determine what a safe setback is in the study area for armor removal. Each of the bluffs and supporting data are found in Appendix A.

Shore Change Analysis The objective of the shore change analysis was to quantify the range of bluff recession from a variety of coastal bluffs to inform what a safe setback distance is for structures located landward of a potential armor removal project. To reach this goal, bluff recession rates were measured from 39 unarmored bluffs throughout eastern Jefferson and Island Counties (excluding the west shore of Whidbey Island). The average length of bluff crest digitizing was approximately 350 ft. Surface geology mapping showed that the majority of the bluffs were comprised of either Vashon lodgement till (31%) or Vashon outwash deposits (23%). At least nine other surface geology units were mapped across 1 or more of the bluffs that were analyzed. Bluff characteristics relevant to erosion rates such as maximum fetch (wave exposure) and shore orientation data were documented for each site and assigned to categories (Table 1). These categories will be used later to extrapolate bluff recession rates (based on bluff characteristics) and identify parcels in which armor removal can be conducted without presenting considerable erosion risk to existing structures. Table 1. Sampling design displaying shoreforms, stratified by fetch and orientation.

Fetch Categories (miles) Orientation Low (< or = 5) Mod (5 – 10) High (>10) North (13) 4 4 5 South (27) 8 7 11 Total (39) 12 11 16

The average measured erosion rate was 0.39 feet per year (ft/yr) across all bluffs (Table 2). The bluff with the least erosion measured 0.22 ft/yr and was from a south‐facing bluff, with only 2‐miles of fetch. Surface geology of the bluff was mapped as glacial till, one of the most resistant and prevalent post‐glacial deposits that occurs in the Puget Sound. The bluff with the greatest erosion faced the northern quadrant and had over 41 miles of fetch. The surface geology of the bluff was mapped as Qguc which is characterized as both undivided fraser and pre‐fraser deposits. The extent of the range of erosion rates is well captured in the standard deviation (0.28 ft/yr). As one might expect, feeder bluff exceptional units (0.57 ft/yr, n=7) eroded considerably faster than feeder bluffs (0.35 ft/yr, n=32). The spatial distribution of the bluff erosion rates is shown in Figure 3. North‐facing bluffs had consistently higher bluff erosion rates, which is likely due to the higher average fetch among the moderate to high exposure categories (S‐facing 12.9 miles, versus N‐facing 17.7 miles; Table 2, Figure 4). This pattern could be due to the sampling and the somewhat arbitrary break in the moderate to high exposure categories at 10‐miles. However, there exists a similar pattern in the natural variability of exposure in northern Puget Sound. In this part of Puget Sound maximum fetch to the south ranges up to approximately 25‐miles. In contrast, north facing bluffs can be exposed to the Strait of Juan de Fuca, where maximum exposure can be up to 50 miles or more. The erosion rates of north‐facing bluffs are slightly faster than south‐facing bluffs but considerably more variable than south‐facing bluffs. Interim Results Analysis NWSF Feeder Bluff Restoration Assessment of Island and Jefferson Cty, Page 6 COASTAL GEOLOGIC SERVICES, INC.

Table 2. Bluffs erosion rates from new shore change data including: average erosion rates, ranges, and standard deviations (stdev) with shore orientation and fetch categories.

Low Mod High N S N S N S Min -0.22 -0.13 -0.25 -0.24 -0.30 -0.12 Max -0.34 -0.64 -1.02 -0.77 -1.53 -0.77 Average -0.27 -0.31 -0.48 -0.36 -0.71 -0.34 Stdev 0.05 0.16 0.36 0.18 0.53 0.17 Range -0.11 -0.51 -0.78 -0.53 -1.23 -0.65

Figure 4. Average erosion rate by shore orientation and exposure categories

Low Mod High 0.00

‐0.10

‐0.20 Rate ‐0.30

‐0.40 Erosion

‐0.50 Average ‐0.60

‐0.70

‐0.80 North South

Analysis of Existing Erosion Rates As previously mentioned, Keuler (1988) measured erosion rates throughout the study area using a different and likely more accurate methodology. These erosion rates were compared with those measured using the shore change analysis approach. It is important to be aware that although the Keuler method of measuring erosion rates has a lower error margin, it is a shorter sampling period, and therefore likely does not capture as many erosion events as the new shore change data. This data limitation could skew the data towards lower erosion rates. Keuler did not measure bluff erosion from many bluffs with low fetch. However erosion rates were more comparable for low to high exposure bluffs that are orientated to the south. Similar to the new shore change analysis work, Keuler’s erosion rates were on average much higher (for sites with moderate and high fetch) along north‐facing bluffs. Table 3 displays a summary of the exposure, orientation, and number of each bluff. Interim Results Analysis NWSF Feeder Bluff Restoration Assessment of Island and Jefferson Cty, Page 7 COASTAL GEOLOGIC SERVICES, INC.

Table 3. Keuler bluff erosion rates (1988) with data including: average erosion rates, ranges, and standard deviations (stdev) with shore orientation, and fetch categories. Low Mod High N S N S N S Min na 0.30 0.10 0.03 0.16 0.26 Max na 0.30 0.30 0.21 0.98 0.49 Average na 0.30 0.19 0.12 0.39 0.37 Stdev na 0.30 0.08 0.13 0.31 0.12 Range na 0.30 0.20 0.18 0.82 0.23

Feasibility Screening This element of the armor removal assessment is complex as considerable uncertainty exists regarding how fast feeder bluffs will recede in the future. Therefore it is important to keep in mind that this approach was developed for a regional‐scale analysis, in which measured rates are extrapolated based on bluff characteristics relevant to erosion rates. The intent of this approach is to identify and filter out parcels in which bulkhead removal is clearly infeasible. Armor removal was only considered feasible when there are no structures at risk on a given property. A site assessment must also be conducted to confirm armor removal feasibility and assess more site specific qualities, hazards, and current management. Bluff recession rates from unarmored bluffs were measured and analyzed with exposure and orientation data, and bluffs were assigned categories based on the results accordingly. Annual bluff recession rates were then projected (for each category) forward 75‐ years, and a safety factor of 25‐ft was added to the 75‐year recession distance. Structures were then queried within range of the bluff crest. Parcels with structures waterward of the “safe setback distance”, will be considered not feasible for armor removal. Historic erosion rates analysis is commonly conducted to forecast the future position of the shoreline (or bluff crest in this case). However, there are several assumptions that make this approach alone sub‐ optimal. For example, relying on hind‐casting alone assumes that conditions will not change in the future. Sea level rise, wave energy, and other implications of climate change such as increased precipitation have been predicted for the shores of the Pacific Northwest (Huppert et al. 2009), each of which are likely to affect the rate at which coastal bluffs recede. Because of these uncertainties the additional 25‐ft safety factor was applied. The resulting setback distances (Table 4) are based on the assumption that there is no previous history of large landslides within the subject parcel. If there is a history of landslides at the site, then armor removal is considered feasible only on parcels in which there are no structures. If there are structures and landslide history, then feasibility needs to be assessed individually at higher resolution. Table 4. Proposed “safe” setback distances to inform feasible armor removal projects. Orientation Fetch North South Low 45 48 Moderate 49 48 High 65 55 Interim Results Analysis NWSF Feeder Bluff Restoration Assessment of Island and Jefferson Cty, Page 8 COASTAL GEOLOGIC SERVICES, INC.

Next Steps The methods and results described in this report are part of a work in progress that will continue to advance over the course of the next month. Next steps include additional spatial and statistical analyses of erosion rate data, refinement and application of the feasibility screening, and the benefits ranking. The approach for the benefits ranking has been drafted but has not yet been tested or applied, therefore was not included in this memo. These applications will identify parcels to focus outreach efforts and work to implement bluff restoration in east Jefferson and Island Counties.

References Digital Shoreline Analysis System (DSAS), Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Ergul, Ayhan. 2013. Digital Shoreline Analysis System (DSAS) version 4.0—An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open‐File Report 2008‐1278. Available online at http://pubs.usgs.gov/of/2008/1278/.

Fletcher, C.; J. Rooney, M. Barbee, S.C. Lim, and B. Richmond. 2003. Mapping shoreline change using digital orthophotogrammetry on Maui, Hawaii. Journal of Coastal Research, SI(38), 106‐124. West Palm Beach (Florida), ISSN 0749‐ 0208.

Huppert, D.D., A. Moore, and K. Dyson. 2009. Impacts of climate on the coasts of Washington State. School of Marine Affairs College of Ocean and Fishery Sciences, University of Washington, Seattle, WA, 98195. Keuler, R.F., 1988. Map showing coastal erosion, sediment supply, and longshore transport in the Port Townsend 30‐ by 60‐ minute quadrangle, Puget Sound region, Washington: US Geological Survey Miscellaneous Investigations Map I‐1198‐E, scale 1:100,000. MacLennan, A.J.1, J.W. Johannessen1, S.A. Williams1, W. J. Gerstel2, J.F. Waggoner1, and A. Bailey3. 2013. Feeder Bluff Mapping of Puget Sound. Prepared by Coastal Geologic Services, for the Washington Department of Ecology and the Washington Department of Fish and Wildlife. Bellingham, Washington. 118p. 42 Maps.

Moore, L.J. 2000. Shoreline Mapping Techniques. Journal of Coastal Research. Vole 16 (1), p. 111‐124. Morton, R.A.; T. Miller, and L. Moore. 2004. National assessment of shoreline change: Part 1: Historical shoreline changes and associated coastal land loss along the U.S. Gulf of Mexico: U.S. Geological Survey Open‐file Report 2004‐1043.

Ruggiero, P.; G. M. Kaminsky, and G. Gelfenbaum. 2003. Linking proxy‐based and datum based shorelines on a high‐energy coastline: implications for shoreline change analysis. Journal of Coastal Research, SI(38), 57‐82. West Palm Beach (Florida), ISSN 0749‐0208. Ruggerio, P. and J.H. List. 2009. Shoreline Position and Change Rate Accuracy. Journal of Coastal Research. Vol 25, No. 5. P. 1069‐ 1081.

Coastal Geologic Services, Inc.

Andrea MacLennan, MS Jim Johannessen, MS and LEG Legend # Keuler Bluffs # Shore Change Bluffs B # 1:400,000 #

# # ## # # # # ## # # # # ### # # # # # # # # # # ## # # # # ## # # # # ## ### #

# #

# #

#

# 0 Feet 46,000 #

Figure 1. Locations of all feeder bluffs from which erosion rates were measured and compiled. NWSF Feeder Bluff Restoration Assessment of E. Jefferson and Island Counties Legend Bluff erosion rate (ft/yr) Low (0-0.26) B Moderate (0.26-0.5) High (0.5-1.0)

Very High (1.0+) 1:400,000

0 Miles 10

Figure 3. Spatial distribution of all erosion rates both measured and compiled.

NWSF Feeder Bluff Restoration Assessment of E. Jefferson and Island Counties Appendix A. Bluff charactetristics for all erosion rate data for Island and East Jefferson County Armor Removal Assessment Erosion rate Strata data Orientation Shore ID Shoreform ID Shoretype Surface geology Fetch Source (ft/yr) available? (quadrant) 9235 -0.22 9353 FB N Qpf 2 N CGS 6084 -0.45 6084 FB N Vlt, Vao 2 S CGS 7168 -0.22 7168 FB N Qgt 2 S CGS 7702 -0.24 7702 FB N Tg, Vao 3 N CGS 4595 -0.24 4595 FB Y Vlt, Vao 3 S CGS 9392 -0.31 9392 FB N Ts 3 S CGS 1799 -0.34 1799 FB Y-CZA Qc(o) 4 N CGS 1970 -0.19 1970 FB Y Qu 4 S CGS 2670 -0.32 2670 FB N Qga(v) 4 S CGS 6595 -0.13 6595 FB N Qgom(e) 4 S CGS 6073 -0.27 6073 FB N Vao 5 N CGS 475 -0.64 475 FB Y Qu 5 S CGS 473 -0.36 473 FB N Qgas(v) 7 N CGS 2106 -0.31 2106 FB N Qgt(v) 7 S CGS 2309 -0.30 2309 FB Y Qguc 7 S CGS 9851 -0.77 9851 FB N Qcw 7 S CGS 2599 -1.02 2599 FB Y Qc 8 N CGS 9883 -0.28 9883 FB N Qapo 8 S CGS 9885 -0.32 9885 FB N Qapo 8 S CGS 7175 -0.25 7175 FB N Qga 9 N CGS 2749 -0.34 2749 FBE Y Qc(o) 9 S CGS 779 -0.30 779 FB Y-CZA Qga(v) 10 N CGS 532 -0.24 532 FB N Qls 10 S CGS 2310 -0.27 2310 FB Y Qguc 11 S CGS 2754 -0.39 2754 FBE Y Qguc 11 S CGS 2755 -0.33 2755 FBE Y-CZA Qgas(v) 12 S CGS 7761 -0.30 7761 FB N Qvt 12 S CGS 7108 -0.30 7108 FB N Qgt 13 N CGS 2330 -0.77 2330 FB N Qc(o) 13 S CGS 5502 -0.42 5502 FB N Qvt, Qva 18 N CGS 2759 -0.31 2759 FBE N Qgas(v) 18 S CGS 5902 -0.12 5902 FB Y Vao 19 S CGS 5903 -0.17 5903 FBE Y Vlt, Vao, Py 19 S CGS 776 -0.23 776 FB Y Qgas(v) 19 S CGS 8329 -0.37 8329 FB Y Vlt, Vao 20 S CGS 7831 -0.49 7831 FB Y Vlt, Vao 23 S CGS 2249 -0.35 2249 FB Y Qvt, Qva, Qu 26 N CGS 7841 -0.92 7841 FBE Y Vlt, Vao 28 N CGS 7093 -1.53 7093 FBE N Qguc 41 N CGS 7 -0.30 NA FB NA Qva 2.4 S Keuler 4 -0.13 NA MOD N Qvt 5.7 N Keuler 19 -0.21 NA FBE Y Qgdm(e) 7.5 S Keuler 23 -0.23 NA FB Y Qguc 8.1 N Keuler 24 -0.10 NA FB Y Qguc 8.1 N Keuler 5 -0.20 NA FBE Y Qva, Qvt 9.1 N Keuler 6 -0.30 NA FBE Y Qva, Qvt 9.1 N Keuler 22 -0.03 NA MOD N Qgd(v) 9.1 S Keuler 21 -0.43 NA NA N Qvt 14.1 N Keuler 17 -0.49 NA FBE N Qgt(v) 15.4 S Keuler 18 -0.36 NA FB N Qgics(e) 16 S Keuler 20 -0.16 NA MOD N Qdgm(e) 18 N Keuler 9 -0.26 NA FBE Y Vlt, Vao, PY 19.7 S Keuler 8 -0.33 NA FBE NA Qva, Qvt 30 N Keuler 1 -0.98 NA MOD N Qgd(v) 48.1 N Keuler 2 -0.23 NA FB N Qgdm(e) 49.8 N Keuler 3 -0.20 NA FBE Y Qls 50.3 N Keuler