ResultsNormalized Vegetation Di�erence Index (NDVI) and the change in NDVI between data from 2015 and 2016, demonstrates electromagnetic re�ective qualities of organic matter and absorbent qualities of inorganic materials. A signi�cant increase in both sedimentation and vegetation cover from 2015 to 2016 is observable in the Elwha River. The Dungeness River data is provided to display baseline estuary complexity. It is important to consider the temporal di�erence of this data. NDVI measures compar-ing raster data of the Elwha River and Dungeness River estuaries are dated May 2015 and June 2016, indicating hydrologic, climatic , and tidal variation may slightly distort NDVI measurements of vegetation cover and health.

Iso Cluster Unsupervised Classi�cation of data from 2015 and 2016, demonstrates electromagnetic re�ective qualities of organic matter and absorbent qualities of inorganic materials. A signi�cant increase of re�ective biomass in both sedimentation and vegetation cover from 2015 to 2016 is observable in the Elwha River estuary. The Dungeness River data is provided to display baseline estuary complexity. It is important to consider the temporal di�erences of this data. Iso Cluster Unsupervised Classi�cation comparing raster data of the Elwha River and Dungeness River estuaries are dated May 2015 and June 2016, indicating hydrologic, climatic , and tidal variation may slightly distort Unsupervised Classi�cation measurements of vegetation cover and health.

From 1923 to 2017 discharge in cubic feet per second, 94 annual values were correlated resulting in a correlation coe�cient of .69 between the two river data sets. Chinook salmon natural spawner annual populations were correlated between the two rivers from 1986 to 2014 for a total of 29 values from each data set. The result showed an insigni�cant relation between the two salmon populations, with a correlation co-e�cient of 0.174. This result was unexpected, however a visual comparison of graphed populations show similar patterns. From 199-2006 and 2014, temperature data for each river for all except winter months was correlated resulting in 150 values with a correlation coe�cient of 0.838. Correlation coe�cients for turbidity, conductivity, Ph and dissolved oxygen content were also calculated using 150 values for each variable, and can be viewed in the table below. The two rivers have very similar trends in water quality, which su�ce for quality Chinook spawning habitat, yet no correlation between the river’s Chinook populations was found.

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1986 2014

Dungeness Chinook

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1986 1990 1994 1998 2002 2006 2010 2014

Elwha Chinook

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1990 1994 1998 2002 2006 2010

IntroductionSediment entrapment from the Elwha and Glines Canyon Dam, and their respective reservoirs Lake Mills and Lake Aldwell, prevent the downstream transportation of nutrient rich sand and gravel and contribute to ecosystem degradation and reduction of anadromous �sh spawning habitat. Sediment deprived water, or ‘hungry water’, moving through the dam spillways possesses greater erosive capacity and also encourages channelization, which prevents channel migration and increases the coarseness of riparian and estuary ecosystems due to the lack of �ne grain sediments. Furthermore, logs and woody debris are prevented from downstream dispersion. Dam and reservoir construction intensi�es sediment entrapment, decreases �oodplain complexity, and deprives riparian and estuary ecosystems (Duda, Warwick, & Magirl, 2011).

Before the dam removal the largest Paci�c salmon species Oncorhynchus tshawytscha, the Chinook salmon, population was limited to the lower Elwha River (Press). Yet, an ideal spawning location for these Elwha Chinook would be a low turbidity area between 5 and 12 degrees celsius (Press). While the dams were in place, salmon populations were unable access colder habitats for spawning. The Dungeness has annual spring Chinook salmon runs while the Elwha Chinook runs occur annually from spring through fall. (WDFW Hatchery Reports)

Suspended sediments have shown a strong relation with turbidity, discharge, light suppression as well as pH (Göransson). Turbidity a�ects the amount of sediment and invertebrates present in the water, these factors can impact a salmon’s growth by a�ecting food availability and reactive distances (Borok). Too high of turbidity can impair a salmon’s ability to react and successfully feed which a�ects the salmon’s growth and contribution to the species population (Borok). Temperature, alsoin�uenced by turbidity, can dictate where and when salmonid populations spawn. Temperature of the Elwha varies seasonally, with large in�ows of snowmelt in the spring and low in�ows of sediment in the fall the �ow of water and temperature vary (Pess). Other variables indicating viable Chinook habitat include dissolved oxygen content, pH and conductivity. This study examines the correlation of chinook habitat indicators over comparable years between the Dungeness River and Elwha River.

AbstractEngineering of hydrological resources, speci�cally dam and reservoir construction, provide communities with hydroelectric power, �ood mitigation, access to irrigation and potable water, transportation and recreation opportunities. While the aforementioned provisions are perceivably integral to the viability of societies and economies they serve, hydrological engineering severely segments, deprives, and disrupts ecosystem services and viability. The deconstruction of the Elwha and Glines Canyon Dams in western Washington State represents the largest dam removal project in the United States and has subsequently initiated the return of nutrient rich sediment deposition and native �sh species to the Elwha River �oodplain. The Dungeness River, a neighbor to the Elwha River, with no history of intensive dam or reservoir construction, will serve as a control for the analysis of biomass viability. Since the Elwha and Glines Canyon dams were removed in 2012 and 2014 respectively, �uvial processes and data have been observed and recorded on the Elwha River. Further examination may potentially serve as a conduit for other dam removal projects. Results of this project will visually communicate biomass and water quality as indicators for ecosystem resilience.

Sedimentation and Biomass as Indicators of Ecosystem Resilience on the Elwha River and Dungeness River, Clallam County, WA

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1999 2000 2001 2002 2003 2004 2005 2006 2014

PH Comparison Tolerant ChinookRange

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Discharge Comparison

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1999 2001 2001 2002 2003 2004 2005 2006 2014

Temperature Comparison

Dungeness ElwhaTolerant Chinook Range Range

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Water Quality Monitoring Sites

Extent of Figures

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Dissolved Oxygen Content Comparison

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Tolerant ChinookRange

References:Borok, Aron. "Turbidity Technical Review." Water Quality (n.d.): n. pag. Department of Environmental Quality (2014).Göransson, G., M. Larson, and D. Bendz. "Variation in Turbidity with Precipitation and Flow in a Regulated River System – River Göta Älv, SW Sweden." Hydrology and Earth System Sciences 17.7 (2013): 2529-542.National Oceanic and Atmospheric Administration (NOAA) https://coast.noaa.gov/dataviewer/#/imagery/search/Morawitz, D. F., Blewett, T. M., Cohen, A., & Marina, A. (2006). Using NDVI to Assess Vegetative Land Cover Change in Central Puget Sound. Environmental Monitoring and Assessment, 114(85).Pess, G. R., et al. "Biological impacts of the Elwha River dams and potential salmonid responses to dam removal." Northwest Science 82 (2008): 72-90.Shafroth, P. B., Fuentes, T. L., Pritekel, C., Beirne, M. M., & Beauchamp, V. B. (2011). Chapter 8 Vegetation of the Elwha River Estuary. Coastal Habitats of the Elhaw River, Washington - Biological and Physical Patterns and Processes Prior to Dam Removal, 225-248. WDFW. "Annual Final Hatchery Escapement Reports." WDFW Publications | Washington Department of Fish & Wildlife. Washington Department of Fish and Wildlife, n.d.

Variable Correla on Coe cientDischarge 0.690Turbidity 0.439 Temp 0.838Conduc vity 0.642Ph 0.594Dissolved oxygen 0.770Chinook Natural Spawners 0.174

MethodsVegetation, hydrological data, and anadromous �sh populations, serving as ecosystem indicators of the Elwha River and Dungeness River estuaries, will be quanti�ed and visualized by utilizing geospatial data and geoprocessing tools.

Normalized Di�erence Vegetation Index (NDVI) is a measurement of vegetation cover and proxy for vegetation health. NDVI measurements are derived from remotely sensed data, speci�cally red (Band 1) and near infrared (Band 4) of the electromag-netic spectrum, in order to analyze vegetation cover and health. Healthy vegetation readily absorbs the red wavelength during photosynthesis, while the near-infrared wavelength is signi�cantly re�ected during this process. This distinction allows researchers’ access to data not visible to the human eye. NDVI is calculated by (Band 4 – Band 1)/(Band4 + Band 1). Change in NDVI is calculated by (2016 NDVI – 2015 NDVI). NDVI has been utilized to compare raster data of the Elwha River and Dungeness River estuaries, dated May 2015 and June 2016, in order to analyze change to vegetation cover and health.

Unsupervised classi�cation of spatial data is useful in determining di�erent types of land cover. Spatial data at one-meter resolution, post dam removal (2015 – 2016), will be used to delineate successional vegetation cover and sedimentation patterns in proximity to the Elwha River and Dungeness River estuaries (Shafroth, Fuentes, Pritekel, Beirne, & Beauchamp, 2011). ‘Composite Raster Tool’ is used to build raster layers containing Band 1 (Red), 2 (Green) and 4 (Near-Infrared), again uti-zling the re�ective quality of as a measure for biomass cover. The ArcMap ‘Image Classi�cation Toolbar’ is used to conduct Iso Cluster Unsupervised Classi�cation. A grey-scale is used to visualize and delineate complex land cover patterns.

Temporal water quality data gathered and organized from multiple online databases was compiled into excel for comparison. Data sources include USGS, WDFW, and the Washington Department of Ecology. Chinook salmon was the only salmonid spe-cies which enough data was available for comparison temporally between the two rivers. The data includes turbidity, tem-perature, discharge, Ph, dissolved oxygen content, and conductivity. The data gathered includes both monthly observations as well as annual averages for each variable, for each river the variables were plotted on a line graph for visual comparison. Correlation factors of variables between rivers were calculated and calculated and organized into a table. In addition, Chi-nook habitat tolerance parameters were chosen after reviewing literature and temporal trends were compared to tolerance values as well as chinook populations.

Within ArcGIS, datasets were properly symbolized and exported to Adobe Illustrator to create �gures for the poster. In addition, graphs created using excel and �gures from ArcMap were imported for embellishment. The Swiss Hillshade technique simulates a three dimensional elevation pro�le by utilizing a digital elevation model. Re�ning shading and removing irregularities of a given area can be accomplished by using geoprocessing tools such as hillshade, focal statistics, and raster calculator. After creating a mosaic using thirty �ve di�erent 10 meter digital elevation model quads, a Swiss Hill -Shade was created for the Elwha River and Dungeness River surrounding areas, displaying aesthetic an elevation pro�le based on 2010 data.

NDVILow High

NDVILow High

NDVILow High

May 2015 June 2016Elwha Estuary

May 2015 June 2016Dungeness Estuary

Biomass RefelctivityLow High

Biomass Re�ectivity Low High

Analysis and Cartography by Drew Lindsey and Royhon AgostineHuxley College of the Environment, Western Washington UniversityAdvised by Professor Andrew Bach and Professor Aquila Flower5/16/2017

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