DOI: 10.5061/dryad.c59zw3rgr
title: Data Archival for Economic Cost Modeling of Chinook Habitat Restoration in the Stillaguamish River Basin

description: We used geospatial data to model economic cost estimates of habitat
 restoration in the Stillaguamish River Basin in the Puget Sound. We
 utilized data pertaining to the streams/rivers, floodplain habitat,
 subbasins, elevation, distance to roads, demographics, and land use within
 the Stillaguamish River Basin to do so. Analysis included using the
 different attributes of the Stillaguamish River Basin to create low and
 high cost estimates for floodplain, engineered log jam, and riparian
 planting habitat restoration. We specifically looked at the slope and size
 of streams, area of habitat that needed to be restored, slopes of the
 riparian area, distance to nearest road, and canopy angles as our model
 inputs. We followed cost estimate guidance provided by the Puget Sound
 Shared Strategy to identify our cost ranges and updated them to todays
 prices using the producer price index. An additional land use analysis was
 performed to quantify the total area and cost of potential agricultural
 land in the basin. Lastly, we investigated the demographics of the region
 to identify areas of POC and low income in relation to proposed
 restoration actions.
description: All data was collected from a variety of different publicly
 available datasets that were collected since 1999. Individual analyses for
 floodplain, engineered log jams, and riparian planting habitat restoration
 were completed in R Studio through a mix of spatial analysis and cost
 modeling. The data was all processed as csv (tabular), DEM (elevation
 raster), and shp (spatial)  files. Data was manipulated from the raw data
 in the analysis and documented in code in R Studio. All scripts used for
 the analyses were either R Markdown or R files. We primarily used base R,
 tidyverse, sf, and other spatial packages for our data manipulation and
 analysis. Figures and final products were created in the analysis and
 included in the GitHub repository and associated code for
 reproducibility.
description: # Data Archival for Economic Cost Modeling of Chinook Habitat Restoration
 in the Stillaguamish River Basin This archive includes data and code for
 the project "Prioritizing Chinook Salmon Habitat Restoration for
 Southern Resident Killer Whale Recovery"  for the Master of
 Environmental Science and Management: Master's Group Project (2024).
 Refer to the supplemental information link for details. Here is a brief
 summary of the main data sets we used and created in our study. This
 summary contextualizes how we used the data, but one should refer to the
 final report's "Methods" section for a full look into how
 the data was used. Analyses and annotated data manipulation are provided
 in the full GitHub repository scripts. All data are publically available
 with locations sourced below and located in the parent directory labeled
 `data`. Some data sets are included in the repository but not used for the
 analyses. **Stream line (STL)** - a folder containing a geopackage that
 has shapefiles for stream reaches within the Stillaguamish River Basin.
 This data was used in our analysis to generate cost estimate model inputs
 pertaining to the terrain of the streams in a given subbasin (such as its
 slope and width). These parameters were used throughout the 3 habitat
 restoration action scenarios as they all required stream reach attributes
 as input for the cost estimates. **Floodplain (STL)** - a folder
 containing a geopackage that has shapefiles of floodplain habitat in the
 Stillaguamish River Basin. Polygons were used in the analysis of
 quantifying the total floodplain habitat in each subbasin and the amount
 that needed to be restored. If a `hab_unit` was labeled as `curr`, then it
 is a current floodplain habitat. If labeled `hist` then it was historical.
 If labeled `both` then it used to be floodplain habitat and it still is.
 We used this to determine whether or not restoration was needed and how
 much. This data was not used in assessing engineered log jams or riparian
 planting actions. **NOAA subbasins (STL)** - a folder containing a
 geopackage that has shapefiles of all of the subbasins within the
 Stillaguamish River Basin. Polygons were used in all aspects of analysis
 to crop floodplain habitat, streams, elevation, land use polygons, and
 other physical characteristics of the basin to individual subbasins. All
 cost estimates were created at a subbasin level using this data set. It
 was also used to visualize our final results in map making. Overall, this
 data was used to segment our analysis into individual subbasins that we
 then used to compare to onea nother. **Elevation** - A folder containing
 DEM files of elevation raster data for the Stillaguamish River Basin.
 Raster data is shown at a 10m resolution across the basin. It was cropped
 to the basin and used in the riparian planting analyses to estimate the
 steepness of terrain and difficulty of accessing riparian vegetation. The
 raster data was cropped to each stream reach within each subbasin where
 there was proposed riparian planting restoration. **land_use** - a folder
 containing a geopackage that has shapefiles on the land use of land
 parcels throughout Snohomish county. These parcels were clipped to the
 Stillaguamish River Basin and the polygons were intersected with those of
 each subbasin. We used this to estimate the total area and percent land
 uses throughout the basin and identify areas of existing agricultural land
 that intersect with historical floodplain habitat that could potentially
 be utilized for restoration. **benefits** - a folder containing a CSV file
 with the estimated increases in Chinook, Steelhead, and Coho salmon from
 each of the 3 different restoration actions by subbasin. It highlights the
 current population and the modeled change in population following
 restoration of the subbasin to historical conditions as modeled by the
 HARP model. **roads** - a folder containing a geopackage that has
 shapefiles of all roads in Stillaguamish County including public roads,
 country roads, park roads and national forest roads. This data was used to
 measure distance of stream reaches to the nearest road in the engineered
 log jams and riparian planting analyses. **POC_WA** - a folder containing
 a geopackage that has the total people and number of people of color by
 census tract. **Poverty_WA** - a folder containing a geopackage that has
 the total people and number of people living under the poverty line by
 census tract. **Unemployment_WA** - a folder containing a geopackage that
 has the total people and number of unemployed people by census tract.
 **Tribal_Jurisdiction_Sno** - a folder containing a geopackage that has
 shapefiles of Indian Trust Lands, Pending Trust Lands, and Fee Simple
 Lands owned by Tribal Members or Tribal Associations. **final_results -**
 a folder containing a geopackage that has has the final costs and benefits
 resulting from each proposed action for each applicable subbasin.
 Subbasins not included implies that there was no change in Chinook
 population from the resulting action. ## Key Variables by Data Set
 **Streamline (STL)** - Key variables used were: `noaaid` Unique reach
 identifier `Habitat Description` of reach habitat type. Large and small
 non-tidal streams are reclassified by width within the HARP model
 `Area_km2` Area of catchment draining to reach (National Elevation
 Dataset, NED) (km2) `slope` Stream gradient (National Elevation Dataset,
 NED) (m/m) `BF_width` Bankfull width, modeled by NOAA (m) `length` Reach
 length (m) `fpw` Width of floodplain at reach (WDNR LiDAR and National
 Elevation Dataset, NED) (m) `can_ang` Current canopy opening angle,
 modeled by NOAA, NOAA riparian condition dataset (°) `hist_ang` Historical
 canopy opening angle, modeled by NOAA, NOAA riparian condition dataset (°)
 `geometry` line strings of the streams **Floodplain (STL)** - Key
 variables used were: `HabUnit Code` indicating habitat type `Period Code`
 indicating time period in which feature exists or existed `Hab_cond` Code
 indicating whether feature appears to be natural in origin, manmade, or
 natural in origin with human modification `noaaid` Numeric code of nearby
 reach `Area_ha` Area of feature ha `geometry` Polygons of the floodplain
 habitat **Subbasins (STL)** - Key variables used were: `noaa_subba` Name
 of subbasin `geometry` Polygons of the subbasins **Elevation** - Key
 variables used were: `elevation` elevation of the raster pixel (m)
 **land_use** - Key variables used were: `MASTER_CAT` category of land use
 `geometry` polygons of the land use parcels **benefits** - Key variables
 used were: `pop` the population of salmon `subbasin` name of the subbasin
 `scenario` proposed intervention or restoration action `n` modeled
 population following restoration `n_curr` modeled current population
 `perc_change` percent change in population of salmon **roads** - Key
 variables used were: `geometry` polygons of roads **POC_WA** - Key
 variables used were: `percent_people_of_color` percent people of color
 **Poverty_WA** - Key variables used were: `percent_living_in_poverty`
 percent of population living in poverty **Unemployment_WA** - Key
 variables used were: `percent_unemployed` percent of population unemployed
 **all_cost_benefit -** Key variables used were: `noa_sbb` subbasin wihtin
 the stillaguamish river basin `ttl_lw_` total lower cost estimate
 `ttl_pp_` total upper cost estimate `ttl_vg_` total average cost estimate
 `pop` salmon species being considered `n` modeled population following
 restoration `n_curr` modeled current population `prc_chn` percent change
 in population of salmon `n_diff` difference in population before and after
 intervention `cb_rati` cost effectiveness ratio `rstrtn_` proposed
 restoration action `sbbsn_n` clean subbasin name `geometry` polygons of
 the subbasins ## File Structure All data is stored in subfolders
 underneath the `Data` folder in the repository. Relevant folders include:
 `elevation` which includes elevation data `HARP` which includes all of the
 `Flowline_STL`, `Floodplain_STL`, `Subbasins_STL`, and `benefits` data
 `roads` which includes all the public road data `land_use` which includes
 all land use data in Snohomish county `POC_WA` which includes all of the
 data pertaining to demographics `Poverty_WA` which contains data
 pertaining to poverty rates `Unemployment_WA` which contains unemployment
 data `Tribal_Jurisdiction_Sno` which contains tribal land data for
 Snohomish County `final_results` contains the `all_cost_benefit` data and
 our final results These data area primarily raw data folders pulled from
 the specified online sources. However, as annotated in the scripts,
 certain data frames were read in, modified, and re-written to minimize
 computation and time spent on the analyses. Other data folders may not
 have a specified purpose as they were used in unrelated analyses or just
 used in the exploration of the analyses. ## Sharing/Access information
 This is a section for linking to other ways to access the data, and for
 linking to sources the data is derived from, if any. Links to other
 publicly accessible locations of the data: Data and data description for
 **Streamline (STL)**, **Floodplain (STL)**, and **Subbasins (STL)** data
 are publicly available at:
 [https://www.fisheries.noaa.gov/resource/tool-app/habitat-assessment-and-restoration-planning-harp-model](https://www.fisheries.noaa.gov/resource/tool-app/habitat-assessment-and-restoration-planning-harp-model) Data and data description for the **Elevation** data are publicly available at: [https://gis.ess.washington.edu/data/raster/tenmeter/byquad/info.html](https://gis.ess.washington.edu/data/raster/tenmeter/byquad/info.html) Data and data description for the **land_use** data are publicly available at: [https://geo.wa.gov/datasets/a0ddbd4e0e2141b3841a6a42ff5aff46_0/explore?filters=eyJOQU1FIjpbIlNub2hvbWlzaCJdfQ%3D%3D&location=46.750570%2C-117.609917%2C6.00](https://geo.wa.gov/datasets/a0ddbd4e0e2141b3841a6a42ff5aff46_0/explore?filters=eyJOQU1FIjpbIlNub2hvbWlzaCJdfQ%3D%3D&location=46.750570%2C-117.609917%2C6.00) Data and data description for the **benefits** data can be requested from: Tim Beechie, Supervisory Research Fish Biologist, Northwest Fisheries Science Center, NOAA [tim.beechie@noaa.gov](mailto:tim.beechie@noaa.gov){.email} Data and data description for the **roads** data are publicly available at: [https://geo.wa.gov/datasets/a12a43c5b10b498ca6612454616bc7fa/about](https://geo.wa.gov/datasets/a12a43c5b10b498ca6612454616bc7fa/about) Data and data description for the **POC_WA** data are publicly available at: [https://geo.wa.gov/datasets/bb24b4accb974940ab4bf2784b9b4a6a_0/explore?location=47.181638%2C-120.811974%2C6.94](https://geo.wa.gov/datasets/bb24b4accb974940ab4bf2784b9b4a6a_0/explore?location=47.181638%2C-120.811974%2C6.94) Data and data description for the **Poverty_WA** data are publicly available at: [https://geo.wa.gov/datasets/WADOH::population-living-in-poverty-current-version/about](https://geo.wa.gov/datasets/WADOH::population-living-in-poverty-current-version/about) Data and data description for the **Unemployment_WA** data are publicly available at: [https://geo.wa.gov/datasets/67c699681b4f49c0adb1b5cada9e1919_0/explore](https://geo.wa.gov/datasets/67c699681b4f49c0adb1b5cada9e1919_0/explore) Data and data description for the **Tribal_Jurisdiction_Sno** data are publicly available at: [https://www.arcgis.com/home/item.html?id=3bcd4cdf822440e7a84e46b8f0b27fba&sublayer=0#overview](https://www.arcgis.com/home/item.html?id=3bcd4cdf822440e7a84e46b8f0b27fba&sublayer=0#overview) Data and data description for the **final_results** data were created in this analysis and stored in this repository ## Code/Software All analyses were performed in R Studio using Version 2023.12.1+402. Annotated code, scripts, final products, and data are provided in the the following GitHub repository: [https://github.com/ramhunte/gp_anadromites](https://github.com/ramhunte/gp_anadromites) **Notes on the Analysis:** Analyses and code are annotated throughout the scripts explaining the data wrangling, cleaning, and analyses process. The repository contains mainly RMD files with annotated code and some sourced R files as well for common functions and data sources used throughout the analyses. Some files were written in R and generated into specified subfolders. Raw data is stored in the `Data` folder, common functions and data read in throughout the analyses are written in the `common.R` file, and the `scripts` folder contains all of our working analyses divided into actions (floodplain (`cost_floodplain.Rmd`), engineered log jams (`cost_elj.Rmd`), and riparian planting (`cost_rp.Rmd`)) as well as demographic analysis (`demographic_overlap.Rmd`), land use (`landuse.Rmd`). Our figures were constructed in the `figures.Rmd` file, and a common `functionsR` script was used to source common functions across the analyses in the scripts folder. `benefit_data.Rmd` wrangles and generates HARP model benefits (increased number of Chinook) that are used throughout the analyses, and the `cost_data.Rmd` reads in and wrangles the costs associated with land use and agriculture. Note that the variables in the raw data files look different than in the individual analyses as names were modified in the `common.R` file.