Case Study: Sensitivity and Uncertainty Analyses for Oregon wind siting

Creating a case study on sensitivity and uncertainty analyses for Oregon wind siting.

Repository Structure

• data
  • raw_data: the raw data integrated in the analysis (Note: original data name and structure were kept except when either name was not descriptive or similar data were put in same directory to simplify input directories)
  • intermediate_data: disaggregated processed data
  • submodel_data: processed data for analyzing in the wind siting submodel
  • suitability_data: final suitability data for offshore wind area region
  • rank_data:
  • sensitivity_data:
  • uncertainty_data:
• code: scripts for cleaning, processing, and analyzing data
• figures: figures generated to visualize analysis
• methodology: detailed methods for the data and analysis

Note for PC users: The code was written on a Mac so to run the scripts replace "/" in the pathnames for directories with two "\".

Please contact Brian Free (brian.free@noaa.gov) with any questions.

Data sources

Generic Data

Layer	Data Source	Data Name	Metadata	Notes
Wind Areas	BOEM	Renewable Energy Leases and Planning Areas	Metadata, Renewable Energy GIS Data	Data are also accessible for download on MarineCadastre (under "Active Renewable Energy Leases")
State Boundary	State of Oregon	Administrative Boundary	Metadata	Geospatial library
Bathymetry	NOAA	Coastal Relief Model Volume 7: Central Pacific	Metadata	More US coverage, alternative download link
Bathymetry	NOAA	Central Oregon	Metadata	NOAA Bathymetry Viewer
Bathymetry	NOAA	Port Orford	Metadata	NOAA Bathymetry Viewer
Bathymetry	NOAA	Crescent City	Metadata	NOAA Bathymetry Viewer
Species Habitat	NOAA	Biologically Important Areas		Alternative dataset (same footprint, different datatable), BIA Map (2015), BIA II Paper (2023), BIA II Map Viewer (2023)

Constraints Data

Layer	Data Source	Data Name	Metadata	Notes
Military	Department of Defense	Combined Wind Assessment for the Oregon Offshore, BOEM, OPNAV, May 2022	Metadata	Data Portal (Human > Military > Combined Oregon Offshore Wind Assessment, OPNAV, May 2022), Data source provider, Alternative link for dataset, InPort
Military	United States Coast Guard	Pacific Coast Port Access Route Study		Federal Registrar, Analysis completed in Districts 11 and 13

Industry and Operations Data

Layer	Data Source	Data Name	Metadata	Notes
Submarine Cable	NOAA	NOAA Chartered Submarine Cable	Metadata

Natural Resources Data

Layer	Data Source	Data Name	Metadata	Notes
Conservation Areas	NOAA	Essential Fisheries Habitat Conservation Areas		Text, Essential Fish Habitat Mapper, Alternative download source
Habitat	NOAA	Leatherback Sea Turtle	Metadata	NMFS ESA Critical Habitat Mapper, InPort, West Coast Specific Download, West Coast Region Protected Resources App, Code of Regulations
Habitat	NOAA	Humpback Whale (Central America DPS)	Metadata	NMFS ESA Critical Habitat Mapper, InPort, West Coast Specific Download, West Coast Region Protected Resources App, Code of Regulations
Habitat	NOAA	Humpback Whale (Mexico DPS)	Metadata	NMFS ESA Critical Habitat Mapper, InPort, West Coast Specific Download, West Coast Region Protected Resources App, Code of Regulations
Habitat	NOAA	Killer Whale (Southern Resident)	Metadata	NMFS ESA Critical Habitat Mapper, InPort, West Coast Specific Download, West Coast Region Protected Resources App, Code of Regulations
Habitat	NOAA	U.S. West Coast Cross-Shelf Habitat Suitability Modeling of Deep-Sea Corals and Sponges	Metadata	NCEI, Link for habitat suitability data only
Habitat	NOAA	Methane Bubble Streams		Merle et al. (2021), data come from the supplemental table and contain points from Reidel et al. (2018) and Johnson et al. (2015)
Habitat	NOAA	Methane Bubble Streams		Reidel et al. (2018), data come from the supplementary data 2 and these data are contained within the Merle et al. (2021) dataset
Habitat	NOAA	Methane Bubble Streams		Johnson et al. (2015), data come from the supporting information document (see S2 and S3) and while these data are contained within the Merle et al. (2021) dataset, S3 does not contain any sites that fall within Oregon call areas
Habitat	USGS	Rainier (H13118 (2018)		Data came ahead of a 2019 EXPRESS cruise aboard the NOAA Ship Lasker (RL-19-05). Nancy Prouty at USGS shared these unpublished location data with Curt Whitmire
Species	NOAA	Marine seabird density	Metadata	These data were combined with vulnerability factors as detailed in Adams et al. (2017) and Kelsey et al. (2018); option for downloading particular data is accessible through the HTTPS
Species	USGS	Population vulnerability, Collision vulnerability, Displacement vulnerability	These data are from the Adams et al. (2017) paper and used by Kelsey et al. (2018)

Fisheries Data

Layer	Data Source	Data Name	Metadata	Notes

Wind Data

Layer	Data Source	Data Name	Metadata	Notes

Data commentary

Datasets explored but not included in analyses due to not located geographically in study area:

• BOEM Active Lease Areas (Geodatabase download link,Shapefile download link, Metadata)
• Anchorage Areas (Metadata)
• BOEM Lease Blocks (Metadata)
• Lightering Zones (Metadata, more information) - Pipelines (Option page, Metadata)
• Shipping Lanes (Federal)
• Unexploded ordnances (Points and areas, metadata)
• BOEM Drilling Platforms (Metadata, Mapping Page, Alternative Platform Structure dataset)

Methodologies

While most data used in the model received a single value, some ranged between 0 and 1. This caused at times a hex cells across the call areas to have more than a single value due to data not sharing the exact same shape and size as the call are hex cells. When this occurred, the analysis chose the minimum value occurring in the hex cell. The minimum value prioritized conservation.

Known issues

The hexagonal grid in R is slightly different than a tessellation grid that ArcGIS Pro generates in its data management toolbox. This is likely due to differences in the number of significant digits used for the calculations and converting acres into meters.

Hexagon nodes in the grid R creates fall approximately 1.3 meters away from similar nodes for the tessellation generated by ArcGIS. In a 10-acre area, this difference is accounts for 0.64% in distance.

Acknowledgements

The marine bird data scripts got adapted from Jeffery Leirness's code and previous analysis.