Jaenicke, Margaret E. Hopkins, Anders L. Kowalski, Kurt P. Bozimowski, Alexandra A. Sanocki, Chris A. 202406 raster digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9OS796H U. S. Geological Survey 2016 vector and raster digital data Reston, VA U. S. Geological Survey https://doi.org/10.5066/P9UAA4HY The US Geological Survey (USGS) created the Wetland Soils 10-meter raster dataset as the second parameter in the Western Lake Erie Restoration Assessment (WLERA) which covers the southwestern shore of Lake Erie. WLERA is a part of the USGS's Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative where coastal areas around the Great Lakes are identified and ranked for potential wetland restoration. This parameter combined data from the National Wetland Inventory (NWI), gSSURGO (Grided Soil Survey Database), and Coastal Change and Analysis Program (C-CAP) to identify wetland soils in the WLERA. Pixels where either of these data sources showed a presence of wetland habitat were set to a value of 1, the remaining were given a value of 0. Please refer to the process steps and https://glcwra.wim.usgs.gov/ for further explanation on the methods. Version 2.0 of this dataset was created with more recently released input data. For information on the changes between versions 1.0 and 2.0, please see the Release History text file. The purpose of the wetland soils dataset is to identify areas of the WLERA study area that have soil types which are suitable for wetland habitats. The presence of these soils makes restoration of lost wetland habitats more viable. The datasets in WLERA Composite 2024 (Jaenicke et al., 2024) were created with more recently published datasets than the WLERA Composite 2016 release (Saarinen, 2016). The foremost among these is the digital elevation model (DEM) which was used to create the study area boundary, the hydroperiod, the dikes and the index composite layers. The elevation data was created from 3DEP DEM tiles published between 2015 and 2019. Updated versions of the following datasets were also used in the creation of WLERA Composite 2024: National Wetland Inventory (NWI) data published in 2023, National Oceanic and Atmospheric Association (NOAA) water level measurements from 1993-2023, Soil Survey Geographic Database (SSURGO) data published in 2022, National Hydrology Dataset (NHD) published in 2023, Protected Areas Database (PAD-US) data published in 2022 and National Land Cover Database (NLCD) data published in 2021. The methodology of the project has largely stayed the same between the WLERA Composite 2016 and WLERA Composite 2024 data release. The notable exception is that there were additional steps used to create the index composite. After the index composite was created using the input parameters and the composite model, a boundary cleaning routine was used to reduce the amount of data noise or lone grid cells present within the index composite. The index composite layer was also reviewed by USGS ecologists after the model was executed and before the data were published, to ensure the accuracy of the results. Based on this review, index composite values returned from the model that did not highlight restorable wetlands were removed from the final dataset. 202406 publication date Complete None planned -83.7447 -82.0833 42.1282 41.2615 ISO 19115 Topic Category environment geoscientificInformation inlandWaters USGS Thesaurus wetland ecosystems aquatic ecosystems freshwater ecosystems remediation surface water (non-marine) hydrology natural resource management water quality Marine Realms Information Bank (MRIB) soil wetland wetland restoration hydrology resource management water quality lake lakeshore stream river Common geographic areas Great Lakes Ohio Michigan Lake Erie Western Lake Erie None. Please see 'Distribution Info' for details. None. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. Kurt P Kowalski U.S. Geological Survey, MIDCONTINENT REGION Research Ecologist mailing address

1451 Green Rd

Ann Arbor MI 48105 US 734-214-9308 734-994-8780 kkowalski@usgs.gov The GLCWRA was produced with funding provided by the Great Lakes Restoration Initiative (GLRI) and in collaboration with the New College of Florida. Digital datasets obtained from public repositories and datasets including the National Hydrography Dataset (NHD), National Wetland Index (NWI), 3D Elevation Program (3DEP), U.S. Census Bureau, National Geospatial Program, U.S. Fish and Wildlife Service, National Oceanic and Atmospheric Association (NOAA), Protected Areas Database of the U.S. (PAD-US), National Land Cover Database (NLDC), Gridded Soil Survey Geographic Database (gSSURGO), Coastal Change Analysis Program (C-CAP) U.S. Geological Survey 2016 application/service Geonarrative map website for GLCWRA study https://glcwra.wim.usgs.gov/ Kurt P Kowalski Justin A. Saarinen 2016 dataset https://www.sciencebase.gov U.S. Geological Survey Previous release of data. See "Supplemental Information" for more context. https://doi.org/10.5066/f74t6ghx The attribute values of this dataset were inspected and confirmed to be within the proper range of values. The attribute values were reviewed, and spatial data was visually inspected to verify the that the data values and their locations accurately describe the purpose of the data. This dataset is considered complete for the information presented, as described in the abstract. This dataset provides coverage for the entire Western Lake Erie Restoration Assessment study area. Approximately 20% of the spatial data was visually inspected to verify the positional accuracy of its features. The review consisted of comparing the spatial data to its input datasets and to underlying GIS basemaps. While this data has been reviewed, the spatial data is only as spatially accurate as the input data sources. This dataset does not have a vertical component, so testing for vertical accuracy was not necessary. National Oceanic and Atmospheric Administration (NOAA) 2016 raster digital data https://coast.noaa.gov/digitalcoast/data/ccapregional.html Digital 2016 publication date C-CAP Identified land use types. United States Fish and Wildlife Story 20230501 vector digital data https://www.fws.gov/program/national-wetlands-inventory/data-download Digital 20230501 publication date MI NWI Identified coastal wetlands habitats in Michigan. United States Department of Agriculture (USDA) Natural Resources Conservation Service 20220829 raster digital data Counties used: Monroe County, MI (MI115) Erie, OH (OH043) Lorain, OH (OH093) Lucas, OH (OH095) Ottawa, OH (OH123) Sandusky, OH (OH143) Wood, OH (OH173) https://websoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx https://websoilsurvey.sc.egov.usda.gov/ Digital 20220829 publication date SSURGO Identified the soil types of the assessment area. Data was downloaded by county from the 'Download Soils Data' tab. United States Fish and Wildlife Service 20230501 vector digital data https://www.fws.gov/program/national-wetlands-inventory/data-download Digital 20230501 publication date OH NWI Identified coastal wetlands habitats in Ohio. ArcGIS Pro 3.0.3 was used for the following steps, where the WLERA DEM was set as the snap raster, 10-meters were the default raster cell size, and UTM 17N was set at the output coordinate system. The 30 meter C-CAP raster was clipped to the WLERA study area and then resampled to 10-meters, using the WLERA DEM as the snap raster. Next the grid was reclassified ("Reclassify" tool) so that the following values were changed to 1: 13 (Palustrine Forested Wetland), 14 (Palustrine Scrub/Shrub Wetland), 15 (Palustrine Emergent Wetland), 21 (Open Water), 22 (Palustrine Aquatic Bed). All other values were reclassified to 0. 20230901 In the NWI wetlands Feature Class, polygons that are permanently flooded have a value of 'H' in the "ATTRIBUTE" field of the attribute table. The wetland polygons for both Michigan and Ohio were selected with the "Select by Attribute" tool and in a new field called 'Value', the selected polygons were assigned a value of '0' while all the other features received a value of '1'. These vector features from both Michigan and Ohio were then clipped to the WLERA study area and merged together into a single feature class. Next this feature class was converted to a raster with the "Polygon to Raster" tool (Value field = 'Value', Cell assignment type = Cell center, Priority field = None, Cellsize = 10m, snap raster = WLERA DEM). 20230901 In ArcGIS Pro, for each county listed below in the SSURGO citation, the 'soilmu_a.shp' polygon Shapefile and 'comp.txt' table were added to the map. The 'soilmu_a' layer was joined to the 'comp' table on the MUKEY and Field108 fields, respectively. Then the polygon layer was projected to UTM Zone 17 and clipped to the WLERA study area. After this was done for each of the counties in the study area, these clipped SSURGO polygon layers were merged together into a single 'soilma_a' polygon layer. A field called 'value' was added to this new contiguous SSURGO layer. Then all of the polygons with 'D' or 'B/D' in the field 'Field80' were selected and given a value of '1' in the new 'value' field. The selection was reversed and the remaining polygons were given a value of '0' in the 'value' field. Then the contiguous 'soilmu_a' layer was converted into a raster with the tool 'Polygon to Raster' where 'value' was the Value field, Cell center was the Cell assignment type, Priority field was NONE, the cell size was 10-meter, the snap raster was the WLERA DEM and the output coordinate system was UTM 17N. 20230901 The binary rasters from the previous three steps were then added together using the "Raster Calculator" tool. The new raster was then transformed to the single binary raster using the "Reclassify" tool, where pixels with a value of 1 or greater was reclassified to 1, and the pixels with a value of 0 were kept at 0. 20230901 Raster Grid Cell 9327 13625 1 Universal Transverse Mercator 17 0.9996 -81.0 0.0 500000.0 0.0 row and column 10.0 10.0 meters North_American_Datum_1983 GRS 1980 6378137.0 298.2572221010042 WLERA_P2_Soils.tif A raster dataset (in geoTIFF format) representing the presence or absents of wetland soils. Producer Defined Value A binary raster representing the presence or absents of wetland soils. Producer Defined 255 Outside the area of interest. Producer defined 0 Represents the absence of wetland soils. Producer defined 1 Represents the presence of wetland soils. Producer defined WLERA_P2_WetlandSoils.zip contains a TIF raster image (WLERA_P2_WetlandSoils.tif) and associated metadata (WLERA_P2_WetlandSoils.tif.xml). NA GS ScienceBase U.S. Geological Survey mailing address

Denver Federal Center, Building 810, Mail Stop 302

Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. Digital Data https://doi.org/10.5066/P9OS796H None 20240515 Kurt P Kowalski U.S. Geological Survey, MIDCONTINENT REGION Research Ecologist mailing address

1451 Green Rd

Ann Arbor MI 48105 US 734-214-9308 734-994-8780 kkowalski@usgs.gov FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998 20250801 11224200 TRUE