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 Hydroperiod 10-meter raster dataset as the first 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 estimates the likelihood that areas within the WLERA study area are inundated by water from Lake Erie. Raster cells in this layer have values ranging from 0 to 100, with higher values cells representing areas more likely to be inundated. This parameter was created by data from the NOAA lake level gage at Toledo, Ohio, and DEM data from the National Elevation Dataset (NED). 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 Hydroperiod dataset represents the likelihood that the landscape will flood within the Western Lake Erie Restoration Assessment (WLERA) study area. Areas with a higher hydroperiod values are better suited to support a coastal wetland habitat. This dataset was derived from a DEM of the study area and Lake Erie water level records collected at the NOAA station in Toledo, Ohio. 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 natural resource management hydrology water quality remediation wetland ecosystems Marine Realms Information Bank (MRIB) keywords water level measurements lake lakeshore wetland wetland restoration hydrology resource management water quality 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. 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. NOAA Tides and Currents 20230324 tabular digital data Hourly data: 3/24/1993 - 8/31/1996 6-min data: 9/1/1996 - 3/24/2023 https://tidesandcurrents.noaa.gov/waterlevels.html?id=9063085&type=Tide+Data&name=Toledo&state=OH Digital 19930324 20230324 ground condition NOAA Water Levels These data were used to reclassify the DEM and create the hydroperiod. U.S. Geological Survey 2011 raster digital data ned19_n41x25_w082x25_oh_north_2006 ned19_n41x25_w082x50_oh_north_2006 ned19_n41x25_w082x75_oh_north_2006 ned19_n41x25_w083x00_oh_north_2006 ned19_n41x25_w083x25_oh_north_2006 ned19_n41x25_w083x50_oh_north_2006 ned19_n41x25_w083x75_oh_north_2006 ned19_n41x25_w084x00_oh_north_2006 ned19_n41x25_w084x25_oh_north_2006 ned19_n41x25_w084x50_oh_north_2006 ned19_n41x25_w084x75_oh_north_2006 ned19_n41x50_w082x00_oh_north_2006 ned19_n41x50_w082x25_oh_north_2006 ned19_n41x50_w082x50_oh_north_2006 ned19_n41x50_w082x75_oh_north_2006 ned19_n41x50_w083x00_oh_north_2006 ned19_n41x50_w083x25_oh_north_2006 ned19_n41x50_w083x50_oh_north_2006 ned19_n41x50_w083x75_oh_north_2006 ned19_n41x50_w084x00_oh_north_2006 ned19_n41x50_w084x25_oh_north_2006 ned19_n41x50_w084x50_oh_north_2006 ned19_n41x75_w082x00_oh_north_2006 ned19_n41x75_w082x25_oh_north_2006 ned19_n41x75_w082x75_oh_north_2006 ned19_n41x75_w083x00_oh_north_2006 ned19_n41x75_w083x25_oh_north_2006 ned19_n41x75_w083x50_mi_monroeco_2009 ned19_n41x75_w083x50_oh_north_2006 ned19_n41x75_w083x75_mi_monroeco_2009 ned19_n41x75_w083x75_oh_north_2006 ned19_n41x75_w084x00_mi_3southerncounties_2010 ned19_n41x75_w084x00_mi_monroeco_2009 ned19_n41x75_w084x00_oh_north_2006 ned19_n41x75_w084x25_mi_3southerncounties_2010 ned19_n41x75_w084x25_oh_north_2006 ned19_n41x75_w084x50_mi_3southerncounties_2010 ned19_n41x75_w084x50_oh_north_2006 ned19_n42x00_w083x25_mi_monroeco_2009 ned19_n42x00_w083x50_mi_monroeco_2009 ned19_n42x00_w083x75_mi_3southerncounties_2010 ned19_n42x00_w083x75_mi_monroeco_2009 ned19_n42x00_w084x00_mi_3southerncounties_2010 ned19_n42x00_w084x00_mi_monroeco_2009 ned19_n42x25_w083x25_mi_monroeco_2009 ned19_n42x25_w083x25_mi_wayneco_2009 ned19_n42x25_w083x50_mi_monroeco_2009 ned19_n42x25_w083x50_mi_wayneco_2009 ned19_n42x25_w083x75_mi_monroeco_2009 ned19_n42x25_w083x75_mi_washtenawco_2009 ned19_n42x25_w083x75_mi_wayneco_2009 ned19_n42x25_w084x00_mi_3southerncounties_2010 ned19_n42x25_w084x00_mi_monroeco_2009 ned19_n42x25_w084x00_mi_washtenawco_2009 ned19_n42x25_w084x25_mi_3southerncounties_2010 ned19_n42x25_w084x25_mi_washtenawco_2009 ned19_n42x25_w084x50_mi_3southerncounties_2010 https://gdg.sc.egov.usda.gov/Catalog/ProductDescription/NED.html https://apps.nationalmap.gov/viewer/ Digital 2005 2010 observed WLERA DEM The DEM data provided an elevation raster from which the hydroperiod dataset was created. NOAA 2023 application/service https://geodesy.noaa.gov/cgi-bin/IGLD85/IGLD85.prl Digital 2023 publication date Datum Conversion Tool This tool was used to convert water level measurements from the International Great Lakes Datum of 1985 to the North American Vertical Datum of 1988. First a combined Digital Elevation Model of 10-meters was created for the approximate area of interest. The most recent LiDAR derived DEM tiles were downloaded from National Elevation Dataset 3-D Elevation Program. Then the files were unzipped and added to ArcGIS Pro 3.0.3. The "Create Mosaic Dataset" geoprocessing tool was run (Coordinate System = UTM 17N, Product Definition = None) and all of the DEM tiles were added to the mosaic dataset using the "Add Rasters to Mosaic Dataset" tool (Raster Type = Raster Dataset, Processing Templates = Default, Input Data = File). Finally, the "Mosaic to New Raster" tool was run to output the DEM as a Geotiff file (Spatial Reference = UTM 17N, Pixel Type = 32 bit signed, Mosaic Operator = Last, Mosaic Colormap Mode = First). 20230313 The National Oceanic and Atmospheric Administration (NOAA) collects water level measurements at gaging stations around the Great Lakes. For the WLERA, Lake Erie water level data was extracted at the Toledo, Ohio station (9063085) using NOAA's API and Python. 30 years of water level data were downloaded. Data at a 6 min frequency were downloaded for the available date range (9/1/1996 - 3/24/2023). Remaining dates (3/24/1993 - 8/31/1996) were supplemented with hourly data to complete the 30-year period. 6 minute measurements were not available before 9/1/1996 at this gage. The daily maximum water levels were found using Python. The water levels were then transformed to the NAVD88 vertical datum using NOAA's Geodesy Tool (https://geodesy.noaa.gov/cgi-bin/IGLD85/IGLD85.prl). 20230615 Using the Python package Pandas (a package for reading, manipulating and writing tabular data) the maximum daily values were extracted from the water level table, sorted in order from least to greatest and duplicates values were dropped. Then in a new column, an integer percentage value was assigned to each remaining water level value. The lowest water level value received a percentage value of '100' and the highest received '0' while all other water level values in between received a representative percentage value. The "rank" function from Pandas was used to calculate these values which represent the inverse percent of the difference between the maximum and the minimum of the filtered water levels. The resulting table was exported and saved as a CSV file. 20230615 The table from the previous step was then imported into ArcGIS Pro 3.0.3. The WLERA Digital Elevation Model (DEM) was reclassified by the Lake Level table using the "Reclassify by Table" tool (the From value field was the minimum, the To value field was the maximum, and the Output value field was the percentage). A new raster was created where the cell values were replaced with the percentage values from the water level table. Any values above or below the water level range were given a NULL value. The output raster was snapped to the WLERA Digital Elevation Model, projected to NAD83 UTM Zone 17N and had 10-meter cell size. 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_P1_Hydroperiod_10m.tif A raster dataset (in geoTIFF format) representing the hydroperiod within the WLERA study area. Producer Defined Value Values in this raster represent an estimation of the likelihood that the underlaying areas will be inundated by Lake Erie. High values mean a higher change of flooding and lower values represent a lesser change of flooding. Producer Defined 255 Outside of the WLERA study area. Producer defined 0 100 WLERA_P1_Hydroperiod.zip contains a TIF raster image (WLERA_P1_Hydroperiod.tif) and associated metadata (WLERA_P1_Hydroperiod.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