<?xml version='1.0' encoding='UTF-8'?>
<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
  <idinfo>
    <citation>
      <citeinfo>
        <origin>Lauren E. Eng</origin>
        <origin>Nathaniel K. Pasley</origin>
        <origin>Brian S. Caruso</origin>
        <origin>Andrew R. Bock</origin>
        <pubdate>20250709</pubdate>
        <title>USGS Dynamic Surface Water Extent (DSWE)-based Inundation Frequencies for Select U.S. Fish and Wildlife Service Mountain-Prairie Region Properties, Wyoming 1982-2020</title>
        <geoform>raster digital data</geoform>
        <pubinfo>
          <pubplace>Reston, VA</pubplace>
          <publish>U.S. Geological Survey</publish>
        </pubinfo>
        <onlink>https://doi.org/10.5066/P13ZTSGR</onlink>
      </citeinfo>
    </citation>
    <descript>
      <abstract>This data release contains grids, in geographic tagged imaged file(.tif) format, summarizing inundation frequency of the U. S. Geological Survey (USGS) Dynamic Surface Water Extent (DSWE) Landsat Science Product at 114 National Wildlife Refuges throughout the U.S. Fish and Wildlife Service (USFWS) Mountain-Prairie Region (Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, Utah, and Wyoming). The DSWE product provides long-term (1982 to present), high temporal resolution data (30-meter) on surface water inundation patterns that can help identify locations of past or current drought conditions. For each refuge, three files were produced using data from different periods: the baseline period (1982-2000), the evaluation period (2001–20), and the period of record (1982-2020). Inundation frequencies for each pixel were derived by dividing the total number of observations classified as any one of the DSWE water classes by the total number of observations of water extent or presence.

This child item contains data for wildlife refuges within the state of Wyoming (WY). See keywords for specific refuges.</abstract>
      <purpose>The purpose of this data release is to provide accurate and reliable information regarding DSWE data inundation dynamics through time at 114 National Wildlife Refuges within the USFWS Mountain-Prairie Region.</purpose>
      <supplinf>The following is a list of commonly used acronyms within the data release--DSWE: Dynamic Surface Water Extent; TIF: tagged image file; USFWS: U.S. Fish and Wildlife Service; NWR, National Wildlife Refuge; FIPS Code (2 Digit State ID), Federal Information Processing Standard Code (2-Digit State Identification); FIPS PUB 5-2 NIST, Federal Information Processing standards publication 5-2 National Institute of Standards and Technology.</supplinf>
    </descript>
    <timeperd>
      <timeinfo>
        <rngdates>
          <begdate>19821101</begdate>
          <enddate>20201231</enddate>
        </rngdates>
      </timeinfo>
      <current>ground condition</current>
    </timeperd>
    <status>
      <progress>Complete</progress>
      <update>None planned</update>
    </status>
    <spdom>
      <bounding>
        <westbc>-111.0500</westbc>
        <eastbc>-104.0500</eastbc>
        <northbc>45.0000</northbc>
        <southbc>40.9900</southbc>
      </bounding>
    </spdom>
    <keywords>
      <theme>
        <themekt>ISO 19115 Topic Category</themekt>
        <themekey>environment</themekey>
      </theme>
      <theme>
        <themekt>Marine Realms Information Bank (MRIB) keywords</themekt>
        <themekey>National Wildlife Refuge</themekey>
      </theme>
      <theme>
        <themekt>USGS Thesaurus</themekt>
        <themekey>hydrology</themekey>
        <themekey>remote sensing</themekey>
        <themekey>surface water (non-marine)</themekey>
        <themekey>droughts</themekey>
      </theme>
      <theme>
        <themekt>USGS Metadata Identifier</themekt>
        <themekey>USGS:674494cad34eacadb5a4afb2</themekey>
      </theme>
      <place>
        <placekt>Common geographic areas</placekt>
        <placekey>Wyoming</placekey>
        <placekey>Bamforth National Wildlife Refuge</placekey>
        <placekey>Cokeville Meadows National Wildlife Refuge</placekey>
        <placekey>Hutton Lake National Wildlife Refuge</placekey>
        <placekey>Mortenson National Wildlife Refuge</placekey>
        <placekey>National Elk Refuge</placekey>
        <placekey>Pathfinder National Wildlife Refuge</placekey>
        <placekey>Seedskadee National Wildlife Refuge</placekey>
      </place>
    </keywords>
    <accconst>None. Please see 'Distribution Info' for details.</accconst>
    <useconst>None. Users are advised to read the accompanying metadata file thoroughly to understand appropriate use and data limitations.</useconst>
    <ptcontac>
      <cntinfo>
        <cntperp>
          <cntper>Lauren Eng</cntper>
          <cntorg>U.S. Geological Survey, ROCKY MOUNTAIN REGION</cntorg>
        </cntperp>
        <cntpos>Hydrologist</cntpos>
        <cntaddr>
          <addrtype>mailing</addrtype>
          <address>201 E. 9th St</address>
          <city>Pueblo</city>
          <state>Colorado</state>
          <postal>81003</postal>
          <country>US</country>
        </cntaddr>
        <cntvoice>719-601-6705</cntvoice>
        <cntemail>leng@usgs.gov</cntemail>
      </cntinfo>
    </ptcontac>
    <datacred>Cooperative funding and assistance with data analysis for this project was provided in part by the USFWS.</datacred>
    <native>Original DSWE data files were processed in Python, version 3.9.15, on an internal USGS cloud-computing platform. Parallelization of project workflows was performed using the Python packages Xarray, version 2022.12.0, and Dask, version 2022.12.1.</native>
    <crossref>
      <citeinfo>
        <origin>U. S. Geological Survey</origin>
        <pubdate>20190923</pubdate>
        <title>Earth Resources Observation and Science (EROS) Center. (2022). Landsat Level-3 Dynamic Surface Water Extent, Collection 2 [dataset]. U.S. Geological Survey</title>
        <edition>2</edition>
        <geoform>raster digital data</geoform>
        <othercit>Jones, J. W., 2019, Improved Automated Detection of Subpixel-Scale Inundation—Revised Dynamic Surface Water Extent (DSWE) Partial Surface Water Tests: Remote Sensing, v. 11, no. 4, 374, https://doi.org/10.3390/rs11040374.</othercit>
        <onlink>https://doi.org/10.5066/P9DPWBUS</onlink>
      </citeinfo>
    </crossref>
    <crossref>
      <citeinfo>
        <origin>S. C. Hoyer</origin>
        <origin>J. J. Hamman</origin>
        <pubdate>20221201</pubdate>
        <title>Xarray</title>
        <edition>2022.12.0</edition>
        <geoform>application/service</geoform>
        <othercit>Hoyer, S. C., and Hamman, J. J., 2022, Xarray (Version 2022.12.0) [Software], available from https://xarray.pydata.org/.</othercit>
        <onlink>https://github.com/pydata/xarray/blob/v2022.12.0/CITATION.cf</onlink>
      </citeinfo>
    </crossref>
    <crossref>
      <citeinfo>
        <origin>Dask Development Team</origin>
        <pubdate>20221201</pubdate>
        <title>Dask</title>
        <edition>2022.12.1</edition>
        <geoform>application/service</geoform>
        <othercit>Dask Development Team, 2022, Dask (Version 2022.12.1) [Software], available from https://dask.org/.</othercit>
        <onlink>https://docs.dask.org/en/stable</onlink>
      </citeinfo>
    </crossref>
    <crossref>
      <citeinfo>
        <origin>Alphabet Inc.</origin>
        <pubdate>20250401</pubdate>
        <title>Google Earth, version 7.3.6.10201</title>
        <geoform>raster digital data</geoform>
        <onlink>https://earth.google.com/web/</onlink>
      </citeinfo>
    </crossref>
    <crossref>
      <citeinfo>
        <origin>Esri</origin>
        <pubdate>2023</pubdate>
        <title>ArcGIS Pro: Release 2.9.5</title>
        <geoform>publication</geoform>
        <othercit>ESRI 2023. ArcGIS Pro: Release 2.9.5. Redlands, CA: Environmental Systems Research Institute.</othercit>
        <onlink>https://pro.arcgis.com/en/pro-app/3.4/get-started/get-started.htm</onlink>
      </citeinfo>
    </crossref>
    <crossref>
      <citeinfo>
        <origin>Python</origin>
        <pubdate>2022</pubdate>
        <title>Python Software Foundation. Python Language Reference</title>
        <edition>3.9.15</edition>
        <geoform>application/service</geoform>
        <onlink>https://www.python.org/</onlink>
      </citeinfo>
    </crossref>
  </idinfo>
  <dataqual>
    <attracc>
      <attraccr>No formal attribute accuracy tests were conducted. The data may have higher inundation frequencies in mountainous terrain, potentially because of environmental challenges affecting precision, including high terrain slope and shadows produced by dense forest. 

Additionally, the evaluation period contains more data than the baseline period because of the increased temporal frequency beginning with Landsat 7 (1999) through the present. This could explain differences for more channelized areas between the two periods. All inundation frequency values are based on all available empirical observations for the respective time periods, and identical processing steps were used for both periods.</attraccr>
    </attracc>
    <logic>All inundation frequency values are within the expected range of 0-100 percent. The hydrologic systems depicted in output files were visually compared to historical imagery in Google Earth (Alphabet Inc., 2025) to ensure the validity of the physical locations where inundation occurred.</logic>
    <complete>This dataset represents the frequency that a given location within a USFWS Mountain-Prairie Region property, and a surrounding 10-kilometer (km) buffer, experienced surface water inundation for a given period.</complete>
    <posacc>
      <horizpa>
        <horizpar>DSWE is derived from published Landsat spectral products (EROS Center, 2021), therefore accuracy is largely determined by Landsat extent and resolution.</horizpar>
      </horizpa>
      <vertacc>
        <vertaccr>DSWE is derived from published Landsat spectral products (EROS Center, 2021), therefore accuracy is largely determined by Landsat extent and resolution.</vertaccr>
      </vertacc>
    </posacc>
    <lineage>
      <srcinfo>
        <srccite>
          <citeinfo>
            <origin>U.S. Fish and Wildlife Service</origin>
            <pubdate>20250311</pubdate>
            <title>USFWS National Realty Tracts</title>
            <geoform>vector digital data</geoform>
            <onlink>https://gis-fws.opendata.arcgis.com/datasets/fws::u-s-fish-and-wildlife-service-national-realty-tracts/explore</onlink>
          </citeinfo>
        </srccite>
        <typesrc>Digital and/or Hardcopy</typesrc>
        <srctime>
          <timeinfo>
            <sngdate>
              <caldate>20250311</caldate>
            </sngdate>
          </timeinfo>
          <srccurr>publication date</srccurr>
        </srctime>
        <srccitea>USFWS (2025)</srccitea>
        <srccontr>Used to derive USFWS National Wildlife Refuge (NWR) boundaries.</srccontr>
      </srcinfo>
      <srcinfo>
        <srccite>
          <citeinfo>
            <origin>John W. Jones</origin>
            <pubdate>20150923</pubdate>
            <title>Efficient Wetland Surface Water Detection and Monitoring via Landsat: Comparison with in situ Data from the Everglades Depth Estimation Network</title>
            <geoform>publication</geoform>
            <pubinfo>
              <pubplace>Basel, Switzerland</pubplace>
              <publish>MDPI</publish>
            </pubinfo>
            <othercit>Jones, J. W., 2015, Efficient Wetland Surface Water Detection and Monitoring via Landsat: Comparison with in situ Data from the Everglades Depth Estimation Network: Remote Sensing, v. 7, no. 9, 12503-12538, https://doi.org/10.3390/rs70912503.</othercit>
            <onlink>https://doi.org/10.3390/rs70912503</onlink>
          </citeinfo>
        </srccite>
        <typesrc>Digital and/or Hardcopy</typesrc>
        <srctime>
          <timeinfo>
            <sngdate>
              <caldate>20150923</caldate>
            </sngdate>
          </timeinfo>
          <srccurr>publication date</srccurr>
        </srctime>
        <srccitea>Jones (2015)</srccitea>
        <srccontr>Publication for the original Dynamic Surface Water Extent (DSWE) algorithm.</srccontr>
      </srcinfo>
      <srcinfo>
        <srccite>
          <citeinfo>
            <origin>John W. Jones</origin>
            <pubdate>20190213</pubdate>
            <title>Improved Automated Detection of Subpixel-Scale Inundation—Revised Dynamic Surface Water Extent (DSWE) Partial Surface Water Tests</title>
            <geoform>publication</geoform>
            <pubinfo>
              <pubplace>Basel, Switzerland</pubplace>
              <publish>MDPI</publish>
            </pubinfo>
            <othercit>Jones, J. W., 2019, Improved Automated Detection of Subpixel-Scale Inundation—Revised Dynamic Surface Water Extent (DSWE) Partial Surface Water Tests: Remote Sensing, v. 11, no. 4, 374, https://doi.org/10.3390/rs11040374.</othercit>
            <onlink>https://doi.org/10.3390/rs11040374</onlink>
          </citeinfo>
        </srccite>
        <typesrc>Digital and/or Hardcopy</typesrc>
        <srctime>
          <timeinfo>
            <sngdate>
              <caldate>20190213</caldate>
            </sngdate>
          </timeinfo>
          <srccurr>publication date</srccurr>
        </srctime>
        <srccitea>Jones (2019)</srccitea>
        <srccontr>Publication for the revised Dynamic Surface Water Extent (DSWE) algorithm.</srccontr>
      </srcinfo>
      <srcinfo>
        <srccite>
          <citeinfo>
            <origin>Earth Resources Observation and Science Center</origin>
            <pubdate>20210720</pubdate>
            <title>Landsat 4-9 U.S. Analysis Ready Data (ARD), Collection 2 [dataset]</title>
            <geoform>raster digital data</geoform>
            <othercit>Earth Resources Observation and Science (EROS) Center. (2021). Landsat 4-9 U.S. Analysis Ready Data, Collection 2 [dataset]. U.S. Geological Survey. https://doi.org/10.5066/P960F8OC</othercit>
            <onlink>https://doi.org/10.5066/P960F8OC</onlink>
          </citeinfo>
        </srccite>
        <typesrc>Digital and/or Hardcopy</typesrc>
        <srctime>
          <timeinfo>
            <rngdates>
              <begdate>19821101</begdate>
              <enddate>20250131</enddate>
            </rngdates>
          </timeinfo>
          <srccurr>observed</srccurr>
        </srctime>
        <srccitea>EROS Center (2021)</srccitea>
        <srccontr>For each USGS Landsat Collection 2 U.S. Analysis Ready Data (ARD) product published, a corresponding Landsat Collection 2 Level-3 DSWE product is produced.</srccontr>
      </srcinfo>
      <srcinfo>
        <srccite>
          <citeinfo>
            <origin>U.S. Geological Survey</origin>
            <pubdate>20250501</pubdate>
            <title>Landsat SpatioTemporal Asset Catalog</title>
            <geoform>raster digital data</geoform>
            <onlink>https://www.usgs.gov/landsat-missions/spatiotemporal-asset-catalog-stac</onlink>
          </citeinfo>
        </srccite>
        <typesrc>Digital and/or Hardcopy</typesrc>
        <srctime>
          <timeinfo>
            <rngdates>
              <begdate>19821101</begdate>
              <enddate>20201231</enddate>
            </rngdates>
          </timeinfo>
          <srccurr>observed</srccurr>
        </srctime>
        <srccitea>USGS (2025)</srccitea>
        <srccontr>The ‘Interpreted Layer with All Masks Applied’ (INWAM) layer produced on a 1:1 basis with Landsat Spectral Reflectance data was accessed from the Landsat SpatioTemporal Asset Catalog (STAC) via Python for the period 1982-2024.</srccontr>
      </srcinfo>
      <procstep>
        <procdesc>Step 1:  Access

The U.S. Fish and Wildlife Service (USFWS) Mountain-Prairie Region 6 includes eight states: Colorado (CO), Kansas (KS), Montana (MT), North Dakota (ND), Nebraska (NE), South Dakota (SD), Utah (UT), and Wyoming (WY). Among these 8 states, there are 114 unique National Wildlife Refuges (NWRs) managed by the USFWS. The spatial boundaries of the Region 6 NWRs were downloaded as a polygon feature dataset in a geodatabase from the USFWS National Realty Tracts open source dataset (NWR Boundaries, 2025).

DSWE is a Landsat Collection 2 (EROS Center, 2021) Level-3 derivative product. For every Landsat Surface Reflectance image published, a series of 5 diagnostic tests of remote sensing indices is run. The indices combine multiple wavelengths upon which thresholds are tested to enhance spectral features like surface water bodies. Each output pixel is classified according to the presence or absence of open water, potential wetland, or cloud, cloud shadow, or snow/ice. Each DSWE product contains a total of eight individual files. The ‘Interpreted Layer with All Masks Applied’ (INWAM) layer produced on a 1:1 basis with Landsat Spectral Reflectance data was accessed from the Landsat SpatioTemporal Asset Catalog (STAC; USGS, 2025) via Python (Python, 2022) for the period 1982-2024.</procdesc>
        <procdate>20240601</procdate>
      </procstep>
      <procstep>
        <procdesc>Step 2: Pre-process

Individual DSWE files were saved to cloud storage to aide in the development of the processing workflow by offering more direct access and shorter load times. The NWR Boundary geometries were then used to access corresponding DSWE Zarr files. The files were loaded into Python as individual Xarray (Hoyer and Hamman, 2022) data arrays and clipped to a 10 km buffer surrounding the NWR Boundary before being concatenated into an Xarray dataset using a distributed Dask (Dask Development Team, 2022) cluster. The dataset was then subsetted into three periods-- baseline (1982-2000), evaluation (2001–20), and period of record (1982-2020). The selected periods were chosen to ensure an adequate dataset for calculating inundation frequencies, to provide a robust historical representation, and to maintain a consistent duration of analysis between the baseline and evaluation period.</procdesc>
        <procdate>20240801</procdate>
      </procstep>
      <procstep>
        <procdesc>Step 3: Process

Within each subset, pixels labelled by the DSWE algorithm (Jones, 2019) as containing cloud, cloud shadow, or snow/ice were reclassified as NoData. Next, pixels labelled as any of the four DSWE classes used to identify the presence of water (Open Water-High Confidence, Open Water-Moderate Confidence, Partial Surface Water-Conservative, and Partial Surface Water-Aggressive) were reclassified to the integer 1. This created a binary water/not-water dataset, as the integer 0 is used by DSWE to identify non-water pixels. The mathematical formula for calculating DSWE-based inundation frequencies ((water observations / total observations) * 100) was then applied in the time dimension at each pixel location, resulting in a single output layer containing the percentage of observations that were labelled as any one of DSWE water classes for the given period.</procdesc>
        <procdate>20241101</procdate>
      </procstep>
    </lineage>
  </dataqual>
  <spdoinfo>
    <direct>Vector</direct>
    <ptvctinf>
      <sdtsterm>
        <sdtstype>G-polygon</sdtstype>
        <ptvctcnt>7</ptvctcnt>
      </sdtsterm>
    </ptvctinf>
  </spdoinfo>
  <spref>
    <horizsys>
      <planar>
        <mapproj>
          <mapprojn>Albers Conical Equal Area</mapprojn>
          <albers>
            <stdparll>29.5</stdparll>
            <stdparll>45.5</stdparll>
            <longcm>-96.0</longcm>
            <latprjo>23.0</latprjo>
            <feast>0.0</feast>
            <fnorth>0.0</fnorth>
          </albers>
        </mapproj>
        <planci>
          <plance>coordinate pair</plance>
          <coordrep>
            <absres>0.6096</absres>
            <ordres>0.6096</ordres>
          </coordrep>
          <plandu>meters</plandu>
        </planci>
      </planar>
      <geodetic>
        <horizdn>D North American 1983</horizdn>
        <ellips>GRS 1980</ellips>
        <semiaxis>6378137.0</semiaxis>
        <denflat>298.257222101</denflat>
      </geodetic>
    </horizsys>
  </spref>
  <eainfo>
    <detailed>
      <enttyp>
        <enttypl>WY_NWR_Boundaries</enttypl>
        <enttypd>Shapefile of National Wildlife Refuges in Wyoming</enttypd>
        <enttypds>USFWS (2025)</enttypds>
      </enttyp>
      <attr>
        <attrlabl>FID</attrlabl>
        <attrdef>Internal feature number.</attrdef>
        <attrdefs>ESRI</attrdefs>
        <attrdomv>
          <rdom>
            <rdommin>0</rdommin>
            <rdommax>6</rdommax>
          </rdom>
        </attrdomv>
      </attr>
      <attr>
        <attrlabl>Shape</attrlabl>
        <attrdef>Geometry data type</attrdef>
        <attrdefs>ESRI</attrdefs>
        <attrdomv>
          <udom>Type of ESRI-derived geometry represented by the shapefile</udom>
        </attrdomv>
      </attr>
      <attr>
        <attrlabl>ORGNAME</attrlabl>
        <attrdef>Name of USFWS National Wildlife Refuge</attrdef>
        <attrdefs>Producer Defined</attrdefs>
        <attrdomv>
          <udom>Name of USFWS National Wildlife Refuge</udom>
        </attrdomv>
      </attr>
      <attr>
        <attrlabl>State</attrlabl>
        <attrdef>State within which all or majority of the refuge is located.</attrdef>
        <attrdefs>Producer Defined</attrdefs>
        <attrdomv>
          <codesetd>
            <codesetn>FIPS Code (2-Digit State Identification)</codesetn>
            <codesets>FIPS PUB 5-2 (NIST)</codesets>
          </codesetd>
        </attrdomv>
      </attr>
    </detailed>
    <detailed>
      <enttyp>
        <enttypl>*REFUGE*.zip</enttypl>
        <enttypd>Subfolders for each NWR in the state containing raster images of DSWE-based inundation frequencies. 

Refer to Process Step 3 for more information regarding the inundation frequencies.</enttypd>
        <enttypds>Producer Defined</enttypds>
      </enttyp>
      <attr>
        <attrlabl>period_of_record_*REF*.tif</attrlabl>
        <attrdef>TIF file for USFWS NWR *REFUGE*</attrdef>
        <attrdefs>Producer Defined</attrdefs>
        <attrdomv>
          <udom>TIF file for the period of record (1982-2020) for the refuge *REF*. Each tif file contains a single output layer containing the frequency that a pixel is classified by DSWE as displaying the presence of surface water. 

Refer to Process Step 3 for more information regarding the inundation frequencies.</udom>
        </attrdomv>
      </attr>
      <attr>
        <attrlabl>baseline_period_*REF*.tif</attrlabl>
        <attrdef>TIF file for USFWS NWR *REFUGE*</attrdef>
        <attrdefs>Producer Defined</attrdefs>
        <attrdomv>
          <udom>TIF file for the baseline period (1982-2000) for the refuge *REF*. Each tif file contains a single output layer containing the frequency that a pixel is classified by DSWE as displaying the presence or absence of surface water. 

Refer to Process Step 3 for more information regarding the inundation frequencies.</udom>
        </attrdomv>
      </attr>
      <attr>
        <attrlabl>evaluation_period_*REF*.tif</attrlabl>
        <attrdef>TIF file for USFWS NWR *REFUGE*</attrdef>
        <attrdefs>Producer Defined</attrdefs>
        <attrdomv>
          <udom>TIF file for the evaluation period (2001–20) for the refuge *REF*. Each tif file contains a single output layer containing the frequency that a pixel is classified by DSWE as displaying the presence of surface water. 

Refer to Process Step 3 for more information regarding the inundation frequencies.</udom>
        </attrdomv>
      </attr>
    </detailed>
  </eainfo>
  <distinfo>
    <distrib>
      <cntinfo>
        <cntorgp>
          <cntorg>U.S. Geological Survey - ScienceBase</cntorg>
        </cntorgp>
        <cntaddr>
          <addrtype>mailing address</addrtype>
          <address>Mail Stop 302</address>
          <city>Denver</city>
          <state>CO</state>
          <postal>80225</postal>
          <country>United States</country>
        </cntaddr>
        <cntvoice>1-888-275-8747</cntvoice>
        <cntemail>sciencebase@usgs.gov</cntemail>
      </cntinfo>
    </distrib>
    <distliab>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.

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.</distliab>
    <stdorder>
      <digform>
        <digtinfo>
          <formname>Digital Data</formname>
        </digtinfo>
        <digtopt>
          <onlinopt>
            <computer>
              <networka>
                <networkr>https://doi.org/10.5066/P13ZTSGR</networkr>
              </networka>
            </computer>
          </onlinopt>
        </digtopt>
      </digform>
      <fees>None</fees>
    </stdorder>
  </distinfo>
  <metainfo>
    <metd>20250709</metd>
    <metc>
      <cntinfo>
        <cntperp>
          <cntper>Lauren E. Eng</cntper>
          <cntorg>U.S. Geological Survey, ROCKY MOUNTAIN REGION</cntorg>
        </cntperp>
        <cntpos>Hydrologist</cntpos>
        <cntaddr>
          <addrtype>mailing</addrtype>
          <address>201 E. 9th St</address>
          <city>Pueblo</city>
          <state>CO</state>
          <postal>81003</postal>
          <country>US</country>
        </cntaddr>
        <cntvoice>719-601-6705</cntvoice>
        <cntemail>leng@usgs.gov</cntemail>
      </cntinfo>
    </metc>
    <metstdn>FGDC Content Standard for Digital Geospatial Metadata</metstdn>
    <metstdv>FGDC-STD-001-1998</metstdv>
  </metainfo>
</metadata>
