8 datasets found
  1. d

    MODFLOW-NWT model data sets for simulating effects of groundwater...

    • catalog.data.gov
    • data.usgs.gov
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). MODFLOW-NWT model data sets for simulating effects of groundwater withdrawals on streamflows in Northwestern Chippewa County [Dataset]. https://catalog.data.gov/dataset/modflow-nwt-model-data-sets-for-simulating-effects-of-groundwater-withdrawals-on-streamflo
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Chippewa County
    Description

    A new groundwater flow model for western Chippewa County, Wisconsin has been developed by the Wisconsin Geological and Natural History Survey (WGNHS) and the U.S. Geological Survey (USGS). An analytic element GFLOW model was constructed and calibrated to generate hydraulic boundary conditions for the perimeter of the more detailed three-dimensional MODFLOW-NWT model. This three-dimensional model uses the USGS MODFLOW-NWT finite difference code, a standalone version of MODFLOW-2005 that incorporates the Newton (NWT) solver. The model conceptualizes the hydrogeology of western Chippewa County as a six-layer system which includes several hydrostratigraphic units. The model explicitly simulates groundwater-surface-water interaction with streamflow routing. Model input included recent estimates of aquifer hydraulic conductivities and a spatial groundwater recharge distribution developed using a GIS-based soil-water-balance model for the study area. Groundwater withdrawals from pumping were simulated for 269 high-capacity wells across the entire model domain, which includes western Chippewa County and portions of eastern Dunn County and southeastern Barron County. Model calibration used the parameter estimation code PEST, and calibration targets included heads and stream flows. Calibration f focused on the period from during 2011 to 2013 when the largest amount of calibration data were available. Following calibration, the model was applied to two distinct scenarios; one evaluating hydraulic impacts of more intensive industrial sand mining and the second evaluating the hydraulicimpacts of more intensive agricultural irrigation practices. Each scenario was developed with input by Chippewa County and a stakeholder group established for this study, and designed to represent reasonable future build-out conditions for both mining and irrigatedagriculture. The mining scenario underscores the potential hydraulic impacts related to changing land-use practices (i.e., hilltops and farm land becoming sand mines), while the irrigated agriculture scenario illustrates the potential hydraulic impacts of intensifying existing land-use practices (i.e., installing new wells to irrigate farm fields).

  2. a

    Flood Zones

    • data-chippewa.opendata.arcgis.com
    • jaspercountymogisintiatives-jcmo.hub.arcgis.com
    • +2more
    Updated Mar 6, 2019
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    Chippewa County (2019). Flood Zones [Dataset]. https://data-chippewa.opendata.arcgis.com/maps/70b7739637254fd992ff7ceca1d3f72f
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    Dataset updated
    Mar 6, 2019
    Dataset authored and provided by
    Chippewa County
    Area covered
    Description

    FEMA flood hazard areas identified on the Flood Insurance Rate Map.

  3. m

    Public Drainage Systems Hydrography, Chippewa County, Minnesota

    • gisdata.mn.gov
    fgdb, html, jpeg, shp
    Updated Jul 9, 2020
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    Chippewa County (2020). Public Drainage Systems Hydrography, Chippewa County, Minnesota [Dataset]. https://gisdata.mn.gov/dataset/us-mn-co-chippewa-water-public-drainage-systems
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    jpeg, html, fgdb, shpAvailable download formats
    Dataset updated
    Jul 9, 2020
    Dataset provided by
    Chippewa County
    Area covered
    Minnesota, Chippewa County
    Description

    This Feature Dataset contains those public drainage system (as defined by Minnesota Statute 103E) layers where Chippewa County, Minnesota is considered the legal drainage authority as defined in MS 103E. This feature dataset may include hydrographic features such as ditch/tile centerlines.

    Follow the links below to the individual metadata pages for each layer:

    Drainage Centerlines: drainage_centerlines.html

    Drainage Authorities: drainage_authorities.html

    Systems: systems.html

  4. w

    Geodetic Control Points, Chippewa County has been working on tightening up...

    • data.wu.ac.at
    • datadiscoverystudio.org
    Updated Aug 19, 2017
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    NSGIC Local Govt | GIS Inventory (2017). Geodetic Control Points, Chippewa County has been working on tightening up their control network over the years. The first network was constructed in 1993, with densification done from 2008-2011., Published in 2011, Not Applicable scale, Chippewa County Government. [Dataset]. https://data.wu.ac.at/schema/data_gov/MDExMDNmNTgtZDVlMy00NGE0LTliYzMtZTc2MGJkZjdhYTcw
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    Dataset updated
    Aug 19, 2017
    Dataset provided by
    NSGIC Local Govt | GIS Inventory
    Area covered
    Chippewa County, ea2fafd36c62882c660af01b6853e6184ccd5131
    Description

    Geodetic Control Points dataset current as of 2011. Chippewa County has been working on tightening up their control network over the years. The first network was constructed in 1993, with densification done from 2008-2011..

  5. a

    Base Flood Elevation

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Mar 6, 2019
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    Chippewa County (2019). Base Flood Elevation [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/chippewa::base-flood-elevation
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    Dataset updated
    Mar 6, 2019
    Dataset authored and provided by
    Chippewa County
    Area covered
    Description

    FEMA flood hazard areas identified on the Flood Insurance Rate Map.

  6. a

    Tax Parcels

    • data-chippewa.opendata.arcgis.com
    • equitable-property-value-co-grant-mn-us.hub.arcgis.com
    • +13more
    Updated Jan 22, 2019
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    Chippewa County (2019). Tax Parcels [Dataset]. https://data-chippewa.opendata.arcgis.com/datasets/tax-parcels
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    Dataset updated
    Jan 22, 2019
    Dataset authored and provided by
    Chippewa County
    Area covered
    Description

    The published representation of real property areas, combined with assessing and tax information from CAMA and Tax systems, and organized for consumption in desktop and web applications.

  7. m

    Address Points, Compiled from Opt-In Open Counties, Minnesota

    • gisdata.mn.gov
    fgdb, jpeg
    Updated Mar 7, 2025
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    Geospatial Information Office (2025). Address Points, Compiled from Opt-In Open Counties, Minnesota [Dataset]. https://gisdata.mn.gov/dataset/loc-addresses-open
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    fgdb, jpegAvailable download formats
    Dataset updated
    Mar 7, 2025
    Dataset provided by
    Geospatial Information Office
    Description

    This dataset is a compilation of address point data from Minnesota suppliers that have opted-in for their address point data to be included in this dataset.

    It includes the following 42 suppliers that have opted-in to share their data openly as of the publication date of this dataset: Aitkin County, Anoka County, Benton County, Carver County, Cass County, Chippewa County, Chisago County, Clay County, Cook County, Dakota County, Douglas County, Fillmore County, Grant County, Hennepin County, Houston County, Isanti County, Itasca County, Koochinching County, Lac qui Parle County, Lake County, Le Sueur County, Lyon County, Marshall County, McLeod County, Morrison County, Mower County, Murray County, Otter Tail County, Pipestone County, Pope County, Ramsey County, Renville County, Saint Louis County, Scott County, Sherburne County, Stearns, Stevens County, Waseca County, Washington County, Wright County, and Yellow Medicine County.

    The two sources of address point data are the Minnesota Next Generation 9-1-1 (NG9-1-1) Program, in collaboration with local data suppliers, and the MetroGIS Metro Address Points Dataset which is on the Minnesota Geospatial Commons:

    The Minnesota NG9-1-1 Program enterprise database provides the data outside of the Metro Region which is provide by the suppliers. The data have been aggregated into a single dataset which implements the MN NG9-1-1 GIS Data Model (https://ng911gis-minnesota.hub.arcgis.com/documents/79beb1f9bde84e84a0fa9b74950f7589/about ).

    Only data which have meet the requirements for supporting NG9-1-1 are in the statewide aggregate GIS data. MnGeo extracts the available data, applies domain translations, and transforms it to UTM Zone 15 to comply with the GAC Address Point attribute schema: https://www.mngeo.state.mn.us/committee/address/address_standard.html.

    The MetroGIS Metro Address Points Dataset was created by a joint collaborative project involving the technical and managerial GIS staff from the ten Metropolitan Counties (Anoka, Carver, Chisago, Dakota, Hennepin, Isanti, Ramsey, Scott, Sherburne, and Washington), the Metropolitan Emergency Services Board, MetroGIS and the Metropolitan Council. The data are pulled in from the Minnesota Geospatial Commons: https://gisdata.mn.gov/dataset/us-mn-state-metrogis-loc-address-points

    ‘Supplier’ is a term used throughout this document. A supplier will typically be a county, but it could also be a public safety answering point (PSAP), region, or tribal nation. The supplier is the agency which provides the individual datasets for the aggregated dataset. The loc_addresses_open_metadata feature layer will contain the geometry/shape of the supplier boundaries, supplier name, supplier type, and feature count.

    Aggregation Process:
    1. Transfer NG9-1-1 data from the DPS Enterprise database.
    2. Download the latest data from the Geospatial Commons for MetroGIS.
    3. Extract, Translate, and Load (ETL) the data to the GAC Address Point Standard schema.
    4. Combine NG9-1-1 data with MetroGIS data.
    5. Filter the data for the Opt-In suppliers

  8. m

    Road Centerlines, Compiled from Opt-In Open Data Counties, Minnesota

    • gisdata.mn.gov
    fgdb, gpkg, html
    Updated Apr 10, 2025
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    Geospatial Information Office (2025). Road Centerlines, Compiled from Opt-In Open Data Counties, Minnesota [Dataset]. https://gisdata.mn.gov/dataset/trans-road-centerlines-open
    Explore at:
    html, gpkg, fgdbAvailable download formats
    Dataset updated
    Apr 10, 2025
    Dataset provided by
    Geospatial Information Office
    Description

    This dataset is a compilation of road centerline data from Minnesota suppliers that have opted-in for their road centerline data to be included in this dataset.

    It includes the following 41 suppliers that have opted-in to share their data openly as of the publication date of this dataset: Aitkin County, Anoka County, Benton County, Carver County, Cass County, Chippewa County, Chisago County, Clay County, Cook County, Dakota County, Douglas County, Fillmore County, Hennepin County, Houston County, Isanti County, Itasca County, Koochinching County, Lac qui Parle County, Lake County, Le Sueur County, Lyon County, Marshall County, McLeod County, Morrison County, Mower County, Murray County, Otter Tail County, Pipestone County, Pope County, Ramsey County, Renville County, Saint Louis County, Scott County, Sherburne County, Stearns, Stevens County, Waseca County, Washington County, Wright County, and Yellow Medicine County.

    The two sources of road centerline data are the Minnesota Next Generation 9-1-1 (NG9-1-1) Program, in collaboration with local data suppliers, and the MetroGIS Road Centerlines (Geospatial Advisory Council Schema) which is on the Minnesota Geospatial Commons:

    The Minnesota NG9-1-1 Program enterprise database provides the data outside of the Metro Region which is provide by the suppliers. The data have been aggregated into a single dataset which implements the MN NG9-1-1 GIS Data Model (https://ng911gis-minnesota.hub.arcgis.com/documents/79beb1f9bde84e84a0fa9b74950f7589/about ).

    Only data which have meet the requirements for supporting NG9-1-1 are in the statewide aggregate GIS data. MnGeo extracts the available data, applies domain translations, and transforms it to UTM Zone 15 to comply with the GAC road centerline attribute schema: https://www.mngeo.state.mn.us/committee/standards/roadcenterline/index.html.

    The MetroGIS Road Centerlines data was created by a joint collaborative project involving the technical and managerial GIS staff from the the Metropolitan Counties (Anoka, Carver, Chisago, Dakota, Hennepin, Isanti, Ramsey, Scott, Sherburne, and Washington), the Metropolitan Emergency Services Board, MetroGIS and the Metropolitan Council. The data are pulled from the Minnesota Geospatial Commons: https://gisdata.mn.gov/dataset/us-mn-state-metrogis-trans-road-centerlines-gac

    ‘Supplier’ is a term used throughout this document. A supplier will typically be a county, but it could also be a public safety answering point (PSAP), region, or tribal nation. The supplier is the agency which provides the individual datasets for the aggregated dataset. The trans_road_centerlines_open_metadata feature layer will contain the geometry/shape of the supplier boundaries, supplier name, supplier type, and feature count.

    Aggregation Process:
    1. Extract NG9-1-1 data from the Department of Public Safety (DPS) Enterprise database.
    2. Download the latest MetroGIS data from the Geospatial Commons.
    3. Extract, Translate, and Load (ETL) the DPS data to the GAC schema.
    4. Combine NG9-1-1 data with MetroGIS data.
    5. Filter the data for the Opt-In Open data counties

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U.S. Geological Survey (2024). MODFLOW-NWT model data sets for simulating effects of groundwater withdrawals on streamflows in Northwestern Chippewa County [Dataset]. https://catalog.data.gov/dataset/modflow-nwt-model-data-sets-for-simulating-effects-of-groundwater-withdrawals-on-streamflo

MODFLOW-NWT model data sets for simulating effects of groundwater withdrawals on streamflows in Northwestern Chippewa County

Explore at:
Dataset updated
Jul 6, 2024
Dataset provided by
United States Geological Surveyhttp://www.usgs.gov/
Area covered
Chippewa County
Description

A new groundwater flow model for western Chippewa County, Wisconsin has been developed by the Wisconsin Geological and Natural History Survey (WGNHS) and the U.S. Geological Survey (USGS). An analytic element GFLOW model was constructed and calibrated to generate hydraulic boundary conditions for the perimeter of the more detailed three-dimensional MODFLOW-NWT model. This three-dimensional model uses the USGS MODFLOW-NWT finite difference code, a standalone version of MODFLOW-2005 that incorporates the Newton (NWT) solver. The model conceptualizes the hydrogeology of western Chippewa County as a six-layer system which includes several hydrostratigraphic units. The model explicitly simulates groundwater-surface-water interaction with streamflow routing. Model input included recent estimates of aquifer hydraulic conductivities and a spatial groundwater recharge distribution developed using a GIS-based soil-water-balance model for the study area. Groundwater withdrawals from pumping were simulated for 269 high-capacity wells across the entire model domain, which includes western Chippewa County and portions of eastern Dunn County and southeastern Barron County. Model calibration used the parameter estimation code PEST, and calibration targets included heads and stream flows. Calibration f focused on the period from during 2011 to 2013 when the largest amount of calibration data were available. Following calibration, the model was applied to two distinct scenarios; one evaluating hydraulic impacts of more intensive industrial sand mining and the second evaluating the hydraulicimpacts of more intensive agricultural irrigation practices. Each scenario was developed with input by Chippewa County and a stakeholder group established for this study, and designed to represent reasonable future build-out conditions for both mining and irrigatedagriculture. The mining scenario underscores the potential hydraulic impacts related to changing land-use practices (i.e., hilltops and farm land becoming sand mines), while the irrigated agriculture scenario illustrates the potential hydraulic impacts of intensifying existing land-use practices (i.e., installing new wells to irrigate farm fields).

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