9 datasets found
  1. a

    NorWeST Stream Temperature Map

    • idaho-epscor-gem3-uidaho.hub.arcgis.com
    Updated Jul 24, 2017
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    U.S. Forest Service (2017). NorWeST Stream Temperature Map [Dataset]. https://idaho-epscor-gem3-uidaho.hub.arcgis.com/datasets/usfs::norwest-stream-temperature-map
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    Dataset updated
    Jul 24, 2017
    Dataset authored and provided by
    U.S. Forest Service
    Description

    This map allows users to determine where there are annual stream temperature thermograph locations by the various tribes and local, state, and federal agencies and see historic stream temperature based on those data. It also allows users to see future modeled stream temperature scenarios. NorWeST Downloads.Observed Temperature Points (points representing a thermograph location in the stream temperature database)Stream Temperature (lines representing modeled streams) These layers automatically turns on as you zoom in.• Mean August Stream Temperature. (S1_93_11) - Historical composite scenario representing 19 year average August mean stream temperatures for 1993 – 2011. • Modeled Future Scenario 2040. (S30_2040D) - Future scenario based on global climate model ensemble averages that represent the A1B warming trajectory for 2040s (2030 - 2059). Future stream deltas within a processing unit were based on similar projected changes in August air temperature and stream discharge, but also accounted for differential warming of streams by using historical temperatures to scale temperature increases so that cold streams warm less than warm streams. This layer needs to be manually turned on by the user.• Modeled Future Scenario 2080. (S32_2080D) - Future scenario based on global climate model ensemble averages that represent the A1B warming trajectory for 2080s (2070 - 2099). Future stream deltas within a processing unit were based on similar projected changes in August air temperature and stream discharge, but also accounted for differential warming of streams by using historical temperatures to scale temperature increases so that cold streams warm less than warm streams. This layer needs to be manually turned on by the user.NorWeST Watershed Polygons

  2. g

    Columbia River Scenario Temperatures and Shade | gimi9.com

    • gimi9.com
    Updated Mar 8, 2024
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    (2024). Columbia River Scenario Temperatures and Shade | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_columbia-river-scenario-temperatures-and-shade
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    Dataset updated
    Mar 8, 2024
    Area covered
    Columbia River
    Description

    This dataset includes supporting data for the paper "Riparian vegetation shade restoration and loss effects on recent and future stream temperatures" by Fuller et al. 2022. Data include temperature predictions for stream reaches in the MidColumbia and Oregon Coast NorWEST processing units for different vegetation (current vegetation, restored riparian vegetation, and riparian vegetation removal) and climate change scenarios (years 2000, 2040, and 2080). Also included are percent shade estimates for the same scenarios and temperature and discharge associated with tributary outlets to the Columbia River. This dataset is associated with the following publication: Fuller, M.R., P. Leinenbach, N.E. Detenbeck, R. Labiosa, and D.J. Isaak. Riparian vegetation shade restoration and loss effects on recent and future stream temperatures. RESTORATION ECOLOGY. Blackwell Publishing, Malden, MA, USA, 30(7): e13626, (2022).

  3. f

    Coefficients and descriptive statistics associated with the multiple linear...

    • figshare.com
    xls
    Updated May 31, 2023
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    T. C. McDonnell; M. R. Sloat; T. J. Sullivan; C. A. Dolloff; P. F. Hessburg; N. A. Povak; W. A Jackson; C. Sams (2023). Coefficients and descriptive statistics associated with the multiple linear regression model for predicting July mean daily maximum stream water temperature (JMMST). [Dataset]. http://doi.org/10.1371/journal.pone.0134757.t002
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    T. C. McDonnell; M. R. Sloat; T. J. Sullivan; C. A. Dolloff; P. F. Hessburg; N. A. Povak; W. A Jackson; C. Sams
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Coefficients and descriptive statistics associated with the multiple linear regression model for predicting July mean daily maximum stream water temperature (JMMST).

  4. f

    Coefficients and descriptive statistics associated with the logistic...

    • plos.figshare.com
    xls
    Updated May 30, 2023
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    T. C. McDonnell; M. R. Sloat; T. J. Sullivan; C. A. Dolloff; P. F. Hessburg; N. A. Povak; W. A Jackson; C. Sams (2023). Coefficients and descriptive statistics associated with the logistic regression model for predicting maximum daily stream water temperature (MDST) sensitivity (high/low) to changes in maximum daily air temperature (MDAT). [Dataset]. http://doi.org/10.1371/journal.pone.0134757.t003
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    xlsAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    T. C. McDonnell; M. R. Sloat; T. J. Sullivan; C. A. Dolloff; P. F. Hessburg; N. A. Povak; W. A Jackson; C. Sams
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Coefficients and descriptive statistics associated with the logistic regression model for predicting maximum daily stream water temperature (MDST) sensitivity (high/low) to changes in maximum daily air temperature (MDAT).

  5. d

    Data from Warix et al. (2023), Local topography and hydraulic conductivity...

    • search.dataone.org
    Updated May 18, 2024
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    Sara Warix; Alexis Navarre-Sitchler; Kamini Singha (2024). Data from Warix et al. (2023), Local topography and hydraulic conductivity influence riparian groundwater age and groundwater-surface water connection [Dataset]. https://search.dataone.org/view/sha256%3Aa71368cdcefa8856a2026b605d8a3a37f87a3243d58c04287aeeea5267646e45
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    Dataset updated
    May 18, 2024
    Dataset provided by
    Hydroshare
    Authors
    Sara Warix; Alexis Navarre-Sitchler; Kamini Singha
    Time period covered
    Apr 11, 2021 - Nov 6, 2021
    Area covered
    Description

    The western U.S. is experiencing increasing rain to snow ratios due to climate change, and scientists are uncertain how changing recharge patterns will affect future groundwater-surface water connection. We examined how watershed topography and streambed hydraulic conductivity impact groundwater age and stream discharge at eight sites along a headwater stream within the Manitou Experimental Forest, CO USA. To do so, we measured: 1) continuous stream and groundwater discharge/level and specific conductivity from April to November, 2021; 2) biweekly stream and groundwater chemistry; 3) groundwater chlorofluorocarbons and tritium in spring and fall; 4) streambed hydraulic conductivity; and 5) local slope. We used the chemistry data to calculate fluorite saturation states that were used to inform end-member mixing analysis of streamflow source. We then combined chlorofluorocarbon and tritium data to estimate the age composition of riparian groundwater. Our data suggest that future stream drying is more probable where local slope is steep and streambed hydraulic conductivity is high. In these areas, groundwater source shifted seasonally, as indicated by age increases, and we observed a high fraction of groundwater in streamflow, primarily interflow from adjacent hillslopes. In contrast, where local slope is flat and streambed hydraulic conductivity is low, streamflow is more likely to persist as groundwater age was seasonally constant and buffered by storage in alluvial sediments. Groundwater age and streamflow paired with characterization of watershed topography and subsurface characteristics enabled identification of likely controls on future stream drying patterns.

  6. f

    Coefficients and descriptive statistics associated with the multiple linear...

    • plos.figshare.com
    xls
    Updated Jun 11, 2023
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    T. C. McDonnell; M. R. Sloat; T. J. Sullivan; C. A. Dolloff; P. F. Hessburg; N. A. Povak; W. A Jackson; C. Sams (2023). Coefficients and descriptive statistics associated with the multiple linear regression model1 for continuous estimates of the strength of maximum daily stream temperature (MDST) and maximum daily air temperature (MDAT) correlations. [Dataset]. http://doi.org/10.1371/journal.pone.0134757.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 11, 2023
    Dataset provided by
    PLOS ONE
    Authors
    T. C. McDonnell; M. R. Sloat; T. J. Sullivan; C. A. Dolloff; P. F. Hessburg; N. A. Povak; W. A Jackson; C. Sams
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    1 This model was only applied to reaches for which MDST was considered to have high sensitivity to increases in MDAT based on the logistic regression model (Table 3).Coefficients and descriptive statistics associated with the multiple linear regression model1 for continuous estimates of the strength of maximum daily stream temperature (MDST) and maximum daily air temperature (MDAT) correlations.

  7. d

    Fish collections in the Niobrara River basin, Nebraska : 1893-2005.

    • datadiscoverystudio.org
    • data.amerigeoss.org
    Updated May 19, 2018
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    (2018). Fish collections in the Niobrara River basin, Nebraska : 1893-2005. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/408c4721566f4365892fbfafc5dc5907/html
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    Dataset updated
    May 19, 2018
    Area covered
    Niobrara River
    Description

    description: White paper on the history of fish collections in the Niobrara River basin, from 1893 to 2005. This paper discusses locations of previous fish sampling, and locations requiring more collecting and information on fish species inhibiting the stream reach or lake. The history of fish sampling and collecting within the Niobrara River basin is discussed, as well as fish species and occurrence in rivers, streams, lakes, and ponds. Recommendations for future stream reaches that require more sampling are provided. Extensive maps of sampling locations, fish species occurrences, and information on native and introduced fish species follows the report.; abstract: White paper on the history of fish collections in the Niobrara River basin, from 1893 to 2005. This paper discusses locations of previous fish sampling, and locations requiring more collecting and information on fish species inhibiting the stream reach or lake. The history of fish sampling and collecting within the Niobrara River basin is discussed, as well as fish species and occurrence in rivers, streams, lakes, and ponds. Recommendations for future stream reaches that require more sampling are provided. Extensive maps of sampling locations, fish species occurrences, and information on native and introduced fish species follows the report.

  8. f

    Range and average elevation (m) of all watersheds contained within each...

    • plos.figshare.com
    xls
    Updated Jun 5, 2023
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    T. C. McDonnell; M. R. Sloat; T. J. Sullivan; C. A. Dolloff; P. F. Hessburg; N. A. Povak; W. A Jackson; C. Sams (2023). Range and average elevation (m) of all watersheds contained within each national forest comprising the study region. [Dataset]. http://doi.org/10.1371/journal.pone.0134757.t006
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOS ONE
    Authors
    T. C. McDonnell; M. R. Sloat; T. J. Sullivan; C. A. Dolloff; P. F. Hessburg; N. A. Povak; W. A Jackson; C. Sams
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Range and average elevation (m) of all watersheds contained within each national forest comprising the study region.

  9. f

    Landscape characteristics used for statistical modeling.

    • figshare.com
    xls
    Updated Jun 3, 2023
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    T. C. McDonnell; M. R. Sloat; T. J. Sullivan; C. A. Dolloff; P. F. Hessburg; N. A. Povak; W. A Jackson; C. Sams (2023). Landscape characteristics used for statistical modeling. [Dataset]. http://doi.org/10.1371/journal.pone.0134757.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    T. C. McDonnell; M. R. Sloat; T. J. Sullivan; C. A. Dolloff; P. F. Hessburg; N. A. Povak; W. A Jackson; C. Sams
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    All variables were calculated as watershed average or percentage, with the exception of drainage density and watershed area.Landscape characteristics used for statistical modeling.

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U.S. Forest Service (2017). NorWeST Stream Temperature Map [Dataset]. https://idaho-epscor-gem3-uidaho.hub.arcgis.com/datasets/usfs::norwest-stream-temperature-map

NorWeST Stream Temperature Map

Explore at:
3 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 24, 2017
Dataset authored and provided by
U.S. Forest Service
Description

This map allows users to determine where there are annual stream temperature thermograph locations by the various tribes and local, state, and federal agencies and see historic stream temperature based on those data. It also allows users to see future modeled stream temperature scenarios. NorWeST Downloads.Observed Temperature Points (points representing a thermograph location in the stream temperature database)Stream Temperature (lines representing modeled streams) These layers automatically turns on as you zoom in.• Mean August Stream Temperature. (S1_93_11) - Historical composite scenario representing 19 year average August mean stream temperatures for 1993 – 2011. • Modeled Future Scenario 2040. (S30_2040D) - Future scenario based on global climate model ensemble averages that represent the A1B warming trajectory for 2040s (2030 - 2059). Future stream deltas within a processing unit were based on similar projected changes in August air temperature and stream discharge, but also accounted for differential warming of streams by using historical temperatures to scale temperature increases so that cold streams warm less than warm streams. This layer needs to be manually turned on by the user.• Modeled Future Scenario 2080. (S32_2080D) - Future scenario based on global climate model ensemble averages that represent the A1B warming trajectory for 2080s (2070 - 2099). Future stream deltas within a processing unit were based on similar projected changes in August air temperature and stream discharge, but also accounted for differential warming of streams by using historical temperatures to scale temperature increases so that cold streams warm less than warm streams. This layer needs to be manually turned on by the user.NorWeST Watershed Polygons

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