Streamflow permanence modeling in Mt. Rainier National Park and surrounding area, Washington, 2018-2020
This data release contains spatially gridded geospatial data (rasters), R scripts, and supporting files to run Random Forest models to predict the probability of late summer surface flow in Mt. Rainier and surrounding area in Washington State for 2018–20. Gridded geospatial data that describes the physical conditions of Mt. Rainier National Park and surrounding area are used to refine the existing PRObability of Streamflow PERmanence (PROSPER) model (Jaeger and others, 2019). All data processing and analysis were scripted with R (version 4.0.4; https://www.r-project.org/) and was executed from the RStudio GUI (version 1.4.1103; https://www.rstudio.com/). R scripts to prepare the geospatial data, develop random forest models, and provide predictions are contained within “MORA_Source_Code.zip”. Geospatial data and supporting files used in these scripts are contained within "MORA_Model_Inputs.zip". Predictions and a suitability grid are contained within "MORA_Model_Outputs.zip."
Jaeger K, Sando R, McShane R, Dunham J, Hockman-Wert D, Kaiser K, Hafen K, Risley J, Blasch K. 2019. Probability of Streamflow Permanence Model (PROSPER): A spatially continuous model of annual streamflow permanence throughout the Pacific Northwest. Journal of Hydrology X, 2: 100005.
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"010:12"
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|
| contactPoint |
{
"fn": "Kristin L. Jaeger",
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"hasEmail": "mailto:kjaeger@usgs.gov"
}
|
| description | This data release contains spatially gridded geospatial data (rasters), R scripts, and supporting files to run Random Forest models to predict the probability of late summer surface flow in Mt. Rainier and surrounding area in Washington State for 2018–20. Gridded geospatial data that describes the physical conditions of Mt. Rainier National Park and surrounding area are used to refine the existing PRObability of Streamflow PERmanence (PROSPER) model (Jaeger and others, 2019). All data processing and analysis were scripted with R (version 4.0.4; https://www.r-project.org/) and was executed from the RStudio GUI (version 1.4.1103; https://www.rstudio.com/). R scripts to prepare the geospatial data, develop random forest models, and provide predictions are contained within “MORA_Source_Code.zip”. Geospatial data and supporting files used in these scripts are contained within "MORA_Model_Inputs.zip". Predictions and a suitability grid are contained within "MORA_Model_Outputs.zip." Jaeger K, Sando R, McShane R, Dunham J, Hockman-Wert D, Kaiser K, Hafen K, Risley J, Blasch K. 2019. Probability of Streamflow Permanence Model (PROSPER): A spatially continuous model of annual streamflow permanence throughout the Pacific Northwest. Journal of Hydrology X, 2: 100005. |
| distribution |
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| identifier | http://datainventory.doi.gov/id/dataset/USGS_62059323d34ec05caca3ab34 |
| keyword |
[
"Mount Rainier National Park",
"Pacific Northwest",
"USGS:62059323d34ec05caca3ab34",
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"climatologyMeteorologyAtmosphere",
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|
| modified | 2022-05-13T00:00:00Z |
| publisher |
{
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|
| spatial | -122.8696, 46.0262, -120.4271, 47.5643 |
| theme |
[
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]
|
| title | Streamflow permanence modeling in Mt. Rainier National Park and surrounding area, Washington, 2018-2020 |
