5 Model Predictions: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins
<p>This data release item contains water temperature predictions for 455 river sites across the U.S. Predictions are from the models described by Rahmani et al. (2021b).</p>
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"010:12"
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|
| contactPoint |
{
"fn": "Farshid Rahmani",
"@type": "vcard:Contact",
"hasEmail": "mailto:fzr5082@psu.edu"
}
|
| description | <p>This data release item contains water temperature predictions for 455 river sites across the U.S. Predictions are from the models described by Rahmani et al. (2021b).</p> |
| distribution |
[
{
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"title": "Digital Data",
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"accessURL": "https://doi.org/10.5066/P9VHMO56",
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|
| identifier | http://datainventory.doi.gov/id/dataset/USGS_6084cb2ed34eadd49d31aeaf |
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|
| modified | 2021-09-27T00:00:00Z |
| publisher |
{
"name": "U.S. Geological Survey",
"@type": "org:Organization"
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|
| spatial | -124.138658984335, 29.1524975232233, -67.8714112090545, 49.0018341836332 |
| theme |
[
"Geospatial"
]
|
| title | 5 Model Predictions: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins |
