Process-guided deep learning water temperature predictions: 6b Sparkling Lake detailed evaluation data
This dataset includes "test data" compiled water temperature data from an instrumented buoy on Sparkling Lake, WI and discrete (manually sampled) water temperature records from North Temperate Lakes Long-TERM Ecological Research Program (NTL-LTER; https://lter.limnology.wisc.edu/). The buoy is supported by both the Global Lake Ecological Observatory Network (gleon.org) and the NTL-LTER. The dataset also includes Sparkling Lake model erformance as measured as root-mean squared errors relative to temperature observations during the test period. This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"010:12"
]
|
| contactPoint |
{
"fn": "Jordan S. Read",
"@type": "vcard:Contact",
"hasEmail": "mailto:jread@usgs.gov"
}
|
| description | This dataset includes "test data" compiled water temperature data from an instrumented buoy on Sparkling Lake, WI and discrete (manually sampled) water temperature records from North Temperate Lakes Long-TERM Ecological Research Program (NTL-LTER; https://lter.limnology.wisc.edu/). The buoy is supported by both the Global Lake Ecological Observatory Network (gleon.org) and the NTL-LTER. The dataset also includes Sparkling Lake model erformance as measured as root-mean squared errors relative to temperature observations during the test period. This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD). |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "Digital Data",
"format": "XML",
"accessURL": "http://dx.doi.org/10.5066/P9AQPIVD",
"mediaType": "application/http",
"description": "Landing page for access to the data"
},
{
"@type": "dcat:Distribution",
"title": "Original Metadata",
"format": "XML",
"mediaType": "text/xml",
"description": "The metadata original format",
"downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.5d92507be4b0c4f70d0d059b.xml"
}
]
|
| identifier | http://datainventory.doi.gov/id/dataset/USGS_5d92507be4b0c4f70d0d059b |
| keyword |
[
"US",
"USGS:5d92507be4b0c4f70d0d059b",
"United States",
"WI",
"Wisconsin",
"biota",
"climate change",
"deep learning",
"environment",
"hybrid modeling",
"inlandWaters",
"machine learning",
"modeling",
"reservoirs",
"temperate lakes",
"temperature",
"thermal profiles",
"water"
]
|
| modified | 2020-08-20T00:00:00Z |
| publisher |
{
"name": "U.S. Geological Survey",
"@type": "org:Organization"
}
|
| spatial | -89.7037723045351, 46.002272195262, -89.6957319045477, 46.0152963952417 |
| theme |
[
"Geospatial"
]
|
| title | Process-guided deep learning water temperature predictions: 6b Sparkling Lake detailed evaluation data |
