Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 2 Observations
<p>This data release component contains mean daily stream water temperature observations, retrieved from the USGS National Water Information System (NWIS) and used to train and validate all temperature models. The model training period was from 2010-10-01 to 2014-09-30, and the test period was from 2014-10-01 to 2016-09-30.</p>
Find Related Datasets
Search by Tags
Click any tag below to search for similar datasets
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"010:12"
]
|
| contactPoint |
{
"fn": "Farshid Rahmani",
"@type": "vcard:Contact",
"hasEmail": "mailto:fzr5082@psu.edu"
}
|
| description | <p>This data release component contains mean daily stream water temperature observations, retrieved from the USGS National Water Information System (NWIS) and used to train and validate all temperature models. The model training period was from 2010-10-01 to 2014-09-30, and the test period was from 2014-10-01 to 2016-09-30.</p> |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "Digital Data",
"format": "XML",
"accessURL": "https://doi.org/10.5066/P97CGHZH",
"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.5f986594d34e198cb77ff084.xml"
}
]
|
| identifier | http://datainventory.doi.gov/id/dataset/USGS_5f986594d34e198cb77ff084 |
| keyword |
[
"AL",
"Alabama",
"DE",
"Delaware",
"GA",
"Georgia",
"IA",
"ID",
"Idaho",
"Iowa",
"KS",
"Kansas",
"MA",
"MD",
"ME",
"MI",
"MS",
"Maine",
"Maryland",
"Massachusetts",
"Michigan",
"Mississippi",
"NC",
"NJ",
"NM",
"NV",
"NY",
"Nevada",
"New Jersey",
"New Mexico",
"New York",
"North Carolina",
"OH",
"OK",
"OR",
"Ohio",
"Oklahoma",
"Oregon",
"PA",
"Pennsylvania",
"RI",
"Rhode Island",
"SC",
"South Carolina",
"TN",
"TX",
"Tennessee",
"Texas",
"US",
"USGS:5f986594d34e198cb77ff084",
"UT",
"United States",
"Utah",
"VA",
"Virginia",
"WA",
"WI",
"WV",
"WY",
"Washington",
"West Virginia",
"Wisconsin",
"Wyoming",
"deep learning",
"environment",
"inlandWaters",
"machine learning",
"modeling",
"streams",
"water resources",
"water temperature"
]
|
| modified | 2020-12-09T00:00:00Z |
| publisher |
{
"name": "U.S. Geological Survey",
"@type": "org:Organization"
}
|
| spatial | -123.32988684, 30.1454932, -70.97964444, 48.90595739 |
| theme |
[
"geospatial"
]
|
| title | Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 2 Observations |
