{"accessLevel": "public", "bureauCode": ["010:12"], "contactPoint": {"@type": "vcard:Contact", "fn": "Samantha K. Oliver", "hasEmail": "mailto:soliver@usgs.gov"}, "description": "This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that makes predictions at 70 river reaches in the upper Delaware River Basin. This section includes predictions from several models, including a model pre-trainer that is predictions from a distance-weighted-average lotic-lentic input network (DWALLIN) model, reservoir outlet temperature predictions from a process-based model, forecasts from a persistence stream water temperature model, and stream water temperature forecasts from two deep learning models, a long-short term memory network and recurrent convolutional graph network model.", "distribution": [{"@type": "dcat:Distribution", "accessURL": "https://doi.org/10.5066/P9NVEA4V", "description": "Landing page for access to the data", "format": "XML", "mediaType": "application/http", "title": "Digital Data"}, {"@type": "dcat:Distribution", "description": "The metadata original format", "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.624f21fad34e21f82769a7b1.xml", "format": "XML", "mediaType": "text/xml", "title": "Original Metadata"}], "identifier": "http://datainventory.doi.gov/id/dataset/USGS_624f21fad34e21f82769a7b1", "keyword": ["NY", "New York", "US", "USGS:624f21fad34e21f82769a7b1", "United States", "deep learning", "environment", "forecast", "hybrid modeling", "inlandWaters", "machine learning", "modeling", "reservoirs", "streams", "temperature", "water", "water resources"], "modified": "2023-06-21T00:00:00Z", "publisher": {"@type": "org:Organization", "name": "U.S. Geological Survey"}, "spatial": "-75.3784656955209, 42.0623798211691, -74.677024617443, 42.1609582001827", "theme": ["geospatial"], "title": "Data to support network-wide 7-day ahead forecasting of water temperature in the Delaware River Basin: 4) model predictions"}