Process-guided deep learning water temperature predictions: 4 Training data
type: Dataset
description: This dataset includes compiled water temperature data from a variety of sources, including the Water Quality Portal (Read et al. 2017), the North Temperate Lakes Long-TERM Ecological Research Program (https://lter.limnology.wisc.edu/), the Minnesota department of Natural Resources, and the Global Lake Ecological Observatory Network (gleon.org). 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).
keyword: amerigeo
keyword: amerigeoss
keyword: ckan
keyword: climate-change
keyword: deep-learning
keyword: geo
keyword: geoss
keyword: hybrid-modeling
keyword: machine-learning
keyword: modeling
keyword: national
keyword: north-america
keyword: reservoirs
keyword: temperate-lakes
keyword: temperature
keyword: thermal-profiles
keyword: united-states
keyword: us
keyword: usgs-5d8a42e3e4b0c4f70d0ae5fd
keyword: water
issued: 2025-11-19T18:02:53.073831
modified: 2020-08-20
theme: {geospatial}
contact point: Organization
  fn: U.S. Geological Survey (Point of Contact)
spatial: Location

US Migrating
type: Agent

Web Resource
type: Distribution
access URL: http://dx.doi.org/10.5066/P9AQPIVD
issued: 2021-11-04T16:38:05.253258
modified: 2025-11-19T18:02:53.054332

Web Resource
type: Distribution
access URL: http://dx.doi.org/10.1029/2019WR024922
issued: 2021-11-04T16:38:05.253262
modified: 2025-11-19T18:02:53.055143

Web Resource
type: Distribution
access URL: https://doi.org/10.1002/2016WR019993
issued: 2021-11-04T16:38:05.253265
modified: 2025-11-19T18:02:53.055859