Process-guided deep learning water temperature predictions: 6a Lake Mendota detailed evaluation data

Description

This dataset includes "test data" compiled water temperature data from an instrumented buoy on Lake Mendota, 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 Lake Mendota 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).

Resources

Name Format Description Link
0 https://doi.org/10.1002/2016WR019993
0 http://dx.doi.org/10.1029/2019WR024922
0 CSDGM IMPORT ERROR: No digtinfo/formcont http://dx.doi.org/10.5066/P9AQPIVD
0 https://doi.org/10.5194/gmd-12-473-2019
33 1810.02880.pdf https://arxiv.org/pdf/1810.02880.pdf
0 http://dx.doi.org/10.5066/F7DV1H10

Tags

  • reservoirs
  • hybrid-modeling
  • modeling
  • temperate-lakes
  • deep-learning
  • usgs-5d925066e4b0c4f70d0d0599
  • united-states
  • thermal-profiles
  • us
  • climate-change
  • water
  • temperature
  • machine-learning

Topics

Categories