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Process-based water temperature predictions in the Midwest US: 5 Model prediction data

Metadata Updated: July 6, 2024

Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. General Lake Model verion 2 process-Based (PB) models were configured and calibrated with training data to reduce root-mean squared error for 449 lakes (PBALL). Uncalibrated models used default configurations (PB0; see Winslow et al. 2016 for details) and no parameters were adjusted according to model fit with observations for 7,150 lakes.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024
Publisher U.S. Geological Survey
Identifier USGS:5db819a8e4b0b0c58b5a4c45
Data Last Modified 20210727
Category geospatial
Public Access Level public
Bureau Code 010:12
Metadata Context
Metadata Catalog ID
Schema Version
Catalog Describedby
Harvest Object Id 76c69fd6-ddfa-4583-9b9b-58517d18b506
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -104.016631682319,37.1076610090681,-83.0716153148296,49.3749961973185
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash 50bc4c5171909040abe694ee1be51994832be6ee9b9c432e8debb20977f3e52c
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -104.016631682319, 37.1076610090681, -104.016631682319, 49.3749961973185, -83.0716153148296, 49.3749961973185, -83.0716153148296, 37.1076610090681, -104.016631682319, 37.1076610090681}

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