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USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Heat Flow Data

This package contains a map surface that depicts the estimated spatial variation of conductive heat flow (mW/m²) in a portion of northern Nevada, the extent of the ‘Nevada Machine Learning Project’ (DE-EE0008762). It was generated using well locations that had an estimated heat flow value from a measured thermal gradient and thermal conductivity, mainly using data from Southern Methodist University, with some additional USGS data. Well data are included along with and a map surface depicting estimated standard error of the heat flow interpolation.

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Author(s) Jacob DeAngelo orcid, Mark F. Coolbaugh
Publication Date 2021-11-30
Beginning Date of Data 2021-07-01
Ending Date of Data 2021-07-01
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DOI https://doi.org/10.5066/P9HRX1LR
Citation DeAngelo, J., and Coolbaugh, M.F., 2021, USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Heat Flow Data: U.S. Geological Survey data release, https://doi.org/10.5066/P9HRX1LR.
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Metadata Date 2021-11-30
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Citations of these data No citations of these data are known at this time.
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License http://www.usa.gov/publicdomain/label/1.0/
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Harvest Source: ScienceBase
Harvest Date: 2021-12-01T04:44:28.804Z