4.8 Article

Global thermal spring distribution and relationship to endogenous and exogenous factors

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NATURE COMMUNICATIONS
卷 13, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41467-022-34115-w

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  1. Italian MIUR [PRIN2017-2017LMNLAW]

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This study digitized and analyzed a dataset of thermal springs worldwide compiled by Gerald Ashley Waring in 1965. Using a machine learning approach, data from 6000 geothermal areas were analyzed and confirmed the dominant role of terrestrial heat flow, topography, volcanism, and extensional tectonics in the formation of thermal springs.
Here we present digitization and analysis of the thermal springs of the world dataset compiled by Gerald Ashley Waring in 1965 into a collection of analog maps. We obtain the geographic coordinates of -6,000 geothermal spring areas, including complementary data (e.g., temperature, total dissolved solids, flow rate), making them available in electronic format. Using temperature and flow rate, we derive the heat discharged from 1483 thermal spring areas (between -10(-5) and -10(3) MW, with a median value of -0.5 MW and -8300 MW in total). We integrate this data set with other global data sets to study the relationship between thermalism and endogenous and exogenous factors with a supervised machine learning algorithm. This analysis confirms a dominant role of the terrestrial heat flow, topography, volcanism and extensional tectonics. This data set offers new insights and will boost future studies in geothermal energy exploration. Data from 6000 geothermal areas worldwide are analyzed with a machine learning approach. The analysis suggests and confirms a dominant role of the terrestrial heat flow, topography, volcanism and extensional tectonics.

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