Open AccessGlobal Drought Clustering Could Mean Big Losses for Mining
Author(s) -
Emily Underwood
Publication year - 2017
Publication title -
eos
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.316
H-Index - 86
eISSN - 2324-9250
pISSN - 0096-3941
DOI - 10.1029/2017eo070397
Subject(s) - cluster analysis , big data , data mining , data science , computer science , artificial intelligence
Long-term climate records could help mining companies and their investors assess the financial risk of water shortages.
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