Next Generation Public Supply Water Withdrawal Estimation for the Conterminous United States Using Machine Learning and Operational Frameworks

Next Generation Public Supply Water Withdrawal Estimation for the Conterminous United States Using Machine Learning and Operational Frameworks

Abstract Estimation of human water withdrawals is more important now than ever due to uncertain water supplies, population growth, and climate change. Fourteen percent of the total water withdrawal in the United States is used for public supply, typically including deliveries to domestic, commercial...

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Bibliographic Details
Main Authors: Ayman Alzraiee, Richard Niswonger, Carol Luukkonen, Josh Larsen, Donald Martin, Deidre Herbert, Cheryl Buchwald, Cheryl Dieter, Lisa Miller, Jana Stewart, Natalie Houston, Scott Paulinski, Kristen Valseth
Format: Article
Language:English
Published: Wiley 2024-07-01
Series:Water Resources Research
Subjects:
national water use
public supply
machine learning
uncertainty
water withdrawal
data driven modeling
Online Access:https://doi.org/10.1029/2023WR036632
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