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Achieving Breakthroughs in Global Hydrologic Science by Unlocking the Power of Multisensor, Multidisciplinary Earth ObservationsOver the last half century, remote sensing has transformed hydrologic science. Whereas early efforts were devoted to observation of discrete variables, we now consider spaceborne missions dedicated to interlinked global hydrologic processes.Furthermore, cloud computing and computational techniquesare accelerating analyses of these data. How will the hydrologic community use these new resources to better understand the world’s water and relatedchallenges facing society? In this Commentary, we suggest that optimizing the benefits of remote sensing for advancing hydrologic research will happen byintegratingmultidisciplinary and multisensor data, leveraging commercial satellite measurements, and employingdata assimilation, cloud computing, and machine learning.We provide several recommendations to these ends.

Plain Language Summary
Observations from satellites have transformed hydrologic science. Early efforts, five decades ago, mapped attributes like snow cover, rainfall, topography, and vegetation, but now we consider new missions specifically designed to study global hydrologic processes. We also take advantageof new technologies like cloud computing and artificial intelligence. We describe strategiesfor maximizing the benefits of remote sensing for hydrology, encouraging research across disciplines using multiple sensors, using new commercially available satellites, and combining remote sensing measurements with hydrologic models.
Document ID
20210023634
Acquisition Source
Goddard Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Michael Durand
(The Ohio State University Columbus, Ohio, United States)
Ana Barros
(University of Illinois at Urbana Champaign Urbana, Illinois, United States)
Jeff Dozier
(University of California, Santa Barbara Santa Barbara, California, United States)
Robert Adler
(University of Maryland, College Park College Park, Maryland, United States)
Sara Cooley
(University of Oregon Eugene, Oregon, United States)
Dara Entekhabi
(Massachusetts Institute of Technology Cambridge, Massachusetts, United States)
Barton A Forman
(University of Maryland, College Park College Park, Maryland, United States)
Alexandra G Konings
(Stanford University Stanford, California, United States)
William P Kustas
(United States Department of Agriculture Washington D.C., District of Columbia, United States)
Jessica D Lundquist
(University of Washington)
Tamlin M Pavelsky
(University of North Carolina Wilmington Wilmington, North Carolina, United States)
Matthew Rodell
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Susan Steele-Dunne
(Delft University of Technology Delft, Zuid-Holland, Netherlands)
Date Acquired
October 29, 2021
Publication Date
October 6, 2021
Publication Information
Publication: AGU Advances
Publisher: Wiley
Volume: 2
Issue: 4
Issue Publication Date: December 1, 2021
e-ISSN: 2576-604X
Subject Category
Earth Resources And Remote Sensing
Funding Number(s)
WBS: 967701.02.03.01.88
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
External Peer Committee
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