Achieving breakthroughs in global hydrologic science by unlocking the power of multi-sensor, multi-disciplinary earth observations

Authors: DURAND, M. - The Ohio State University; BARROS, A. - Duke University; DOZIER, J. - University Of California; ALDER, R. - University Of Maryland; COOLEY, S. - Stanford University; ENTEKHABI, D. - Massachusetts Institute Of Technology; KONINGS, A. - Stanford University; Kustas, William - Bill; LUNDQUIST, J. - University Of Washington; PAVELSKY, T. - University Of North Carolina; RODELL, M. - National Aeronautics And Space Administration (NASA); FORMAN, B. - University Of Maryland; STEELE-DUNNE, S. - Delft University Of Technology

Submitted to: AGU Advances
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/4/2021
Publication Date: 10/6/2021
Citation: Durand, M., Barros, A., Dozier, J., Alder, R., Cooley, S., Entekhabi, D., Konings, A., Kustas, W.P., Lundquist, J., Pavelsky, T., Rodell, M., Forman, B., Steele-Dunne, S. 2021. Achieving breakthroughs in global hydrologic science by unlocking the power of multi-sensor, multi-disciplinary earth observations. AGU Advances. https://doi.org/10.1029/2021AV000455.
DOI: https://doi.org/10.1029/2021AV000455

Interpretive Summary: Remote sensing measurements have led to paradigmatic advances across the geosciences, including in fields related to the hydrosphere: atmospheric and ocean sciences, and hydrology. The vantage of earth orbit allows sensors to spatially resolve surficial and subsurface properties planetwide, shedding new light on global processes. In this Commentary, based in part on a panel discussion at the AGU 2019 Fall Meeting, we make recommendations for optimizing the benefits of remote sensing for advancing global scale hydrologic research, including escaping research silos by pursuing multi-disciplinary and multi-sensor data integration, leveraging commercially available satellite measurements, and the increasing adoption of computational techniques such as data assimilation, cloud computing, and machine learning.

Technical Abstract: Over the last half century, remote sensing has transformed hydrologic science. Whereas early efforts were devoted to observation of variables with hydrologic relevance such as precipitation, topography and vegetation indices, we now use and aim for spaceborne missions dedicated to or specifically designed for the study of global hydrological processes, with new missions in the launch queue and under development. Global analysis of these data is is being accelerated by cloud computing and advanced computational techniques. How will the hydrologic community use these new resources to better understand the world’s water and the water-related challenges facing society? In this Commentary, based in part on a panel discussion at the AGU 2019 Fall Meeting, we make recommendations for optimizing the benefits of remote sensing for advancing global scale hydrologic research, including escaping research silos by pursuing multi-disciplinary and multi-sensor data integration, leveraging commercially available satellite measurements, and the increasing adoption of computational techniques such as data assimilation , cloud computing, and machine learning