A Decade of Data‐Driven Water Budgets: Synthesis and Bibliometric Review

Author:

Moyers Kelley1ORCID,Sabie Robert2ORCID,Waring Emily1ORCID,Preciado Jorge2ORCID,Naughton Colleen C.1ORCID,Harmon Thomas1ORCID,Safeeq Mohammad1ORCID,Torres‐Rua Alfonso3ORCID,Fernald Alexander2ORCID,Viers Joshua H.1ORCID

Affiliation:

1. Department of Civil and Environmental Engineering University of California, Merced Merced CA USA

2. New Mexico Water Resources Research Institute New Mexico State University Las Cruces NM USA

3. Civil and Environmental Engineering Department Utah State University Logan UT USA

Abstract

AbstractScarce water resources across the globe have prompted the development of data‐driven water budgets to account for and distribute limited water more effectively across various land uses and purposes. Data‐driven approaches for estimating individual water budget components have been extensively developed and subsequently reviewed (e.g., evapotranspiration, precipitation, groundwater, surface water, runoff), but the state of the art of data‐driven approaches for estimating and integrating complete water budgets has not been the subject of a review paper to our knowledge. In this review, we fill this void by reviewing 81 systematically identified publications from the last decade (2012–2022) on data‐driven water budget approaches. We describe the current state of measurements and data products for data‐driven water budgets for various spatiotemporal scales. Our analysis suggests that spatiotemporal parameters drive the approach for data‐driven water budgets, with larger spatiotemporal scales relying more on satellite remote sensing data products and smaller spatiotemporal scales relying more on ground‐based monitoring. The incorporation of satellite remote sensing data products and ground‐based monitoring was common across various spatiotemporal scales and enabled the estimation of complete water budgets in areas of limited data availability. We conclude that improved reporting of simplifying assumptions, uncertainty analysis methods, and data sources are required for the alignment of water budget estimations between resource managers at varied spatiotemporal scales. Our review calls for the standardization of data‐driven water budget reporting protocols to improve the interpretability of data‐driven water budgets across decision‐makers working at various spatiotemporal scales.

Funder

National Institute of Food and Agriculture

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

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