Evapotranspiration Everywhere, All the Time

Towards a Unified View From Earth Observation

Short Survey (2026)
Author(s)

Joshua B. Fisher (Hydrosat USA, Chapman University)

Martha C. Anderson (USDA-ARS Hydrology and Remote Sensing Laboratory)

Diego G. Miralles (Universiteit Gent)

Kanishka Mallick (Université de Toulouse)

Paul C. Stoy (University of Wisconsin-Madison)

Youngryel Ryu (Seoul National University)

Wim G.M. Bastiaanssen (Hydrosat USA, TU Delft - Water Systems Monitoring & Modelling)

Research Group
Water Systems Monitoring & Modelling
DOI related publication
https://doi.org/10.1111/gcb.70898 Final published version
More Info
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Publication Year
2026
Language
English
Research Group
Water Systems Monitoring & Modelling
Journal title
Global Change Biology
Issue number
5
Volume number
32
Article number
e70898
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Abstract

Scientists want to know everything, everywhere, and all the time. This is particularly true in Earth science, where we seek to understand processes that span from the molecular to the planetary scale in how the world works, how it affects us, and how we impact it—especially the water cycle. Evapotranspiration (ET) was the last component to be measured in closing the water cycle: for decades, closing the water budget meant adding up all the measurable components, then inferring ET as the residual. Early measurements relied on water loss from pans and weighing lysimeters, followed by sensors inserted into plants to monitor sap flow and leaf chambers capturing transpiration. Scaling up to ecosystems became possible through eddy-covariance flux towers and further across landscapes through proximal sensing with drones, aircraft, and, ultimately, with satellites. While enormous progress has been made to measure or estimate ET everywhere and all the time, no single approach has yet achieved both simultaneously. Flux towers help with all the time, but not everywhere. Satellites can do everywhere, but not all the time (except, in part, for geostationary satellites, though with insufficient spatial coverage and resolution). A new advent of smallsat constellations is moving us to everywhere and all the time in detail, though we are only in the beginning of that era. This paper discusses the evolution and revolution of Earth observation for ET, as we advanced from the first Landsat and development of ET models through the progression of increasingly higher spatiotemporal resolution across international space agencies and commercial industry with increasing ET model sophistication, cloud computing, and machine learning. We continue to march ahead towards ET everywhere, all the time, and use that knowledge to better manage water and sustain our planet.