GEE-DisALEXI: cloud-based implementation of  the DisALEXI model for evapotranspiration  monitoring using Google Earth Engine

Yang, Yun; Anderson, Martha; Morton, Charles; Kang, Yanghui; Gao, Feng; Duan, Weina; Liu, Hui; Volk, John; Hain, Christopher

doi:10.5194/gmd-19-6967-2026

Articles | Volume 19, issue 14

https://doi.org/10.5194/gmd-19-6967-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-6967-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 14

Model description paper

|

30 Jul 2026

Model description paper |

| 30 Jul 2026

GEE-DisALEXI: cloud-based implementation of the DisALEXI model for evapotranspiration monitoring using Google Earth Engine

Yun Yang, Martha Anderson, Charles Morton, Yanghui Kang, Feng Gao, Weina Duan, Hui Liu, John Volk, and Christopher Hain

Data sets

Water Balance Based Evapotranspiration for HUC08 Basins in Western United States [Dataset] Yun Yang and Weina Duan https://doi.org/10.5281/zenodo.18762901

Model code and software

GEE-DisALEXI V0.0.33 ET Model [Figure] Yun Yang et al. https://doi.org/10.5281/zenodo.18675103

Short summary

Evapotranspiration (ET) describes the transfer of water from land to the atmosphere and is fundamental to understanding agriculture, ecosystems, and drought. We implemented the established DisALEXI model on Google Earth Engine (GEE-DisALEXI), enabling scalable, high-resolution ET mapping over large regions. This paper evaluates this version's accuracy, highlights example applications, discusses limitations, and outlines opportunities for future improvements.