Crop water use dynamics over arid and semi-arid croplands in the lower Colorado River Basin

ABSTRACT

Numerous studies have evaluated the application of Remote Sensing (RS) techniques for mapping actual evapotranspiration (ETa) using Vegetation-Index-based (VI-based) and surface energy balance methods (SEB). SEB models computationally require a large effort for application. VI-based methods are fast and easy to apply and could therefore potentially be applied at high resolution; however, the accuracy of VI-based methods in comparison to SEB-based models remains unclear. We tested the ETa computed with the modified 2-band Enhanced Vegetation Index (METEVI2) implemented in the Google Earth Engine – for mapping croplands’ water use dynamics in the Lower Colorado River Basin. We compared METEVI2 with the well-established RS-based products of OpenET (Ensemble, eeMETRIC, SSEBop, SIMS, PT_JPL, DisALEXI and geeSEBAL). METEVI2 was then evaluated with measured ETa from four wheat fields (2017–2018). Results indicated that the monthly ETa variations for METEVI2 and OpenET models were comparable, though of varying magnitudes. On average, METEVI2 had the lowest difference rate from the average observed ETa with 17 mm underestimation, while SIMS had the highest difference rate (82 mm). Findings show that METEVI2 is a cost-effective ETa mapping tool in drylands to track crop water use. Future studies should test METEVI2’s applicability to croplands in more humid regions.

KEYWORDS:

• METEVI2
• Remote sensing-based ETa
• Crop water consumption
• Google Earth Engine
• OpenET

Acknowledgments

Our special thanks to the financial support (Ph.D. scholarship) given by the German Academic Exchange Service (DAAD). We would like to gratefully acknowledge NASA and the USGS for providing the open-access satellite data (Landsat and MODIS), Google for the GEE platform, the Bureau of Reclamation at the Boulder City office, the U.S. Department of Agriculture, Agricultural Research Service, for provisional data provided by Douglas J. Hunsaker and Andrew N. French. We are also immensely grateful to our colleagues at the University of Arizona and USGS for their scientific input and assistance. Any use of trade, firm or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Part of the data that support the findings of this study is available from the corresponding author upon reasonable request.

Additional information

Funding

This research was funded by the German Academic Exchange Service (DAAD) to support the Ph.D. degree. We acknowledge support by the Open Access Publication Funds of the Göttingen University.