Articles | Volume 24, issue 3
https://doi.org/10.5194/hess-24-1251-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-1251-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Mar 2020
Research article |
| 20 Mar 2020
| 20 Mar 2020
BESS-STAIR: a framework to estimate daily, 30 m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt
College of Agricultural, Consumer and Environmental Sciences,
University of Illinois at Urbana Champaign, Urbana, Illinois, USA
Center for Advanced Bioenergy and Bioproducts Innovation, University
of Illinois at Urbana Champaign, Urbana, Illinois, USA
Kaiyu Guan
CORRESPONDING AUTHOR
College of Agricultural, Consumer and Environmental Sciences,
University of Illinois at Urbana Champaign, Urbana, Illinois, USA
Center for Advanced Bioenergy and Bioproducts Innovation, University
of Illinois at Urbana Champaign, Urbana, Illinois, USA
National Center of Supercomputing Applications, University of Illinois
at Urbana Champaign, Urbana, Illinois, USA
Ming Pan
Department of Civil and Environmental Engineering, Princeton
University, New Jersey, USA
Youngryel Ryu
Department of Landscape Architecture and Rural Systems Engineering,
Seoul National University, Seoul, Republic of Korea
Bin Peng
College of Agricultural, Consumer and Environmental Sciences,
University of Illinois at Urbana Champaign, Urbana, Illinois, USA
National Center of Supercomputing Applications, University of Illinois
at Urbana Champaign, Urbana, Illinois, USA
Sibo Wang
National Center of Supercomputing Applications, University of Illinois
at Urbana Champaign, Urbana, Illinois, USA
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Short summary
Quantifying crop water use at each field every day is challenging because of the complexity of the evapotranspiration (ET) process and the unavailability of data at high spatiotemporal resolutions. We fuse multi-satellite data and employ a sophisticated model to estimate ET at 30 m resolution and a daily interval. With validation against 86 site years of ground truth in the US Corn Belt, we are confident that our ET estimation is accurate and a reliable tool for water resource management.
Quantifying crop water use at each field every day is challenging because of the complexity of...
