BESS-STAIR: a framework to estimate daily, 30&thinsp;m, and all-weather crop evapotranspiration using multi-source satellite data  for the US Corn Belt

Jiang, Chongya; Guan, Kaiyu; Pan, Ming; Ryu, Youngryel; Peng, Bin; Wang, Sibo

doi:https://doi.org/10.5194/hess-24-1251-2020

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.

https://doi.org/10.5194/hess-24-1251-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 3

Research article

|

20 Mar 2020

Research article |

| 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

Chongya Jiang, Kaiyu Guan, Ming Pan, Youngryel Ryu, Bin Peng, and Sibo Wang

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Final revised paper (published on 20 Mar 2020)
Preprint (discussion started on 08 Aug 2019)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'referee comments', Anonymous Referee #1, 02 Sep 2019
- AC1: 'Response to reviewer #1', chongya jiang, 04 Dec 2019
RC2: 'Interactive comment on “BESS-STAIR: a framework to estimate daily, 30-meter, and allweather crop evapotranspiration using multi-source satellite data for the U.S. Corn Belt” by C. Jiang et al.', Anonymous Referee #2, 06 Nov 2019
- AC2: 'Response to reviewer #2', chongya jiang, 04 Dec 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to revisions (further review by editor and referees) (06 Dec 2019) by Lixin Wang

AR by chongya jiang on behalf of the Authors (06 Dec 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (05 Jan 2020) by Lixin Wang

RR by Anonymous Referee #1 (14 Feb 2020)

ED: Publish as is (14 Feb 2020) by Lixin Wang

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.