Articles | Volume 21, issue 2
https://doi.org/10.5194/hess-21-1263-2017
https://doi.org/10.5194/hess-21-1263-2017
Research article
 | 
02 Mar 2017
Research article |  | 02 Mar 2017

Feasibility analysis of using inverse modeling for estimating field-scale evapotranspiration in maize and soybean fields from soil water content monitoring networks

Foad Foolad, Trenton E. Franz, Tiejun Wang, Justin Gibson, Ayse Kilic, Richard G. Allen, and Andrew Suyker

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by Editor and Referees) (27 Oct 2016) by Matthew McCabe
AR by Trenton Franz on behalf of the Authors (07 Dec 2016)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (24 Dec 2016) by Matthew McCabe
RR by Anonymous Referee #3 (11 Jan 2017)
RR by Anonymous Referee #2 (30 Jan 2017)
ED: Publish subject to minor revisions (further review by Editor) (31 Jan 2017) by Matthew McCabe
AR by Trenton Franz on behalf of the Authors (09 Feb 2017)  Author's response    Manuscript
ED: Publish as is (14 Feb 2017) by Matthew McCabe
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Short summary
Estimates of evapotranspiration are vital for validation of models. However, those datasets are often limited to research applications. Here, we explore using vadose zone modeling with widespread and readily available soil water content monitoring networks. While this work focused on one agricultural site, the framework can be used everywhere there is basic data. The resulting evapotranspiration and soil water content measurements are valuable benchmarks for evaluation of land surface models.