Articles | Volume 21, issue 6
https://doi.org/10.5194/hess-21-2953-2017
https://doi.org/10.5194/hess-21-2953-2017
Research article
 | 
16 Jun 2017
Research article |  | 16 Jun 2017

Assessment of irrigation physics in a land surface modeling framework using non-traditional and human-practice datasets

Patricia M. Lawston, Joseph A. Santanello Jr., Trenton E. Franz, and Matthew Rodell

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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: Publish subject to revisions (further review by Editor and Referees) (26 Apr 2017) by Matthew McCabe
AR by Patricia Lawston-Parker on behalf of the Authors (28 Apr 2017)  Author's response    Manuscript
ED: Publish subject to revisions (further review by Editor and Referees) (03 May 2017) by Matthew McCabe
ED: Referee Nomination & Report Request started (03 May 2017) by Matthew McCabe
RR by Anonymous Referee #2 (05 May 2017)
ED: Publish as is (07 May 2017) by Matthew McCabe
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Short summary
Irrigation can affect the weather by making the air cooler and more humid, potentially causing changes to clouds and rainfall. This study uses new datasets to test how well irrigation is simulated in a model. We find the model applies more water than farmers' data show, but the water is applied at the right time in the growing season and improves the modeled wetness of the soil. These results will help improve irrigation modeling and thus understanding of human impacts on the water cycle.