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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 20, issue 8
Hydrol. Earth Syst. Sci., 20, 3361–3377, 2016
https://doi.org/10.5194/hess-20-3361-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 20, 3361–3377, 2016
https://doi.org/10.5194/hess-20-3361-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 23 Aug 2016

Research article | 23 Aug 2016

Comparing the Normalized Difference Infrared Index (NDII) with root zone storage in a lumped conceptual model

Nutchanart Sriwongsitanon et al.
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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 (04 Dec 2015) by Bart van den Hurk
AR by Nutchanart Sriwongsitanon on behalf of the Authors (25 Mar 2016)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (06 Apr 2016) by Bart van den Hurk
RR by Juraj Parajka (21 Apr 2016)
ED: Reconsider after major revisions (04 May 2016) by Bart van den Hurk
AR by Anna Wenzel on behalf of the Authors (14 Jun 2016)  Author's response
ED: Publish subject to minor revisions (Editor review) (20 Jul 2016) by Bart van den Hurk
AR by Hubert H.G. Savenije on behalf of the Authors (25 Jul 2016)  Author's response    Manuscript
ED: Publish as is (27 Jul 2016) by Bart van den Hurk
Publications Copernicus
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Short summary
We demonstrated that the readily available NDII remote sensing product is a very useful proxy for moisture storage in the root zone of vegetation. We compared the temporal variation of the NDII with the root zone storage in a hydrological model of eight catchments in the Upper Ping River in Thailand, yielding very good results. Having a reliable NDII product that can help us to estimate the actual moisture storage in catchments is a major contribution to prediction in ungauged basins.
We demonstrated that the readily available NDII remote sensing product is a very useful proxy...
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