Articles | Volume 24, issue 11
https://doi.org/10.5194/hess-24-5173-2020
https://doi.org/10.5194/hess-24-5173-2020
Research article
 | 
09 Nov 2020
Research article |  | 09 Nov 2020

Identifying the optimal spatial distribution of tracers for optical sensing of stream surface flow

Alonso Pizarro, Silvano F. Dal Sasso, Matthew T. Perks, and Salvatore Manfreda

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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) (15 Jul 2020) by Nunzio Romano
AR by Alonso Pizarro on behalf of the Authors (02 Aug 2020)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (22 Aug 2020) by Nunzio Romano
RR by Anonymous Referee #2 (25 Aug 2020)
RR by Anonymous Referee #3 (01 Sep 2020)
RR by Anonymous Referee #1 (04 Sep 2020)
ED: Publish subject to minor revisions (review by editor) (14 Sep 2020) by Nunzio Romano
AR by Alonso Pizarro on behalf of the Authors (17 Sep 2020)  Author's response   Manuscript 
ED: Publish as is (27 Sep 2020) by Nunzio Romano
AR by Alonso Pizarro on behalf of the Authors (28 Sep 2020)
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Short summary
An innovative approach is presented to optimise image-velocimetry performances for surface flow velocity estimates (and thus remotely sensed river discharges). Synthetic images were generated under different tracer characteristics using a numerical approach. Based on the results, the Seeding Distribution Index was introduced as a descriptor of the optimal portion of the video to analyse. A field case study was considered as a proof of concept of the proposed framework showing error reductions.