Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks

Beaufort, Aurélien; Lamouroux, Nicolas; Pella, Hervé; Datry, Thibault; Sauquet, Eric

doi:https://doi.org/10.5194/hess-22-3033-2018

Articles | Volume 22, issue 5

https://doi.org/10.5194/hess-22-3033-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-22-3033-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 5

Research article

|

24 May 2018

Research article |

| 24 May 2018

Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks

Aurélien Beaufort, Nicolas Lamouroux, Hervé Pella, Thibault Datry, and Eric Sauquet

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Final revised paper (published on 24 May 2018)
Preprint (discussion started on 15 Nov 2017)

Interactive discussion

Status: closed

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

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RC1: 'Review of BEAUFORT et al. “Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks”', Anne Van Loon, 22 Dec 2017
- AC1: 'Reply to referee #1', Aurélien Beaufort, 06 Mar 2018
RC2: 'Beaufort et al., Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks, Catherine Sefton (Referee), 11 Feb 2018', Catherine Sefton, 11 Feb 2018
- AC2: 'Reply to referee #2', Aurélien Beaufort, 06 Mar 2018

Peer-review completion

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

ED: Publish subject to minor revisions (further review by editor) (22 Mar 2018) by Laurent Pfister

AR by Aurélien Beaufort on behalf of the Authors (23 Mar 2018) Author's response

ED: Publish subject to technical corrections (29 Apr 2018) by Laurent Pfister

Dear authors,
following up on the submission of your revised manuscript, I am pleased to accept your manuscript for publication in HESS. All major suggestions/remarks made by the two referees have been addressed. In its current version, some very minor technical points remain to be corrected (corrections/suggestions marked in capital letters):
150 … RHT (Theoretical Hydrographic Network; Pella et al., 2012) and the drainage area and the elevation => ';' deleted before Pella et al.
152 … while most of the gauging stations record flows of 152 CATCHMENTS of medium size …
217 … processes (e.g. storage capacity); it was chosen after a few trials. =>This last sentence reads a bit strange… if you decide to keep it, possibly say a word on which criteria was used for the final choice ?
237 … Models were calibrated against OBSERVATIONS available …
240 Thus there are two SETS of regressions parameters specific to each dataset for both LLR and LR models leading to different predictions of RPoD.
247 Note THAT when …
271-273 (and throughout text) … I am not 100% sure that ‘drying’ is the right wording… especially in this section it reads a bit weird. Rather use ‘drying statuses’ or ‘drying events (as mentioned sometimes in the text)’ wherever possible?
463 … Some aquatic species can persist in A dry reach …
477-478 For rainfall-driven river flow REGIMES, …
481 … could improve our approach without. => Not clear what ‘without’ means here… ?
491 … levels, LEADING to increased flow intermittence.
494 … and as A consequence flow alteration at ONDE sites.
522 … to ASSESS the relative performance of the two models.
542-543 … one key driver FOR the composition and persistence of aquatic species.
549 … and CONTRIBUTES to densify the flow state observation network.
Thank you for considering these suggestions in the final version of the manuscript.
Congratulations for the upcoming publication of your manuscript and thank you for having chosen HESS to publish your research.
Best regards,
Laurent Pfister

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AR by Aurélien Beaufort on behalf of the Authors (02 May 2018) Manuscript

Short summary

Streams which may stop flowing are poorly gauged. To improve their characterisation, we use an extended network providing monthly visual observations stating whether streams are flowing or not across France. These observations are combined with discharge and groundwater level in models to predict daily regional probability of drying. This approach allows identification of the most impacted regions by flow intermittence and estimation of the probability of drying dynamics over the last 27 years.