Impacts of high inter-annual variability of rainfall on a century  of extreme hydrologic regime of northwest Australia

Rouillard, A.; Skrzypek, G.; Dogramaci, S.; Turney, C.; Grierson, P. F.

doi:https://doi.org/10.5194/hess-19-2057-2015

Articles | Volume 19, issue 4

https://doi.org/10.5194/hess-19-2057-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/hess-19-2057-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 19, issue 4

Research article

|

29 Apr 2015

Research article |

| 29 Apr 2015

Impacts of high inter-annual variability of rainfall on a century of extreme hydrologic regime of northwest Australia

A. Rouillard, G. Skrzypek, S. Dogramaci, C. Turney, and P. F. Grierson

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Final revised paper (published on 29 Apr 2015)
Supplement to the final revised paper
Preprint (discussion started on 24 Oct 2014)

Interactive discussion

Status: closed

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

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- Supplement

RC C5776: 'Review of “Impacts of a changing climate on a century of extreme flood regime of northwest Australia”', Anonymous Referee #1, 20 Dec 2014
RC C5967: 'Review of Roulliard et al. Impacts of a changing climate on a century of extreme flood regime of northwest Australia', Anonymous Referee #2, 08 Jan 2015
AC C6337: 'Responses to Referees and list of changes in the manuscript', Alexandra Rouillard, 05 Feb 2015
EC C6487: 'Editor note', Efrat Morin, 14 Feb 2015

Peer-review completion

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

ED: Reconsider after major revisions (14 Feb 2015) by Efrat Morin

AR by Alexandra Rouillard on behalf of the Authors (19 Feb 2015)

ED: Referee Nomination & Report Request started (14 Mar 2015) by Efrat Morin

RR by Anonymous Referee #2 (23 Mar 2015)

Suggestions for revision or reasons for rejection

The authors have done a good job revising this MS, and should be congratulated, I hope my comments have proved constructive rather than obstructive. The statistical analysis is a lot more transparent, and I would urge the authors to refer to the model as a 'statistical model' throughout the paper so as to distinguish it from a model based on physics. I would also encourage the authors to provide the new information contained in their response at least as supplementary information.
The increased information contained in the response (not available during the initial review) does raise more questions. Specifically, the large negative departure of the predicted time series of FA area when FA-1 is not included in the model (Figure 1b in the response). Regardless of the R2 value, this does raise some issues. The first is that if FA-1 acts as an autoregressive variable, then an autoregressive model is usually adopted to formally account for this. The second, and somewhat perplexing issue, is how the authors actually know what the variable FA-1 is if they are using it to predict FA for the following month? I understand that this is one of four variables used to predict dFA in the calibration period (i.e. when they are able to measure this from the remote sensing data), but the extrapolation of this series back to 1912 implies they have data for all these independent variables going back that far (such as it appears for total rain and rain days). From what I can see the authors have data for two of the variables going back to 1912, but use a model with 4 variables for prediction, but there doesn’t appear to be actual data for the latter 2 (FA-1 and Int). Is this the case, and if so, what numbers do they use in the model in their place? Or have I missed something here? If I’ve got this totally wrong I think the authors need to at least clarify this last step. Finally, the Cross-Validation Error should be plotted with the final predicted time series as error bounds to show the values are not a precisely known line, and give a visual sense of this error, not just one contained within the table (otherwise the figure is at risk of being misleading).
I also appreciate the authors have modified the interpretation of the negative FA values in the MS, and this seems reasonable. However, negative values are presented as a continuous series in the time series figure giving the impression that these are representative of an actual physical process. Positive values are obviously an accurate estimate of the actual water area on the marsh itself, but negative values are not an accurate estimate of anything (i.e. they certainly can't be expected to match the time series of the vadose zone water content or the groundwater elevation), so we are left with these precise looking wiggly lines below 0 whose values doesn't actually mean anything (other than they are less than 0 and an unsaturated zone is developing). One option is to highlight this in the figure, or at the very least provide this explanation in the text within the relevant section.
With these comments to be addressed, the paper looks good for publication.

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ED: Publish subject to minor revisions (Editor review) (25 Mar 2015) by Efrat Morin

AR by Alexandra Rouillard on behalf of the Authors (05 Apr 2015) Author's response Manuscript

ED: Publish as is (09 Apr 2015) by Efrat Morin

AR by Alexandra Rouillard on behalf of the Authors (15 Apr 2015) Author's response Manuscript

Short summary

We reconstructed a 100-year monthly history of flooding and drought of a large wetland in arid northwest Australia, using hydroclimatic data calibrated against 25 years of satellite images. Severe and intense regional rainfall, as well as the sequence of events, determined surface water expression on the floodplain. While inter-annual variability was high, changes to the flood regime over the last 20 years suggest the wetland may become more persistent in response to the observed rainfall trend.