Using dry and wet year hydroclimatic extremes to guide future hydrologic projections

Oni, Stephen; Futter, Martyn; Ledesma, Jose; Teutschbein, Claudia; Buttle, Jim; Laudon, Hjalmar

doi:https://doi.org/10.5194/hess-20-2811-2016

Articles | Volume 20, issue 7

https://doi.org/10.5194/hess-20-2811-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/hess-20-2811-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 20, issue 7

Research article

|

13 Jul 2016

Research article |

| 13 Jul 2016

Using dry and wet year hydroclimatic extremes to guide future hydrologic projections

Stephen Oni, Martyn Futter, Jose Ledesma, Claudia Teutschbein, Jim Buttle, and Hjalmar Laudon

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Final revised paper (published on 13 Jul 2016)
Supplement to the final revised paper
Preprint (discussion started on 20 Jan 2016)
Supplement to the preprint

Interactive discussion

Status: closed

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

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RC1: 'Revision/suggestions to the authors', Anonymous Referee #1, 21 Feb 2016
- AC2: 'Response to anonymous reviewer 2', Stephen Oni, 28 Mar 2016
RC2: 'Comments on manuscript', Patrick Willems, 13 Mar 2016
- AC1: 'Response to reviewer 2 (Patrick Williems)', Stephen Oni, 28 Mar 2016

Peer-review completion

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

ED: Reconsider after major revisions (06 Apr 2016) by Niko Verhoest

AR by Stephen Oni on behalf of the Authors (04 May 2016) Author's response Manuscript

ED: Referee Nomination & Report Request started (15 May 2016) by Niko Verhoest

RR by Anonymous Referee #1 (10 Jun 2016)

RR by Patrick Willems (12 Jun 2016)

Suggestions for revision or reasons for rejection

This paper much improved. It is now ready for publication. If revision would be recommended, I made the following notes, which may be considered for further improving the manuscript.

Lines 24-25: “… hydrologic model calibration for climate impact studies should be based on years that best approximate expected future conditions.”: this is a strong statement. Also other types of validation may be done.

Line 63: extend sentence to: “… depends on the length of the time series used for calibration and validation”

Line 67: it may be clarified that what is mainly tested in such split-sample approach is whether the model is not overtuned, often related to overparameterization

Lines 90-93: The sentence “Our expectation …” needs rephrasement. I suggest to rephrase sentences as follows: “Such uncertainty quantification will allow us to assess the limitations and uncertainties in hydrological model based climate change impact analysis related to the hydrological model calibration strategies and to compare these with the uncertainty related to the climate models.”

Section 2.2.: The old greenhouse gas scenarios (SRES based) were applied. These became outdated in the meantime; the new RCP based scenarios should be used in current climate change impact studies. However, because the focus of this paper lies on the methodology rather than on the impact results, it is acceptable to rely on the old SRES scenarios.

Line 171: “NS .. dropped close to zero”: Sure? The NS should be close to 1 (or at least above 0)

Lines 229: “The model performed better when calibrated to wet and dry conditions …”: it may be clarified that this is logical because otherwise (e.g. using the NS) too much weight is given to the central part of the distribution (many more values in that part).

Section 3.5: This is an interesting approach and analysis!

Line 292: I am not sure that “average” is the proper wording here

Line 331: “other metrics”: OK, but none of these focus on the (high) extremes.
Another way to evaluate the model for its performance in describing extremes is the approach presented in Willems (2009) or the one by Van Steenbergen et al. (2012)

Line 344: “towards high flows”: not fully true (as discussed earlier in the paper as well): because the high flow durations are typically shorter than the low flow durations, they may receive lower weight rather than higher weight (because of the squared flow terms) in the NS computation

Section 4.5: You may add that climate change in many places of the world leads to more extremes, both high and low flows.

Many references are rather old; it would be good to add some more recent ones. Let me suggest some.

Line 58: Other references next to Li et al., 2015, that may be added here are Breuer et al. (2009) and Vansteenkiste et al. (2014a)
Line 71: next to Butts et al., 2004, and Refsgaard et al., 2006, another more recent reference that can be added here is Vansteenkiste et al. (2014)
Line 85: next to Refsgaard et al., 2014, another recent reference is Andréassian et al. (2014).
Line 326: Another reference that may be added here is Willems (2009)
Lines 347-348: That the uncertainty is higher in extrapolating low flows (compared to high flows) was also shown by others: Vansteenkiste et al. (2014b), Velázquez et al. (2012), Bae et al. (2011), Najafi et al. (2011), Maurer et al. (2010), …

References:
Andréassian, V., F. Bourgin, L. Oudin, T. Mathevet, C. Perrin, J. Lerat, L. Coron, L. Berthet, (2014), ‘Seeking genericity in the selection of parameter sets: impact on hydrological model efficiency’, Water Resources Research, 50(10), 8356-8366.
Bae, D.-H., Jung, I.-W., Lettenmaier, D.-P. (2011), ‘Hydrologic uncertainties in climate change from IPCC AR4 GCM simulations of the Chungju Basin, Korea’. Journal of Hydrology, 401, 90–105.
Breuer L., Huisman J.A., Willems P., Bormann H., Bronstert A., Croke B.F.W., Frede H., Gräff T., Hubrechts L., Jakeman A.J., Kite G.W., Lanini J., Leavesley G., Lettenmaier D.P., Lindström G., Seibert J., Sivapalan M., Viney N.R. (2009), ‘Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) I: Model intercomparison of current land use’, Advances in Water Resources, 32(2), 129-146.
Maurer, E.-P., Brekke, L.-D., Pruitt, T. (2010), ‘Contrasting lumped and distributed hydrology models for estimating climate change impacts on California watersheds’, J. Am. Water Resour. Assoc., 46(5), 1024-1035.
Najafi, M.-R., Moradkhani, H., Jung, I.-W. (2011), ‘Assessing the uncertainties of hydrologic model selection in climate change impact studies’. Hydrological Processes, 25(18), 2814–2826.
Van Steenbergen, N., Willems, P. (2012), ‘Method for testing the accuracy of rainfall-runoff models in predicting peak flow changes due to rainfall changes, in a climate changing context’, Journal of Hydrology, 414-415, 425-434
Vansteenkiste, Th., Tavakoli, M., Van Steenbergen, N., De Smedt, F., Batelaan, O., Pereira, F., Willems, P. (2014a), ‘Intercomparison of five lumped and distributed models for catchment runoff and extreme flow simulation’, Journal of Hydrology, 511C, 335-349
Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., De Smedt, F., Batelaan, O., Pereira, F., Willems, P. (2014b), ‘Intercomparison of hydrological model structures and calibration approaches in climate scenario impact projections’, Journal of Hydrology, 519, 743–755
Velázquez, J.-A., Schmid, J., Ricard, S., Muerth, M.-J., Gauvin St-Denis, B., Minville, M., Chaumont, D., Caya, D., Ludwig, R., Turcotte, R. (2012), ‘An ensemble approach to assess hydrological models’ contribution to uncertainties in the analysis of climate change impact on water resources’. Hydrology and Earth System Sciences, 17, 565-578.
Willems P. (2009), ‘A time series tool to support the multi-criteria performance evaluation of rainfall-runoff models’, Environmental Modelling & Software, 24(3), 311-321

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ED: Publish subject to minor revisions (Editor review) (13 Jun 2016) by Niko Verhoest

AR by Stephen Oni on behalf of the Authors (21 Jun 2016) Author's response Manuscript

ED: Publish as is (22 Jun 2016) by Niko Verhoest

AR by Stephen Oni on behalf of the Authors (23 Jun 2016) Manuscript

Short summary

This paper presents an important framework to improve hydrologic projections in cold regions. Hydrologic modelling/projections are often based on model calibration to long-term data. Here we used dry and wet years as a proxy to quantify uncertainty in projecting hydrologic extremes. We showed that projections based on long-term data could underestimate runoff by up to 35% in boreal regions. We believe the hydrologic modelling community will benefit from new insights derived from this study.