Incorporating experimentally derived streamflow contributions  into model parameterization to improve discharge prediction

Hartmann, Andreas; Payeur-Poirier, Jean-Lionel; Hopp, Luisa

doi:https://doi.org/10.5194/hess-27-1325-2023

Articles | Volume 27, issue 6

https://doi.org/10.5194/hess-27-1325-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-27-1325-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 27, issue 6

Research article

|

28 Mar 2023

Research article |

| 28 Mar 2023

Incorporating experimentally derived streamflow contributions into model parameterization to improve discharge prediction

Andreas Hartmann, Jean-Lionel Payeur-Poirier, and Luisa Hopp

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Final revised paper (published on 28 Mar 2023)
Supplement to the final revised paper
Preprint (discussion started on 28 May 2021)

Interactive discussion

Status: closed

RC1:
'Comment on hess-2021-179', Christian Birkel, 16 Jun 2021

The comment was uploaded in the form of a supplement: https://hess.copernicus.org/preprints/hess-2021-179/hess-2021-179-RC1-supplement.pdf

Citation: https://doi.org/10.5194/hess-2021-179-RC1
- AC1: 'Reply on RC1', Andreas Hartmann, 11 Nov 2021
  
  Dear referee, thanks for your patience. A newborn daughter, a new position and a move from western to eastern Germany created some unavoidable delay. Please finally find our response attached.
  
  Citation: https://doi.org/10.5194/hess-2021-179-AC1
CC1:
'Comment on hess-2021-179', John Ding, 16 Jun 2021

I share the concern expressed by Referee Christian Birkel that
”- Figure 5 is quite hard to interpret and I suggest to use a log-scale for streamflow visualization.” (In RC1, lines 6 - 7 from the end.)
In addition to a log-transformed discharge variable, log Q, I suggest a Negative Inverse Square Root (NISR)-transformed one , −1/√Q, (e.g., Ding, 2020), be used to plot the two monsoon season hydrographs in year 2013 and 2014.
References
Ding, J. (2020). Interactive comment on ”HESS Opinions: Improving the evaluation of groundwater representation in continental to global scale models” by Tom Gleeson et al., Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess- 2020-378-SC2.

Citation: https://doi.org/10.5194/hess-2021-179-CC1
- AC3: 'Reply on CC1', Andreas Hartmann, 11 Nov 2021
  
  Thank you for your advice. We will provide Figure 5 with Q transferred in log scale. We will also try the suggested NSIR.
  
  Citation: https://doi.org/10.5194/hess-2021-179-AC3
RC2:
'Comment on hess-2021-179', Anonymous Referee #2, 21 Jul 2021

The comment was uploaded in the form of a supplement: https://hess.copernicus.org/preprints/hess-2021-179/hess-2021-179-RC2-supplement.pdf

Citation: https://doi.org/10.5194/hess-2021-179-RC2
- AC2: 'Reply on RC2', Andreas Hartmann, 11 Nov 2021
  
  Dear referee, thanks for your patience. A newborn daughter, a new position and a move from western to eastern Germany created some unavoidable delay. Please finally find our response attached.
  
  Citation: https://doi.org/10.5194/hess-2021-179-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

ED: Reconsider after major revisions (further review by editor and referees) (14 Jan 2022) by Jim Freer

AR by Andreas Hartmann on behalf of the Authors (18 Oct 2022) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (11 Nov 2022) by Jim Freer

RR by Christian Birkel (23 Nov 2022)

RR by Anonymous Referee #2 (03 Jan 2023)

ED: Publish subject to minor revisions (review by editor) (17 Jan 2023) by Jim Freer

AR by Andreas Hartmann on behalf of the Authors (20 Jan 2023) Author's response Author's tracked changes Manuscript

ED: Publish as is (28 Feb 2023) by Jim Freer

AR by Andreas Hartmann on behalf of the Authors (03 Mar 2023)

Short summary

We advance our understanding of including information derived from environmental tracers into hydrological modeling. We present a simple approach that integrates streamflow observations and tracer-derived streamflow contributions for model parameter estimation. We consider multiple observed streamflow components and their variation over time to quantify the impact of their inclusion for streamflow prediction at the catchment scale.