A wavelet-based approach to streamflow event identification  and modeled timing error evaluation

Towler, Erin; McCreight, James L.

doi:https://doi.org/10.5194/hess-25-2599-2021

Articles | Volume 25, issue 5

https://doi.org/10.5194/hess-25-2599-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-25-2599-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 25, issue 5

Research article

|

19 May 2021

Research article |

| 19 May 2021

A wavelet-based approach to streamflow event identification and modeled timing error evaluation

Erin Towler and James L. McCreight

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Final revised paper (published on 19 May 2021)
Preprint (discussion started on 22 Sep 2020)
Supplement to the preprint

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Review', Uwe Ehret, 20 Oct 2020
- SC1: 'Note on missing tables', James McCreight, 21 Oct 2020
- AC1: 'Response to Reviewer 1', Erin Towler, 16 Dec 2020
SC2: 'tables, post facto', James McCreight, 21 Oct 2020
RC2: 'Review of "A Wavelet-Based Approach to Streamflow Event Identification and Modeled Timing Error Evaluation"', Cedric David, 24 Oct 2020
- AC2: 'Response to Reviewer 2', Erin Towler, 16 Dec 2020

Peer-review completion

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

ED: Publish subject to revisions (further review by editor and referees) (21 Jan 2021) by Matthew Hipsey

AR by Erin Towler on behalf of the Authors (24 Feb 2021) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (01 Mar 2021) by Matthew Hipsey

RR by Uwe Ehret (01 Mar 2021)

ED: Publish subject to technical corrections (07 Apr 2021) by Matthew Hipsey

AR by Erin Towler on behalf of the Authors (08 Apr 2021) Author's response Manuscript

Short summary

We present a wavelet-based approach to quantify streamflow timing errors for model evaluation and development. We demonstrate the method using real and simulated stream discharge data from several locations. We show how results can be used to identify potential hydrologic processes contributing to the timing errors. Furthermore, we illustrate how the method can document model performance by comparing timing errors across versions of the National Water Model.