Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.153
IF5.153
IF 5-year value: 5.460
IF 5-year
5.460
CiteScore value: 7.8
CiteScore
7.8
SNIP value: 1.623
SNIP1.623
IPP value: 4.91
IPP4.91
SJR value: 2.092
SJR2.092
Scimago H <br class='widget-line-break'>index value: 123
Scimago H
index
123
h5-index value: 65
h5-index65
Preprints
https://doi.org/10.5194/hess-2020-323
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2020-323
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  22 Sep 2020

22 Sep 2020

Review status
This preprint is currently under review for the journal HESS.

A Wavelet-Based Approach to Streamflow Event Identification and Modeled Timing Error Evaluation

Erin Towler and James L. McCreight Erin Towler and James L. McCreight
  • National Center for Atmospheric Research (NCAR), P.O. Box 3000, Boulder, CO 80307

Abstract. Streamflow timing errors (in the units of time) are rarely explicitly evaluated, but are useful for model evaluation and development. Wavelet-based approaches have been shown to reliably quantify timing errors in streamflow simulations, but have not been applied in a systematic way that is suitable for model evaluation. This paper provides a step-by-step methodology that objectively identifies events, and then estimates timing errors for those events, in a way that can be applied to large-sample, high-resolution predictions. Step 1 applies the wavelet transform to the observations, and uses statistical significance to identify observed events. Step 2 utilizes the cross-wavelet transform to calculate the timing errors for the events identified in Step 1. The approach also includes a quantification of the confidence in the timing error estimates. The methodology is illustrated using real and simulated stream discharge data from several locations to highlight key method features. The method groups event timing errors by dominant timescales, which can be used to identify the potential processes contributing to the timing errors and the associated model development needs. For instance, timing errors that are associated with the diurnal melt cycle are identified. The method is also useful for documenting and evaluating model performance in terms of defined standards. This is illustrated by showing version-over-version performance of the National Water Model (NWM) in terms of timing errors.

Erin Towler and James L. McCreight

Interactive discussion

Status: open (until 17 Nov 2020)
Status: open (until 17 Nov 2020)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Erin Towler and James L. McCreight

Erin Towler and James L. McCreight

Viewed

Total article views: 260 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
219 38 3 260 14 4 6
  • HTML: 219
  • PDF: 38
  • XML: 3
  • Total: 260
  • Supplement: 14
  • BibTeX: 4
  • EndNote: 6
Views and downloads (calculated since 22 Sep 2020)
Cumulative views and downloads (calculated since 22 Sep 2020)

Viewed (geographical distribution)

Total article views: 220 (including HTML, PDF, and XML) Thereof 219 with geography defined and 1 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 26 Oct 2020
Publications Copernicus
Download
Citation