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-2019-639
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2019-639
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  20 Dec 2019

20 Dec 2019

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

A time-varying parameter estimation approach using split-sample calibration based on dynamic programming

Xiaojing Zhang1,2 and Pan Liu1,2 Xiaojing Zhang and Pan Liu
  • 1State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
  • 2Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University

Abstract. Although the parameters of hydrological models are usually regarded as constant, temporal variations can occur in a changing environment. Thus, effectively estimating time-varying parameters becomes a significant challenge. Following a survey of existing estimation methodologies, this paper describes a new method that combines (1) the basic concept of split-sample calibration (SSC), whereby parameters are assumed to be stable for one sub-period, and (2) the parameter continuity assumption, i.e., the differences between parameters in consecutive time steps are small. Dynamic programming is then used to determine the optimal parameter trajectory by considering two objective functions: maximization of simulation accuracy and maximization of parameter continuity. The efficiency of the proposed method is evaluated by two synthetic experiments, one with a simple two-parameter monthly model and the second using a more complex 15-parameter daily model. The results show that the proposed method is superior to SSC alone, and outperforms the ensemble Kalman filter if the proper sub-period length is used. An application to the Wuding River basin indicates that the soil water capacity parameter varies before and after 1972, which can be interpreted according to land use and land cover changes. Further application to the Xun River basin shows that parameters are generally stationary on an annual scale, but exhibit significant changes over seasonal scales. These results demonstrate that the proposed method is an effective tool for identifying time-varying parameters in a changing environment.

Xiaojing Zhang and Pan Liu

Interactive discussion

Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Login for Authors/Editors] [Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Xiaojing Zhang and Pan Liu

Xiaojing Zhang and Pan Liu

Viewed

Total article views: 685 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
544 121 20 685 27 28
  • HTML: 544
  • PDF: 121
  • XML: 20
  • Total: 685
  • BibTeX: 27
  • EndNote: 28
Views and downloads (calculated since 20 Dec 2019)
Cumulative views and downloads (calculated since 20 Dec 2019)

Viewed (geographical distribution)

Total article views: 483 (including HTML, PDF, and XML) Thereof 478 with geography defined and 5 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 28 Sep 2020
Publications Copernicus
Download
Short summary
Rainfall-runoff models are useful tools for streamflow simulation, however, efforts are needed to investigate how their parameters vary in response to climate changes and human activities. Thus, this study proposes a new method for estimating time-varying parameters, by considering both simulation accuracy and parameter continuity. The results show the proposed method is more effective for identifying temporal variations of parameters, and can simultaneously provide good streamflow simulation.
Rainfall-runoff models are useful tools for streamflow simulation, however, efforts are needed...
Citation