Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.240
IF5.240
IF 5-year value: 5.768
IF 5-year
5.768
CiteScore value: 8.9
CiteScore
8.9
SNIP value: 1.713
SNIP1.713
IPP value: 5.53
IPP5.53
SJR value: 3.18
SJR3.18
Scimago H <br class='widget-line-break'>index value: 71
Scimago H
index
71
h5-index value: 51
h5-index51
Volume 8, issue 3
Geosci. Model Dev., 8, 791–804, 2015
https://doi.org/10.5194/gmd-8-791-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 8, 791–804, 2015
https://doi.org/10.5194/gmd-8-791-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model experiment description paper 25 Mar 2015

Model experiment description paper | 25 Mar 2015

Optimization of model parameters and experimental designs with the Optimal Experimental Design Toolbox (v1.0) exemplified by sedimentation in salt marshes

J. Reimer1, M. Schuerch2, and T. Slawig1 J. Reimer et al.
  • 1Institute of Computer Science, Future Ocean – Kiel Marine Sciences, Christian-Albrechts-University Kiel, 24098 Kiel, Germany
  • 2Institute of Geography, Future Ocean – Kiel Marine Sciences, Christian-Albrechts-University Kiel, 24098 Kiel, Germany

Abstract. The geosciences are a highly suitable field of application for optimizing model parameters and experimental designs especially because many data are collected.

In this paper, the weighted least squares estimator for optimizing model parameters is presented together with its asymptotic properties. A popular approach to optimize experimental designs called local optimal experimental designs is described together with a lesser known approach which takes into account the potential nonlinearity of the model parameters. These two approaches have been combined with two methods to solve their underlying discrete optimization problem.

All presented methods were implemented in an open-source MATLAB toolbox called the Optimal Experimental Design Toolbox whose structure and application is described.

In numerical experiments, the model parameters and experimental design were optimized using this toolbox. Two existing models for sediment concentration in seawater and sediment accretion on salt marshes of different complexity served as an application example. The advantages and disadvantages of these approaches were compared based on these models.

Thanks to optimized experimental designs, the parameters of these models could be determined very accurately with significantly fewer measurements compared to unoptimized experimental designs. The chosen optimization approach played a minor role for the accuracy; therefore, the approach with the least computational effort is recommended.

Please read the corrigendum first before accessing the article.
Publications Copernicus
Download
Notice on corrigendum

The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.

Short summary
Model parameters are usually optimized based on measurements. These measurements are often time-consuming or costly. The conditions under which theses measurements are carried out, also called experimental designs, can be optimized so that with minimum effort and cost a maximum accuracy can be achieved. For this, we present different approaches together with their implementation in an MATLAB toolbox. We demonstrate their application to different models for sedimentation in salt marshes.
Model parameters are usually optimized based on measurements. These measurements are often...
Citation