Back to Search Start Over

Inverse Infiltration Modeling of Dike Covers Made of Dredged Material Using PEST and AMALGAM

Inverse Infiltration Modeling of Dike Covers Made of Dredged Material Using PEST and AMALGAM

Authors :
Tim Jurisch
Stefan Cantré
Fokke Saathoff
Source :
Geosciences, Vol 11, Iss 2, p 41 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

A variety of studies recently proved the applicability of different dried, fine-grained dredged materials as replacement material for erosion-resistant sea dike covers. In Rostock, Germany, a large-scale field experiment was conducted, in which different dredged materials were tested with regard to installation technology, stability, turf development, infiltration, and erosion resistance. The infiltration experiments to study the development of a seepage line in the dike body showed unexpected measurement results. Due to the high complexity of the problem, standard geo-hydraulic models proved to be unable to analyze these results. Therefore, different methods of inverse infiltration modeling were applied, such as the parameter estimation tool (PEST) and the AMALGAM algorithm. In the paper, the two approaches are compared and discussed. A sensitivity analysis proved the presumption of a non-linear model behavior for the infiltration problem and the Eigenvalue ratio indicates that the dike infiltration is an ill-posed problem. Although this complicates the inverse modeling (e.g., termination in local minima), parameter sets close to an optimum were found with both the PEST and the AMALGAM algorithms. Together with the field measurement data, this information supports the rating of the effective material properties of the applied dredged materials used as dike cover material.

Details

Language :
English
ISSN :
20763263
Volume :
11
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Geosciences
Publication Type :
Academic Journal
Accession number :
edsdoj.9dd49827649340e3a54a753d05d4d86a
Document Type :
article
Full Text :
https://doi.org/10.3390/geosciences11020041