HR: 15:25h
AN: H13I-08    [Abstracts]
TI: Hierarchical and Adaptive Concepts in the Identification of Reaction Parameters in Multicomponent Reactive Transport Models
AU: * Knabner, P W
EM: knabner@am.uni-erlangen.de
AF: University of Erlangen-Nuremberg Department of Mathematics, Martensstrasse 3, Erlangen, D91054, Germany
AU: Blume, M
EM: blume@am.uni-erlangen.de
AF: University of Erlangen-Nuremberg Department of Mathematics, Martensstrasse 3, Erlangen, D91054, Germany
AB: Recent challenges like bioremediation, longterm underground storage of reactive waste or underground carbondioxide sequestration require more and more complex multicomponent reactive transport models. Athough being demanding concerning their efficient numericical approximation, the decisive bottleneck in using such models seems to lie in the availability of the increasing range of reaction parameters entering such a model (Monod parameters in multplicative Monod models in conjunction with bioremediation, rate parameters in kinetic mass action law models, ...). We address the reliable and accurate identification of such parameters from one of most controlled experimental set ups, namely from soil column breakthrough curves (letting the upscaling issue aside), but the following methology can also applied to field experiments. It is wellknown that the (missing) sensitivity and the correlation of parameters prevent a reliable reconstruction from naive history matching (output least squares minimization). For a fixed experimental setup we propose a systematic use of the singular values of the sensitivity matrix in the definition of the error functional to design an adaptive approach in which after each termination in a (local) minimum the error functional is changed. Applications to the identification of Monod parameters show significant improvements in possible accuracy. Furthermore this approach is combined with a hierarchical concept to filter out the most sensitive parameters and identify them first. In a further step these approaches can be used also within experimental design to find more appropriate sequences of experiments which can be taken into account into an multiexperiment identification approach.
DE: 0412 Biogeochemical kinetics and reaction modeling (0414, 0793, 1615, 4805, 4912)
DE: 0418 Bioremediation
DE: 1805 Computational hydrology
DE: 1846 Model calibration (3333)
DE: 1849 Numerical approximations and analysis
SC: Hydrology [H]
MN: 2007 Fall Meeting