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Complexity vs. Simplicity: Groundwater model ranking using information criteria

Engelhardt, Irina ; De Aguinaga, J. G. ; Mikat, Heiko ; Schüth, Christoph ; Liedl, R. (2014)
Complexity vs. Simplicity: Groundwater model ranking using information criteria.
In: Groundwater, 52 (4)
doi: 10.1111/gwat.12080
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

A groundwater model characterized by a lack of field data about hydraulic model parameters and boundary conditions combined with many observation data sets for calibration purpose was investigated concerning model uncertainty. Seven different conceptual models with a stepwise increase from 0 to 30 adjustable parameters were calibrated using PEST. Residuals, sensitivities, the Akaike information criterion (AIC and AICc), Bayesian information criterion (BIC), and Kashyap's information criterion (KIC) were calculated for a set of seven inverse calibrated models with increasing complexity. Finally, the likelihood of each model was computed. Comparing only residuals of the different conceptual models leads to an overparameterization and certainty loss in the conceptual model approach. The model employing only uncalibrated hydraulic parameters, estimated from sedimentological information, obtained the worst AIC, BIC, and KIC values. Using only sedimentological data to derive hydraulic parameters introduces a systematic error into the simulation results and cannot be recommended for generating a valuable model. For numerical investigations with high numbers of calibration data the BIC and KIC select as optimal a simpler model than the AIC. The model with 15 adjusted parameters was evaluated by AIC as the best option and obtained a likelihood of 98%. The AIC disregards the potential model structure error and the selection of the KIC is, therefore, more appropriate. Sensitivities to piezometric heads were highest for the model with only five adjustable parameters and sensitivity coefficients were directly influenced by the changes in extracted groundwater volumes.

Typ des Eintrags: Artikel
Erschienen: 2014
Autor(en): Engelhardt, Irina ; De Aguinaga, J. G. ; Mikat, Heiko ; Schüth, Christoph ; Liedl, R.
Art des Eintrags: Bibliographie
Titel: Complexity vs. Simplicity: Groundwater model ranking using information criteria
Sprache: Englisch
Publikationsjahr: Juli 2014
Verlag: Wiley-Blackwell
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Groundwater
Jahrgang/Volume einer Zeitschrift: 52
(Heft-)Nummer: 4
DOI: 10.1111/gwat.12080
URL / URN: http://www.ncbi.nlm.nih.gov/pubmed/23750914 http://doi.wiley...
Kurzbeschreibung (Abstract):

A groundwater model characterized by a lack of field data about hydraulic model parameters and boundary conditions combined with many observation data sets for calibration purpose was investigated concerning model uncertainty. Seven different conceptual models with a stepwise increase from 0 to 30 adjustable parameters were calibrated using PEST. Residuals, sensitivities, the Akaike information criterion (AIC and AICc), Bayesian information criterion (BIC), and Kashyap's information criterion (KIC) were calculated for a set of seven inverse calibrated models with increasing complexity. Finally, the likelihood of each model was computed. Comparing only residuals of the different conceptual models leads to an overparameterization and certainty loss in the conceptual model approach. The model employing only uncalibrated hydraulic parameters, estimated from sedimentological information, obtained the worst AIC, BIC, and KIC values. Using only sedimentological data to derive hydraulic parameters introduces a systematic error into the simulation results and cannot be recommended for generating a valuable model. For numerical investigations with high numbers of calibration data the BIC and KIC select as optimal a simpler model than the AIC. The model with 15 adjusted parameters was evaluated by AIC as the best option and obtained a likelihood of 98%. The AIC disregards the potential model structure error and the selection of the KIC is, therefore, more appropriate. Sensitivities to piezometric heads were highest for the model with only five adjustable parameters and sensitivity coefficients were directly influenced by the changes in extracted groundwater volumes.

Fachbereich(e)/-gebiet(e): 11 Fachbereich Material- und Geowissenschaften
11 Fachbereich Material- und Geowissenschaften > Geowissenschaften
11 Fachbereich Material- und Geowissenschaften > Geowissenschaften > Fachgebiet Hydrogeologie
Hinterlegungsdatum: 17 Apr 2018 12:36
Letzte Änderung: 19 Apr 2021 12:41
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