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@ARTICLE{Engelhardt:155363,
      author       = {Engelhardt, I. and De Aguinaga, J. G. and Mikat, H. and
                      Schüth, C. and Liedl, R.},
      title        = {{C}omplexity vs. {S}implicity: {G}roundwater {M}odel
                      {R}anking {U}sing {I}nformation {C}riteria},
      journal      = {Ground water},
      volume       = {52},
      number       = {4},
      issn         = {0017-467X},
      address      = {Oxford [u.a.]},
      publisher    = {Wiley-Blackwell},
      reportid     = {FZJ-2014-04532},
      pages        = {573 - 583},
      year         = {2014},
      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.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {246 - Modelling and Monitoring Terrestrial Systems: Methods
                      and Technologies (POF2-246) / 255 - Terrestrial Systems:
                      From Observation to Prediction (POF3-255)},
      pid          = {G:(DE-HGF)POF2-246 / G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000339509600012},
      pubmed       = {pmid:23750914},
      doi          = {10.1111/gwat.12080},
      url          = {https://juser.fz-juelich.de/record/155363},
}