The Impact of Groundwater Model Parametrization on Calibration Fit and Prediction Accuracy—Assessment in the Form of a Post-Audit at the SLOVNAFT Oil Refinery Site, in Slovakia
The present work is focused on the effect of increasing model complexity on calibration fit and prediction accuracy. Groundwater flow was numerically simulated at a field site with a hydraulic groundwater protection system in operation with many pumping and observation wells at the site of the Slovn...
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MDPI AG
2023-02-01
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| Online Access: | https://www.mdpi.com/2073-4441/15/5/839 |
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| author | Martin Zatlakovič Dávid Krčmář Kamila Hodasová Ondra Sracek Štefan Marenčák Ľubica Durdiaková Alexander Bugár |
| author_facet | Martin Zatlakovič Dávid Krčmář Kamila Hodasová Ondra Sracek Štefan Marenčák Ľubica Durdiaková Alexander Bugár |
| author_sort | Martin Zatlakovič |
| collection | DOAJ |
| description | The present work is focused on the effect of increasing model complexity on calibration fit and prediction accuracy. Groundwater flow was numerically simulated at a field site with a hydraulic groundwater protection system in operation with many pumping and observation wells at the site of the Slovnaft refinery in southwestern Slovakia. The adjusted parameters during the calibration included hydraulic conductivity, as well as recharge, evapotranspiration, and riverbed conductance. Four model scenarios were built (V1–V4) within the model calibration for the conditions in the year 2008, with increasing complexity mainly within artificial K-field zonation, which was created and step-wise upgraded based on groundwater head residuals’ distribution. Selected descriptive statistics were evaluated together with chosen information criteria after the models were calibrated. Subsequently, the real predictive accuracy of individual calibrated scenarios was evaluated for conditions in the year 2019 in the form of a post-audit. Within the overall evaluation, the calibration fit increased with increased parameterization complexity. However, the Akaike information criterion, corrected Akaike information criterion, and Bayesian information criterion detected opposite trends for model predictability. A post-audit of prediction accuracy revealed a significant improvement of the V2, V3, and V4 scenarios against the simplest V1 scenario. However, among the V2–V4 scenarios, the degree of prediction accuracy improvement was almost insignificant. The level of effort spent on V3 and V4 parameterization seems disproportionate to the benefit of a negligible improvement in prediction accuracy. Groundwater flow path analysis showed that similarly successful scenarios (measured by prediction accuracy) can generate very different groundwater pathlines. |
| first_indexed | 2024-03-11T07:06:51Z |
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| last_indexed | 2024-03-11T07:06:51Z |
| publishDate | 2023-02-01 |
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| series | Water |
| spelling | doaj.art-b6e7b61ccf1d48d3ab8033aaf9bed8242023-11-17T08:53:42ZengMDPI AGWater2073-44412023-02-0115583910.3390/w15050839The Impact of Groundwater Model Parametrization on Calibration Fit and Prediction Accuracy—Assessment in the Form of a Post-Audit at the SLOVNAFT Oil Refinery Site, in SlovakiaMartin Zatlakovič0Dávid Krčmář1Kamila Hodasová2Ondra Sracek3Štefan Marenčák4Ľubica Durdiaková5Alexander Bugár6Department of Engineering Geology, Hydrogeology and Applied Geophysics, Faculty of Natural Science, Comenius University in Bratislava, Ilkovičova 3278/6, 84215 Bratislava, SlovakiaDepartment of Engineering Geology, Hydrogeology and Applied Geophysics, Faculty of Natural Science, Comenius University in Bratislava, Ilkovičova 3278/6, 84215 Bratislava, SlovakiaDepartment of Engineering Geology, Hydrogeology and Applied Geophysics, Faculty of Natural Science, Comenius University in Bratislava, Ilkovičova 3278/6, 84215 Bratislava, SlovakiaDepartment of Geology, Faculty of Science, Palacký University Olomouc, 17. listopadu 1192/12, 771 46 Olomouc, Czech RepublicVÚRUP, a.s., Vlčie Hrdlo, P.O. Box 50, 82003 Bratislava, SlovakiaVÚRUP, a.s., Vlčie Hrdlo, P.O. Box 50, 82003 Bratislava, SlovakiaDepartment of Engineering Geology, Hydrogeology and Applied Geophysics, Faculty of Natural Science, Comenius University in Bratislava, Ilkovičova 3278/6, 84215 Bratislava, SlovakiaThe present work is focused on the effect of increasing model complexity on calibration fit and prediction accuracy. Groundwater flow was numerically simulated at a field site with a hydraulic groundwater protection system in operation with many pumping and observation wells at the site of the Slovnaft refinery in southwestern Slovakia. The adjusted parameters during the calibration included hydraulic conductivity, as well as recharge, evapotranspiration, and riverbed conductance. Four model scenarios were built (V1–V4) within the model calibration for the conditions in the year 2008, with increasing complexity mainly within artificial K-field zonation, which was created and step-wise upgraded based on groundwater head residuals’ distribution. Selected descriptive statistics were evaluated together with chosen information criteria after the models were calibrated. Subsequently, the real predictive accuracy of individual calibrated scenarios was evaluated for conditions in the year 2019 in the form of a post-audit. Within the overall evaluation, the calibration fit increased with increased parameterization complexity. However, the Akaike information criterion, corrected Akaike information criterion, and Bayesian information criterion detected opposite trends for model predictability. A post-audit of prediction accuracy revealed a significant improvement of the V2, V3, and V4 scenarios against the simplest V1 scenario. However, among the V2–V4 scenarios, the degree of prediction accuracy improvement was almost insignificant. The level of effort spent on V3 and V4 parameterization seems disproportionate to the benefit of a negligible improvement in prediction accuracy. Groundwater flow path analysis showed that similarly successful scenarios (measured by prediction accuracy) can generate very different groundwater pathlines.https://www.mdpi.com/2073-4441/15/5/839numerical modelingmodel predictabilitycalibrationpredictioninformation criteria |
| spellingShingle | Martin Zatlakovič Dávid Krčmář Kamila Hodasová Ondra Sracek Štefan Marenčák Ľubica Durdiaková Alexander Bugár The Impact of Groundwater Model Parametrization on Calibration Fit and Prediction Accuracy—Assessment in the Form of a Post-Audit at the SLOVNAFT Oil Refinery Site, in Slovakia Water numerical modeling model predictability calibration prediction information criteria |
| title | The Impact of Groundwater Model Parametrization on Calibration Fit and Prediction Accuracy—Assessment in the Form of a Post-Audit at the SLOVNAFT Oil Refinery Site, in Slovakia |
| title_full | The Impact of Groundwater Model Parametrization on Calibration Fit and Prediction Accuracy—Assessment in the Form of a Post-Audit at the SLOVNAFT Oil Refinery Site, in Slovakia |
| title_fullStr | The Impact of Groundwater Model Parametrization on Calibration Fit and Prediction Accuracy—Assessment in the Form of a Post-Audit at the SLOVNAFT Oil Refinery Site, in Slovakia |
| title_full_unstemmed | The Impact of Groundwater Model Parametrization on Calibration Fit and Prediction Accuracy—Assessment in the Form of a Post-Audit at the SLOVNAFT Oil Refinery Site, in Slovakia |
| title_short | The Impact of Groundwater Model Parametrization on Calibration Fit and Prediction Accuracy—Assessment in the Form of a Post-Audit at the SLOVNAFT Oil Refinery Site, in Slovakia |
| title_sort | impact of groundwater model parametrization on calibration fit and prediction accuracy assessment in the form of a post audit at the slovnaft oil refinery site in slovakia |
| topic | numerical modeling model predictability calibration prediction information criteria |
| url | https://www.mdpi.com/2073-4441/15/5/839 |
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