Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/C066D3FD-F864-47CD-9002-0740DA77C7EB | ||
| Year | 2019 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
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| Bibliographic Citation | I. Matiatos, E.A. Varouchakis and M.P. Papadopoulou, "Performance evaluation of multiple groundwater flow and nitrate mass transport numerical models," Environ. Model. Assess., vol. 24, no. 6, pp. 659-675, Dec. 2019. doi: 10.1007/s10666-019-9653-7 https://doi.org/10.1007/s10666-019-9653-7 | ||
| Appears in Collections |
Benchmarking of different numerical models simulating groundwater flow and contaminant mass transport is the aim of the present study, in order to determine criteria for the selection of numerical model(s) that could be better tailored to the needs of a specific region. This analysis aims at evaluating the performance of a finite difference-based numerical model (MODFLOW-ΜΤ3DMS), a finite element-based numerical model (FEFLOW), and a hybrid finite element-finite difference coupling numerical model (Princeton Transport Code-PTC), all developed to simulate groundwater flow and nitrate mass transport in an alluvial aquifer. The evaluation of the models’ performance is assessed based on statistical measures and graphical performance analysis of the model point predictions to the observed values. The outcome of the analysis showed that among the three groundwater simulation models, FEFLOW algorithm exhibited the best performance in simulating both groundwater level and nitrate mass distribution. All simulation algorithms were found to offer different advantages, so in principle the selection of the appropriate model(s) should be done in accordance with the problem’s characteristics and/ or in a complementary way in order to achieve accurate representation of the aquifer system and thus optimal groundwater resources management. Even though the selection of the most suitable groundwater simulation algorithm is case-oriented, however, fractional gross error (FGE) was proven to be a reliable indicator that could be used by modelers to select the most suitable groundwater algorithm based on the available groundwater data.
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