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Comparison of a black-box model to a traditional numerical model for hydraulic head prediction

Tapoglou Evdokia, Chatzakis Alexandros, Karatzas Giorgos

Απλή Εγγραφή


URIhttp://purl.tuc.gr/dl/dias/41E97DD5-5D86-48C0-BCCE-9499E876D205-
Αναγνωριστικόhttps://journal.gnest.org/journal-paper/comparison-black-box-model-traditional-numerical-model-hydraulic-head-prediction-
Αναγνωριστικόhttps://doi.org/10.30955/gnj.002002-
Γλώσσαen-
Μέγεθος10 pagesen
ΤίτλοςComparison of a black-box model to a traditional numerical model for hydraulic head predictionen
ΔημιουργόςTapoglou Evdokiaen
ΔημιουργόςΤαπογλου Ευδοκιαel
ΔημιουργόςChatzakis Alexandrosen
ΔημιουργόςΧατζακης Αλεξανδροςel
ΔημιουργόςKaratzas Giorgosen
ΔημιουργόςΚαρατζας Γιωργοςel
ΕκδότηςGlobal NESTen
ΠερίληψηTwo different methodologies for hydraulic head simulation were compared in this study. The first methodology is a classic numerical groundwater flow simulation model, Princeton Transport Code (PTC), while the second one is a black-box approach that uses Artificial Neural Networks (ANNs). Both methodologies were implemented in the Bavaria region in Germany at thirty observation wells. When using PTC, meteorological and geological data are used in order to compute the simulated hydraulic head following the calibration of the appropriate model parameters. The ANNs use meteorological and hydrological data as input parameters. Different input parameters and ANN architectures were tested and the ANN with the best performance was compared with the PTC model simulation results. One ANN was trained for every observation well and the hydraulic head change was simulated on a daily time step. The performance of the two models was then compared based on the real field data from the study area. The cases in which one model outperforms the other were summarized, while the use of one instead of the other depends on the application and further use of the model.en
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2018-07-02-
Ημερομηνία Δημοσίευσης2016-
Θεματική ΚατηγορίαArtificial neural networken
Θεματική ΚατηγορίαGroundwater modelingen
Θεματική ΚατηγορίαHydraulic head change simulationen
Θεματική ΚατηγορίαPrinceton transport codeen
Βιβλιογραφική ΑναφοράE. Tapoglou, A. Chatzakis and G. P. Karatzas, "Comparison of a black-box model to a traditional numerical model for hydraulic head prediction," Global Nest J., vol. 18, no. 4, pp. 761-770, Dec. 2016. doi: 10.30955/gnj.002002 en

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