Groundwater level simulation using gene expression programming and M5 model tree combined with wavelet transform.

Bahmani, Ramin; Solgi, Abazar et Ouarda, Taha B. M. J. ORCID: https://orcid.org/0000-0002-0969-063X (2020). Groundwater level simulation using gene expression programming and M5 model tree combined with wavelet transform. Hydrological Sciences Journal , vol. 65 , nº 8. pp. 1430-1442. DOI: 10.1080/02626667.2020.1749762.

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Résumé

In order to understand and adequately manage hydrological stress, it is necessary to simulate groundwater levels accurately. In this research, gene expression programming (GEP) and M5 model tree (M5) are used to simulate monthly groundwater levels. The models are combined with wavelet transform to produce two hybrid models: wavelet gene expression programming (WGEP) and wavelet M5 model tree (WM5). For the simulation, groundwater level, temperature and precipitation values from three observation wells and one meteorological station, located in Iran, are used. The results indicate that the hybrid models, WGEP and WM5, lead to a better performance than the simple models, GEP and M5. The performance of the two hybrid models is similar. It is also observed that selecting a suitable time lag for inputs plays an important role in the accuracy of the simple models. The selection of a suitable decomposition level strongly affects the accuracy of hybrid models.

Type de document:	Article
Mots-clés libres:	groundwater level; gene expression programming; hybrid model; M5 model tree; wavelet transform
Centre:	Centre Eau Terre Environnement
Date de dépôt:	24 juill. 2020 13:33
Dernière modification:	15 févr. 2022 20:32
URI:	https://espace.inrs.ca/id/eprint/10336

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