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Multivariate geostatistical modelling of geotechnical characteristics of the alluvial deposits in West Thessaly, Greece

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Abstract

Land subsidence due to ground-water overexploitation in the Western Thessaly basin resulted in the manifestation of ground deformations. In order to investigate the mechanism of this phenomenon, borehole data regarding geomechanical properties of soil were examined. Based on these data, the spatial variability of soil compression index (Cc) was evaluated in relation to other geotechnical parameters, by means of multivariate geostatistics. Multivariate statistics and geostatistics were combined and compared to evaluate the estimation methods of Cc. Principal component analysis (PCA) was applied in order to highlight the relationships between the geotechnical parameters. Through cross-validation, multiple linear regression, kriging and cokriging were tested as estimators of the Cc. The results show that spatial correlation of the target variable is less important than its correlation to the auxiliary variables. Cross-validation demonstrates that kriging with two PCA factors and application of inverse transform gives the best results for Cc estimates.

Résumé

Affaissement de terrain en raison de la surexploitation des eaux souterraines dans le bassin de la Thessalie occidentale, abouti à la manifestation de déformations de terrain. Afin d'étudier la mécanisme de ce phénomène, des données concernant les propriétés géomécaniques des forages du sol ont été examinés. Sur la base de ces données, la variabilité spatiale de la compression index (Cc) du sol est évaluée par rapport à d'autres paramètres géotechniques, au moyen de la géostatistique multivariée. Statistiques et géostatistiques multivariées ont été combinés et comparés afin d'évaluer la méthode d'estimation de Cc. Analyse en Composantes Principales (PCA) a été appliquée afin de mettre en évidence les relations entre les paramètres géotechniques. Grâce validation croisée, régression linéaire multiple, krigeage et cokrigeage ont été testés comme estimateurs de Cc. Les résultats montrent que la corrélation spatiale de variable cible est moins importante que sa corrélation avec les variables auxiliaires. Cross-validation démontre que le krigeage avec deux facteurs de l'APC et de l'application de la transformée inverse donne les meilleurs résultats pour Cc estimations.

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Acknowledgments

The authors acknowledge Edafos S.A., Ferrovial Agroman S.A. and HellasLab for the supply of all necessary borehole data for the analysis.

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Authors and Affiliations

  1. School of Mining and Metallurgical Engineering, National Technical University of Athens, 9 Heroon Polytechniou St, 15780, Athens, Greece

    D. Sideri, K. Modis & D. Rozos

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  1. D. Sideri
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  2. K. Modis
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  3. D. Rozos
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Correspondence to D. Sideri.

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Sideri, D., Modis, K. & Rozos, D. Multivariate geostatistical modelling of geotechnical characteristics of the alluvial deposits in West Thessaly, Greece. Bull Eng Geol Environ 73, 709–722 (2014). https://doi.org/10.1007/s10064-013-0568-2

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