Inclinometer and piezometer measurements have been carried out since 2005 in a slow active earthflow in a clay shale formation of the Italian Southern Apennines. Previous studies outlined the main geometrical and kinematic features of the landslide and the pore pressure response to rainfall. Displacement rates seem to depend on the hydrological conditions as suggested by their seasonal variations. The availability of long time series of data, in some periods recorded in continuum, allows the use of a data mining approach to evaluate the relations among displacement rates in different points of the landslide, and between displacement rates and rainfall. To define such relations, the evolutionary modelling technique EPRMOGA, based on a genetic algorithm, has been used in this paper. The results give a deeper insight into the landslide behaviour on the one hand and, on the other hand, show the reliability of the technique, also in building up management scenarios. In particular, the results show that the landslide displacement rates in different points of the slip surface, although characterized by different values, are linearly dependent and thus have the same time trend, supporting the hypothesis of a constant soil discharge mechanism of movement. Piezometric data in single points cannot be used, in the considered case, to forecast displacements. The obtained relations allow to quantify the displacement rate variations due to contemporary rainfall. The influence of past rainfall is shown to decrease exponentially with temporal distance. Furthermore, the EPRMOGA simulations seem to confirm that there are no other dominant causes, besides rainfall, responsible of displacement rate variations in time.

Relationships between rain and displacements of an active earthflow: a data-driven approach by EPRMOGA

VASSALLO, ROBERTO;Grimaldi, G. M.;DI MAIO, Caterina;
2016

Abstract

Inclinometer and piezometer measurements have been carried out since 2005 in a slow active earthflow in a clay shale formation of the Italian Southern Apennines. Previous studies outlined the main geometrical and kinematic features of the landslide and the pore pressure response to rainfall. Displacement rates seem to depend on the hydrological conditions as suggested by their seasonal variations. The availability of long time series of data, in some periods recorded in continuum, allows the use of a data mining approach to evaluate the relations among displacement rates in different points of the landslide, and between displacement rates and rainfall. To define such relations, the evolutionary modelling technique EPRMOGA, based on a genetic algorithm, has been used in this paper. The results give a deeper insight into the landslide behaviour on the one hand and, on the other hand, show the reliability of the technique, also in building up management scenarios. In particular, the results show that the landslide displacement rates in different points of the slip surface, although characterized by different values, are linearly dependent and thus have the same time trend, supporting the hypothesis of a constant soil discharge mechanism of movement. Piezometric data in single points cannot be used, in the considered case, to forecast displacements. The obtained relations allow to quantify the displacement rate variations due to contemporary rainfall. The influence of past rainfall is shown to decrease exponentially with temporal distance. Furthermore, the EPRMOGA simulations seem to confirm that there are no other dominant causes, besides rainfall, responsible of displacement rate variations in time.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11563/115020
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