GNGTS 2019 - Atti del 38° Convegno Nazionale

720 GNGTS 2019 S essione 3.2 extreme events. So far, the water level has been under the thresholds of interest, except for one small flood event, so data have always experimented the same 3D effect. So far, for studying variations in time-lapse data, we did not correct the data, since in differences between different days the common 3D effects are removed. 3D effect removing algorithm was developed in order to correct data if the boundary conditions change. Furthermore, when converting resistivity images to water content maps, it is important to correct the data to obtain real values. So far apparent resistivity pseudosections are individually inverted with Res2dinv (Loke, 2018), using the L2-norm option. Time changes in inverted resistivity sections are studied taking into account weather datasets. The aim is to analyse the response of the levee body to rainfall events and changes in temperature. An example of data variability with rainfall is shown in Fig. 3, corresponding to the variations in resistivity due to change in soil water content due to a rainy Fig. 3 - a) Time-intensity graph of rainfall registered by the meteorological station for the period 1April – 1 June 2019, red arrows indicate the two selected days; b) inverted section of 1 April 2019 dataset; c) inverted section of 1 June 2019 dataset; d) variation in soil resistivity between 1 April and 1 June 2019.