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In the Upper Alento River Catchment (UARC; southern Italy), two test sites, having different physiographic and soil features, were instrumented with SoilNet wireless sensor networks controlling GS3 (METER Group, Inc. USA) capacitance sensors deployed at soil depths of 15 and 30 cm at twenty locations to monitor soil permittivity, soil temperature, and apparent electrical conductivity. The conversion of soil permittivity into soil water content is challenging given the high clay content of the soil. Therefore, the both factory and Topp’s calibration functions are compromising soil water content dynamics with underestimated dynamics during dry periods and overestimations in the wet season. In addition, the soil moisture measurements is influenced by the very strong soil temperature variations. In this study we combined a laboratory calibration with in-situ intensive validation campaigns. The laboratory calibration of GS3 electromagnetic sensors was carried out on repacked soil samples by simultaneously measuring soil permittivity and soil water content at prescribed temperature steps within the range observed in the field (from 4.5 °C and 31.9 °C). A new empirical regression-based calibration law was developed for the two study areas to relax the impact of soil temperature on the measurement of soil permittivity. The temperature-corrected approach was validated in the field by taking thermo-gravimetric measurements of soil water content using a stainless steel soil core sampler over five field campaigns at soil depths of 15 and 30 cm. Our results demonstrated that the proposed site-specific calibrations properly reflect the seasonal dynamics of observed soil water content and outperform both factory and Topp’s calibration functions.

Hydrological processes along mountain hillslopes involve complex interaction between soil storage and surface and subsurface flow, drainage and evapotranspiration. To capture this complexity, time-lapse extensive and intensive measurements are needed, potentially capable of providing spatially dense information in 3D and time frequent data. To this end, hydro-geophysical methods (ground penetration radar, GPR, electromagnetic induction, EMI and electrical resistivity tomography, ERT) based on electrical and electromagnetic laws are widely used as they naturally link to the electrical properties of soil moisture. ERT produces, especially in time lapse mode and using permanent installations, very detailed images of the water dynamics along hillslopes. While ERT requires galvanic contact with the ground, and thus relatively slow operations, EMI can be applied over large areas in a very short time. This method has been used for decades, mainly to produce apparent electrical conductivity (ECa) maps. Only recently, inversion of EMI data as a function of depth has become a viable practice.In this work, we present two cases of hillslope monitoring using non-invasive methods, both performed as part of the WATZON project, funded by the Italian Ministry of University and Research (MIUR). The first case is the Mediterranean catchment of the Alento River, in southern Italy. The monitoring was carried out using 7 different EMI surveys, acquired in multifrequency mode (FDEM) between August 2020 and December 2021. The purpose of this survey was to characterize the structure of the basin’s subsoil within the first few meters, as well as to record the variation of electrical conductivity (EC) associated with seasonal variations. The second case is related to the Apennines catchment of the Re Della Pietra, located at the border between Tuscany and Emilia-Romagna in central Italy. The monitoring was carried out through 6 different EMI surveys, acquired in multifrequency mode (FDEM) between August 2020 and May 2021. The purpose of this survey was to characterize the structure of the basin’s subsoil within the first few meters, as well as to record the variation of electrical conductivity (EC) associated with seasonal variations. Furthermore, ERT measurements were carried out along a fixed line on the ground, according to the direction of the maximum slope. The combination of EMI and ERT proved particularly effective in delineating the hydrologic dynamics of the hillslope.