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Effective techniques for spatial data analysis are required to address the growing need to develop and improve management plans at regional or continental scales. The main purpose of this research is to evaluate the impact of change of spatial support on digital soil mapping. The study is based on the availability of more than 3,300 soil samples collected from the uppermost horizons of farmlands in Campania, an administrative region of southern Italy of about 13,700 km2. Each soil sample was subjected to laboratory tests to determine the following point-referenced primary soil properties: sand and clay contents, oven-dry soil bulk density, soil organic matter, pH, calcium carbonate, and rock fragments. These seven soil properties were mapped over the entire region by using as covariates the following terrain attributes, obtained from the digital terrain model (DTM; 75 m/pixel): elevation, slope, plan curvature, profile curvature, and flow accumulation. Two composite indicators of soil quality were then determined: 1) the soil organic carbon stock (SOCS) in Campania, and 2) the recharge transit time in the alluvial plain of the Sele River where information about the mean annual depth to groundwater is available.In this study, it was crucial to evaluate the epistemic uncertainty associated with the change of support when fusing the point-referenced soil measurements with the block-based terrain attributes. A key issue of our analysis is the modification of the anamorphosis model based on a block rather than a point. Accordingly, our results show how the estimates change when a properly-corrected block Gaussian anamorphosis model is employed instead of the point Gaussian one.By way of conclusion, when the main interest of an investigation is to obtain a map of average soil attributes, the change of support might have little influence on the final estimates, especially when working with nearly symmetrical distributions of soil properties. On the other hand, if one should infer the uncertainty of a variable, as in soil vulnerability mapping, then the change of support matters and is an issue to be adequately accounted for in the spatial analysis of environmental data.

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.

Bioavailability of some major and trace elements was evaluated in 1,993 topsoil samples collected across Campania region (Southern Italy). A main focus was made on Al, Ca, K, Mg, Cu, Tl since they are linked, for different reasons, to agriculture. Bioavailability was assessed by an extraction with ammonium nitrate and the data were compared with the pseudo-total concentration determined by Aqua Regia digestion. Geochemical maps of the pseudo-total and bioavailable concentrations were generated using a multifractal inverse distance weighted (MIDW) interpolation. In addition, the spatial distribution patterns of the percent bioavailability of elements, based on the ratio among bioavailable and the pseudo-total fractions, were also determined. The median value of the percent bioavailability showed the order Ca > K >> Mg. Tl >> Cu >> Al and it represents a positive finding in terms of both agricultural productivity and environmental quality. Further, a multiple linear regression was finally applied to data to unveil any dependence of the bioavailable fraction on the pseudo-total content of elements. The grain size distribution and organic matter content of samples were later included to evaluate their possible role in promoting the environmental availability of elements. The pseudo-total concentrations of Al, Ca, K, and Mg alone resulted to be poorly able to predict the variability of the bioavailable fraction. The addition of the grain size distribution and organic matter content to the models expanded the predictive capability of Ca, K, and Mg whereas a marginal improvement was showed by Al, Cu, and Tl. This study represents a methodological contribution to a better understanding of the processes underlying the spatial variability of chemical elements in soil. Considering the positive outcomes obtained, further researches were planned to include more variables (e.g. soil pH, redox potential, content in Iron and Manganese oxides, etc.) in the predictive models. Istituto Zooprofilattico Sperimentale del Mezzogiorno (IZSM); University of Napoli Federico II; Campania Trasparente - Attivita di monitoraggio integrato per la Regione Campania; Dipartimento di Scienze della Terra, dell'Ambiente e delle Risorse (DiSTAR); Fondo per le Misure Anticiliche e la Salvaguardia dell'Occupazione - Azione B4 ?Mappatura del Territorio"; [Del.G.R. n. 497/2013] Published version The work has been supported by the Istituto Zooprofilattico Sperimentale del Mezzogiorno (IZSM) by means of the Contract with the Dipartimento di Scienze della Terra, dell'Ambiente e delle Risorse (DiSTAR), University of Napoli Federico II in the framework of the "Campania Trasparente - Attivita di monitoraggio integrato per la Regione Campania" Project funded in the framework of Del.G.R. n. 497/2013: Fondo per le Misure Anticiliche e la Salvaguardia dell'Occupazione - Azione B4 ?Mappatura del Territorio" approved with Executive Decree DG "Sviluppo Economico" n.585, September 14, 2015 (Research Unit Responsibles: Prof. B. De Vivo, Prof. Stefano Albanese).

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.