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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.

The stable isotope composition of water (δ18O and δ2H) represents a useful tool to distinguish among different water pools along the soil-plant-atmosphere continuum. Using δ2H and δ18O as tracers helps gain a better understanding of plant root water uptake and dominant ecohydrological processes. To determine which pools of water are used for plant physiologic functions and returned to the atmosphere by transpiration, a common approach is to analyze the isotopic composition of water in both soil and plant. Cryogenic water extraction (CWE; Orlowski et al., 2016) is the most widely used laboratory-based technique to extract water from soil samples for isotopic analysis. However, recent studies have shown that the extraction conditions (time, temperature, and vacuum) and soil physical and chemical properties may affect the extracted soil-water isotope composition even significantly.We have developed an efficient and cost-effective cryogenic vacuum equipment to extract water from soil or vegetation and this presentation aims at discussing some preliminary results. The equipment has been specifically designed to meet the following requirements: i) enable to quantify the accuracy of a CWE continuous flow extraction line, and ii) identify a specific extraction standard protocol for soil and vegetation samples. Two experiments have been carried out to evaluate the isotope fractionation induced by the system and how different operational parameters (i.e. times and temperature of extraction) can affect the results. Firstly, a known water isotopic ratio was processed by the vacuum system to determine the measurement accuracy and reproducibility by comparing pre- and post-processed water isotopic signatures. The likely causes of observed biases induced by sample processing are assessed and a relevant correction procedure is suggested. Subsequently, measurements were carried out on replicated samples taken from two differently-textured soils that, after being dried, were saturated in the laboratory up to different water content values with water of known isotopic composition. Also, plant samples were collected from plants grown in a greenhouse and irrigated with water of known isotopic composition.Water from all samples was extracted by our CWE system and then analyzed using an isotope ratio mass spectrometer in Gas Bench mode for analyses and in temperature conversion elemental analysis (TC/EA) mode for. Preliminary results have quantified the isotope fractions on average of -1.6 ‰ for δ18O and 14.2 ‰ for δ2H. Normalization of stable isotopes from unknown samples according to observed fractionation has enabled the observed bias to become virtually zero, leading to a replicate reproducibility of δ18O and δ2H for soil water of 0.6 ‰ and 3 ‰, respectively. The analyses carried out up to now did not find statistical evidence that the soil types and soil-water contents may affect the extraction method and the accuracy of our protocol.

The Italian initiative WATZON (WATer mixing in the critical ZONe) is a network of instrumented sites, bringing together six pre-existing long-term research observatories monitoring different compartments of the Critical Zone - the Earth's permeable near-surface layer from the tops of the trees to the bottom of the groundwater. These observatories cover different climatic and physiographic characteristics over the country, providing information over a climate and eco-hydrologic transect connecting the Mediterranean to the Alps. With specific initial scientific questions, monitoring strategies, databases, and modeling activities, the WATZON observatories and sites is well representative of the heterogeneity of the critical zone and of the scientific communities studying it. Despite this diversity, all WATZON sites share a common eco-hydrologic monitoring and modelling program with three main objectives:1) assessing the description of water mixing process across the critical zone by using integrated high-resolution isotopic, geophysical and hydrometeorological measurements from point to catchment scale, under different physiographic conditions and climate forcing;2) testing water exchange mechanisms between subsurface reservoirs and vegetation, and assessing ecohydrological dynamics in different environments by coupling the high-resolution data set from different critical zone study sites of the initiative with advanced ecohydrological models at multiple spatial scales;3) developing a process-based conceptual framework of ecohydrological processes in the critical zone to translate scientific knowledge into evidence to support policy and management decisions concerning water and land use in forested and agricultural ecosystems.This work provides an overview of the WATZON network, its objectives, scientific questions, and data management, with a specific focus on existing initiatives for linking data and models based on WATZON data.

The stable isotope composition of water (δ18O and δ2H) represents a useful tool to distinguish among different water pools along the soil-plant-atmosphere continuum. Using δ2H and δ18O as tracers helps gain a better understanding of plant root water uptake and dominant ecohydrological processes. To determine which pools of water are used for plant physiologic functions and returned to the atmosphere by transpiration, a common approach is to analyze the isotopic composition of water in both soil and plant. Cryogenic water extraction (CWE; Orlowski et al., 2016) is the most widely used laboratory-based technique to extract water from soil samples for isotopic analysis. However, recent studies have shown that the extraction conditions (time, temperature, and vacuum) and soil physical and chemical properties may affect the extracted soil water isotope composition even significantly. We have developed an efficient and cost-effective cryogenic vacuum equipment to extract water from soil or vegetation and this presentation aims at discussing some preliminary results. The equipment has been specifically designed to meet the following requirements: i) enable to quantify the accuracy of a CWE continuous flow extraction line, and ii) identify a specific extraction standard protocol for soil and vegetation samples. Two experiments have been carried out to evaluate the isotope fractionation induced by the system and how different operational parameters (i.e. times and temperature of extraction) can affect the results. Firstly, a known water isotopic ratio was processed by the vacuum system to determine the measurement accuracy and reproducibility by comparing pre- and post-processed water isotopic signatures. The likely causes of observed biases induced by sample processing are assessed and a relevant correction procedure is suggested. Subsequently, measurements were carried out on replicated samples taken from two differently-textured soils that, after being dried, were saturated in the laboratory up to different water content values with water of known isotopic composition. Also, plant samples were collected from plants grown in a greenhouse and irrigated with water of known isotopic composition. Water from all samples was extracted by our CWE system and then analyzed using an isotope ratio mass spectrometer in Gas Bench mode for analyses and in temperature conversion elemental analysis (TC/EA) mode for. Preliminary results have quantified the isotope fractions on average of -1.6 ‰ for δ18O and 14.2 ‰ for δ2H. Normalization of stable isotopes from unknown samples according to observed fractionation has enabled the observed bias to become virtually zero, leading to a replicate reproducibility of δ18O and δ2H for soil water of 0.6 ‰ and 3 ‰, respectively. The analyses carried out up to now did not find statistical evidence that the soil types and soil water contents may affect the extraction method and the accuracy of our protocol. Powered by TCPDF (www.tcpdf.org).

Water balance components depend on annual rainfall amount and seasonality in Mediterranean catchments. A high percentage of the annual rainfall occurs between late fall and early spring and feeds natural and artificial water reservoirs. This amount of water stored in the mild-rainy season is used to offset rainfall shortages in the hot-dry season (between late spring and early fall). Observed seasonal anomalies in historical records are quite episodic, but an increase of their frequency might exacerbate water stress or water excess if the rainy season shortens or extends its duration, e.g. due to climate change. Hydrological models are useful tools to assess the impact of seasonal anomalies on the water balance components and this study evaluates the sensitivity of water yield, evapotranspiration and groundwater recharge on changes in rainfall seasonality by using the Soil Water Assessment Tool (SWAT) model. The study area is the Upper Alento River Catchment (UARC) in southern Italy where a long time-series of daily rainfall is available from 1920 to 2018. To assess seasonality anomalies, we compare two approaches: a “static” approach based on the Standardized Precipitation Index (SPI), and a “dynamic” approach that identifies the rainy season by considering rainfall magnitude, timing, and duration. The former approach rigidly selects three seasonal features, namely rainy, dry, and transition seasons, the latter being occasionally characterized by similar properties to the rainy or dry periods. The “dynamic” approach, instead, is based on a time-variant duration of the rainy season and enables to corroborate the aforementioned results within a probabilistic framework. A dry seasonal anomaly is characterized by a decrease of 241 mm in annual average rainfall inducing a concurrent decrease of 116 mm in annual average water yield, 60 mm in actual evapotranspiration and 66 mm in groundwater recharge. We show that the Budyko curve is sensitive to the seasonality regime in UARC by questioning the implicit assumption of temporal steady-state between annual average dryness and evaporative index. Although the duration of the rainy season does not exert a major control on water balance, we have been able to identify seasonal-dependent regression equations linking water yield to dryness index over the rainy season.

Water balance components at catchment scale are strongly related to annual rainfall amount. Nonetheless, water resources availability in Mediterranean catchments depends also on rainfall seasonality. Indeed, a high percentage of annual rainfall occurs between late fall and early spring and feeds natural and artificial water reservoirs. This amount of water stored in the mild-rainy season is used to offset rainfall shortages in the hot-dry season (between late spring and early fall). Observed seasonal anomalies in historical records are quite episodic, but an increase of their frequency might exacerbate water stress or water excess if the rainy season shortens or extends its duration, e.g. due to climate change. Hydrological models are useful tools to assess the impact of seasonal anomalies on the water balance components and this study evaluates the sensitivity of water yield, evapotranspiration and groundwater recharge on changes in rainfall seasonality by using the Soil Water Assessment Tool (SWAT) model. The study area is the Upper Alento River Catchment (UARC) in southern Italy where a long time-series of daily rainfall is available from 1920 to 2018. To assess seasonality anomalies, we compare two distinct approaches: a static approach based on the Standardized Precipitation Index (SPI), and a dynamic approach that identifies the rainy season by considering rainfall magnitude, timing, and duration. The former approach rigidly selects three seasonal features, namely rainy, dry, and transition seasons, the latter being occasionally characterized by similar properties to the rainy or dry periods. The dynamic approach, instead, is based on a time-variant duration of the rainy season and enables to corroborate the aforementioned results within a probabilistic framework. A dry seasonal anomaly is characterized by a decrease of 241 mm in annual average rainfall inducing a concurrent decrease of 116 mm in annual average water yield, 60 mm in actual evapotranspiration and 66 mm in groundwater recharge. We show that the Budyko curve is sensitive to the seasonality regime in UARC by questioning the implicit assumption of temporal steady-state between annual average dryness and evaporative index. Although the duration of the rainy season does not exert a major control on water balance, we have been able to identify seasonal-dependent regression equations linking water yield to dryness index over the rainy season.

L’erosione idrica del suolo dipende sia da fattori naturali sia da azioni antropiche ed è notevolmente influenzata dalla aggressività della precipitazione (la cosiddetta erosività, R). Per valutazioni accurate di questo fattore climatico è necessario disporre di ampie serie storiche di dati di pioggia con aggregazione sub-oraria che, purtroppo, sono invece disponibili solo per un numero ridotto di stazioni, peraltro spesso distribuite in modo poco uniforme su un territorio di interesse. L’ammodernamento delle reti pluviometriche con sensori automatici ha reso più agevole disporre di tali informazioni, ma solo per gli ultimi 10-15 anni. Pertanto, soprattutto per scopi tecnico-applicativi, è necessario ricorrere a metodi di stima semplificati che utilizzano principalmente dati di pioggia giornaliera, solitamente più numerosi e rilevati in stazioni ben distribuite spazialmente. Dal punto di vista operativo, è altresì necessario fornire indicazioni circa il grado di incertezza associata all’uso di relazioni empiriche semplificate rispetto a metodi più rigorosi. In questo studio sono stati utilizzati dati di pioggia giornaliera in Regione Campania aggiornati al 2017 e sono state utilizzate tre diverse espressioni empiriche per stimare l’indice R. I risultati ottenuti sono stati confrontati con quelli che derivano da un metodo di stima più accurato e hanno confermato l’importanza di analizzare i caratteri di erosività in termini stagionali. Le analisi hanno anche consentito di identificare i periodi dell’anno in cui sono da attendersi maggiori incertezze nelle stime semplificate dell’aggressività della precipitazione.