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The research presented in this paper aims at providing a statistical model that is capable of estimating soil water content based on weather data. The model was tested using a long-time series of field experimental data from continuous monitoring at a test site in Oltrepò Pavese (northern Italy). An innovative statistical function was developed in order to predict the evolution of soil–water content from precipitation and air temperature. The data were analysed in a framework of robust statistics by using a combination of robust parametric and non-parametric models. Specifically, a statistical model, which includes the typical seasonal trend of field data, has been set up. The proposed model showed that relevant features present in the field of experimental data can be obtained and correctly described for predictive purposes. [ABSTRACT FROM AUTHOR]

Facing global warming's consequences is a major issue in the present times. Regarding the climate, projections say that heavy rainfalls are going to increase with high probability together with temperature rise; thus, the hazard related to rainfall-induced shallow landslides will likely increase in density over susceptible territories. Different modeling approaches exist, and many of them are forced to make simplifications in order to reproduce landslide occurrences over space and time. Process-based models can help in quantifying the consequences of heavy rainfall in terms of slope instability at a territory scale. In this study, a narrative review of physically based deterministic distributed models (PBDDMs) is presented. Models were selected based on the adoption of the infinite slope scheme (ISS), the use of a deterministic approach (i.e., input and output are treated as absolute values), and the inclusion of new approaches in modeling slope stability through the ISS. The models are presented in chronological order with the aim of drawing a timeline of the evolution of PBDDMs and providing researchers and practitioners with basic knowledge of what scholars have proposed so far. The results indicate that including vegetation's effects on slope stability has raised in importance over time but that there is still a need to find an efficient way to include them. In recent years, the literature production seems to be more focused on probabilistic approaches. [ABSTRACT FROM AUTHOR]

Complex materials exhibit a dielectric behavior that can shed light on their chemophysical structure through a comprehension of the physical mechanisms originating that behavior. For the interpretation of a complex dielectric shape, where multiple relaxations are present (and usually described by semi-empirical functions), a correct interpretation of each simple relaxation is necessary. The separation of often closely overlapped relaxation curves requires the verification of the meaningfulness of such multiple relaxations and to determine their number and relative magnitudes, in other words to resort to a fitting procedure. However, often the physical interpretation of the fitting parameters is not straightforward, and their physical meaning is arguable. The application of even-order derivative spectroscopy is here demonstrated to be able to detect the presence and location of multiple dielectric relaxations, acting on the experimental data without any "a priori" hypothesis. [ABSTRACT FROM AUTHOR]

Wind-energy production may be expanded beyond regions with high-average wind speeds (such as the Midwest U.S.A.) to sites with lower-average speeds (such as the Southeast U.S.A.) by locating favorable regional matches between natural wind-speed and energy-demand patterns. A critical component of wind-power evaluation is to incorporate wind-speed dynamics reflecting documented diurnal and seasonal behavioral patterns. Conventional probabilistic approaches remove patterns from wind-speed data. These patterns must be restored synthetically before they can be matched with energy-demand patterns. How to accurately restore wind-speed patterns is a vexing problem spurring an expanding line of papers. We propose a paradigm shift in wind power evaluation that employs signal-detection and nonlinear-dynamics techniques to empirically diagnose whether synthetic pattern restoration can be avoided altogether. If the complex behavior of observed wind-speed records is due to nonlinear, low-dimensional, and deterministic system dynamics, then nonlinear dynamics techniques can reconstruct wind-speed dynamics from observed wind-speed data without recourse to conventional probabilistic approaches. In the first study of its kind, we test a nonlinear dynamics approach in an application to Sugarland Wind—the first utility-scale wind project proposed in Florida, USA. We find empirical evidence of a low-dimensional and nonlinear wind-speed attractor characterized by strong temporal patterns that match up well with regular daily and seasonal electricity demand patterns. [ABSTRACT FROM AUTHOR]

Abstract: Shallow landslides frequently occur during transient rainfall infiltration and under partially saturated conditions. However, a detailed analysis of what triggers them, particularly in clayey soils, is often hindered by the lack of field measurements. It is uncommon, in fact, to capture their occurrence in an instrumented natural slope. This paper presents results from an integrated field experiment monitoring the soil-water and displacement conditions that lead to the occurrence of a shallow landslide in partially saturated clays. The integration of a variety of experimental techniques allowed for the examination of interplay between soil hydrological and mechanical properties. This research also evaluates a slope stability model based on the suction stress concept. Since the model was applied after the occurrence of the landslide, the results are interpreted as a hind-casting technique for model evaluation. Nevertheless, the detailed field measurements acquired during the monitoring activity and the occurrence of a landslide during the experiment provided significant information on model parameters and data interpretation. The station provides remote satellite monitoring of data on weather variables, soil water content and soil suction. A time domain reflectometry cable was installed vertically to detect potential soil failure. The experimental area had a high probability of landslide occurrence. Indeed, slope failure occurred during the observation period, showing the effectiveness of the station in detecting the occurrence, time and depth of landslides. The landslide was triggered in consequence of changes in suction stress. The failure plane occurred at a depth of 1.4m, corresponding to the interface between a superficial layer of higher permeability of 1 to 1.45m thickness, slipping over a compacted substrate having lower permeability. The analysis allowed for testing of the validity of the model and the description of the triggering mechanisms of the observed shallow landslide in unsaturated conditions, indicating that oscillations in soil matric suction were the dominant variables determining soil failure. [Copyright &y& Elsevier]

Abstract: Ground Penetrating Radar (GPR) can assist decision making in a number of fields by enhancing our knowledge of subsurface features. Non-destructive investigations and controls of civil structures are improving day by day, however the scientific literature reports only a few documented cases of GPR applications to the detection of voids and discontinuities in hydraulic defense structures such as river embankments and levee systems. We applied GPR to the monitoring of river levees for detecting animal burrows, which may trigger levee failures by piping. The manageability and the non-invasiveness of GPR have resulted to be particularly suitable for this application. First because GPR is an extensive investigation method that enables one to rapidly cover a wide area, locating voids that are difficult and costly to locate using other intrusive methods. Second, GPR returns detailed information about the possible presence of voids and discontinuities within river embankments. We document a series of successful GPR applications to detect animal burrows in river levees. [Copyright &y& Elsevier]

Abstract: We present a numerical, catchment-scale model that solves flow equations of surface and subsurface flow in a three-dimensional domain. Surface flow is described by the two-dimensional parabolic approximation of the St. Venant equation, using Manning’s equation of motion; subsurface flow is described by the three-dimensional Richards’ equation for the unsaturated zone and by three-dimensional Darcy’s law for the saturated zone, using an integrated finite difference formulation. The hydrological component is a dynamic link library implemented within a comprehensive model which simulates surface energy, radiation budget, snow melt, potential evapotranspiration, plant development and plant water uptake. We tested the model by comparing distributed and integrated three-dimensional simulated and observed perched water depth (PWD), stream flow data, and soil water contents for a small catchment. Additional tests were performed for the snow melting algorithm as well as the different hydrological processes involved. The model successfully described the water balance and its components as evidenced by good agreement between measured and modelled data. [Copyright &y& Elsevier]

Abstract: In this paper, different characteristics of runoff and eroded sediments were investigated as well as changes in textural composition of the original soil, on experimental plots. The objectives were to investigate the particle size distribution of the eroded sediments, as a function of soil, crop, and meteorological variables, and changes in texture due to water erosion over time. The study was performed on experimental plots in the Apennines mountain range, in northern Italy, where an automated system for measuring runoff water and sediment was installed. Runoff water, sediment yield and sediment mean diameters were analyzed as a function of land cover, rainfall kinetic energy and stream power. In particular, the study investigated: (a) the sediment particle size distribution using laser diffraction, (b) the effect of rainfall kinetic energy, stream power and crop coverage on runoff, sediment yield and sediment particle size distribution and (c) the changes in soil texture on the cultivated field plots, over a period of 15years. The results of this study showed: (a) the particle size distribution of the eroded sediment was generally unimodal and the dominant fraction characterizing the eroded sediments was the one with a mean particle diameter ranging from 4.3 to 13.1μm, comprised in the silt range, (b) the mean particle diameter changed depending on the rainfall kinetic energy and the stream power, with a positive correlation between particle diameter and rainfall kinetic energy under bare soil, and (c) the effect of long-term erosion showed that the original soil textural composition experienced a statistically significant change over a period of 15years, with a decrease in the silt fraction and a relative increase in the clay fraction, due to losses of silt in the eroded sediments. [Copyright &y& Elsevier]

Pressure plates are commonly used to measure the soil water retention curve. Low plate and soil conductance, lack of plate-soil contact, and soil dispersion, however, make this method often unreliable at low water potentials. We investigated how errors in the determination of the water retention curve affect the soil hydraulic properties and the computation of plant-available water. We first determined soil water retention data for a silt loam soil using pressure plates only and a combination of pressure plates and a dew point meter. The two sets of soil water retention data were then analyzed using different models for describing the hydraulic properties. The soil water retention curves determined with the two methods deviated at potentials less than about -20 m H2O, with the pressure plate apparatus data yielding larger water contents than the dew point meter at the same water potentials. These results indicate that soil water retention curves determined from pressure plates may be in error at potentials less than -20 m H2O, which may lead to substantial errors in water flow calculations. These errors can be eliminated by using a combination of pressure plates and dew point measurements to determine the water retention curve. [ABSTRACT FROM AUTHOR]

• Comparative studies for particle size distribution over a wide range of texture. • Analysis of Pipette, Laser Diffraction, Digital Imaging and Sedigraph. • Equivalent limits between Pipette and Laser Diffraction for silt and clay. • Updated textural triangles for soil classification with Laser Diffraction. Laser diffraction analysis is a fast, reliable and automated method that provides detailed and highly resolved soil and sediment particle size distribution. In recent studies, the methods were compared against independent methods based on direct observation of particles by digital imaging. The data showed that laser diffraction results were in better agreement with the digital imaging independent method than with sedimentation-based methods. However, analysis was performed over a limited number of samples. In this study, 47 soil samples with a wide range of textural properties were analyzed with Laser Diffraction, Pipette, Sieving, Sedigraph and Digital Imaging methods. Detailed statistical analysis using Altman plots and Honest Significant Difference tests demonstrated (at 95% significance) that the five methods do not show statistically significant differences for grain sizes above 100 µm. However, in the lower end of the size range, i.e. less or equal to 50 µm, Laser Diffraction showed much better agreement with the reference method selected for comparison, which was Digital Imaging. New regression equations were derived with slope coefficients for linear regressions between Pipette and Laser of 0.2952 (R2 = 0.8625) for clay, 1.4261 (R2 = 0.5746) for silt and 1.031 (R2 = 0.6586) for sand, classified with the International Soil Science Society (ISSS) system. For the United States Department of Agriculture (USDA) classification system, the slopes were: 0.261 (R2 = 0.8625) for clay, 1.3493 (R2 = 0.8179) for silt and 1.063 (R2 = 0.888) for sand. These data were consistent with previous studies. Based on regression and equivalent diameters, Laser Diffraction data were represented on textural triangles for classification, allowing for employing Laser Diffraction for soil texture classification. Two alternative for representing the Laser Diffraction data in textural triangles were employed: (1) using regression equations to convert data to be represented on the standard triangles and (2) modify the upper limit for the clay range, from 2 to 8 μm. Finally, based on the additional evidence presented in this research, demonstrating that the Laser Diffraction was in better agreement with the optical method with respect to traditional sedimentation methods, it is suggested that the standards for particle size analysis be changed from sedimentation to Laser Diffraction methodologies. [ABSTRACT FROM AUTHOR]

Summary: The quantification of soil evaporation and of soil water content dynamics near the soil surface are critical in the physics of land-surface processes on regional and global scales, in particular in relation to mass and energy fluxes between the ground and the atmosphere. Although it is widely recognized that both liquid and gaseous water movement are fundamental factors in the quantification of soil heat flux and surface evaporation, their computation is still rarely considered in most models or practical applications. Moreover, questions remain about the correct computation of key factors such as the soil surface resistance or the soil surface temperature. This study was conducted to: (a) implement a fully coupled numerical model to solve the governing equations for liquid water, water vapor, and heat transport in bare soils, (b) test the numerical model with detailed measurements of soil temperature, heat flux, water content, and evaporation from the surface, and (c) test different formulations for the soil surface resistance parameter and test their effect on soil evaporation. The code implements a non-isothermal solution of the vapor flux equation that accounts for the thermally driven water vapor transport and phase changes. Simulated soil temperature, heat flux, and water content were in good agreement with measured values. The model showed that vapor transport plays a key role in soil mass and energy transfer and that vapor flow may induce sinusoidal variations in soil water content near the surface. Different results were obtained for evaporation calculations, depending on the choice of the soil surface resistance equation, which was shown to be a fundamental term in the soil–atmosphere interactions. The results also demonstrated that soil water dynamics are strongly linked to temperature variations and that it is important to consider coupled transport of heat, vapor and liquid water when assessing energy dynamics in soils. [Copyright &y& Elsevier]

Abstract: Time Domain Reflectometry (TDR) is a widespread technique for measurement of soil water content (SWC). The main assumption behind the use of Time Domain Reflectometry (TDR) is of negligible losses, therefore assuming that only the real part determines the value of the TDR-measured apparent dielectric permittivity. This assumption does not hold for soils where surfaces are conductive (clay soils) or where high concentrations of electrolyte are present in the soil solution (saline soils) because under these conditions the contribution of the imaginary part becomes important. One of the main effects of dielectric losses on the TDR measurement is overestimation of SWC. In this study we present a methodology for separating the real and the imaginary part from the measurement of the apparent dielectric permittivity. This approach allows correction of the SWC overestimation, by using the TDR-measured electrical conductivity as indicator of dielectric losses. Oven-dry gravimetric soil water content was used as an independent method for soil water content assessment. The original SWC overestimation (in respect to the oven-dry gravimetric based measurement) reached values of up to 20% of total soil saturation, after the correction the differences were reduced to a 3–5%. The methodology can be applied based on knowledge of measured permittivity and electrical conductivity only, making it readily applicable to field experiments. [Copyright &y& Elsevier]

Summary: The Water Erosion Prediction Project (WEPP) model was tested using data from a detailed study conducted on experimental plots in the Apennines Mountain Range, northern Italy. Runoff, soil water and sediment data, together with weather information, were collected on an hourly basis at the study site. WEPP was first applied to simulate transient surface runoff, soil water and erosion. Two important input parameters, the biomass energy ratio for crop and the effective hydraulic conductivity of surface soil, were calibrated using field-observed runoff, soil water, erosion and plant biomass data. The calibrated model was then used to simulate the hydrologic and erosion impacts of three typical crop rotations, thereby to evaluate their abilities in reducing surface runoff and sediment yield. Results indicated that, with the definition of a restrictive layer at the bottom of the soil profile and the calibration of the two crucial model parameters, WEPP could adequately account for the water balance for the modeled experimental plot. For the study area, continuous corn with a conservation practice that delayed primary and secondary tillages produced low surface runoff and soil erosion, from both field observation and WEPP modeling. However, this mono-cultural practice may lead to accelerated soil-quality degradation. On the other hand, a four-year-rotation, corn–wheat–alfalfa–alfalfa, was predicted to substantially reduce soil erosion and has potential to become a sustainable cropping system under the pedo-climatic settings of the study area. [Copyright &y& Elsevier]

Abstract: The Shiozawa and Campbell Gaussian bimodal model describes the particle size distribution (PSD) in soils as a weighted sum of two fractions: the primary minerals (sand and silt) and the secondary minerals (clay) fraction, each described by a Gaussian function. This model was developed and tested using traditional sedimentation techniques analysis for PSD such as sieving and hydrometer. Because of the lack of particle size distribution data in the clay range, Shiozawa and Campbell set the mean and the standard deviation in the clay fraction as a constant. Today, the availability of laser diffraction (LD) techniques makes it possible to overcome this limit and test the model by using a soil dataset that includes the clay fraction distribution. This paper describes the results of the test of the Shiozawa and Campbell Gaussian bimodal model on eight samples, six of them from different locations in Washington State (USA) and two from a hillside area of Northern Italy. PSD analysis was performed with sedimentation techniques, small-angle laser diffraction apparatus and transmission electron microscopy, the latter allowing measurement of very fine particles (sizes down to 0.05 μm). To test the effect of the PSD technique on the particle-size measurement and therefore on the model reliability, a comparison between sedimentation techniques and LD was performed. Moreover a validation of the LD method in the clay range was performed by comparison of LD to Transmission Electron Microscopy and Image Analysis methodologies. The results from the bimodal model showed that the model provides a good characterization of PSD for five of the eight samples analyzed only, revealing that more complex distributions are required for a loam, a silt loam and for a clay soil, where multimodal modes were found. The comparison between sedimentation technique and LD showed that the volume percentage of the clay-size fraction obtained by laser diffraction was lower than the mass percentage of the clay-size fraction measured by pipette. The silt fraction displayed the opposite trend. Transmission Electron Microscopy and Image Analysis of the clay fraction showed that Laser Diffraction provides an overestimation of the mean diameter in the clay fraction, when particles are assumed to be represented as spheres. [Copyright &y& Elsevier]

Examines the validity of mass-based fragmentation model to accurately characterize particle-size distribution in soils. Use of wet sieving, pipette and light diffraction techniques to obtain particle size distribution; Derivation of a power-law relation between mass and size of soil particles.

The vadose zone of steep slopes is often affected by rainfall-induced shallow landslides, which can cause widespread direct and indirect damage to the terrain and infrastructures, as well as urban and rural developments. Starting from these issues, the main focus of this special issue is on presenting the advances in shallow landslide hydrology from both the earth sciences and soil mechanics perspectives and their influence on behavior and triggering of shallow landslides. [Extracted from the article]

• New algorithm and software. • Simultaneous measurement of soil dry density and water content with Time Domain Reflectometry. • Evaluation of new methodology for measuring soil density and water content. • Identification of best fit equation for measuring soil water content. • Identification of best fit parameters for soil density measurements. Time domain reflectometry can be applied to measure soil bulk density. Monitoring of bulk density over large areas for geo-statistical analysis requires a fast and effective method allowing for acquisition of many data points. Methods are available in the literature to obtain density from TDR. However, algorithms for simultaneous measurements of density and soil water content are not available. Moreover, the methodologies presented in the literature requires tests and evaluation. In this study a new algorithm implemented into a software was developed and the method tested over samples having different textural properties. It is shown that the method provided a measurement of density with an accuracy between 1 and 3 %. The new algorithm implements an automated methodology combined with a non-linear least square optimization, allowing for analysis of many waveforms at a time. Several equations to derive soil water content from electric permittivity were tested, showing that dielectric mixing models provides more accurate results. Moreover, the optimization of parameters allows for analysis and application to multiple materials. The method was confirmed robust and suitable for field-monitoring applications. [ABSTRACT FROM AUTHOR]

• Measurement of dielectric permittivity with reflected waves GPR was obtained. • Evaluation of Water Content Estimation Equations using wide range of textures. • Authors identified best fit dielectric mixing model equation and critical analysis of current equations. • Sensitity Analysis of the best fit model identifying most critical parameters. Soil water content has an important impact on many fundamental biophysical processes. The quantification of soil water content is necessary for different applications, ranging from large-scale calibration of global-scale climate models to field and catchment scale monitoring in hydrology and agriculture. Many techniques are available today for measuring soil water content, ranging from point scale soil water content sensors to global scale, active and passive, microwave satellites. Geophysical methods are important methods, used for several decades, to measure soil water content at different scales. Among these methods, ground penetrating radar has been shown to be one of the most reliable and promising ones. Soil water content measurement using ground penetrating radar requires the application of parametric equations that will convert the measured dielectric permittivity to water content. While several studies have been performed to test equations for soil water content sensors such as time domain reflectometry, a few studies have been performed to test different formulae for application to ground penetrating radar. In this study, we compare available formulae for converting dielectric permittivity obtained from detailed laboratory scale measurement of reflected waves using ground penetrating radar. Four soils covering a wide range of textures were used and the measured soil water contents were compared with values obtained from gravimetric measurements. Results showed that the dielectric mixing model of Roth et al. (1990) provided the best fit for individual soil textural classes, except for sandy soils. However, for all data combined the dielectric mixing model performed much better with significant difference in coefficient and determination and root mean square error. Empirical equations developed from calibration of time domain reflectometry performed poorly when applied to estimation of soil water content obtained from ground penetrating radar. Differences in sample volume, frequency of operation and data analysis between ground penetrating radar and time domain reflectometry, suggest to use more flexible and robust electromagnetic mixing formulae, allowing for incorporating the dielectric properties of constituents materials and geometrical features of the media. Sensitivity analysis was then performed to provide detailed information for the most accurate application of the selected dielectric model. Sensitivity analysis showed that the geometric parameter α and the dielectric permittivity of the solid phase ∊ s are the two most sensitive parameters, determining important variations in the estimation of soil water content. Based on these results, these two parameters are suggested as fitting parameters, to be selected if the model is fitted to data. Otherwise, the model can be successfully used without calibration, as presented in this study, by using α = 0.5 (as also suggested by the authors) and ∊ s = 4, which is an average value for soil minerals. [ABSTRACT FROM AUTHOR]

For many years papers have been published showing differences between sedimentation-based methods against laser diffraction. Differences were found especially in the fine texture ranges and regression equations were presented to convert data obtained between different methods. In this paper we aimed at understanding which method is closer to an independent measurement of particle size. We selected a new, automated image analysis technique as a reference method. Since with this new method each individual particle is photographed, its pixels counted and its shape analysed, we assumed this method as the reference method against which test the accuracy of sedimentation methods and laser diffraction. Comparison showed that laser diffraction was in better agreement with the independent optical methods, indicating that the sedimentation methods tend to largely overestimate the finer fractions of the distribution. Considering the results presented in this research, and the methodological disadvantages of sedimentation methods, we propose to employ laser diffraction as a standard method for particle size analysis in soils. [ABSTRACT FROM AUTHOR]

The pore–solid interface and its characteristics play a key role in chemical interactions between minerals in the solid soil matrix and the liquid in pore space and, consequently, solute transport in soils. Specific surface area (SSA), typically measured to characterize the pore–solid interface, depends not only on the particle size distribution (PSD) but also on particle shapes and surface roughness. In this note, we investigate the effects of surface roughness and probing molecule size on SSA estimation, use concepts from fractals, and theoretically estimate SSA from PSD and the water retention curve (WRC). The former is used to characterize the particle sizes and the latter to approximately quantify the pore–solid interface roughness by determining the surface fractal dimension. To evaluate our approach, we use five Washington and 21 Arizona soils for which both PSDs and WRCs were accurately measured over a wide range of particle sizes and matric potentials. Comparison with the experiments show that the proposed method estimates the SSA reasonably well, with RMSE = 16.8 and 30.1 m2 g–1 and average relative error = –56 and –35% for the Washington and Arizona datasets, respectively. [ABSTRACT FROM AUTHOR]

Applies multifractal methods to characterize contrasting soil particle-size distributions. Soil textural classes; Multifractal parameters; Difference between the capacity and entropy dimensions.

The decentralized production of electrical energy from wind requires the installation of more and more underground power cables. From an economic standpoint it is very important to estimate the cables' lifetime, which strongly depends on the temperature. A correct estimation of cable temperature requires an accurate description of the heat balance equation around the cable. Most of the models used to assess heat dissipation from cables, however, do not consider that the soil thermal conductivity strongly depends on soil water content and hydraulic dynamics in the vicinity of the cable. The high temperature around the cable induces a water–vapor cycle in the soil: liquid water evaporates near the cable, and this vapor condensates in the more distant and colder parts of the soil. Above a critical heat dissipation rate, the soil around the cable dries out and the water–vapor cycle breaks down. In this study, we analytically estimated the critical heat dissipation rate as a function of soil type, soil temperature, and water content. We validated the analytical estimation by comparison to a numerical solution of the coupled heat–water–vapor transport for various soil types and conditions. The numerical code was validated by simulating a soil drying experiment. The proposed estimation of thermal instabilities in soils could become a powerful tool in the design of underground electrical power cable systems. [ABSTRACT FROM AUTHOR]

The precise spatio-temporal estimation of subsurface hydrological states and water fluxes is still a challenge in hydrology, because most hydrological processes are highly nonlinear and controlled by time-varying boundary conditions. Hence, numerical models are required for their comprehensive representation. Another challenge is that soils are spatially heterogeneous and the identification and accurate spatial representation of such heterogeneity is still an area of intensive research in the field of hydrogeophysics. To date, there are only very few approaches that combine all the available information from classical pedological soil characterization, hydrological monitoring, geophysical subsurface characterization and state-of the art hydrological modeling to achieve a comprehensive estimation of hydrological states and fluxes. The primary objective of this project is to apply an integrated approach for improved process-based soil hydrological modeling of hillslope-scale vadose zone water fluxes. The approach builds on the integration of classical pedological expertise for soil characterization, on accurate monitoring of soil water content as well as on state-of-the-art time-lapse geophysical measurements for the characterization of subsurface heterogeneity. It finally integrates the gathered information into a physically-based numerical model that is capable of simulating soil water fluxes including saturated and unsaturated water flow, surface runoff, soil evaporation, plant water uptake, snow accumulation and melt with high spatial and temporal resolution.The project will expand the suite of approaches currently available for estimating soil water fluxes towards a new dimension as the combination offers the opportunity to maximize the potentials of available measurement and modeling techniques and to minimize the sources of uncertainty in the predicted states and fluxes. It will provide important knowledge needed for transferring this approach to larger scales where accurate quantification of soil water fluxes at the farm or catchment scale is required for a more efficient water and nutrient management in the context of sustainable food production and climate change. [ABSTRACT FROM AUTHOR]

A proper assessment of the soil effective stress state is crucial in many cases to identify a potential geological/geotechnical hazard as shallow landslides or failure of levees that may have a significant impact on human activities and development. This paper is aimed at validating a methodology for the expeditious and economic determination of effective stress state in the vadose zone recently proposed by Lo Presti et al. in 2016. The method is based on the interpretation of cone penetration tests (CPTu). Its validation was carried out by comparing the CPTu predicted values of suction against the measured ones in a well-documented and monitored site. The comparison also includes the prediction of suction that was obtained by using the so-called Modified Kovacs model (MK). Moreover, additional data of water content and saturation degree from another site were used to predict the suction by using the MK model. These values of suction were compared with those inferred by the CPTu. [ABSTRACT FROM AUTHOR]

The evaluation of shallow soils water content is very important in many fields, and different hydrological models are widely applied to simulate field-scale water flow and soil water content. The degree of saturation of a shallow soil is a time-varying variable, depending on different weather conditions. In many applications, it is useful to directly correlate the soil degree of saturation to time series of rainfall amount. This paper presents a simplified empirical model, which allows for computation of the soil degree of saturation using readily available climate data on air temperature and rainfall depths. The model is tested with in situ measurements of soil water content collected at three sites in the Emilia Romagna region in northern Italy. The experimental data are compared with the results obtained from the simplified model over an observation period of almost 5 years. The model has been used to generate soil water content time series at different depths and requires a separate calibration for each depth where the degree of saturation is computed. A discussion on the model's calibration is also carried out to clarify the model sensitivity to the different parameters and the choice of input data. [ABSTRACT FROM AUTHOR]

River embankments stability is a key aspect in geohazard assessment and underestimating its failure risk may result in unexpected and severe damages. Changes in hydraulic and climatic boundary conditions are responsible for transient water flow within the embankments, consequently the related soil water content and pore-water pressure distributions vary with time. Therefore, it is crucial to investigate their hydraulic and retention behaviour in order to assess in a reliable way the safety margins towards instability mechanisms. To obtain a realistic estimate of key variables in time and space, as a function of external conditions, a combination of field measurements, laboratory testing and suitably calibrated numerical analyses should be used. To achieve this purpose, a full-scale monitoring system was implemented on a cross section of an embankment along the river Secchia (Modena, Italy), mainly measuring the pore-water pressure (including suction) and the water content at different depths. A relatively large variety of different sensors have been installed, to compare their performance in terms of robustness and reliability, and collected data have been interpreted with the help of laboratory and field geotechnical characterisation. The article describes such system and the sensors used, their capabilities and the installation techniques, resulting in quite innovative solutions for the specific application. The spatial variability of the monitored variables is also finally presented and discussed. The proposed integrated monitoring system, which aims at making use of affordable and commercially available sensors that can be therefore installed along extensive river stretches, appears a fundamental starting point to assess potential risks of such geotechnical infrastructures in real-time and to devise well-balanced related mitigation measures. • Design and implementation of a full-scale monitoring system in a river embankment. • Pore pressure/suction and water content measured during seepage to significant depth. • Monitoring data collected for a period of 2 years are showed and discussed. • Smooth changes with depth and similar retention behaviour despite soil heterogeneity. • Spatial distribution of pore pressure/suction is estimated using site measurements. [ABSTRACT FROM AUTHOR]

The identification of the triggering mechanism of rainfall-induced, shallow landslides requires a complete understanding of the hydro-mechanical response of soil, which can be represented through the trends of the degree of soil saturation. In this paper, multiple annual cycles of soil saturation obtained through field monitoring were used to validate an empirical model based on climate data. Both field measurements and model outputs were used to conduct simplified slope stability analysis to evaluate the model chain capability in predicting the temporal occurrence of shallow failures. Field data were collected on a testsite slope located in Oltrepò Pavese (Northern Italy), where a shallow landslide occurred during the monitoring period. The experimental trends of the degree of saturation at various depths in the soil profile were compared with the calculated values and showed good agreement. Landslide triggering is reached when the soil is completely saturated. Both measured and modeled trends of soil saturation correctly identified the triggering time of the shallow landslide and the depth of the sliding surface, 1.0 m below the ground surface, in the test slope. The obtained results indicated the possibility of extending this approach for theassessment of the initiation time and the depth of shallow landslides, particularly for preliminary susceptibility evaluations, based on widely available climate data. [ABSTRACT FROM AUTHOR]