Identification of lateral discontinuities via multi-offset phase analysis of surface wave data

Surface wave methods are based on the inversion of observed Rayleigh wave phase-velocity dispersion curves. The goal is to estimate mainly the shear-wave velocity profile of the investigated site. The model used for the interpretation is 1D, hence results obtained wherever lateral variations are present cannot be considered reliable.In this paper, we study four synthetic models, all with a lateral heterogeneity. When we process the entire corresponding seismograms with traditional f-. k approach, the resulting 1D profiles are representative of the subsurface properties averaged over the whole length of the receivers lines. These results show that classical analysis disregards evidences of sharp lateral velocity changes even when they show up in the raw seismograms.In our research, we implement and test over the same synthetic models, a novel robust automated method to check the appropriateness of 1D model assumption and locate the discontinuities. This new approach is a development of the recent multi-offset phase analysis with the following further advantages: it does not need previous noise evaluation and more than one shot.Only once the discontinuities are clearly identified, we confidently perform classical f-k dispersion curve extraction and inversion separately on both sides of the discontinuity. Thus the final results, obtained by putting side by side the 1D profiles, are correct 2D reconstructions of the discontinuous S-wave distributions obtained without any additional ad-hoc hypotheses

A combination of the Hashin-Shtrikman bounds aimed at modelling electrical conductivity and permittivity of variably saturated porous media

In this paper, we propose a novel theoretical model for the dielectric response of variably saturated porous media. The model is first constructed for fully saturated systems as a combination of the well-established Hashin and Shtrikman bounds and Archie's first law. One of the key advantages of the new constitutive model is that it explains both electrical conductivity-when surface conductivity is small and negligible-and permittivity using the same parametrization. The model for partially saturated media is derived as an extension of the fully saturated model, where the permittivity of the pore space is obtained as a combination of the permittivity of the aqueous and non-aqueous phases. Model parameters have a well-defined physical meaning, can be independently measured, and can be used to characterize the pore-scale geometrical features of the medium. Both the fully and the partially saturated models are successfully tested against measured values of relative permittivity for a wide range of porous media and saturating fluids. The model is also compared against existing models using the same parametrization, showing better agreement with the data when all the parameters are independently estimated. An example is also presented to demonstrate how the model can be used to predict the relative permittivity when only electrical conductivity is measured, or vice vers

Vertical Radar Profiles for the Characterization of Deep Vadose Zones

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Measuring and modeling water-related soil-vegetation feedbacks in a fallow plot

Abstract. Land fallowing is one possible response to shortage of water for irrigation. Leaving the soil unseeded implies a change of the soil functioning that has an impact on the water cycle. The development of a soil crust in the open spaces between the patterns of grass weed affects the soil properties and the field-scale water balance. The objectives of this study are to test the potential of integrated non-invasive geophysical methods and ground-image analysis and to quantify the effect of the soil–vegetation interaction on the water balance of fallow land at the local- and plot scale. We measured repeatedly in space and time local soil saturation and vegetation cover over two small plots located in southern Sardinia, Italy, during a controlled irrigation experiment. One plot was left unseeded and the other was cultivated. The comparative analysis of ERT maps of soil moisture evidenced a considerably different hydrologic response to irrigation of the two plots. Local measurements of soil saturation and vegetation cover were repeated in space to evidence a positive feedback between weed growth and infiltration at the fallow plot. A simple bucket model captured the different soil moisture dynamics at the two plots during the infiltration experiment and was used to estimate the impact of the soil vegetation feedback on the yearly water balance at the fallow site

Monitoring and modelling of soil–plant interactions: the joint use of ERT, sap flow and eddy covariance data to characterize the volume of an orange tree root zone

Abstract. Mass and energy exchanges between soil, plants and atmosphere control a number of key environmental processes involving hydrology, biota and climate. The understanding of these exchanges also play a critical role for practical purposes e.g. in precision agriculture. In this paper we present a methodology based on coupling innovative data collection and models in order to obtain quantitative estimates of the key parameters of such complex flow system. In particular we propose the use of hydro-geophysical monitoring via "time-lapse" electrical resistivity tomography (ERT) in conjunction with measurements of plant transpiration via sap flow and evapotranspiration (ET) from eddy covariance (EC). This abundance of data is fed to spatially distributed soil models in order to characterize the distribution of active roots. We conducted experiments in an orange orchard in eastern Sicily (Italy), characterized by the typical Mediterranean semi-arid climate. The subsoil dynamics, particularly influenced by irrigation and root uptake, were characterized mainly by the ERT set-up, consisting of 48 buried electrodes on 4 instrumented micro-boreholes (about 1.2 m deep) placed at the corners of a square (with about 1.3 m long sides) surrounding the orange tree, plus 24 mini-electrodes on the surface spaced 0.1 m on a square grid. During the monitoring, we collected repeated ERT and time domain reflectometry (TDR) soil moisture measurements, soil water sampling, sap flow measurements from the orange tree and EC data. We conducted a laboratory calibration of the soil electrical properties as a function of moisture content and porewater electrical conductivity. Irrigation, precipitation, sap flow and ET data are available allowing for knowledge of the system's long-term forcing conditions on the system. This information was used to calibrate a 1-D Richards' equation model representing the dynamics of the volume monitored via 3-D ERT. Information on the soil hydraulic properties was collected from laboratory and field experiments. The successful results of the calibrated modelling exercise allow for the quantification of the soil volume interested by root water uptake (RWU). This volume is much smaller (with a surface area less than 2 m2, and about 40 cm thick) than expected and assumed in the design of classical drip irrigation schemes that prove to be losing at least half of the irrigated water which is not taken up by the plants

2016 Central Italy Earthquakes: comparison between GPS signals and low-cost distributed MEMS arrays

Abstract. Modern seismic ground-motion sensors have reached an excellent performance quality in terms of dynamic range and bandwidth resolution. The weakest point in the recording of seismic events remains spatial sampling and spatial resolution, due to the limited number of installed sensors. A significant improvement in spatial resolution can be achieved by the use of non-conventional motion sensors, such as low-cost distributed sensors arrays or positioning systems, capable of increasing the density of classical seismic recording networks. In this perspective, we adopted micro-electro mechanical system (MEMS) sensors to integrate the use of standard accelerometers for moderate-to-strong seismic events. In addition, we analyse high-rate distributed positioning system data that also record soil motion. In this paper, we present data from the 2016 Central Italy earthquakes as recorded by a spatially dense prototype MEMS array installed in the proximity of the epicentral area, and we compare the results to the signal of local 1s GPS stations. We discuss advantages and limitations of this joint approach, reaching the conclusion that such low-cost sensors and the use of high rate GPS signal could be an effective choice for integrate the spatial density of stations providing strong-motion parameters

Understanding the dynamics of enhanced light non-aqueous phase liquids (LNAPL) remediation at a polluted site: Insights from hydrogeophysical findings and chemical evidence

This study intricately unfolds a pioneering methodology for remediating contaminants in a persistent light non-aqueous phase liquids (LNAPL)-contaminated site. The remediation strategy seamlessly integrates enhanced desorption and in-situ chemical oxidation (ISCO), orchestrating the injection of PetroCleanze® (a desorbent) and RegenOx® (an oxidizer) through meticulously designed wells. These injections, based on detailed geological and hydrogeological assessments, aim at mobilizing residual contaminants for subsequent extraction. Real-time subsurface dynamics are investigated through geophysical monitoring, employing electrical resistivity tomography (ERT) to trace reagent migration pathways via their effect on bulk electrical conductivity. The integration of groundwater sampling data aims at providing additional insights into the transformations of contaminants in the spatiotemporal context. Vivid two-dimensional time-lapse ERT sections showcase the evolution of resistivity anomalies, providing high-resolution evidence of the heterogeneity, dispersion pathways of desorbent and oxidant, and residual LNAPL mobilization. Hydrochemical analyses complement this, revealing effective mobilization processes with increasing aqueous concentrations of total petroleum hydrocarbons (TPH) over time. Speciation analysis unveils the intricate interplay of desorption and oxidation, portraying the dynamic fractionation of hydrocarbon components. The hydrogeophysical and data-driven framework not only delivers qualitative and quantitative insights into reagent and contaminant distribution but also enhances understanding of spatial and temporal physio-chemical changes during the remediation process. Time-lapse ERT visually narrates the reagent's journey through time, while chemical analyses depict the unfolding processes of desorption and oxidation across space and time. The coupling of hydrogeophysical and chemical findings pictures the transformations of pollutants following the sequence of product injection and the push and pull activities, capturing the removal of mobilized contaminants through hydraulic barrier wells. This enhanced understanding proves instrumental towards optimizing and tailoring remediation efforts, especially in heterogeneous environmental settings. This study establishes a new standard for a sophisticated and innovative contaminant remediation approach, advancing environmental practices through the harmonized analysis of geophysical and chemical data

Combining Models of Root-Zone Hydrology and Geoelectrical Measurements: Recent Advances and Future Prospects

Recent advances in measuring and modeling root water uptake along with refined electrical petrophysical models may help fill the existing gap in hydrological root model parametrization. In this paper, we discuss the choices to be made to combine root-zone hydrology and geoelectrical data with the aim of characterizing the active root zone. For each model and observation type we discuss sources of uncertainty and how they are commonly addressed in a stochastic inversion framework. We point out different degrees of integration in the existing hydrogeophysical approaches to parametrize models of root-zone hydrology. This paper aims at giving emphasis to stochastic approaches, in particular to Data Assimilation (DA) schemes, that are generally identified as the best way to combine geoelectrical data with Root Water Uptake (RWU) models. In addition, the study points out a more suitable objective function taken from the optimal transport theory that better captures complex geometry of root systems. Another pathway for improvement of geoelectrical data integration into RWU models using DA relies on the use of stem based methods as a leverage to introduce more extensive root knowledge into RWU macroscopic hydrological models

Analysis of time-lapse data error in complex conductivity imaging to alleviate anthropogenic noise for site characterization

Previous studies have demonstrated the potential benefits of the complex conductivity (CC) imaging over electrical resistivity tomography for an improved delineation of hydrocarbonimpacted sites and accompanying biogeochemical processes. However, time-lapse CC field applications are still rare, in particular for measurements performed near anthropogenic structures such as buried pipes or tanks, which are typically present at contaminated sites. To fill this gap, we have developed CC imaging (CCI) results for monitoring data collected in Trecate (northwest Italy), a site impacted by a crude oil spill. Initial imaging results reveal only a poor correlation with seasonal variations of the groundwater table at the site (approximately 6 m). However, it is not clear to which extend such results are affected by anthropogenic structures present at the site. To address this, we performed a detailed analysis of the misfit between direct and reciprocal time-lapse differences. Based on this analysis, we were able to discriminate spatial and temporal sources of systematic errors, with the latter commonly affecting measurements collected near anthropogenic structures. Following our approach, CC images reveal that temporal changes in the electrical properties correlate well with seasonal fluctuations in the groundwater level for areas free of contaminants, whereas contaminated areas exhibit a constant response over time characterized by a relatively high electrical conductivity and a negligible polarization effect. In accordance with a recent mechanistic model, such a response can be explained by the presence of immiscible fluids (oil and air) forming a continuous film through the micro and macropores, hindering the development of ion-selective membranes and membrane polarization. Our results demonstrate the applicability of CCI for an improved characterization of hydrocarboncontaminated areas, even in areas affected by cultural noise