ALBERT

Description: 〈span〉〈div〉ABSTRACT〈/div〉Modern seismic ground‐motion sensors reached excellent response quality in terms of dynamic and bandwidth resolution. The weakest point in the recording of the strong‐motion wavefield is the spatial sampling and resolution, due to the limited number of installed sensors, often at large distances. A significant improvement in spatial resolution can be achieved by the use of low‐cost distributed sensors arrays, capable of recording seismic events with a dense sensors network. In this perspective, microelectro mechanical system (MEMS) sensors could efficiently integrate the use of standard accelerometers for moderate‐to‐strong seismic events. In this article, we present data from the 2016 Central Italy earthquakes, recorded by a spatially dense prototype MEMS array installed in the neighborhood of the epicenter area. MEMS records are compared against the national strong‐motion network data, suggesting that these very low‐cost sensors could be an effective choice for increasing the spatial density of stations to provide strong‐motion peak parameters.〈/span〉

Description: 〈span〉〈div〉ABSTRACT〈/div〉Modern seismic ground‐motion sensors reached excellent response quality in terms of dynamic and bandwidth resolution. The weakest point in the recording of the strong‐motion wavefield is the spatial sampling and resolution, due to the limited number of installed sensors, often at large distances. A significant improvement in spatial resolution can be achieved by the use of low‐cost distributed sensors arrays, capable of recording seismic events with a dense sensors network. In this perspective, microelectro mechanical system (MEMS) sensors could efficiently integrate the use of standard accelerometers for moderate‐to‐strong seismic events. In this article, we present data from the 2016 Central Italy earthquakes, recorded by a spatially dense prototype MEMS array installed in the neighborhood of the epicenter area. MEMS records are compared against the national strong‐motion network data, suggesting that these very low‐cost sensors could be an effective choice for increasing the spatial density of stations to provide strong‐motion peak parameters.〈/span〉

Description: Inversion of surface wave dispersion properties is commonly used to derive shear wave velocity depth profiles. However, one of the critical and yet rarely considered issues in this ill-posed inversion process is mode contamination. Rayleigh dispersion modes are the theoretically possible solutions of motion. Experimentally, we define Rayleigh dispersion properties from spectra energy maxima in some domain (as f–k), thus possibly producing only apparent experimental dispersion curves, where energy spreads onto several modes. If this phenomenon is not recognized, the inversion of an apparent dispersion curve can produce results unrelated to the actual subsurface structure. In this work, we present the results of synthetic tests that highlight the most common subsoil conditions and acquisition pitfalls that can give rise to surface wave mode contamination. In particular, we consider three typical subsoil structures that can produce this phenomenon: 1) a simple two-layer system with a strong impedance contrast, 2) a layered system with velocity inversion, and 3) a two-layer system having a lateral discontinuity. It is known that all such systems produce, to some extent, situations in which Rayleigh wave energy propagates at higher modes rather than on the fundamental mode. We also consider the impact of acquisition parameters, which influence mode contaminations mainly as a consequence of inadequate spatial sampling. This exercise leads to identifying the most critical subsoil characteristics that control ambiguous mode inversion. We finally propose possible a priori detectors and warnings for the most critical subsoil conditions leading to mode contamination.

Description: The surface wave method is a popular tool for geotechnical characterization because it supplies a cost-effective testing procedure capable of retrieving the shear wave velocity structure of the near-surface. Several acquisition and processing approaches have been developed to infer the Rayleigh wave dispersion curve which is then inverted. Typically, in active testing, single-component vertical receivers are used. In most cases, the inversion is carried out assuming that the experimental dispersion curve corresponds to a single mode, mostly the fundamental Rayleigh mode, unless clear evidence dictates the existence of a more complex response, e.g., in presence of low-velocity layers and inversely dispersive sites. A correct identification of the modes is essential to avoid serious errors. Here we consider the typical case of higher-mode misidentification known as "osculation" ("kissing"), where the energy peak shifts at low frequencies from the fundamental to the first higher mode. This jump occurs, with a continuous smooth transition, around a well-defined frequency where the two modes get very close to each other. Osculation happens generally in presence of strong velocity contrasts, typically with a fast bedrock underlying loose sediments. The practical limitations of the acquired active data affect the spectral and modal resolution, making it often impossible to identify the presence of two modes. In some cases, modes have a very close root and cannot be separated at the osculation point. In such cases, mode misidentification can create a large overestimation of the bedrock velocity and a large error on its depth. We examine the subsoil conditions that can generate this unwanted condition, and the common field acquisition procedures that can contribute to producing data having such deceptive Rayleigh dispersion characteristics. This mode misidentification depends strongly on the usual approach of measuring only the vertical component of ground motion, as the mode osculation is linked to the Rayleigh wave ellipticity polarization, and therefore we conclude that multicomponent data, using also horizontal receivers, can help discern the multimodal nature of surface waves. Finally, we introduce a priori detectors of subsoil conditions, based on passive microtremor measurements, that can act as warnings against the presence of mode osculation, and relate these detectors to the frequencies at which dispersion curves can be misidentified. Theoretical results are confirmed by real data acquisition tests.

Description: 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.

Description: 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 a 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.

Description: 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.

Description: 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 4-D Electrical Resistivity Tomography (ERT) in conjunction with measurements of plant transpiration via sap flow and evapotranspiration from Eddy Covariance (EC). This abundance of data is fed to a spatially distributed soil model 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 setup, consisting of 48 buried electrodes on 4 instrumented micro boreholes (about 1.2 m deep) placed at the corners of a square (about 1.3 m in side) 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 TDR soil moisture measurements, soil water samples, 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 pore water electrical conductivity. Irrigation, precipitation, sap flow and ET data are available allowing 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 modeling exercise allow the quantification of the soil volume interested by root water uptake. This volume is much smaller (with a surface area less than 2 m2, and about 40 cm thickness) than expected and assumed in the design of classical drip irrigation schemes that prove to be losing at least half of the irrigated water that is not uptaken by the plants.