1,721,066 research outputs found
Georadar measurements for the snow cover density
Full text linkGround Probing Radar (GPR) devices is adopted for the analysis of thickness and the mechanical properties (density) of the snow cover in some test site in Alps, in Northern Italy. The performances of standard radar systems for the snow cover characterisation are analysed, the main aim is to assess the reliability of the method to estimate the snow density, the snowpack thickness and the depth resolution in terms of capability to detect thin layers. The main relationships between the electrical permittivity and the density of the dry-snow are applied to estimate the density vertical profiles inferred by the GPR investigation. The data were calibrated and compared with the results coming from direct measurements of the density and thickness. © 2009 Science Publications
An overview on cryogeophysics in the alpine environment
Full text linkGeophysics allows us to characterise glaciers and snow properties in order to evaluate the hazard associated with the evolution of the snow/ice masses. The danger is often associated with recent phenomena of rapid deglaciation with consequent collapses of ice and rock, or with releases of water contained in the glaciers. The morphology of the rock substrate and the presence of various kinds of conduits and cavities, making up the internal hydrological network, can be investigated by seismic and radar methods; the presence of water in internal cavities of temperate glaciers can be successfully detected through georadar measurements. In the nivological context, the geophysical approach, adopting seismic and electromagnetic methods, can serve as a tool to characterise and monitor some physical properties of the snowpack. The evaluation of these parameters makes it possible to estimate the risk and the imminence associated with the snow-gliding avalanche release. We discuss the basic theoretical background of the relationships between geophysical investigated parameters and ice/snow properties; moreover, we illustrate some examples of applications of seismic and electromagnetic methods to detect the snow and ice properties in high elevation Alpine regions
Analysis of borehole guided waves for geotechnical application
Full text linkThe reliability of Stoneley waves (SWs) is discussed for the characterisation of the mechanical properties of soft and hard rock in borehole seismic techniques using source on the surface and hydrophones as receivers. The SWs propagate along the fluid-filled borehole; the propagation is affected by the mechanical and hydraulic properties of the fluid and the surrounding medium. At low frequencies, in a non-diffusive medium (impermeable formation), the wave velocity depends on the density, the wave velocity of the fluid and the shear modulus of the formation. The models adopted to infer the wave velocity in elastic formations in uncased and cased boreholes are discussed. We discuss two examples to check the discrepancies between the theoretical and the experimental evidence. The presence of casing in soft rock greatly reduces the sensitivity of the SW propagation to the mechanical properties of the medium. In hard rock, the scattering of the primary wavefields could be adopted to detect the presence of rock mass discontinuities (fractures). © 2007 - OGS
Analysis of GPR Data for Snow Water Equivalent
No full textGPR permits to map over large the thickness and density of snow pack: these parameters are required when the snow water equivalent has to be estimated. The results of GPR, conducted on a slope in the Alps in Northern Italy, are discussed. The data acquisition along several profiles was repeated in different period of the winter season. The GPR data were calibrated with direct observations of density and thickness of the snow cover: this led to estimate the average wave velocity of the snow pack. When the snow is in dry conditions, the wave velocity values can be converted in density values using simple mixing rules. The good accuracy in the estimate of the average density and snow pack thickness by combining electromagnetic data permits to assess the effectiveness of the approach for the snow water equivalent analysis.Copyright 2008, European Association of Geoscientists and Engineers
Laboratory testing of FBGs for pipeline monitoring
Full text linkThe monitoring of the effects of geohazards on pipelines can be addressed by optical fiber Bragg gratings (FBGs). They are sensitive to strain and bending, and are installed on the external surface of pipelines at discrete locations. A joint approach of theoretical analysis and laboratory experiments is useful to check the reliability of the performance of this technology. We focus on the theoretical analysis of pipeline buckling and investigate the reliability of FBG monitoring both by examining the analytical model available and by performing a laboratory-scale experiment. The novelty lies in the analysis of models and methods originally developed for the detection of pipeline upheaval buckling caused by externally imposed forces in the context of service loads (temperature). Although thermal strain is very relevant in view of its potentially disruptive effects on both pipelines and the FBG response, it has not been yet fully investigated. We point out the merits of the approach, such as the functionality and simplicity of design, the accessibility and inexpensiveness of materials, the controllability and repeatability of processes, the drawbacks are also described, such as temperature effects, the problem of slipping of gages and the challenge of performing quasi-distributed strain measurements
Ambient seismic noise and microseismicity monitoring of a prone-to-fall quartzite tower (Ormea, NW Italy)
Full text linkRemote sensing techniques are leading methodologies for landslide characterization and monitoring. However, they may be limited in highly vegetated areas and do not allow for continuously tracking the evolution to failure in an early warning perspective. Alternative or complementary methods should be designed for potentially unstable sites in these environments. The results of a six-month passive seismic monitoring experiment on a prone-to-fall quartzite tower are here pre-sented. Ambient seismic noise and microseismicity analyses were carried out on the continuously recorded seismic traces to characterize site stability and monitor its possible irreversible and reversible modifications driven by meteorological factors, in comparison with displacement measured on site. No irreversible modifications in the measured seismic parameters (i.e., natural resonance fre-quencies of the tower, seismic velocity changes, rupture-related microseismic signals) were detected in the monitored period, and no permanent displacement was observed at the tower top. Results highlighted, however, a strong temperature control on these parameters and unusual preferential vibration directions with respect to the literature case studies on nearly 2D rock columns, likely due the tower geometric constraints, as confirmed by 3D numerical modeling. A clear correlation with the tower displacement rate was found in the results, supporting the suitability of passive seismic monitoring systems for site characterization and early waning purposes
Special Issue “Remote Sensing in Applied Geophysics”
Full text linkThe Special Issue "Remote Sensing in Applied Geophysics" is focused on recent and upcoming advances in the combined application of remote sensing and applied geophysics techniques, sharing the advantages of being non-invasive research methods, suitable for surface and near-surface high-resolution investigations of even wide and remote areas. Applied geophysics analyzes the distribution of physical properties in the subsurface for a wide range of geological, engineering and environmental applications at different scales. Geophysical surveys are usually carried out deploying or moving the appropriate instrumentation directly on the ground surface. However, recent technological advances have brought to the development of innovative acquisition systems more typical of the remote sensing community (e.g., airborne surveys and unmanned aerial vehicle systems). At the same time, while applied geophysics mainly focuses on the subsurface, typical remote sensing techniques have the ability to accurately image the Earth's surface with high-resolution investigations carried out by means of terrestrial, airborne, or satellite-based platforms. The integration of surface and subsurface information is often crucial for several purposes, including the georeferencing and processing of geophysical data, the characterization and time-lapse monitoring of surface and near-surface targets, and the reconstruction of highly detailed and comprehensive 3D models of the investigated areas. Contributions to the issue showing the added value of surface reconstruction and/or monitoring in the processing and interpretation of geophysical data, integration and cross-comparison of geophysical and remote sensing techniques were required to the research community. Contributions discussing the results of pioneering geophysical acquisitions by means of innovative remote systems were also addressed as interesting topics. The Special Issue received great attention in the combined community of applied geophysicists and remote sensing researchers. A total of 15 papers are included in the Special Issue, covering a wide range of applications. This is one of the highest number of papers among the Remote Sensing Special Issues, showing great interest in the proposed topic. The relevant number of contributions also highlights the relevance and increasing need for integration between remote sensing and ground-based geophysical exploration or monitoring methods. In particular, one of the main fields of research showing the potential integration of the geophysical and remote sensing techniques is archaeological exploration
On the optimization of electromagnetic geophysical data: Application of the PSO algorithm
No full textParticle Swarm optimization (PSO) algorithm resolves constrained multi-parameter problems and is suitable for simultaneous optimization of linear and nonlinear problems, with the assumption that forward modeling is based on good understanding of ill-posed problem for geophysical inversion.
We apply PSO for solving the geophysical inverse problem to infer an Earth model, i.e. the electrical resistivity at depth, consistent with the observed geophysical data.
The method doesn't require an initial model and can be easily constrained, according to external information for each single sounding.
The optimization process to estimate the model parameters from the electromagnetic soundings focuses on the discussion of the objective function to be minimized. We discuss the possibility to introduce in the objective function vertical and lateral constraints, with an Occam-like regularization. A sensitivity analysis allowed us to check the performance of the algorithm. The reliability of the approach is tested on synthetic, real Audio-Magnetotelluric (AMT) and Long Period MT data. The method appears able to solve complex problems and allows us to estimate the a posteriori distribution of the model parameters
Geophysical Recipe to Model the Covid-19 Epidemic
No full textThe coronavirus pneumonia epidemic, caused by SARS-CoV-2, was classified by the World Health
Organization as a public health emergency of international concern on January 30th, 2020. The new
SARS-CoV-2 was named coronavirus disease 2019 (COVID-19). Countries have reacted with different
actions to control the source of infection, to inhibit the way of transmission and to protect the susceptible
population. Italy has been strongly impacted by the diffusion of the contagion with about 30000
fatalities at mid-May 2020.
The SEIR (Susceptible-Exposed-Infectious-Removed) model predicts the time-evolution of the
epidemic phenomenon, based on the analysis of the infection and recovery rates. The prediction is based
on the solution of a system of differential equations, usually solved according to a deterministic method.
We propose a probabilistic approach, often used in geophysics, to solving the SEIR model of COVID19 epidemic diffusion in Italy and in its most impacted northern regions. Particularly, we solve the
differential equations of the SEIR model by adopting a metaheuristic method, the Particle Swarm
Optimization (PSO) algorithm, belonging to the family of computational swarm intelligence (Kennedy
and Eberhart, 1995). The similarities with geophysical problems are many: the geophysical measures
are replaced by official data on the spread of the infection, there is a consolidated predictive model and
the goal is to estimate the model coefficients, in order to satisfy the experimental data. Like the
geophysical inverse problem, the SEIR differential equations represent an ill-posed problem, whose
solution is not unique. The advantage of the PSO approach is that the adaptive exploration of the space
domain of the solutions decreases the risk of being trapped into a local minimum and it iteratively
searches for the global minimum as the final solution. Moreover, the PSO method provides several
scenarios so that the a-posteriori reliability of the model-solution can be evaluated (Godio and Santilano,
2018). The modelling was carried out by using observed data up to the mid of April with a 30-day
prediction
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