2D Self-Potential tomographies for studying groundwater flows in the Varco d'Izzo landslide (Basilicata, southern Italy)

Colangelo, G.; Lapenna, Vincenzo; Perrone, Angela; Piscitelli, S.; Telesca, Luciano

doi:10.1016/j.enggeo.2006.09.014

Cited by 45 publications

(30 citation statements)

References 15 publications

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“…Two-(2D) and threedimensional (3D) SP inversions were found adequate in most cases (e.g. Hämmann et al, 1997;Colangelo et al, 2006;Minsley et al, 2007). The solution to this problem requires developing an efficient inversion algorithm to obtain meaningful intensity and distribution of the subsurface current sources when applied to field data.…”

Section: Introductionmentioning

confidence: 96%

A new inversion algorithm for estimating the best fitting parameters of some geometrically simple body to measured self-potential anomalies

Essa

Mehanee

Smith

2008

Exploration Geophysics

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We have developed a new least-squares inversion approach to determine successively the depth (z), polarization angle, and electric dipole moment of a buried structure from the self-potential (SP) anomaly data measured along a profile. This inverse algorithm makes it possible to use all the observed data when determining each of these three parameters. The problem of the depth determination has been parameterised from the forward modelling operator, and transformed into a nonlinear equation in the form j(z) = 0 by minimising an objective functional in the least-squares sense. Using the estimated depth and applying the least-squares method, the polarization angle is then determined from the entire observed data by a linear formula. Finally, knowing the depth and polarization angle, the dipole moment is expressed by a linear equation and is computed using the whole measured data. This technique is applicable for a class of geometrically simple anomalous bodies, including the semi-infinite vertical cylinder, the infinitely long horizontal cylinder, and the sphere. The method is tested and verified on numerical examples with and without random noise. It is also successfully applied to two real datasets from mineral exploration in Germany and Turkey, and we have found that the estimated depths and the other SP model parameters are in good agreement with the known actual values.

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Section: Introductionmentioning

confidence: 96%

A new inversion algorithm for estimating the best fitting parameters of some geometrically simple body to measured self-potential anomalies

Essa

Mehanee

Smith

2008

Exploration Geophysics

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“…Some examples where geoelectrical data sets are manipulated in bespoke ways do exist, for example, the use of apparent resistivity (Palis, Lebourg, Tric, et al, ), transfer resistance data (Merritt et al, ), and 3‐D ER arrays (Uhlemann et al, ). The use of SP methods is also noted, although in a much reduced capacity to ER (Colangelo et al, ). In total, 20 time‐lapse ER monitoring surveys are identified in the literature: Bièvre et al (), Crawford and Bryson (), Friedel et al (), Gance et al (), Grandjean et al (), Jomard et al (), Lebourg et al (), Lehmann et al (), Lucas et al (), Luongo et al (), Merritt et al (), Palis, Lebourg, Vidal, et al (), Palis, Lebourg, Tric, et al (), Supper et al (), Travelletti et al (), Uhlemann et al (), and Xu et al ().…”

Section: Geophysical Monitoring Of Landslides: Methods and Case Studiesmentioning

confidence: 99%

Geophysical Monitoring of Moisture‐Induced Landslides: A Review

Whiteley

Chambers

Uhlemann

et al. 2019

Reviews of Geophysics

204

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Geophysical monitoring of landslides can provide insights into spatial and temporal variations of subsurface properties associated with slope failure. Recent improvements in equipment, data analysis, and field operations have led to a significant increase in the use of such techniques in monitoring. Geophysical methods complement intrusive approaches, which sample only a very small proportion of the subsurface, and walk-over or remotely sensed data, which principally provide information only at the ground surface. In particular, recent studies show that advances in geophysical instrumentation, data processing, modeling, and interpretation in the context of landslide monitoring are significantly improving the characterization of hillslope hydrology and soil and rock hydrology and strength and their dynamics over time. This review appraises the state of the art of geophysical monitoring, as applied to moisture-induced landslides. Here we focus on technical and practical uses of time-lapse methods in geophysics applied to monitoring moisture-induced landslide. The case studies identified in this review show that several geophysical techniques are currently used in the monitoring of subsurface landslide processes. These geophysical contributions to monitoring and predicting the evolution of landslide processes are currently underrealized. Hence, the further integration of multiple-parametric and geotechnically coupled geophysical monitoring systems has considerable potential. The complementary nature of certain methods to map the distribution of subsurface moisture and elastic moduli will greatly increase the predictive and monitoring capacity of early warning systems in moisture-induced landslide settings. Figure 4. The geophysical methods identified in the 31 case studies, shown by mode of acquisition and method. The acronyms for each method are shown in the lower boxes.

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“…This impediment resulted in five significantly different landslide inventory maps for the corresponding study area, where slope failures damaged several road connections, private homes, and commercial buildings [3][4][5]. At the same time conventional DInSAR techniques might be severely compromised to monitor surface motions in areas where few scatterers or coherent targets exist.…”

Section: Introductionmentioning

confidence: 99%

Intermittent small baseline subset (ISBAS) InSAR analysis to monitor landslides in Costa Della Gaveta, Southern Italy

Novellino

Cigna

Sowter

et al. 2015

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

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This work presents a Differential SAR Interferometry (DInSAR) analysis of slow-moving landslides in Costa della Gaveta (southern Italy) exploiting the improved spatial density of radar targets provided by the novel Intermittent SBAS (ISBAS) algorithm. Several landslides occurred in this area over the past decade, producing a ground displacement of several centimeters and causing unsafe road and rail traffic conditions. In the 2.4 km 2 study area, ISBAS analysis of TerraSAR-X data acquired in 2010-2011 has shown the presence of sixteen phenomena with a southeastern main direction of motion. The DInSAR results agree with both the magnitude and the deformation mechanisms that were mapped during field observations and reported in the geotechnical literature.

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2D Self-Potential tomographies for studying groundwater flows in the Varco d'Izzo landslide (Basilicata, southern Italy)

Cited by 45 publications

References 15 publications

A new inversion algorithm for estimating the best fitting parameters of some geometrically simple body to measured self-potential anomalies

A new inversion algorithm for estimating the best fitting parameters of some geometrically simple body to measured self-potential anomalies

Geophysical Monitoring of Moisture‐Induced Landslides: A Review

Intermittent small baseline subset (ISBAS) InSAR analysis to monitor landslides in Costa Della Gaveta, Southern Italy

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