Three-dimensional model and late stage warping of the Plattengneis Shear Zone in the Eastern Alps

The Plattengneis shear zone is a 250–600 m thick, flat lying, Cretaceous, eclogite facies, mylonitic shear zone, with north-over-south transport direction, that is exposed over almost 1000 km² in the Koralpe region along the eastern margin of the Alps. Although the shear zone is one of the largest in the Alps, its role in the Eoalpine metamorphic evolution and the subsequent exhumation of the region, remain enigmatic and its large-scale geometry is not well understood. The outcrop pattern suggests that the shear zone is made up of a single sheet that is folded into a series of open syn- and antiforms with wavelengths of about 10 km. Eclogite bodies occur above, within and below the shear zone and there is no metamorphic grade change across the shear zone. In the south, the fold axes strike east–west and plunge shallowly to the east. In the north, the fold axes are oriented in north–south direction and form a dome shaped structure of the shear zone. Total shortening during this late stage warping event was of the order of 5%. Indirect evidence constrains this folding event to have occurred between 80 and 50 Ma and the fold geometry implies that the final exhumation in the Koralpe occurred somewhat later than further north. Interestingly, the shear zone appears to strike out of the topography in the south and dip into the topography in the north, so that north of the shear zone only hanging-wall rocks are exposed and south of it only foot-wall rocks. Possibilities for the geometric relationship of the Plattengneis shear zone with the surrounding south dipping detachments are discussed.     

An investigation of upper mantle heterogeneity beneath the Archaean and Proterozoic crust of western Canada from Lithoprobe controlled-source seismic experiments

Observations of upper mantle reflectivity at numerous locations around the world have been linked to the presence of a heterogeneous distribution of rock types within a broad layer of the upper mantle. This phenomenon is observed in wide-angle reflection data from Lithoprobe's Alberta Basement Transect [the SAREX and Deep Probe experiments of 1995] and Trans-Hudson Orogen Transect [the THoRE experiment of 1993]. SAREX and Deep Probe image the Archaean lithosphere of the Hearne and Wyoming Provinces, whereas THoRE images the Archaean and Proterozoic lithosphere of the Trans-Hudson Orogen and neighbouring areas.Finite-difference synthetic seismograms are used to constrain the position and physical properties of the reflective layer. SAREX/Deep Probe modelling uses a 2-D visco-elastic finite-difference routine; THoRE modelling uses a pseudospectral algorithm. In both cases, the upper mantle is parameterized in terms of two media. One medium is the background matrix; the other is statistically distributed within the first as a series of elliptical bodies. Such a scheme is suitable for modelling: (1) variations in lithology (e.g., a peridotite matrix with eclogite lenses) or (2) variations in rheology (e.g., lenses of increased strain within a less strained background).The synthetic seismograms show that the properties of heterogeneities in the upper mantle do not change significantly between the two Lithoprobe transects. Beneath the Trans-Hudson Orogen in Saskatchewan, the layer is best modelled to lie at depths between 80 and 150 km. Based on observations from perpendicular profiles, anisotropy of the heterogeneities is inferred. Beneath the Precambrian domains of Alberta, 400 km to the west, upper mantle heterogeneities are modelled to occur between depths of 90 and 140 km. In both cases the heterogeneous bodies within the model have cross-sectional lengths of tens of kilometers, vertical thicknesses less than 1 km, and velocity contrasts from the background of − 0.3 to − 0.4 km/s. Based on consistency with complementary data and other results, the heterogeneous layer is inferred to be part of the continental lithosphere and may have formed through lateral flow or deformation within the upper mantle.     

A way to synchronize models with seismic faults for earthquake forecasting: Insights from a simple stochastic model

Numerical models are starting to be used for determining the future behaviour of seismic faults and fault networks. Their final goal would be to forecast future large earthquakes. In order to use them for this task, it is necessary to synchronize each model with the current status of the actual fault or fault network it simulates (just as, for example, meteorologists synchronize their models with the atmosphere by incorporating current atmospheric data in them). However, lithospheric dynamics is largely unobservable: important parameters cannot (or can rarely) be measured in Nature. Earthquakes, though, provide indirect but measurable clues of the stress and strain status in the lithosphere, which should be helpful for the synchronization of the models.The rupture area is one of the measurable parameters of earthquakes. Here we explore how it can be used to at least synchronize fault models between themselves and forecast synthetic earthquakes. Our purpose here is to forecast synthetic earthquakes in a simple but stochastic (random) fault model. By imposing the rupture area of the synthetic earthquakes of this model on other models, the latter become partially synchronized with the first one. We use these partially synchronized models to successfully forecast most of the largest earthquakes generated by the first model. This forecasting strategy outperforms others that only take into account the earthquake series. Our results suggest that probably a good way to synchronize more detailed models with real faults is to force them to reproduce the sequence of previous earthquake ruptures on the faults. This hypothesis could be tested in the future with more detailed models and actual seismic data.     

Radiomagnetotelluric mapping, groundwater numerical modelling and 18-Oxygen isotopic data as combined tools to determine the hydrogeological system of a landslide prone area

Three methods were combined to determine the groundwater recharge and transfer processes of a landslide prone area. First, the radiomagnetotelluric method was used to investigate the distribution of electrical resistivity (ρ) of the subsurface and build a three-dimensional model of permeability (k), through an experimental relation between ρ and k. Second, this structural model of permeability and additional climatologic data were used to fix boundary and recharge conditions to perform a three-dimensional and transient numerical simulation of the groundwater flow. Finally 18-Oxygen time series observed at the main springs were used to validate the model. This association of methods led to an improved characterization of the groundwater flow system at local scale and a better understanding of the role of this system on the landslide phenomenon. This structured approach is thought to be useful to design specific remediation strategies to drain the unstable mass.     

Bayesian Spatial Modelling of Gamma Ray Count Data

Gamma ray logging is a method routinely employed by geophysicists and environmental engineers in site geology evaluations. Modelling of gamma ray data from individual boreholes assists in the local identification of major lithological changes; modelling these data from a network of boreholes assists with lithological mapping and spatial stratigraphic correlation. In this paper we employ Bayesian spatial partition models to analyse gamma ray data spatially. In particular, a spatial partition is defined via a Voronoi tessellation and the mean intensity is assumed constant in each cell of the partition. The number of vertices generating the tessellation as well as the locations of vertices are assumed unknown, and uncertainty about these quantities is described via a hierarchical prior distribution. We describe the advantages of the spatial partition modelling approach in the context of smoothing gamma ray count data and describe an implementation that may be extended to the fitting of a more general model than a constant mean within each cell of the partition. As an illustration of the methodology we consider a data set collected from a network of eight boreholes, which is part of a geophysical study to assist in mapping the lithology of a site. Gamma ray logs are linked with geological information from cores and the spatial analysis of log data assists with predicting the lithology at unsampled locations.     

Driving forces of tropical deforestation: The role of remote sensing and spatial models

Remote sensing technologies are increasingly used to monitor landscape change in many parts of the world. While the availability of extensive and timely imagery from various satellite sensors can aid in identifying the rates and patterns of deforestation, modelling techniques can evaluate the socioeconomic and biophysical forces driving deforestation processes. This paper briefly reviews some emerging spatial methodologies aimed at identifying driving forces of land use change and applies one such methodology to understand deforestation in Mexico. Satellite image classification, change analysis and econometric modelling are used to identify the rates, hotspots and drivers of deforestation in a case study of the southern Yucatán peninsular region, an enumerated global hotspot of biodiversity and tropical deforestation. In particular, the relative roles of biophysical and socioeconomic factors in driving regional deforestation rates are evaluated. Such methodological approaches can be applied to other regions of the forested tropics and contribute insights to conservation planning and policy.