The Lemnos 8 January 2013 (M w = 5.7) earthquake: fault slip,aftershock properties and static stress transfer modeling in the north Aegean Sea

We investigate mainshock slip distribution and aftershock activity of the 8 January 2013 M _w?=?5.7 Lemnos earthquake, north Aegean Sea. We analyse the seismic waveforms to better understand the spatio-temporal characteristics of earthquake rupture within the seismogenic layer of the crust. Peak slip values range from 50 to 64 cm and mean slip values range from 10 to 12 cm. The slip patches of the event extend over an area of dimensions 16?×?16 km². We also relocate aftershock catalog locations to image seismic fault dimensions and test earthquake transfer models. The relocated events allowed us to identify the active faults in this area of the north Aegean Sea by locating two, NE–SW linear patterns of aftershocks. The aftershock distribution of the mainshock event clearly reveals a NE–SW striking fault about 40 km offshore Lemnos Island that extends from 2 km up to a depth of 14 km. After the mainshock most of the seismic activity migrated to the east and to the north of the hypocenter due to (a) rupture directivity towards the NE and (b) Coulomb stress transfer. A stress inversion analysis based on 14 focal mechanisms of aftershocks showed that the maximum horizontal stress is compressional at N84°E. The static stress transfer analysis for all post-1943 major events in the North Aegean shows no evidence for triggering of the 2013 event. We suggest that the 2013 event occurred due to tectonic loading of the North Aegean crust.     

Numerical Modeling of Sediment Mass Sliding and Tsunami Generation: The Case of February 7, 1963, in Corinth Gulf,Greece

Numerical modeling of a landslide process at the continental slope by taking into account slope parameters is performed for the tsunami event of February 7, 1963, reported in the Corinth Gulf, central Greece. A layered sediment structure was considered, and an initial external dynamic action at the landslide process was introduced. The results obtained were quite consistent with the observational runup data as well as with the results arrived at by conventional rigid-body and viscous-fluid models. However, this approach permits to describe in detail the formation of several wave groups and particular tsunami characteristics that are strongly dependent on the landslide model.     

Bounding surface plasticity model for the seismic liquefaction analysis of geostructures

This paper presents the constitutive relations and the simulative potential of a new plasticity model developed mainly for the seismic liquefaction analysis of geostructures. The model incorporates the framework of critical state soil mechanics, while it relies on bounding surface plasticity with a vanished elastic region to simulate the non-linear soil response. Key constitutive ingredients of the new model are: (a) the inter-dependence of the critical state, the bounding and the dilatancy (open cone) surfaces on the basis of the state parameter ψ, (b) a (Ramberg–Osgood type) non-linear hysteretic formulation for the “elastic” strain rate, (c) a discontinuously relocatable stress projection center related to the “last” load reversal point, which is used for mapping the current stress point on model surfaces and as a reference point for introducing non-linearity in the “elastic” strain rate and finally (d) an empirical index of the directional effect of sand fabric evolution during shearing, which scales the plastic modulus. In addition, the paper outlines the calibration procedure for the model constants, and exhibits its accuracy on the basis of a large number of laboratory element tests on Nevada sand. More importantly, the paper explores the potential of the new model by presenting simulations of the VELACS centrifuge tests of Models No 1 and 12, which refer to the free-field liquefaction response of Nevada sand and the seismic response of a rigid foundation on the same sand, respectively. These simulations show that the new model can be used successfully for the analysis of widely different boundary value problems involving earthquake soil liquefaction, with the same set of model constants calibrated on the basis of laboratory element tests.     

Comparison of ten notable meteorological drought indices on tracking the effect of drought on streamflow

ABSTRACT

Ten notable meteorological drought indices were compared on tracking the effect of drought on streamflow. A 730-month dataset of precipitation, temperature and evapotranspiration for 88 catchments in Oregon, USA, representing pristine conditions, was used to compute the drought indices. These indices were correlated with the monthly streamflow datasets of the minimum, maximum and mean discharge, and the discharge monthly fluctuation; it was revealed that the 3-month Z-score drought index (Z3) has the best association with the four streamflow variables. The Mann-Kendall trend detection test applied to the latter index time series mainly highlighted a downward trend in the autumn and winter drought magnitude (DM) and an upward trend in the spring and summer DM (p = 0.05). Finally, the Pettitt test indicated an abrupt decline in the annual and autumn DM, which began in 1984 and 1986, respectively.     

Potentiality of feed-forward neural networks for classifying dark formations to oil spills and look-alikes

Radar backscatter values from oil spills are very similar to backscatter values from very calm sea areas and other ocean phenomena. Several studies aiming at oil spill detection have been conducted. Most of these studies rely on the detection of dark areas, which have high Bayesian probability of being oil spills. The drawback of these methods is a complex process, mainly because non-linearly separable datasets are introduced in statistically based decisions. The use of neural networks (NNs) in remote sensing has increased significantly, as NNs can simultaneously handle non-linear data of a multidimensional input space. In this article, we investigate the ability of two commonly used feed-forward NN models: multilayer perceptron (MLP) and radial basis function (RBF) networks, to classify dark formations in oil spills and look-alike phenomena. The appropriate training algorithm, type and architecture of the optimum network are subjects of research. Inputs to the networks are the original synthetic aperture radar image and other images derived from it. MLP networks are recognized as more suitable for oil spill detection.     

Factors Affecting Differential Settlements of Framed Structures

The estimation of settlements, differential settlements and relative rotations on critical positions of the foundation is indispensable when carrying out analyses of both ultimate and serviceability limit states. The use of finite element method is recommended in cases where soil?Cstructure interaction is expected to be significant. The scope of this paper is a contribution to the investigation of general trends in the effects of main parameters on the interaction. A typical five-span frame building with varying rigidity was examined by using finite element numerical method under 2-D conditions. Soil below the foundation was simulated as linearly elastic or elastoplastic medium. The effects of superstructure and foundation rigidity are closely related to the effect of soil deformability thereby analyses were performed in terms of relative rigidity factors. The effects of specific foundation types, namely isolated footings, flexible and rigid mat, were investigated in detail. The conclusions were focused on the development of normalized differential settlements, on the influence of the relative rigidity factor as well as on the determination of those cases where the interaction approach is necessary to be used for the analysis.     

Factors affecting the distribution of potentially toxic elements in surface soils around an industrialized area of northwestern Greece

In order to investigate the factors influencing the distribution of 32 potentially toxic elements in the Ptolemais–Kozani basin, northwestern Greece, 38 soil samples were collected and analyzed. Concentrations of Al, Ca, Fe, K, Mg, Mn, Na, P, Ti, Ba, Co, Cr, Cu, La, Li, Ni, Pb, Sc, Sr, V, Y, and Zn were determined by ICP-AES and concentrations of As, Bi, Cd, Cs, Mo, Rb, Sb, Th, Tl, and U by ICP-MS. Bivariate analysis, principal component analysis, and geostatistical analysis were employed to investigate the factors influencing the distribution of the elements determined in the study area. The results indicate that the distribution of the majority of elements determined, especially for Cr, Ni, and associated elements, is greatly influenced by the geology and geomorphology of the study area. Principal component analysis has yielded four factors that explain over 77% of the total variance in the data. These factors are as follows: lithophilic elements that are associated with Al silicates minerals of K (factor I: 29.4%), ultramafic rocks (factor II: 20.5%), elements that are coprecipitated with Fe and Mn oxides (factor III: 18.0%), and anthropogenic activities (factor IV: 9.3%). The anthropogenic activities that influence the distribution of several potentially toxic elements (i.e., Cd, Cu, Pb, Zn) are agricultural practices and the deposition of fly ash in the vicinity of the local power stations.     

An algorithm for fast 3D inversion of surface electrical resistivity tomography data: application on imaging buried antiquities

In this work a new algorithm for the fast and efficient 3D inversion of conventional 2D surface electrical resistivity tomography lines is presented. The proposed approach lies on the assumption that for every surface measurement there is a large number of 3D parameters with very small absolute Jacobian matrix values, which can be excluded in advance from the Jacobian matrix calculation, as they do not contribute significant information in the inversion procedure. A sensitivity analysis for both homogeneous and inhomogeneous earth models showed that each measurement has a specific region of influence, which can be limited to parameters in a critical rectangular prism volume. Application of the proposed algorithm accelerated almost three times the Jacobian (sensitivity) matrix calculation for the data sets tested in this work. Moreover, application of the least squares regression iterative inversion technique, resulted in a new 3D resistivity inversion algorithm more than 2.7 times faster and with computer memory requirements less than half compared to the original algorithm. The efficiency and accuracy of the algorithm was verified using synthetic models representing typical archaeological structures, as well as field data collected from two archaeological sites in Greece, employing different electrode configurations. The applicability of the presented approach is demonstrated for archaeological investigations and the basic idea of the proposed algorithm can be easily extended for the inversion of other geophysical data.     

Contribution of geophysical methods to karst-system exploration: an overview

The karst environment is one of the most challenging in terms of groundwater, engineering and environmental issues. Geophysical methods can provide useful subsurface information in karst regions concerning, for instance, hazard estimation or groundwater exploration and vulnerability assessment. However, a karst area remains a very difficult environment for any geophysical exploration; selection of the best-suited geophysical method is not always straightforward, due to the highly variable and unpredictable target characteristics. The state of the art is presented, in terms of the contributions made by geophysical methods to karst-system exploration, based on extensive analysis of the published scientific results. This report is an overview and should be used as a preliminary methodological approach, rather than a guideline.