Do landslides follow landslides? Insights in path dependency from a multi-temporal landslide inventory

Landslides are a major category of natural disasters, causing loss of lives, livelihoods and property. The critical roles played by triggering (such as extreme rainfall and earthquakes), and intrinsic factors (such as slope steepness, soil properties and lithology) have previously successfully been recognized and quantified using a variety of qualitative, quantitative and hybrid methods in a wide range of study sites. However, available data typically do not allow to investigate the effect that earlier landslides have on intrinsic factors and hence on follow-up landslides. Therefore, existing methods cannot account for the potentially complex susceptibility changes caused by landslide events. In this study, we used a substantially different alternative approach to shed light on the potential effect of earlier landslides using a multi-temporal dataset of landslide occurrence containing 17 time slices. Spatial overlap and the time interval between landslides play key roles in our work. We quantified the degree to which landslides preferentially occur in locations where landslides occurred previously, how long such an effect is noticeable, and how landslides are spatially associated over time. We also investigated whether overlap with previous landslides causes differences in landslide geometric properties. We found that overlap among landslides demonstrates a clear legacy effect (path dependency) that has influence on the landslide affected area. Landslides appear to cause greater susceptibility for follow-up landslides over a period of about 10  years. Follow-up landslides are on average larger and rounder than landslides that do not follow earlier slides. The effect of earlier landslides on follow-up landslides has implications for understanding of the landslides evolution and the assessment of landslide susceptibility.     

Pan-European ground-motion prediction equations for the average horizontal component of PGA,PGV, and 5 %-damped PSA at spectral periods up to 3.0 s using the RESORCE dataset

This article presents a set of Ground-Motion Prediction Equations (GMPEs) for Europe and the Middle East, derived from the RESORCE strong motion data bank, following a standard regression approach. The parametric GMPEs are derived for the peak ground acceleration, peak ground velocity, and 5 %-damped pseudo-absolute acceleration response spectra computed over 23 periods between 0.02 and 3 s, considering the average horizontal-component ground-motions. The GMPEs are valid for distances less than 300 km, hypocentral depth up to 35 km and over the magnitude range 4–7.6. Two metrics for the source-to-station distance (i.e. Joyner-Boore and hypocentral) are considered. The selected dataset is composed by 2,126 recordings (at a period of 0.1 s) related to 365 earthquakes, that includes strong-motion data from 697 stations.The EC8 soil classification (four classes from A to D) discriminates recording sites and four classes (normal, reverse, strike-slip, and unspecified) describe the style of faulting. A subset which contains only stations with measured Vs30 and earthquakes with specified focal mechanism (1,224 records from 345 stations and 255 earthquakes) is used to test of the accuracy of the median prediction and the variability associated to the broader data set. A random effect regression scheme is applied and bootstrap analyses are performed to estimate the 95 % confidence levels for the parameters. The total standard deviation sigma is decomposed into between-events and within-event components, and the site-to-site component is evaluated as well. The results show that the largest contribution to the total sigma is coming from the within-event component. When analyzing the residual distributions, no significant trends are observed that can be ascribed to the earthquake type (mainshock-aftershock classification) or to the non-linear site effects. The proposed GMPEs have lower median values than global models at short periods and large distances, while are consistent with global models at long periods $(\hbox {T} > 1)$  s. Consistency is found with two regional models developed for Turkey and Italy, as the considered dataset is dominated by waveforms recorded in these regions.     

Performance of masonry buildings during the Emilia 2012 earthquake

The earthquake sequence started on May \(20\) th 2012 in Emilia (Italy) affected a region where masonry constructions represent a large part of the existing building stock and the construction of new modern masonry buildings is a common practice. The paper is focused on the performance of common architectural configurations, typical for residential or business use. The large majority of old masonry buildings is made of fired clay bricks. The seismic performance of these buildings is particularly interesting since major past earthquakes in Italy affected areas with mainly stone masonry structures. Apart from examples showing systematic or peculiar structural deficiencies governing the vulnerability of several buildings, the overall seismic performance of these structures to repeated shaking, with PGA as large as 0.25–0.3 g was rather good, despite the major part of them were only conceived for carrying vertical loads. In fact, seismic design is mandatory in the area only since 2003. Modern low-rise masonry buildings erected after this date and incorporating seismic design and proper detailing resulted in most cases practically undamaged. The examples reported in the paper allow an evaluation of the superior performance of seismically designed modern masonry buildings in comparison to older ones.     

Nonlinear seismic behaviour of wall-frame dual systems accounting for soil–structure interaction

The aim of this paper is to study the effects of soil–structure interaction on the seismic response of coupled wall-frame structures on pile foundations designed according to modern seismic provisions. The analysis methodology based on the substructure method is recalled focusing on the modelling of pile group foundations. The nonlinear inertial interaction analysis is performed in the time domain by using a finite element model of the superstructure. Suitable lumped parameter models are implemented to reproduce the frequency-dependent compliance of the soil-foundation systems. The effects of soil–structure interaction are evaluated by considering a realistic case study consisting of a 6-storey 4-bay wall-frame structure founded on piles. Different two-layered soil deposits are investigated by varying the layer thicknesses and properties. Artificial earthquakes are employed to simulate the earthquake input. Comparisons of the results obtained considering compliant base and fixed base models are presented by addressing the effects of soil–structure interaction on displacements, base shears, and ductility demand. The evolution of dissipative mechanisms and the relevant redistribution of shear between the wall and the frame are investigated by considering earthquakes with increasing intensity. Effects on the foundations are also shown by pointing out the importance of both kinematic and inertial interaction. Finally, the response of the structure to some real near-fault records is studied. Copyright © 2012 John Wiley & Sons, Ltd.     

Paleomagnetic dating of the most recent silicic eruptive activity at Pantelleria (Strait of Sicily)

We report on the paleomagnetism of ten sites in the products of the most recent silicic eruptive cycle of Pantelleria, Strait of Sicily. Previously radiometrically dated at 5–10 ka, our comparison with proxies for geomagnetic field directions allows us to narrow considerably the time window during which these eruptions occurred. The strongly peralkaline composition causes the magmas to have low viscosities, locally resulting in strong agglutination of proximal fall deposits. This allows successful extraction of paleomagnetic directions from the explosive phases of eruptions. One of our sites was located in the Serra della Fastuca fall deposit, produced by the first explosive event of the eruptive cycle. The other nine sites were located in the most recent explosive (pumice fall and agglutinate from Cuddia del Gallo and Cuddia Randazzo) and effusive (Khaggiar lava) products. The (very similar) paleomagnetic directions gathered from eight internally consistent sites were compared to reference geomagnetic field directions of the last 5–10 ka. Directions from Cuddia del Gallo agglutinate and Khaggiar flows translate into 5.9- to 6.2-ka ages, whereas the Fastuca pumices yield a slightly older age of 6.2–6.8 ka. Hence, the most recent silicic eruptive cycle lasted at most a millennium and as little as a few centuries around 6.0 ka. Paleomagnetically inferred ages are in good agreement with published (and calibrated by us) ¹⁴C dates from paleosols/charcoals sampled below the studied volcanic units, whereas K/Ar data are more scattered and yield ∼30% older ages. Our data show that the time elapsed since the most recent silicic eruptions at Pantelleria is comparable to the quiescence period separating the two latest volcanic cycles.     

Seismic fragility curves of as-built single-span masonry arch bridges

Masonry arch bridges are crucial elements in the railway transportation network throughout Europe. Although significant advances in seismic risk assessment of various bridge types have been made by developing fragility curves of generalized classes of structures, there are no comparable tools for masonry arch structures. In this context, this paper presents the construction of seismic fragility curves of single-span masonry bridges according to the limit analysis method. An iterative procedure is implemented to define the capacity curve of the equivalent single degree of freedom system through non-linear kinematic analysis. The process involves determination of the collapse mechanism, calculation of the limit load multiplier, and definition of the thrust line. The intrinsic variability of the seismic action is incorporated with the use of different sets of elastic spectra compatible with EC 8 Type-1 spectrum for various types of soil, with peak ground acceleration varying over the range 0.05–1.5 g. The fragility curves of the generalized classes of single-span masonry bridges are finally obtained from the effective ranges of the main geometric and material parameters affecting arch bridge capacity.     

Landslide HotSpot Mapping by means of Persistent Scatterer Interferometry

Landslide detection and mapping represent fundamental requirements for every hazard and risk evaluation and consequent improvement of the management strategies for such natural hazards. Optical and radar remote sensing can be used to observe landslide-induced ground deformation, ranging from regional to local scales. This work presents a methodology called Landslide HotSpot Mapping; this approach integrates cartographic, thematic and optical data with Persistent Scatterer Interferometry for the identification of extremely slow to very slow moving landslides, and for the evaluation of their state of activity and intensity. This methodology scans wide areas to detect hotspots, which are narrow unstable zones characterized by higher landslide hazard. To these hotspots, priority has to be given when planning field surveys and in situ validation campaigns, so that field work time and effort can be optimized and significantly reduced. The approach is tested in Central Calabria, over a 4,470?km² area located in southern Italy. ENVISAT ascending images acquired between 2003 and 2009 and processed with the Persistent Scatterer Pairs (PSP) technique are used to analyse deformation patterns. Combining conventional photo-interpretation with the analysis of PSP data, 64 new landslides are identified and the spatial (boundaries) and temporal (activity) information of 980 pre-mapped phenomena (23.6% of updated inventory) are updated. 1,012 active (continuous or reactivated) landslides are identified and 4 hotspot areas selected: San Fili, Rende, Lago, Catanzaro. Urgent field checks have to be organized for these hotspots to validate the satellite-based observations and to design appropriate mitigation measures to reduce impacts on the elements at risk.     

Engineering ground motion record selection in the ITalian ACcelerometric Archive

This paper introduces REXELite, an internet version of REXEL, a software for automatic selection of ground motion suites for nonlinear dynamic analysis of structures. REXELite was developed with the aim of integrating an advanced earthquake records’ repository, such as the ITalian ACcelerometric Archive (ITACA), with a tool to define seismic input for engineering seismic analysis according to international standards (with priority to Europe). In fact, REXELite allows to define target design spectra according either to Eurocode 8 or to the Italian building code, and to search ITACA for suitable sets of seven records (comprised of one or two horizontal ground motion components) matching such target spectra: on average, in a user-specified period range, and with the desired tolerance. The records in the set also have, individually and according to some criteria, the most similar spectral shape with respect to that of the code. Selection options include magnitude, source-to-site distance, soil conditions and, if desired, linear scaling of records to reduce further record-to-record variability of the selected suite.     

Ground motion prediction equations derived from the Italian strong motion database

We present a set of ground motion prediction equations (GMPEs) derived for the geometrical mean of the horizontal components and the vertical, considering the latest release of the strong motion database for Italy. The regressions are performed over the magnitude range 4?C6.9 and considering distances up to 200?km. The equations are derived for peak ground acceleration (PGA), peak ground velocity (PGV) and 5%-damped spectral acceleration at periods between 0.04 and 2?s. The total standard deviation (sigma) varies between 0.34 and 0.38?log₁₀ unit, confirming the large variability of ground shaking parameters when regional data sets containing small to moderate magnitude events (M?<?6) are used. The between-stations variability provides the largest values for periods shorter than 0.2?s while, for longer periods, the between-events and between-stations distributions of error provide similar contribution to the total variability.