Arc magmatism in eastern Kumaun Himalaya,India: A study based on geochemistry of granitoid rocks

Petrochemical studies of granitoid rocks from the eastern part of Kumaun region suggest that the leading edge of India represents an active arc during Late Paleoproterozoic times. It has been observed that melt generation for granodiorite rocks from the eastern Almora Nappe and Chhiplakot klippe along with the Askot klippe was caused through a subduction‐related process involving hydrous partial melting of a Paleoproterozoic amphibole‐ and/or garnet‐bearing mafic source with the involvement of sediments from the subduction zone. The medium‐ to high‐K basic rocks, common in subduction‐related magmatic arcs, can also explain the generation of the high‐K granodiorites of the Chhiplakot klippe. The augen gneisses from the eastern Almora nappe and Chhiplakot klippe along with the Askot klippe further show geochemical similarity with the associated granodiorites, suggesting there is a genetic linkage with one another.     

Seasonal deformation regime of rifts in lowland rivers

Various schemes of within-year transformations of rifts from spring flood to low-water period and autumn freshets have been considered. Such transformations have been shown to manifest themselves in the displacement of rift trough from the upper to the lower point bars, accumulation of sediments in one phase of water regime and erosion of ridges in the other phase, as well as in the advancement of ridge-type micro- and meso-forms of channel relief onto rift saddle. Differences have been revealed between the regimes of rifts composed of sand and pebble-boulder sediments; specific features were identified in the regime of rifts in rivers in permafrost zones and rifts with rock protrusions on the bed.     

The Aterno valley strong-motion array: seismic characterization and determination of subsoil model

The paper focuses on the strong motion array deployed in the upper Aterno River Valley, in the immediate outskirts north-west of the town of L’Aquila, which is part of the Italian Strong Motion Network operated by the Department of Civil Protection. The array is composed of six accelerometric stations located along a cross section of the valley. The importance of this array relies on the fact that a large amount of high-quality records were obtained during the 2009 L’Aquila seismic sequence, from both the mainshock and several aftershocks. These data are especially important to investigate site effects in sediment-filled valleys during moderate earthquakes in epicentral area because well-documented observational studies are very limited in the literature. However, the main drawback for the study of site effects in the Aterno valley is the lack of a detailed knowledge of the geometry of the valley, soil layering and dynamic properties of materials. The main motivation for this study stems from the need to provide a reliable subsoil model of the valley coupled with high-quality strong motion data. Based on the above, in the framework of S4 project, a major effort was undertaken to get a trustworthy cross section of the valley by an ad hoc investigation, comprising geological and geotechnical surveys as well as an extensive geophysical campaign, characterized by both active and passive measurements. These results were complemented by additional geological and geotechnical data available in the literature. By merging all the information acquired, a 2D subsoil model of the transversal section of the upper Aterno valley has been produced. The valley is characterised by an asymmetric shape with a shallower rock basement at the western edge of the valley that deepens at the valley centre. Moreover, based on the results of geophysical tests, representative V_s values were assigned to the different lithologic units forming the alluvial deposits filling the valley. Shear wave velocity is a fundamental parameter for ground response studies and it is also effective in classifying the accelerometric station from a seismic point of view. The 2D model may be therefore, considered a benchmark model for future studies of site effects. It will offer the possibility to examine site effects with a complex underlying geology and to validate the results of numerical simulations of site response analyses with the numerous observations from earthquake recordings, both for weak and strong ground motion conditions.     

A model study on the effects of input motion on the seismic behaviour of tunnels

Tunnel behaviour under earthquake loading is affected by many factors such as shape, depth and stiffness of the tunnel lining and the nature of the input motion. However, current knowledge on the effects of these parameters on the seismic behaviour of tunnels is limited to lack of experimental or field data. Existing analytical methods are based on assumptions, the validity of which needs to be established using carefully conducted experimental studies and numerical analyses. This paper focuses on the effects of input motion characteristics on seismic behaviour of circular and square tunnels. Dynamic centrifuge tests were carried out on model tunnels using input motions of different amplitude and frequency. Accelerations and earth pressures around the tunnels were measured. Complementary Finite Element analyses were conducted with different types of input motions. Results show that magnitude of the maximum input acceleration plays a crucial role on the maximum and residual lining forces, which the tunnel experiences.     

Stochastic evaluation of simple pairing approaches to reconstruct incomplete rainfall time series

Two-station pairing approaches are routinely used to infill missing information in incomplete rainfall databases. We evaluated the performance of three simple methodologies to reconstruct incomplete time series in presence of variable nonlinear correlation between data pairs. Nonlinearity stems from the statistics describing the marginal peak-over-threshold (POT) values of rainfall events. A Monte Carlo analysis was developed to quantitatively assess expected errors from the use of chronological pairing (CP) with linear and nonlinear regression and frequency pairing (FP). CP is based on a priori selection of regression functions, while FP is based on matching the probability of non-exceedance of an event from one time series with the probability of non-exceedance of a similar event from another time series. We adopted a generalized Pareto (GP) model to describe POT events, and a t-copula algorithm to generate reference nonlinearly correlated pairs of random temporal distributions distributed according with the GP model. The results suggest that the optimal methodology strongly depends on GP statistics. In general, CP seems to provide the lowest errors when GP statistics were similar and correlation became linear; we found that a power-2 function performs well for the selected statistics when the number of missing points is limited. FP outperforms the other methods when POT statistics are different and variables are markedly nonlinearly correlated. Ensemble-based results seem to be supported by the analysis of observed precipitation at two real-world gauge stations.