We provide a database of the coseismic geological surface effects following the Mw 6.5 Norcia earthquake that hit central Italy on 30 October 2016. This was one of the strongest seismic events to occur in Europe in the past thirty years, causing complex surface ruptures over an area of >400 km2. The database originated from the collaboration of several European teams (Open EMERGEO Working Group; about 130 researchers) coordinated by the Istituto Nazionale di Geofisica e Vulcanologia. The observations were collected by performing detailed field surveys in the epicentral region in order to describe the geometry and kinematics of surface faulting, and subsequently of landslides and other secondary coseismic effects. The resulting database consists of homogeneous georeferenced records identifying 7323 observation points, each of which contains 18 numeric and string fields of relevant information. This database will impact future earthquake studies focused on modelling of the seismic processes in active extensional settings, updating probabilistic estimates of slip distribution, and assessing the hazard of surface faulting.

, a moderate earthquake (M w = 6.3; M l = 5.8) struck the Abruzzo region in central Italy, causing more than 300 fatalities and heavy damage to L'Aquila and surrounding villages. Coseismic surface effects have been thoroughly documented by timely field surveys as well as by remote sensing analyses of satellite images. The outstanding quality of geological, seismological, geodetic, and interferometric synthetic aperture radar (InSAR) information arguably represents the best ever data set made available immediately after a moderate seismic event. Based on this data set, we aim at testing the capability of coupled geological and InSAR data to map surface faulting patterns associated with moderate earthquakes. Coseismic ground ruptures have been mapped at a scale of 1:500 in the whole epicentral area. Traces of surface ruptures have been inferred from linear phase discontinuities identified in the interferogram. A very good agreement between the two methods resulted in the characterization of the main surface rupture along the Paganica fault. The same approach applied to ground ruptures hypothesized along other capable fault segments provided more questionable results. Thus, the combined field and InSAR approach appeared useful for detecting continuous surface ruptures exceeding 1 km in length and showing displacements greater than a few centimeters. These are the typical faulting parameters for moderate earthquakes (6.0 < M w < 6.5) in central Apennines. For continuous ground cracks shorter than a few hundred meters and/or that show displacements smaller than 1-2 cm, the described approach may be less helpful, most probably due to the limited resolution of the data.Citation: Guerrieri, L., et al. (2010), InSAR data as a field guide for mapping minor earthquake surface ruptures: Ground displacements along the Paganica Fault during the 6

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Inundation maps are a fundamental tool for coastal risk management and in particular for designing evacuation maps and evacuation planning. These in turn are a necessary component of the tsunami warning systems’ last-mile. In Italy inundation maps are informed by a probabilistic tsunami hazard model. Based on a given level of acceptable risk, Italian authorities in charge for this task recommended to consider, as design hazard intensity, the average return period of 2500 years and the 84th percentile of the hazard model uncertainty. An available, regional-scale tsunami hazard model was used that covers the entire Italian coastline. Safety factors based on analysis of run-up variability and an empirical coastal dissipation law on a digital terrain model (DTM) were applied to convert the regional hazard into the design run-up and the corresponding evacuation maps with a GIS-based approach. Since the regional hazard cannot fully capture the local-scale variability, this simplified and conservative approach is considered a viable and feasible practice to inform local coastal risk management in the absence of high-resolution hazard models. The present work is a first attempt to quantify the uncertainty stemming from such procedure. We compare the GIS-based inundation maps informed by a regional model with those obtained from a local high-resolution hazard model. Two locations on the coast of eastern Sicily were considered, and the local hazard was addressed with the same seismic model as the regional one, but using a higher-resolution DTM and massive numerical inundation calculations with the GPU-based Tsunami-HySEA nonlinear shallow water code. This study shows that the GIS-based inundation maps used for planning deal conservatively with potential hazard underestimation at the local scale, stemming from typically unmodeled uncertainties in the numerical source and tsunami evolution models. The GIS-based maps used for planning fall within the estimated “error-bar” due to such uncertainties. The analysis also demonstrates the need to develop local assessments to serve very specific risk mitigation actions to reduce the uncertainty. More in general, the presented case-studies highlight the importance to explore ways of dealing with uncertainty hidden within the high-resolution numerical inundation models, e.g., related to the crude parameterization of the bottom friction, or the inaccuracy of the DTM.

A primitive cryptodiran turtle, Indochelys spatulata gen. et sp. nov., is described from the Early Jurassic Kota Formation, a member of the Upper Gondwana Group in the Pranhita‐Godavari Valley, Deccan, India. The shell morphology of Indochelys differs substantially from that of the Triassic Proganochelys of Germany but is significantly similar to the oldest known Early Jurassic cryptodire, Kayentachelys, from the Kayenta Formation of Arizona. Indochelys also shares many shell characters with the Late Jurassic North American turtles, in particular Dinochelys. The new family Indochelyidae is proposed, which probably has the same phyletic status as that of Kayentachelyidae, with both evolving simultaneously in different regions.