Hearing impairment is the most common inherited human sensory defect. Nonsyndromic Hearing Impairment (NSHI) is the most genetically heterogeneous trait known. Over 70 loci have been mapped and a total of 19 genes have been identified. We report here a novel locus (DFNA 30) for autosomal dominant NSHI that we mapped to chromosome 15q25-26 in an Italian four-generation family. The haplotype analysis has identified a critical interval of 18 cM between markers D15S151 and D15S130. This region does not overlap with DFNB16 locus but partially coincides with the otosclerosis (OTS) locus. Localisation of the locus DFNA30 is a first step towards the identification of the gene. European Journal of Human Genetics (2001) 9, 667 ± 671.

Propagation models can study the runout and deposit of potential flow-like landslides only if a reliable estimate of the shape and size of the volumes involved in the phenomenon is available. This aspect becomes critical when a collapse has not yet occurred and the estimation of the unstable volume is not uniquely predictable. This work proposes a strategy to overcome this problem, using two established analysis methods in sequence; first, a Strength Reduction Method (SRM)-based 3D FEM allows the estimate of the instable volume; then, this data becomes an input for a Smoothed Particle Hydrodynamics (SPH)-based model. This strategy is applied to predict the possible evolution of Sant’Andrea landslide (North-Eastern Italian Alps). Such a complex landslide, which affects anhydrite–gypsum rocks and is strongly subject to rainfall triggering, can be considered as a prototype for the use of this procedure. In this case, the FEM–SRM model is adopted, which calibrates using mapping, monitoring, geophysical and geotechnical data to estimate the volume involved in the potential detachment. This volume is subsequently used as the input of the SPH model. In this second phase, a sensitivity analysis is also performed to complete the evaluation of the most reliable final soil deposits. The performed analyses allow a satisfactory prediction of the post-collapse landslide evolution, delivering a reliable estimate of the volumes involved in the collapse and a reliable forecast of the landslide runout.

The risk assessment of a rapid landslide is a difficult topic, even if based on the results of numerical analyses. The hypotheses on which every model is developed, the choice of rheological laws to be adopted, and the selection of soil parameters make the simulation results highly dependent on the user. This is particularly evident when there is no model calibration for the specific site or reliable information on soil properties. The paper presents a forecasting process obtained using a Monte Carlo approach in coupling with a propagation model developed with the SPH integration technique. The Monte Carlo analysis allows automatically carrying out a large number of simulations, each performed using an independent parameter set randomly selected within a priori assigned statistical distributions. The numerical results are then analysed with statistical tools to create a risk map based of the frequency of the unstable mass runouts. In this way, it is possible to reduce the user dependence of results and increase the examined potential scenarios. The procedure is here applied to the case study of the Sant’Andrea landslide, a slope movement active since several decades in the municipality of Perarolo di Cadore (Belluno, Italy). This complex slide involves an about 30 m-thick deposit of calcareous debris overlying anhydrite-gypsum rocks. Depending on the intensity and duration of rain, the slope alternates phases characterized by slow displacements and significant accelerations, then followed by a long relaxation period in which the displacement rate slowly regresses, without returning to the previous condition of movement. In recent years, the landslide activity has caused a progressive enlargement of the unstable area and a gradual increase of the basal rate, thus increasing the risk that the landslide may suddenly undergo to the collapse. Moving from the knowledge of the unstable volume, an SPH propagation model is used to study the area affected by the debris-flow runout. In particular, the analysis aims to define a statistical strategy to perform and interpret a large number of simulations and to create the consequent risk map. The analyses carried out lead to a satisfactory interpretation of the spatial variability of the deposit heights referred to the post-failure conditions, useful for the development of a risk analysis, from which a site risk map can be obtained.

A new method for measuring spatially dense surface displacements of a landslide at daily intervals and over a long period of time is here presented. The method allows the evaluation of displacements based on a digital image correlation technique applied to a temporal sequence of photos, daily captured by one or more fixed cameras. In comparison to other topographical method this new procedure has a lower accuracy, but provides distributed daily measurements, spatially very dense over the entire landslide area. The multi-view configuration also allows the reconstruction and the update of the 3D surface of the landslide. This work presents some preliminary results obtained by applying this innovative technique to a complex landslide located in the municipality of Perarolo di Cadore (NE Italy), also known as Sant’Andrea landslide. The landslide is characterized by active slow movements involving detrital deposits, about 30 m thick, overlying gypsum-anhydrite rocks. Its activity is strongly correlated to both heavy and long-lasting rain events and to its particular geological conditions. Recently, the alternating phases characterized by slow movements and significant accelerations led to a progressive enlargement of the affected area. Three cameras installed on a stable slope facing the landslide allow to record the intermittent activity and the peculiar behaviour of different parts of the slope. The displacements thus obtained are also compared with those deriving from conventional techniques. Finally, the accuracy of this new method is discussed.

<p>Early warning for complex landslides is a difficult task since their evolution could depend on the combination of various predisposing and triggering geological (e.g. rock type, water circulation) and climatic factors (e.g. rainfall, snowmelt). Depending on the type of phenomenon, the temporal evolution of a landslide can be monitored in several ways, from classical to recent advances in remote sensing and in-situ measurements. The potential of real-time monitoring by ground-based radar interferometry (GB-InSAR) is exploited here to improve the understanding of the kinematic evolution of a complex landslide in the Italian Alps. To this end, the integrated use of long-term, spatially distributed GB-InSAR data and of a classical Robotic Total Station (RTS) monitoring is analyzed and discussed for the Sant’Andrea landslide, located in the municipality of Perarolo di Cadore (Belluno, Italy), a rotational slide in heterogeneous materials. Due to the landslide features, the use of these two different techniques is complementary: GB-InSAR measures a continuous field of motion, although along LOS, that is suitable for detecting unstable sectors and quantifying the space-time variations of the kinematics on the entire slope, whereas RTS is able to acquire tridimensional displacement data, very useful to monitor single points and to correctly interpret the GB-InSAR data. The landslide position, just upstream of the village center, represents a relevant hydrogeological risk for the inhabitants. This complex mass movement involves a clay-calcareous debris mass overlying an anhydrite-gypsum dolomitic bedrock. The kinematic activity exhibits an alternation of slow displacements, as long-term creep, and episodic or seasonal accelerations, strongly related to rainfall triggering in response to both heavy and lasting events. Based on the intensity and duration of rainfall, the significant accelerations are followed by a relaxation period with a slow regression of the displacement rate, usually without returning to the previous values. <br>The analysis carried out by combining the mapping of 3D point-based displacements and LOS surface velocity fields allows distinguishing mechanisms and sensitivity of the landslide sectors to rainfall inputs, as well as to understand the wide range of mechanical behaviors shown by the slope during the monitoring period. Such information aims to quantitatively evaluate the trigger-response signals to rainfall events to predict accelerating trends of the landslide displacements as well as possible failures. The proposed monitoring and modelling framework will be soon implemented in an operational early warning procedure using real-time, high-frequency GB-InSAR data together with RTS and weather forecasts, in accordance with local authorities of Civil Protection.</p><p> </p>