1,070 research outputs found

    Information system on hydrological and geomorphological catastrophes in Italy (SICI): a tool for managing landslide and flood hazards

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    International audienceSince 1990, we have maintained a database of historical information on landslides and floods in Italy, known as the National Research Council's AVI (Damaged Urban Areas) archive. The database was originally designed to respond to a request of the Minister of Civil Protection, and was aimed at helping the regional assessment of landslide and flood risk in Italy. The database was compiled in 1991-1992 to cover the period 1917 to 1990, and then updated to cover systematically the period 1917 to 2000, and non-systematically the periods 1900 to 1916 and 2001 to 2002. The database currently contains information on more than 32000 landslide events occurred at more than 21000 sites, and on more than 29000 flood events occurred at more than 14000 sites. Independently from the AVI archive, we have obtained other databases containing information on damage caused by mass movements and inundations, daily discharge measurements and solid-transport measurements at selected gauging stations, bibliographical and reference information on landslides and inundations, and a catalogue of National legislation on hydrological and geological hazards and risk in Italy. The databases are part of an information system known as SICI (an Italian acronym for Sistema Informativo sulle Catastrofi Idrogeologiche, Information System on Hydrological and Geomorphological Catastrophes), which is currently the largest single repository of historical information on landslides and floods in Italy. After an outline of the history and evolution of the AVI Project archive, we present and discuss: (a) the structure of the SICI information system, including the hardware and software solutions adopted to maintain, manage, update, use and disseminate the information stored in the various databases, (b) the type and amount of information stored in each database, including an estimate of their completeness, and (c) examples of recent applications of the information system, including a web-based GIS system to show the location of sites historically affected by landslides and floods, and an estimate of geo-hydrological (i.e. landslide and flood) risk in Italy based on the available historical information

    Il rischio idrogeologico in Italia e il ruolo della ricerca scientifica

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    In Italia, le frane e le inondazioni sono fenomeni diffusi, ricorrenti e pericolosi. Fra il 1960 e il 2011 ci sono stati almeno 789 eventi di frana che hanno prodotto oltre 5000 vittime (di cui 3417 morti e 15 dispersi) in 522 comuni (6,4% del totale). Nello stesso periodo si sono verificati almeno 505 eventi d’inondazione che hanno prodotto più di 1700 vittime (di 753 morti e 68 dispersi), in 372 comuni (4,6% del totale). Fra il 2005 e il 2011, si sono avuti 82 eventi di frana che hanno prodotto oltre 480 vittime (101 morti, 6 dispersi, 374 feriti) in 70 comuni, e 39 inondazioni in altrettanti comuni con 89 vittime (59 morti, 1 disperso, 29 feriti). Nel periodo 2005-2011 tutte le Regioni hanno sofferto almeno un evento di frana o d’inondazione con vittime, a conferma della diffusione geografica del rischio geo-idrologico. Le cifre dimostrano inequivocabilmente come l’impatto che gli eventi geo-idrologici hanno sulla popolazione sia un problema prioritariamente di rilevanza sociale che enfatizza la rilevanza delle attività scientifiche che possano conseguire risultati utili a ridurre gli effetti negativi

    Exploring the effects of seismicity on landslides and catchment sediment yield: An Italian case study

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    Recent studies showed that contemporary average catchment sediment yields (SY, [t km− 2 y− 1]) at regional and continental scales are often strongly correlated to spatial patterns of seismic activity. Nonetheless, we currently have little insights into the mechanisms that explain these correlations. We investigated how spatial patterns of SY in Italy are linked to patterns of seismic activity. For a dataset of 103 Italian catchments with average SY measured over a period of years to decades, we extracted tectonic and none-tectonic variables that potentially explain observed differences in SY. These include proxies for vertical uplift rates and cumulative seismic moments (CSM) associated with historic earthquakes of different ranges of magnitude. Results showed that also across Italy, SY is significantly correlated to seismicity. However, SY showed much stronger correlations with proxies of seismicity relating to small but frequent earthquakes (2 ≤ Mw < 4) than with proxies relating to tectonic uplift or large, potentially landslide-triggering earthquakes (Mw ≥ 4). Analyses of a dataset of about 500,000 landslides across Italy showed very comparable trends: spatial patterns of landslides within similar lithological units generally show a significant positive correlation with CSM of weak but frequent seismicity and generally not with CSM of large earthquakes. These results suggest that, on a decadal time scale and at a regional/continental spatial scale, frequent but relatively weak seismicity may exert a more important geomorphic impact than large earthquake events or tectonic uplift. © 2016 Elsevier B.V

    Improving predictive power of physically based rainfall-induced shallow landslide models: a probabilistic approach

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    Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are based on deterministic laws. These models extend spatially the static stability models adopted in geotechnical engineering, and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the operation of the existing models lays in the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of rainfall-induced shallow landslides. For the purpose, we have modified the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) code. The new code (TRIGRS-P) adopts a probabilistic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. [..]Comment: 25 pages, 14 figures, 9 tables. Revised version; accepted for publication in Geoscientific Model Development on 13 February 201


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    In recent years, the architecture domain, driven by today's digital transition, has been actively exploring the world of digital twins, also thanks to the technological advancement that supports the progress on the issue. Within this context, the present work deals with the wide world of Architectural Cultural Heritage digitization. It aims to obtain a tool to support knowledge, investigation, and management of the built heritage. The research proposes an approach for digital twin development that comprehensively describes the architectural asset, including elements that are no longer present or visible. For this purpose, the three-dimensional model collects the available heterogeneous geometric datum, inevitably characterized by different levels of accuracy. The digitization model designed involves the coexistence of objects belonging to different Levels of Geometric Information (LOGI). All types of data then cooperate in defining the overall geometric information. Therefore, this framework allows for exploiting geometric information from both geomatics digital surveys and historical sources. This system allows obtaining a digital model that includes the different evolutionary phases of architectural assets by providing an overall view of these structures, an essential notion for operating properly on this kind of architecture. The digitization system was tested on a particular case study, the Ghirlanda of the Castello Sforzesco in Milan. The complexity of the property and the richness of the information heritage guided this choice, providing the basis for an appropriate and effective experimental activity

    Changes in the occurrence of rainfall-induced landslides in Calabria, southern Italy, in the 20th century

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    Abstract. Only a few studies have investigated the geographical and temporal variations in the frequency and distribution of rainfall-induced landslides, and the consequences of the variations on landslide risk. Lack of information limits the possibility to evaluate the impact of environmental and climate changes on landslide frequency and risk. Here, we exploit detailed historical information on landslides and rainfall in Calabria, southern Italy, between 1921 and 2010 to study the temporal and the geographical variation in the occurrence of rainfall-induced landslides and in their impact on the population. We exploit a catalogue with information on historical landslides from June 1920 to December 2010, and daily rainfall records obtained by a network of 318 rain gauges in the same period, to reconstruct 448 493 rainfall events (RE). Combining the rainfall and the landslide information, we obtain a catalogue of 1466 rainfall events with landslides (REL), where an REL is the occurrence of one or more landslide during or immediately after a rainfall event. We find that (i) the geographical and the temporal distributions of the rainfall-induced landslides have changed in the observation period, (ii) the monthly distribution of the REL has changed in the observation period, and (iii) the average and maximum cumulated event rainfall that have resulted in landslides in the recent 30-year period 1981–2010 are lower than the rainfall necessary to trigger landslides in previous periods, whereas the duration of the RE that triggered landslides has remained the same. We attribute the changes to variations in the rainfall conditions and to an increased vulnerability of the territory. To investigate the variations in the impact of REL on the population, we compared the number of REL in each of the 409 municipalities in Calabria with the size of the population in the municipalities measured by national Censuses conducted in 1951, 1981, and 2011. We adopted two strategies; the first strategy considered impact as IREL = #REL / P, and the second strategy measured impact as RREL = #REL × P, where #REL is the total number of REL in a period, and P is the size of the population in the same period and geographical area. The analysis has revealed a complex pattern of changes in the impact of rainfall-induced landslides in Calabria in the recent past, with areas where IREL and RREL have increased, and other areas where they have decreased. Municipalities where IREL has increased are mainly in the mountains, and municipalities where RREL has increased are mainly along the coasts. The complexity of the changes in the frequency and impact of rainfall-induced landslides observed in Calabria suggests that it remains difficult and uncertain to predict the possible variations in the frequency and impact of landslide in response to future climatic and environmental changes

    Impact of mapping errors on the reliability of landslide hazard maps

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    International audienceIdentification and mapping of landslide deposits are an intrinsically difficult and subjective operation that requires a great effort to minimise the inherent uncertainty. For the Staffora Basin, which extends for almost 300 km2 in the northern Apennines, three landslide inventory maps were independently produced by three groups of geomorphologists. In comparing each map with the others, large positional discrepancies arise (in the range of 55?65%). When all three maps are overlain, the locational mismatch of landslide deposit polygons increases to over 80%. To assess the impact of these errors on predictive models of landslide hazard, for the study area discriminant models were built up from the same set of geological-geomorphological factors as predictors, and the occurrence of landslide deposits within each terrain-unit, derived from each inventory map, as dependent variable. The comparison of these models demonstrates that statistical modelling greatly minimises the impact of input data errors which remain, however, a major limitation on the reliability of landslide hazard maps

    Identification and mapping of recent rainfall-induced landslides using elevation data collected by airborne Lidar

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    International audienceA high resolution Digital Elevation Model with a ground resolution of 2 m×2 m (DEM2) was obtained for the Collazzone area, central Umbria, through weighted linear interpolation of elevation points acquired by Airborne Lidar Swath Mapping. Acquisition of the elevation data was performed on 3 May 2004, following a rainfall period that resulted in numerous landslides. A reconnaissance field survey conducted immediately after the rainfall period allowed mapping 70 landslides in the study area, for a total landslide area of 2.7×105 m2. Topographic derivative maps obtained from the DEM2 were used to update the reconnaissance landslide inventory map in 22 selected sub-areas. The revised inventory map shows 27% more landslides and 39% less total landslide area, corresponding to a smaller average landslide size. Discrepancies between the reconnaissance and the revised inventory maps were attributed to mapping errors and imprecision chiefly in the reconnaissance field inventory. Landslides identified exploiting the Lidar elevation data matched the local topography more accurately than the same landslides mapped using the existing topographic maps. Reasons for the difference include an incomplete or inaccurate view of the landslides in the field, an unfaithful representation of topography in the based maps, and the limited time available to map the landslides in the field. The high resolution DEM2 was compared to a coarser resolution (10 m×10 m) DEM10 to establish how well the two DEMs captured the topographic signature of landslides. Results indicate that the improved topographic information provided by DEM2 was significant in identifying recent rainfall-induced landslides, and was less significant in improving the representation of stable slopes
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