L. Ermini

Radiocarbon Data on Lateglacial and Holocene Landslides in the Northern Apennines

The Emilia Romagna slope of the Northern Apennines is strewnwith over 32,000 landslides, 5,000 of which are larger than 1 million cubic metres. They representthe remains of geomorphic agents that shaped the Apennines during the Holocene. Dating themby means of radiocarbon methods adds a contribution to the knowledge about the last periodof the geological geomorphological history of the Apennines. They can also be used to examinethe influence of Quaternary climatic changes on the instability of slopes and, for practicalor planning functions, to assess the periodicity of activity phases of the landslides. Thedating has been carried out on wood remnants buried under the landslide bodies. In some cases theentire tree trunk was found.In this paper we present radiocarbon dating of 20 casestudies in the Northern Apennines. Results range approximately from 13790–13670 cal y BP to950–790 cal`y BP. The oldest case is that of the Morsiano earth-flow, while the younger datedevent is represented by the Marano case that represents an example of how radiometric analysescan further enhance the available historical data. In the Cavola case, wood remnants of different ageswere found at different depths (from 9 to 45 m), allowing the dating of the first and followingperiods of activity of the landslide. The results are discussed and some considerations on the correlationbetween landslide occurrence and Holocene climate changes are proposed.

An Inventory-Based Approach to Landslide Susceptibility Assessment and its Application to the Virginio River Basin, Italy

An inventory-based method for the assessment of landslide susceptibility is presented in this article. The method has been tested in the Virginio River Basin, a tributary of the Arno River whose confluence is located about 20 km downstream from Florence (Italy). The scope of this study includes setting up a procedure for landslide hazard zoning to be applied by those urban planners typically working on small areas at large scale. The proposed method deals with traditional and well-known landslide hazard analyses, based on geomorphological tools, and its most original contribution is represented by the attempt to carry out and apply a technique for landslide hazard assessment that takes into account two different scales of analysis. The basis of a detailed landslide inventory and the first phase of this research was an in-depth geomorphological investigation at basin scale (1:25,000–1:10,000). This was aimed at indicating the most important factors influencing the landslide processes within the area, which also turned out to be the most generally accepted factors: a) slope gradient in which the landslide originated, b) lithology, and c) land cover. Once those factors were defined as thematic vector data, they were expressed using GIS overlay mapping, allowing the identification, for the entire Virginio River basin, of first-order homogeneous domains (Unique Condition Units, UCUs) that contain, for each landslide type, unique combinations (domains) of the selected hillslope stability factors. The domains are the basic Terrain Units for the subsequent landslide susceptibility assessment and mapping, which was carried out at slope scale (1:10,000–1:2,000). Landslide factors not identified in the first phase of analysis, but considered to have played an important role in contributing to the activation of the mass movements, so-called second-order landslide preparatory factors, have been taken into account in the second phase of the analysis. Once mapped and spatially referenced, these factors were overlain by vector-based GIS techniques to define second-order UCUs which, in turn, constituted the basis of a landslide susceptibility function. Essentially, this is a logic function based on the presence/absence of preparatory factors and slope instability indicators within previously selected Unique Condition Terrain Units. The final mapping of the areas characterized by different landslide susceptibility levels was performed by vector- and raster-based GIS techniques on the basis of the number and rank of the preparatory factors. The final landslide susceptibility classes, defined by a logical and easily replicable procedure, are considered to be useful in the decision-making procedures associated with territorial planning.

Analisi della suscettibilità da frana a scala di bacino (Bacino del Fiume Arno, Toscana-Umbria, Italia)

This paper presents the methodology adopted and the outcomes obtained in a recent analysis of landslide hazard in the Basin of Arno River (Central Italy), about 9100 km, as part of a project sponsored by the Basin Authority of the Arno River started in the year 2002 and completed in the year 2005. All the required data were recorded in a GIS-database and synthesized in several thematic maps and in a landslide inventory. According to the landslide types prevailing in the study area and the results of statistical analysis, five preparatory factors were selected: slope, lithology, land cover, profile curvature and upslope contributing area, which after GIS-overlay operations generated the basic units for the statistical treatment (Unique Conditions Units). The hazard assessment was extended to landslide-free areas by the application of multivariate statistical methods, implemented in ANN (Artificial Neural Networks). The neural predictors were trained using a selected training set. The neural networks affected by acceptable errors and having a high generalization potential were applied to the total data set, in order to generate prediction values for the susceptibility index for each UCU. Finally, the output values were reclassified in different hazard levels on the basis of threshold criteria and validated by comparison with the inventory map. In average, 81% to 96% of the area affected by instability was correctly classified by the prediction. Moreover, the model shows the occurrence of highly hazardous areas in zones with no mapped landslides, that can indicate possible problems of incompleteness or undersampling of the inventory itself. Key terms: landslide, hazard, artificial neural networks Termini chiave: frane, pericolosità, reti neurali artificiali

A Cost Effective Methodology for the Rapid Evaluation of the Flood Susceptibility Along Anthropized Rivers

On the basis of the recent experience over the perifluvial areas of the Arno river (Italy), a cost effective approach is proposed to make a preliminary assessment of the flood susceptibility along urbanized rivers. This method encompass two operative phases: a rapid mapping of all the most important natural and artificial elements connected to the hydraulic risk and a reasoned analysis of the collected information with some topographic data that are usually stored in the public offices. The first step includes a field survey using a GPS (global positioning system) device in Real Time Kinematic (RTK) mode and the developing of a local geoid model whose application allows to convert the measured ellipsoidal heights in orthometric heights affected with errors ≤5 cm. Consequently a properly structured GIS geodatabase can be built in order to visualize the spatial distribution of the mapped elements and to store the most important technical data. The second step includes some analyses that allow to define all the most detailed implications for the hydraulic risk in urban and suburban areas. In particular the combination of the previously obtained orthometric heights with the available flow levels data for various return periods is able to produce the preliminary evaluation of the most dangerous dikes in terms of overflowing. Such result, joined to the surface water flow model of the urbanized perifluvial areas which relies on the processing of digital terrain data coming from LIDAR acquisitions, provides significant flood susceptibility scenarios.