The present study aims at improving data availability and quality for the last 80-90 years for daily precipitation in the Calabria region (southern Italy). First, the original database was homogenised and the gaps filled in for 129 daily rain gauges for the 1916-2006 period. Then, precipitation variability and change were evaluated at an adequate spatial resolution. Monthly and annual total precipitation (P), number of wet days (WDs), and precipitation intensity (PI) were calculated for each series. With regard to the monthly total precipitation a general negative trend, albeit not everywhere significant, was detected, in particular for the autumn-winter period, while in summer the tendency was toward an increase in total precipitation. The monthly behaviour of WDs was not very different from that observed for P: a diffuse negative trend was detected in most months, particularly evident and significant in January, with the exception of April and the summer months, for which the tendency was toward an increase. Regarding the PI, a general negative and often significant trend was found for the entire region and for almost all the months, except summer. Attention was also focused on tendencies in the different PI categories, revealing negative trends in high-intensity categories, especially coming from the winter season.Finally, running trend analysis revealed that the previously discussed tendencies were not persistent throughout the series length, but depended on the period examined. This important aspect should be taken into account when different results based on different time windows are compared.
Slow-moving landslides yearly induce huge economic losses worldwide in terms of damage to facilities and interruption of human activities. Within the landslide risk management framework, the consequence analysis is a key step entailing procedures mainly based on identifying and quantifying the exposed elements, defining an intensity criterion and assessing the expected losses. This paper presents a two-scale (medium and large) procedure for vulnerability assessment of buildings located in areas affected by slow-moving landslides. Their intensity derives from Differential Interferometric Synthetic Aperture Radar (DInSAR) satellite data analysis, which in the last decade proved to be capable of providing cost-effective long-term displacement archives. The analyses carried out on two study areas of southern Italy (one per each of the addressed scales) lead to the generation, as an absolute novelty, of both empirical fragility and vulnerability curves for buildings in slow-moving landslide-affected areas. These curves, once further validated, can be valuably used as tools for consequence forecasting purposes and, more in general, for planning the most suitable slow-moving landslide risk mitigation strategies
The geometric and kinematic characterization of landslides affecting urban areas is a challenging goal that is routinely pursued via geological/geomorphological method and monitoring of ground displacements achieved by geotechnical and, more recently, advanced differential interferometric synthetic aperture radar (A-DInSAR) data. Although the integration of all the above-mentioned methods should be planned a priori to be more effective, datasets resulting from the independent use of these different methods are commonly available, thus making crucial the need for their standardized a posteriori integration. In this regard, the present paper aims to provide a contribution by introducing a procedure that, taking into account the specific limits of geological/geomorphological analyses and deep/surface ground displacement monitoring via geotechnical and A-DInSAR data, allows the a posteriori integration of the results by exploiting their complementarity for landslide characterization. The approach was tested in the urban area of Lungro village (Calabria region, southern Italy), which is characterized by complex geological/geomorphological settings, widespread landslides and peculiar urban fabric. In spite of the different level of information preliminarily available for each landslide as result of the independent use of the three methods, the implementation of the proposed procedure allowed a better understanding and typifying of the geometry and kinematics of 50 landslides. This provided part of the essential background for geotechnical landslide models to be used for slope stability analysis within landslide risk mitigation strategies
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.