Application of a GIS-aided method for the assessment of volcaniclastic soil sliding susceptibility to sample areas of Campania (Southern Italy)

Abstract

A significant part of Campania is extensively covered by volcaniclastic soils, deriving from the alteration of airfall-sedimented formations of layered ashes and pumices that were ejected by Campi Flegrei and Mt. Somma–Vesuvius during explosive eruptions.\ud Where such soils cover steep slopes cut in carbonate bedrock, landforms depend essentially on the morpho-evolution of such slopes prior to the deposition of the volcaniclastic soils, because these are generally present only as thin veneers, up to a few meters of total thickness. Historical records and local literature testify that, in this part of Campania, landslides that originate on carbonate slopes covered by such soils and terminate at their foot or at gully outlets are frequent, following critical rainfall events. Such landslides can be classified as complex, occurring initially as debris slides, but rapidly evolving into debris avalanches and/or debris flows. The localization of the initial sliding areas (i.e. ‘‘sources’’) on the slopes depends on both the spatial distribution of characters of the soil cover and the spatial distribution of the triggering rainfall events. It therefore appears reasonable to separate the two aspects of the problem and focus on the former one, in order to attempt an assessment of soil sliding susceptibility in the event of landslide-triggering rainfall. In this paper, some results of the application of a method aimed at such an assessment are presented. The method, called SLIDE (from SLiding Initiation areas DEtection), is based on the concept that, for a spatially homogeneous soil cover and a spatially homogeneous landslide-triggering rainfall sequence, different values of threshold slope gradient for limit equilibrium conditions exist, depending on morphological characters of the soil cover, such as its continuity and planform curvature. The method is based on the assessment of (1) soil cover presence, (2) discontinuities within soil cover, (3) slope gradients and curvature, by means of good resolution DEMs. It has been applied to sample carbonate slopes of Campania, where landslides originated either repeatedly or recently.\ud Results are encouraging, and a soil sliding susceptibility map of a large area, based on a simplified version of method, is also presented

Storminess and geo-hydrological events affecting small coastal basins in a terraced Mediterranean environment

“…Flash floods are very dangerous, often resulting in the loss of life due to the fact that they can deliver enormous amounts of water and debris in a very short space of time (Gaume et al, 2009;Tarolli et al, 2012). These events, normally, have a special impact in mountain areas, where the effects of extreme precipitations are heightened by slope steepness (Calcaterra et al, 2003;Fiorillo et al, 2001;Lebel et al, 2011;Pereira et al, 2010;Perriello Zampelli et al, 2012). However, coastal environments with mountain-like geomorphological features can also be seriously exposed to accelerated erosion and landslide and flood risks (Guthrie and Evans, 2004;Cevasco et al, 2010;Santo et al, 2012).…”

Incorporating the Effects of Complex Soil Layering and Thickness Local Variability into Distributed Landslide Susceptibility Assessments

“…The common approaches used to define susceptibility maps of rainfall-induced flowtype landslides in this area consider geomorphological and stratigraphic factors including slope angle, cover thickness and presence of natural or artificial discontinuities [84,86]. However, the highly variable and contrasting hydraulic properties of ash-fall pyroclastic soil horizons can impact the modeling of infiltration processes and thus storage dynamics and pore water pressure distribution [33,[110][111][112].…”

“…Over recent years, some authors identified the basic factors controlling the susceptibility to initial landsliding, which were recognized in small-scale specific geomorphological and anthropogenic features, such as knickpoints, morphological discontinuities related to outcropping carbonate rocky cliffs and artificial cuts into the pyroclastic mantle, excavated for the construction of mountain roads [67,75,76,[81][82][83][84][85][86]. Given the undoubted cause/effect relationship between landslide triggering and rainfall patterns [87][88][89][90][91], the comprehension of temporal and spatial hydrological dynamics is a key factor to understand the landslide triggering processes into these layered soils, which can store a large amount of water over the pressure-head interval ranging between the field capacity and the permanent wilting point [33].…”

Landslide Susceptibility Estimation Using GIS. Evritania Prefecture: A Case Study in Greece

“…Up to now, several algorithms and models have been proposed for generating landslide susceptibility, mainly including Analytical Hierarchy Process-(AHP) (Khezri, 2010), Logistic Regression (Carrara, 1983), Fuzzy Logic (Gee, 1991), Artificial Neural Network (ANN) analysis (Caniani et al, 2008), modeling approaches (Perriello Zampelli et al, 2012), Fuzzy Analytical Hierarchy Process (Liu et al, 2007), Geographically weighted principal component analysis (Faraji Sabokbar et al, 2014) etc., most of which are related to the weight of landslide factors. So, undoubtedly, the above studies demonstrate that many techniques have been used for landslide susceptibility mapping and have achieved excellent results.…”