We present the methodologies adopted and the outcomes obtained in the analysis of landslide risk in the basin of the Arno River (Central Italy) in the framework of a project sponsored by the Basin Authority of the Arno River, started in the year 2002 and completed at the beginning of 2005. In particular, a complete set of methods and applications for the assessment of landslide susceptibility and risk are described and discussed.A new landslide inventory of the whole area was realized, using conventional (aerial-photo interpretation and field surveys) and nonconventional methods (e.g. remote sensing techniques such as DIn-SAR and PS-InSAR).The great majority of the mapped mass movements are rotational slides (75%), solifluctions and other shallow slow movements (17%) and flows (5%), while soil slips, and other rapid landslides, seem less frequent everywhere within the basin. The relationships between landslide characteristics and environmental factors have been assessed through statistical analysis. As expected, the results show a strong control of land cover, lithology and morphology on landslide occurrence. The landslide frequency-size distribution shows a typical scaling behaviour already underlined in other landslide inventories worldwide. The assessment of landslide hazard in terms of probability of occurrence in a given time, based for mapped landslides on direct and indirect observations of the state of activity and recurrence time, has been extended to landslide-free areas through the application of statistical methods implemented in an artificial neural network (ANN). Unique conditions units (UCU) were defined by the map overlay of landslide preparatory factors (lithology, land cover, slope gradient, slope curvature and upslope contributing area) and afterwards used to construct a series of model vectors for the training and test of the ANN. Various different ANNs were selected throughout the basin, until each UCU was assigned a degree of membership to a susceptibility and a hazard class. Model validation confirms that prediction results are very good, with an average percentage of correctly recognized mass movements of about 85%. The analysis also revealed the existence of a large number of unmapped mass movements, thus contributing to the completeness of the final inventory. Temporal hazard was estimated via the translation of state of activity in recurrence time and hence probability of occurrence. The following intersection of hazard values with vulnerability and exposure figures, obtained by reclassification of digital vector mapping at 1:10,000 scale, lead to the definition of risk values for each terrain unit for different periods of time into the future. The final results of the research are now undergoing a process of integration and implementation within land planning and risk prevention policies and practices at local and national level.
In this paper the main results of an experimental investigation on the beginning of sediment transport of incoherent granular materials in shallow viscous flows are presented. The experiments, performed in a laboratory flume in both laminar and smooth turbulent flow conditions, complement the data already available in literature, and confirm that the hyperbolic trend shown by the Shields curve when the grain Reynolds number X decreases to zero is not supported by experimental evidence. In addition, they confirm the Yalin and Karahan (1979) hypothesis on the existence of a distinct curve for the inception of sediment transport in viscous dominated flows. On the basis of the observed phenomenology, we propose to interpret the process as a function of the probability distribution of the repose angle of the grains of the erodible bed. Accordingly, a simple mechanical relation is derived that explains the pattern exhibited by the experimental data. RÉSUMÉDans cet article sont présentés les principaux résultats d'une étude expérimentale sur le début du transport de sediments de matériaux non cohésifs dans les écoulements visqueux en faible profondeur. Les experiences, effectuées dans un canal en laboratoire, sur des écoulements laminaires et faiblement turbulents, complètent les données de la littérature disponibles actuellement, et confirment le fait que le comportement hyperbolique montré par la courbe de Shields n'est pas vérifié expérimentalement quand le nombre de Reynolds du grain, X, tend vers zéro. De plus, elles confirment l'hypothèse de Yalin et Karahan (1979) sur l'existence d'une courbe distincte pour le début du transport de sediments dans les écoulement a viscosité prépondérante. Sur la base des phénomènes observes, nous proposons d'interpréter le processus comme une fonction de la loi de probabilité de Tangle de repos des grains du lit érodable. On en déduit alors une relation mécanique simple qui explique la forme des données expérimentales. be regarded as fixed, then equation (1) can be rewritten as follows
We investigate flow through porous media by solving the Navier-Stokes equations in 3D porous structures using the lattice Boltzmann method. We analyse the distribution of local specific dissipation of mechanical energy and we use this quantity to investigate the microscopic origin of absolute permeability. The averaging of this quantity on a flow crosssection provides a methodology to locate energy losses and to spot the appropriate scale of the permeability Representative Elementary Volume (REV). The effectiveness of the approach is shown by a numerical study of the flow field in simplified porous media for which experimental results are available.
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.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.