Experimental study on the rheological behaviour of debris flow material in the Campania region

Abstract. A model able to describe all the processes involved in a debris flow can be very complex owing to the sudden changing of the material that turns from solid into liquid state. The two phases of the phenomenon are analysed separately referring to soil mechanics procedures with regard to the trigger phase, and to an equivalent fluid for the post-failure phase. The present paper is devoted to show the experimental results carried out to evaluate the behaviour assumed by a pyroclastic-derived soil during the flow. A traditional fluid tool has been utilized: a standard rotational rheometer equipped with two different geometries. The soils tested belong to deposits that cover the slopes of the Campania region, Italy, often affected by debris flows. The influence of solid concentration Cv and grain size distribution was tested: the soils were destructurated, sieved and mixed with water starting from the in situ porosity. All material mixtures showed a non-Newtonian fluid behaviour with a yield stress τy that increases with a solid volumetric concentration and decreases for an increase of sand fraction. The experimental data were fitted with standard model for fluids. A simple relation between Cv and τy was obtained. The yield stress seems to be a key parameter for describing and predicting the post-failure behaviour of debris flows. These results suggest that in the field a small change in solid fraction, due to rainfall, will cause a slight decrease of the static yield stress, readily inducing a rapid flow which will stop only when the dynamic yield stress is reached, namely on a much smoother slope. This can explain the in situ observed post-failure behaviour of debris flows, which are able to flow over very long distances even on smooth slopes.

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Deposition Prediction of Debris Flow Alluvial Fan Based on Experimental Study

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.518-523.4819 ◽

2012 ◽

Vol 518-523 ◽

pp. 4819-4822

Author(s):

Jin Feng Liu ◽

Shun Yang ◽

Guo Qiang Ou

Keyword(s):

Experimental Study ◽

Debris Flow ◽

Statistical Method ◽

Laboratory Experiments ◽

Empirical Models ◽

Alluvial Fan ◽

Disaster Prevention ◽

Average Accuracy ◽

Hazardous Area ◽

Debris Flow Disaster

The deposition prediction of debris flow hazardous area is very important for organizing and implementing debris flow disaster prevention and reduction. This paper selected the data base from laboratory experiments and applied the multiple regression statistical method to establish a series of empirical calculation models for delimiting the debris flow hazardous areas on the alluvial fan. The empirical models for predicting the maximum deposition length (Lc), the maximum deposition width (Bmax) and the maximum deposition thichness (Z0) under the condition of different debris flow volumes (V), densities (rm) and slopes of accumulation area (θd) were establised. And the verification results indicated that the established models can predict the debris flow hazards area with the average accuracy of 86%.

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Debris-flow susceptibility assessment through cellular automata modeling: an example from 15–16 December 1999 disaster at Cervinara and San Martino Valle Caudina (Campania, southern Italy)

Natural Hazards and Earth System Science ◽

10.5194/nhess-3-457-2003 ◽

2003 ◽

Vol 3 (5) ◽

pp. 457-468 ◽

Cited By ~ 46

Author(s):

G. Iovine ◽

S. Di Gregorio ◽

V. Lupiano

Keyword(s):

Cellular Automata ◽

Debris Flow ◽

Urban Areas ◽

Debris Flows ◽

Soil Cover ◽

Southern Italy ◽

Landslide Risk ◽

Campania Region ◽

Optimal Values ◽

Debris Flow Susceptibility

Abstract. On 15–16 December 1999, heavy rainfall severely stroke Campania region (southern Italy), triggering numerous debris flows on the slopes of the San Martino Valle Caudina-Cervinara area. Soil slips originated within the weathered volcaniclastic mantle of soil cover overlying the carbonate skeleton of the massif. Debris slides turned into fast flowing mixtures of matrix and large blocks, downslope eroding the soil cover and increasing their original volume. At the base of the slopes, debris flows impacted on the urban areas, causing victims and severe destruction (Vittori et al., 2000). Starting from a recent study on landslide risk conditions in Campania, carried out by the Regional Authority (PAI –Hydrogeological setting plan, in press), an evaluation of the debris-flow susceptibility has been performed for selected areas of the above mentioned villages. According to that study, such zones would be in fact characterised by the highest risk levels within the administrative boundaries of the same villages ("HR-zones"). Our susceptibility analysis has been performed by applying SCIDDICA S3–hex – a hexagonal Cellular Automata model (von Neumann, 1966), specifically developed for simulating the spatial evolution of debris flows (Iovine et al., 2002). In order to apply the model to a given study area, detailed topographic data and a map of the erodable soil cover overlying the bedrock of the massif must be provided (as input matrices); moreover, extent and location of landslide source must also be given. Real landslides, selected among those triggered on winter 1999, have first been utilised for calibrating SCIDDICA S3–hex and for defining "optimal" values for parameters. Calibration has been carried out with a GIS tool, by quantitatively comparing simulations with actual cases: optimal values correspond to best simulations. Through geological evaluations, source locations of new phenomena have then been hypothesised within the HR-zones. Initial volume for these new cases has been estimated by considering the actual statistics of the 1999 landslides. Finally, by merging the results of simulations, a deterministic susceptibility zonation of the considered area has been obtained. In this paper, aiming at illustrating the potential for debris-flow hazard analyses of the model SCIDDICA S3–hex, a methodological example of susceptibility zonation of the Vallicelle HR-zone is presented.

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A probabilistic model for assessing debris flow propagation at regional scale: a case study in Campania region, Italy

10.5194/egusphere-egu21-2224 ◽

2021 ◽

Author(s):

Luca Crescenzo ◽

Gaetano Pecoraro ◽

Michele Calvello ◽

Richard Guthrie

Keyword(s):

Debris Flow ◽

Debris Flows ◽

Regional Scale ◽

Erosion And Deposition ◽

Campania Region ◽

Source Areas ◽

Model Input ◽

Travel Path ◽

Debris Avalanches ◽

Modelling Approach

<p>Debris flows and debris avalanches are rapid to extremely rapid landslides that tend to travel considerable distances from their source areas. Interaction between debris flows and elements at risk along their travel path may result in potentially significant destructive consequences. One of the critical challenges to overcome with respect to debris flow risk is, therefore, the credible prediction of their size, travel path, runout distance, and depths of erosion and deposition. To these purposes, at slope or catchment scale, sophisticated physically-based models, appropriately considering several factors and phenomena controlling the slope failure mechanisms, may be used. These models, however, are computationally costly and time consuming, and that significantly hinders their applicability at regional scale. Indeed, at regional scale, debris flows hazard assessment is usually carried out by means of qualitative approaches relying on field surveys, geomorphological knowledge, geometric features, and expert judgement.</p><p>In this study, a quantitative modelling approach based on cellular automata methods, wherein individual cells move across a digital elevation model (DEM) landscape following behavioral rules defined probabilistically, is proposed and tested. The adopted model, called LABS, is able to estimate erosion and deposition soil volumes along a debris flow path by deploying at the source areas autonomous subroutines, called agents, over a 5 m spatial resolution DEM, which provides the basic information to each agent in each time-step. Rules for scour and deposition are based on mass balance considerations and independent probability distributions defined as a function of slope DEM-derived values and a series of model input parameters. The probabilistic rules defined in the model are based on data gathered for debris flows and debris avalanches that mainly occurred in western Canada. This study mainly addresses the applicability and the reliability of this modelling approach to areas in southern Italy, in Campania region, historically affected by debris flows in pyroclastic soils. To this aim, information on inventoried debris flows is used in different study areas to evaluate the effect on the predictions of the model input parameter values, as well as of different native DEM resolutions.</p>

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