A prototype system for space–time assessment of rainfall-induced shallow landslides in Italy

Montrasio, Lorella; Valentino, Roberto; Corina, Angela; Rossi, Lauro; Rudari, Roberto

doi:10.1007/s11069-014-1239-8

Cited by 36 publications

(16 citation statements)

References 49 publications

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“…In this synthetic study, the assumption of homogeneous mechanical properties allows for direct comparison of the FS results obtained for the two soil textures and to attribute differences only to eco-hydrological properties, without having to consider the impact of highly variable mechanical parameters. Homogeneity has also been assumed for large scale basins [e.g., Montrasio et al, 2014].…”

Section: Model Setup and Input Datamentioning

confidence: 99%

Modeling the hydrological and mechanical effect of roots on shallow landslides

Arnone

Caracciolo

Noto

et al. 2016

Water Resources Research

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This study proposes a new methodology for estimating the additional shear strength (or cohesion) exerted by vegetation roots on slope stability analysis within a coupled hydrological‐stability model. The mechanical root cohesion is estimated within a Fiber Bundle Model framework that allows for the evaluation of the root strength as a function of stress‐strain relationships of populations of fibers. The use of such model requires the knowledge of the root architecture. A branching topology model based on Leonardo's rule is developed, providing an estimation of the amount of roots and the distribution of diameters with depth. The proposed methodology has been implemented into an existing distributed hydrological‐stability model able to simulate the dynamics of factor of safety as a function of soil moisture dynamics. The model also accounts for the hydrological effects of vegetation, which reduces soil water content via root water uptake, thus increasing the stability. The entire methodology has been tested in a synthetic hillslope with two configurations of vegetation type, i.e., trees and shrubs, which have been compared to a configuration without vegetation. The vegetation has been characterized using roots data of two mediterranean plant species. The results demonstrate the capabilities of the topological model in accurately reproducing the observed root structure of the analyzed species. For the environmental setting modeled, the effects of root uptake might be more significant than the mechanical reinforcement; the additional resistance depends strictly on the vegetation root depth. Finally, for the simulated climatic environment, landslides are seasonal, in agreement with past observations.

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Section: Model Setup and Input Datamentioning

confidence: 99%

Modeling the hydrological and mechanical effect of roots on shallow landslides

Arnone

Caracciolo

Noto

et al. 2016

Water Resources Research

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“…SLIP has been already tested as a prototype early warning system for this type of phenomena at a national scale. However, an over-prediction of the unstable areas has generally resulted, mainly due to the poor spatial resolution of DEM, together with the assumption of constant input parameters (such as the soil thickness) over large areas (Montrasio et al, 2014). Conversely, the good quality of the results obtained from the back-analysis of the 2009 event, both in terms of spatial and temporal prediction, suggests the application of the model within an early warning system at the catchment scale.…”

Section: Discussionmentioning

confidence: 99%

“…The specific characteristics of SLIP allow to take into account the contribution to the soil shear strength due to the partial saturation and the effect of the preceding rainfalls. For its features, including the recent implementation at the basin scale (which allows the model to handle geospatial datasets), SLIP has been adopted by the Department of National Civil Protection as a prototype early-warning system for rainfall induced shallow landslides at a national scale (Montrasio et al, 2014). The first objective of this work is to assess the performance of the model by reproducing via back-analysis the landslide event occurred in 2009 in north-eastern Sicily (Southern Italy), for which a comprehensive landslide inventory is available (as well as detailed rainfall and DEM data).…”

Section: Contents Lists Available At Sciencedirectmentioning

confidence: 99%

Prediction of shallow landslide occurrence: Validation of a physically-based approach through a real case study

Schilirò

Montrasio

Mugnozza

2016

Science of The Total Environment

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“…Capparelli and Tiranti 2010;Aleotti 2004) or deterministic models (e.g. Montrasio et al 2014;Chien et al 2015). The most common types applied in landslide EWS are basic rainfall thresholds.…”

Section: Review Of Current Approaches 21 Landslide Early Warning Sysmentioning

confidence: 99%

Spatially distributed rainfall information and its potential for regional landslide early warning systems

Canli

Loigge²,

Glade

2017

Nat Hazards

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Crucial to most landslide early warning system (EWS) is the precise prediction of rainfall in space and time. Researchers are aware of the importance of the spatial variability of rainfall in landslide studies. Commonly, however, it is neglected by implementing simplified approaches (e.g. representative rain gauges for an entire area). With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on deterministic and geostatistical methods. With kriging usually being a labour-intensive, manual task, a simplified variogram modelling routine was applied for the automated processing of up-to-date point information data. Validation showed quite satisfactory results, yet it also revealed the drawbacks that are associated with univariate geostatistical interpolation techniques which solely rely on rain gauges (e.g. smoothing of data, difficulties in resolving small-scale, highly intermittent rainfall). In the perspective, the potential use of citizen scientific data is highlighted for the improvement of studies on landslide EWS.

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A prototype system for space–time assessment of rainfall-induced shallow landslides in Italy

Cited by 36 publications

References 49 publications

Modeling the hydrological and mechanical effect of roots on shallow landslides

Modeling the hydrological and mechanical effect of roots on shallow landslides

Prediction of shallow landslide occurrence: Validation of a physically-based approach through a real case study

Spatially distributed rainfall information and its potential for regional landslide early warning systems

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