A test of transferability for landslides susceptibility models under extreme climatic events: application to the Messina 2009 disaster

A model building strategy is tested to assess the susceptibility for extreme climatic events driven shallow landslides. In fact, extreme climatic inputs such as storms typically are very local phenomena in the Mediterranean areas, so that with the exception of recently stricken areas, the landslide inventories which are required to train any stochastic model are actually unavailable. A solution is here proposed, consisting in training a susceptibility model in a source catchment, which was implemented by applying the binary logistic regression technique, and exporting its predicting function (selected predictors regressed coefficients) in a target catchment to predict its landslide distribu…

Characterization of the soil properties in agricultural areas affected by shallow landslides: application in Messina area (Sicily).

The determination of soil properties is considerable challenge when it is aimed to evaluate the spatial distribution of one or more parameters across significant surfaces. In fact, terrain sampling and field data are punctual measurement; therefore, quantitative models are needed to predict the spatial distribution of soil attributes. The spatialization of field and laboratory data is a very important information in landslide studies. Raster layers displaying soil properties can be used both for statistical models and for the parameterization of physically based models. The purpose of this work is to produce a detailed hydrological and mechanical characterization of the soil affected by sha…

Assessment of Gully Erosion Susceptibility Using Multivariate Adaptive Regression Splines and Accounting for Terrain Connectivity

In this work, we assessed gully erosion susceptibility in two adjacent cultivated catchments of Sicily (Italy) by employing multivariate adaptive regression splines (MARS) and a set of geo-environmental variables. To explore the influence of hydrological connectivity on gully occurrence we measured the changes of performance occurred when adding one by one nine predictors reflecting terrain connectivity to a base model that included contributing area and slope gradient. Receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were used to evaluate models performance. Gully predictive models were trained in both the catchments and submitted to internal (in the ca…

Exploring the effect of absence selection on landslide susceptibility models: A case study in Sicily, Italy

Abstract A statistical approach was employed to model the spatial distribution of rainfall-triggered landslides in two areas in Sicily (Italy) that occurred during the winter of 2004–2005. The investigated areas are located within the Belice River basin and extend for 38.5 and 10.3 km 2 , respectively. A landslide inventory was established for both areas using two Google Earth images taken on October 25th 2004 and on March 18th 2005, to map slope failures activated or reactivated during this interval. Geographic Information Systems (GIS) were used to prepare 5 m grids of the dependent variables (absence/presence of landslide) and independent variables (lithology and 13 DEM-derivatives). Mul…

A multi-scale regional landslide susceptibility assessment approach: the SUFRA_SICILIA (SUscettibilità da FRAna in Sicilia) project

The SUFRA project is based on a three level susceptibility mapping. According to the availability of more detailed data, the three scale for susceptibility mapping are increased respect to the ones suggested by the TIER group to 1:100,000, 1:50,000 and 1:25,000/1:10,000. The mapping levels exploit climatic, soil use (CORINE2009) and seismic informative layers, differentiating in the details of the core data (geology and topography), in the quality and resolution of the landslide inventory and in the modelling approach (Tab. 1). SUFRA_100 is based on a heuristic approach which is applied by processing a geologic layer (produced by ARTA integrating pre-CARG 1:100,000 geologic maps); the DEM e…

The geo-hydrologic event in the Peloritan – Ionian area of 2009: debris-flow susceptibility assessment by means of forward logistic regression

On the 1st of October 2009, the area centred on the village of Giampilieri (Messina), on the Ionian side of the Peloritan belt, suffered thousands of landslides activated in the time lapse of about five hours, which caused 36 victims, more than 100 injured and more than 0.5M€ of damage to structures. This unprecedented phenomenon was triggered by an exceptional meteorological event, recorded at the foothills with 250mm of rain in just 8 hours; this amount of rainfall was cumulated to two previous events (16/IX: 75mm; 23/IX: 190mm) for a total amount of more than 500mm in less than two weeks. Due to the peculiar triggering conditions a huge number of debris flows involved the shallow weather…

Multi-scale regional landslide susceptibility assessment in Sicily (Italy): The Sufra Sicilia Project

Un approccio multi-scala per la valutazione della suscettibilità da frana a livello regionale: il progetto SUFRA (SUscettibilità da FRAna) in Sicilia

L’attuale versione del PAI (Piano Stralcio per l'Assetto Idrogeologico) disponibile per il territorio siciliano è fortemente dipendente dallo scenario di dissesti passati censiti e catalogati, sulla base dei quali, utilizzando un sistema di matrici di valutazione, è possibile ricavare le condizioni di rischio geomorfologico associato. Questo stadio costituisce un primo grande avanzamento delle conoscenze a partire dal quale è ora necessario procedere alla valutazione della suscettibilità da frana e all’adozione dunque di uno strumento di analisi territoriale con carattere previsionale. La realizzazione di una cartografia della suscettibilità da frana a scala regionale pone d’altra parte una…

Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north-eastern Sicily, Italy)

This study aims at evaluating the performance of the Maximum Entropy method in assessing landslide susceptibility, exploiting topographic and multispectral remote sensing predictors. We selected the catchment of the Giampilieri stream, which is located in the north-eastern sector of Sicily (southern Italy), as test site. On 1 October 2009, a storm rainfall triggered in this area hundreds of debris flow/avalanche phenomena causing extensive economical damage and loss of life. Within this area a presence-only-based statistical method was applied to obtain susceptibility models capable of distinguishing future activation sites of debris flow and debris slide, which where the main source of fai…

Comparing binary logistic regression and stochastic gradient boosting techniques in debris-flows susceptibility modelling: application in North-Eastern Sicily

Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north-eastern Sicily, Italy)

This study aims at evaluating the performance of the Maximum Entropy method in assessing landslide susceptibility, exploiting topographic and multispectral remote sensing predictors. We selected the catchment of the Giampilieri stream, which is located in the north-eastern sector of Sicily (southern Italy), as test site. On 1 October 2009, a storm rainfall triggered in this area hundreds of debris flow/avalanche phenomena causing extensive economical damage and loss of life. Within this area a presence-only-based statistical method was applied to obtain susceptibility models capable of distinguishing future activation sites of debris flow and debris slide, which where the main source of fai…

Landslide susceptibility modelling for extreme rainfall-triggered multiple landslides: a key study from the 2009 event in the Giampilieri Area(Sicily, Italy)

Confronto di due approcci statistici non parametrici per la valutazione della suscettibilità da frana nella catena appenninica settentrionale siciliana: tavolette I.G.M.I. Scillato e Caltavuturo

Oggigiorno, la valutazione della diversa importanza delle variabili geoambientali nel determinare le condizioni di suscettibilità da frana di un’area è uno dei problemi più attuali della geologia. L’uso ed il confronto di due differenti approcci statistici, ha consentito di stimare le condizioni di predisposizione all’instabilità gravitativa dei versanti, per un esteso settore settentrionale della catena appenninica siciliana, ricadente all’interno delle tavolette I.G.M.I. nn. 259 I SE “Scillato” e 259 II NE “Caltavuturo”. L’area oggetto della sperimentazione, estesa circa 200 Km2, è stata suddivisa in maniera semi-automatica in 1827 unità idro-morfologiche o unità di versante. Per ciascun’…

Exploring relationships between grid cell size and accuracy for debris-flow susceptibility models: a test in the Giampilieri catchment (Sicily, Italy)

Debris flows are among the most hazardous phenomena in nature, requiring the preparation of suscep- tibility models in order to cope with this severe threat. The aim of this research was to verify whether a grid cell-based susceptibility model was capable of predicting the debris- flow initiation sites in the Giampilieri catchment (10 km2), which was hit by a storm on the 1st October 2009, resulting in more than one thousand landslides. This kind of event is to be considered as recurrent in the area as attested by historical data. Therefore, predictive models have been prepared by using forward stepwise binary logistic regression (BLR), a landslide inventory and a set of geo- environmental …

Improving transferability strategies for debris flow susceptibility assessment: Application to the Saponara and Itala catchments (Messina, Italy)

Abstract Debris flows can be described as rapid gravity-induced mass movements controlled by topography that are usually triggered as a consequence of storm rainfalls. One of the problems when dealing with debris flow recognition is that the eroded surface is usually very shallow and it can be masked by vegetation or fast weathering as early as one-two years after a landslide has occurred. For this reason, even areas that are highly susceptible to debris flow might suffer of a lack of reliable landslide inventories. However, these inventories are necessary for susceptibility assessment. Model transferability, which is based on calibrating a susceptibility model in a training area in order t…

Regional debris flow susceptibility assessment using HRDEM: Example of the city area of Messina (Sicily, Italy)

Shallow landslide and debris flows are among the most dangerous natural hazards triggered by extreme meteorological events. These phenomena have recently caused catastrophic scenarios in Italy (e.g. in Sarno-Quindici and Giampilieri) and, according to expected changes in the climate pattern, an increasing frequency of these phenomena is expected. The aim of this research is to assess the debris flow susceptibility in the Giampilieri area (Sicily) using a spatially-distributed debris flow runout model based on topographic information. The application of the model starts with the identification of the source areas from which debris flows are propagated on the basis of frictional laws and flow…

Predicting storm-triggered debris flow events: application to the 2009 Ionian Peloritan disaster (Sicily, Italy)

Abstract. The main assumption on which landslide susceptibility assessment by means of stochastic modelling lies is that the past is the key to the future. As a consequence, a stochastic model able to classify past known landslide events should be able to predict a future unknown scenario as well. However, storm-triggered multiple debris flow events in the Mediterranean region could pose some limits on the operative validity of such an expectation, as they are typically resultant of a randomness in time recurrence and magnitude and a great spatial variability, even at the scale of small catchments. This is the case for the 2007 and 2009 storm events, which recently hit north-eastern Sicily …

Modeling landslide susceptibility by using GIS-analysis and multivariate adaptive regression splines

Landslide susceptibility may be evaluated by defining statistical relationships between the spatial distribution of past slope failures and the variability of landslide triggering factors. In this research, susceptibility to landsliding was assessed by employing multivariate adaptive regression splines (MARS), a statistical model that has been rarely used to this aim. The experiment was carried out in an area of central Sicily (Italy), which is severely affected by shallow landslides mainly occurring during the wet autumn- winter semester. Bedrock lithology and a set of primary and secondary topographic attributes were exploited as proxies of main landslide driving factors. The robustness o…

Binary logistic regression versus stochastic gradient boosted decision trees in assessing landslide susceptibility for multiple-occurring landslide events: application to the 2009 storm event in Messina (Sicily, southern Italy)

This study aims to compare binary logistic regression (BLR) and stochastic gradient treeboost (SGT) methods in assessing landslide susceptibility within the Mediterranean region for multiple-occurrence regional landslide events. A test area was selected in the north-eastern sector of Sicily (southern Italy) where thousands of debris flows and debris avalanches triggered on the first October 2009 due to an extreme storm. Exploiting the same set of predictors and the 2009 event landslide archive, BLR- and SGT-based susceptibility models have been obtained for the two catchments separately, adopting a random partition (RP) technique for validation. In addition, the models trained in one catchm…

Exploring relationships between pixel size and accuracy for debris flow susceptibility models: a test in the Giampilieri catchment (Sicily, Italy).

Debris flows are among the most hazardous phenomena in nature, which typically take the form of multiple-occurrence regional landslide events triggered by intense driving inputs such as storms or earthquakes. The main tasks of this study were to verify whether cell-based susceptibility models is capable of predicting debris flow initiations in the Giampilieri catchment (southern Italy) and to explore the relationships between the pixel size of the adopted mapping units in terms of predictive performances of the derived models. The Giampilieri catchment is a small area (10km 2 ) hit by a storm on the 1 st October 2009 which resulted in the triggering of more than one thousand landslides and …

OPTIMIZING STOCHASTIC SUSCEPTIBILITY MODELLING FOR DEBRIS FLOW LANDSLIDES: PIXEL SIZE EFFECTS, PROBLEMS IN CHRONO-VALIDATION, 2D SPATIALLY DISTRIBUTED MODELLING OF THE PROPAGATION PHASE. APPLICATIONS TO THE 2009 MESSINA EVENT.