Modelling of Landslide-Triggering Factors - A Case Study in the Northern Apennines, Italy

Floris, Mario; Veneri, Francesco

doi:10.1007/978-3-540-39918-6_82

Cited by 24 publications

(10 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Range: range of validity for the threshold; Error: for the new thresholds defined in this work, standard errors associated with the estimation of the intercept α and the slope β of the threshold curve. Source: 1-6, this work; 7, Caine (1980);8, Innes (1983); 9, Jibson (1989); 10, Clarizia et al (1996); 11, Crosta and Frattini (2001); 12, Cannon and Gartner (2005); 13-16, Guzzetti et al (2008);17-19, Guzzetti et al (2007); 20, Ceriani et al (1994) in Bacchini and Zannoni (2003);21, Calcaterra et al (2000); 22, Aleotti (2004);23, Cancelli and Nova (1985); 24-29, Bolley and Olliaro (1999);30, Marchi et al (2002); 31, Floris et al (2004);32-35, Giannecchini (2005). See also Fig.…”

Section: Frequentist Methodsmentioning

confidence: 98%

“…For a rainfall duration D of 24 h (one day), I is 0.7 mm hr −1 for T 1 , 0.8 mm hr −1 for T B , and 1.0 mm hr −1 for T 5 . In the Abruzzo Region, the T 1 threshold is the most conservative, for the Cancelli and Nova (1985); 24-29, Bolley and Olliaro (1999); 30, Marchi et al (2002); 31, Floris et al (2004);32-35, Giannecchini (2005). Numbers refer to # in Table 1. entire range of considered durations, 0.5 h<D<600 h. Also, the T B threshold is slightly steeper (β=0.59) than the T 1 and T 5 thresholds (β=0.55).…”

Section: Frequentist Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Rainfall thresholds for the possible occurrence of landslides in Italy

Brunetti

Peruccacci

Rossi

et al. 2010

Nat. Hazards Earth Syst. Sci.

474

409

View full text Add to dashboard Cite

Abstract. In Italy, rainfall is the primary trigger of landslides that frequently cause fatalities and large economic damage. Using a variety of information sources, we have compiled a catalogue listing 753 rainfall events that have resulted in landslides in Italy. For each event in the catalogue, the exact or approximate location of the landslide and the time or period of initiation of the slope failure is known, together with information on the rainfall duration D, and the rainfall mean intensity I , that have resulted in the slope failure. The catalogue represents the single largest collection of information on rainfall-induced landslides in Italy, and was exploited to determine the minimum rainfall conditions necessary for landslide occurrence in Italy, and in the Abruzzo Region, central Italy. For the purpose, new national rainfall thresholds for Italy and new regional rainfall thresholds for the Abruzzo Region were established, using two independent statistical methods, including a Bayesian inference method and a new Frequentist approach. The two methods proved complementary, with the Bayesian method more suited to analyze small data sets, and the Frequentist method performing better when applied to large data sets. The new regional thresholds for the Abruzzo Region are lower than the new national thresholds for Italy, and lower than the regional thresholds proposed in the literature for the Piedmont and Lombardy Regions in northern Italy, and for the Campania Region in southern Italy. This is important, because it shows that landslides in Italy can be triggered by less severe rainfall conditions than previously recognized. The Frequentist method experimented in this work allows for the definition of multiple minimum rainfall thresholds, each based on a different exceedance probability level. This makes the thresholds suited for the design of probabilistic schemes for the prediction of rainfall-induced landslides. A scheme based on four probabilistic thresholds is proposed. The four threshCorrespondence to: M. T. Brunetti (mariateresa.brunetti@irpi.cnr.it) olds separate five fields, each characterized by different rainfall intensity-duration conditions, and corresponding different probability of possible landslide occurrence. The scheme can be implemented in landslide warning systems that operate on rainfall thresholds, and on precipitation measurements or forecasts.

show abstract

Section: Frequentist Methodsmentioning

confidence: 98%

Section: Frequentist Methodsmentioning

confidence: 99%

Rainfall thresholds for the possible occurrence of landslides in Italy

Brunetti

Peruccacci

Rossi

et al. 2010

Nat. Hazards Earth Syst. Sci.

474

409

View full text Add to dashboard Cite

show abstract

“…Moscardo mountain catchment, Friuli, NE Italy (Marchi et al, 2002), and (iii) the Valzangona area, Marche, central Italy (Floris et al, 2004); and it is significantly lower than the threshold curves proposed by Giannecchini (2005) for the Apuane Alps, and by Giannecchini et al (2012) for the Serchio Basin, Tuscany. The obtained threshold is similar to the curves proposed by Bolley and Olliaro (1999) for the Rho and Perilleux mountain catchments, in Piedmont.…”

Section: Discussionmentioning

confidence: 73%

Rainfall events with shallow landslides in the Entella catchment (Liguria, Northern Italy)

Roccati¹,

Faccini²,

Luino³

et al. 2018

Preprint

View full text Add to dashboard Cite

Abstract. In the recent decades, the Entella River basin, in the Liguria Apennines, Northern Italy, was hit by numerous intense rainfall events that triggered shallow landslides, soil slips and debris flows, causing casualties and extensive damage. landslides occurred primarily at the same time or within six hours from the maximum peak rainfall intensity, and at or near the geographical location where the rainfall intensity was largest. Adopting a Frequentist approach, we define the event rainfall intensity-event duration ID, threshold for the possible initiation of shallow landslides and debris flows in the Entella 20River basin. The threshold is lower than most of the thresholds proposed in the literature for similar mountain catchments, local areas and single regions in Italy. Analysis of the antecedent rainfall conditions for different periods, from 3 to 15 days, revealed that the antecedent rainfall did not play a significant role in the initiation of landslides in the Entella catchment. We expect that our findings will be useful in regional to local landslides early warning systems, and for land-planning aimed at reducing landslides risk in the study area. 25

show abstract

“…Efforts to develop adequate theoretical models for debris flow have been limited by the lack of understanding of how such flows occur with regard to the given site conditions such as (1) geomorphology, (2) geology, (3) hydraulic properties, and (4) soil conditions (Pierson 1994;Floris et al 2004). However, since the debris flows have led to many disasters, the literatures have to be reviewed for a possible resolution.…”

Section: Introductionmentioning

confidence: 98%

“…As a matter of fact, the obstacle for analyzing the debris flow involved many environmental factors which require a good strategy to extract their importance (Pachauri and Pant 1992;Donati and Turrini 2002;Carrara et al 2003). Floris et al (2004) reported the core triggering factors of debris flow in Northern Apennines (Italy). The slope, which consists of mainly clayey and clayeymarly terrains, has been affected by landslide triggering phenomena.…”

Section: Introductionmentioning

confidence: 98%

The knowledge expression on debris flow potential analysis through PCA + LDA and rough sets theory: a case study of Chen-Yu-Lan watershed, Nantou, Taiwan

et al. 2010

View full text Add to dashboard Cite

Debris flow is often performed through identifying and analyzing the soil condition, hydraulic, geomorphological factors and vegetation conditions. In the present study, a spatial information analysis system is combined with a linear statistical method (principle components analysis with linear discriminant analysis, PCA ? LDA) and an advanced data mining technique (discrete rough sets, DRS) to investigate the debris flow occurrence based on geomorphological and vegetation conditions factors. The analyzed data sources include (1) digital elevation model: to investigate the variation in the landscape, and (2) remote sensing data: to analyze the vegetation and plant conditions on the ground surface. The objective of this research is to define a method with the ability to forecast the level of debris flow susceptibility through the parallel study of statistical outcomes (PCA ? LDA) and data mining results (DRS). The outcomes from PCA ? LDA are inadequate due to the thresholds of the influenced variables not being examined. In this study, the DRS approach not only showed satisfactory results for the thresholds of influenced variables in the study area, but also the occurrence rules of debris flow are generated. Finally, the results show superior classification accuracy (70.8% for debris flow occurrence) for the DRS method over those of PCA ? LDA analysis (54.2% for debris flow occurrence) for the analysis of debris flow occurrence. Therefore, this is an encouraging preliminary approach in the hazard assessment of debris flow.

show abstract

Modelling of Landslide-Triggering Factors - A Case Study in the Northern Apennines, Italy

Cited by 24 publications

References 1 publication

Rainfall thresholds for the possible occurrence of landslides in Italy

Rainfall thresholds for the possible occurrence of landslides in Italy

Rainfall events with shallow landslides in the Entella catchment (Liguria, Northern Italy)

The knowledge expression on debris flow potential analysis through PCA + LDA and rough sets theory: a case study of Chen-Yu-Lan watershed, Nantou, Taiwan

Contact Info

Product

Resources

About