Updating and tuning a regional-scale landslide early warning system

Lagomarsino, Daniela; Segoni, Samuele; Fanti, Riccardo; Catani, Filippo

doi:10.1007/s10346-012-0376-y

Cited by 91 publications

(86 citation statements)

References 14 publications

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“…In WP 3 the research activities include the development of a physically-based model, called HIRESSS Mercogliano et al 2013), for the real time prediction of shallow landslides induced by rain on large areas, predictive statistical models (SIGMA and MACUMBA models) (Martelloni et al 2012;Lagomarsino et al 2013;Segoni et al 2014a, b;Rosi et al 2016) based on the identification of rainfall thresholds for triggering landslides, and a nowcasting system which includes a forecasting and alert system valid at the national level for landslides with fast kinematics (not monitorable by satellite).…”

Section: Wcoe (2014-2017) Activities Research Activitiesmentioning

confidence: 99%

Advanced Technologies for Landslides (WCoE 2014–2017, IPL-196, IPL-198)

Tofani

Catani

Moretti

et al. 2017

Advancing Culture of Living With Landslides

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Section: Wcoe (2014-2017) Activities Research Activitiesmentioning

confidence: 99%

Advanced Technologies for Landslides (WCoE 2014–2017, IPL-196, IPL-198)

Tofani

Catani

Moretti

et al. 2017

Advancing Culture of Living With Landslides

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“…The literature presents many examples of landslide early warning systems operating at local scale (Lollino et al, 2002;Blikra, 2008;Intrieri et al, 2012;Thiebes et al, 2013b; among others), while the scientific references to regional warning systems are much rarer (Wilson (2004), NOAA-USGS (2005), Lagomarsino et al (2013), Calvello et al (2015b), Stähli et al (2015) and references therein). The characteristics of landslide warning systems at local scale are strongly affected by numerous constraints and factors, from time to time different, related to the characteristics of the boundary value problem to address.…”

Section: Regional Systems For Rainfall-induced Landslidesmentioning

confidence: 99%

“…The Italian system, which is called SANF, is based on sub-hourly rainfall measurements obtained by a national network of 1950 rain gauges, quantitative rainfall forecasts and cumulated rainfall-duration rainfall thresholds. Besides the national system, following a recent national law written on this subject (DPCM, 2004), other relevant experiences are also present in many Italian regions, such as in Emilia Romagna (Berti et al, 2012;Lagomarsino et al, 2013), Piemonte (Tiranti and Rabuffetti, 2010), Campania (DGR n. 299/2005), Toscana (DGR n. 895/2013, DGR Figure 1. Scheme of the components of regional early warning systems for rainfall-induced landslides.…”

Section: Regional Systems For Rainfall-induced Landslidesmentioning

confidence: 99%

“…Especially for LEWSs operating at regional scale (ReLEWSs), empirical evaluations are often carried out by simply analyzing the time frames during which significant high-consequence landslides occurred in the test area (Keefer et al, 1987;Baum and Godt, 2010;Capparelli and Tiranti, 2010;Aleotti, 2004). Alternatively, the performance evaluation is based on 2 by 2 contingency tables computed for the joint frequency distribution of landslides and alerts, both considered as dichotomous variables (Yu et al, 2003;Cheung et al, 2006;Godt et al, 2006;Restrepo et al, 2008;Tiranti and Rabuffetti, 2010;Kirschbaum et al, 2012;Martelloni et al, 2012;Peres and Cancelliere, 2012;Staley et al, 2013;Lagomarsino et al, 2013Lagomarsino et al, , 2015Greco et al, 2013;Segoni et al, 2014;Gariano et al, 2015;Stähli et al, 2015). The four elements of these tables -i.e., correct alerts (CAs) or true positives; missed alerts, false negatives or type II errors; false alerts, false positives or type I errors; true negatives (TNs) -are then used to assess the weight of the correct predictions in relation to the model errors by means of a series of statistical indicators of the model performance.…”

Section: Introductionmentioning

confidence: 99%

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Assessing the performance of regional landslide early warning models: the EDuMaP method

Calvello

Piciullo

2016

Nat. Hazards Earth Syst. Sci.

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Abstract.A schematic of the components of regional early warning systems for rainfall-induced landslides is herein proposed, based on a clear distinction between warning models and warning systems. According to this framework an early warning system comprises a warning model as well as a monitoring and warning strategy, a communication strategy and an emergency plan. The paper proposes the evaluation of regional landslide warning models by means of an original approach, called the "event, duration matrix, performance" (EDuMaP) method, comprising three successive steps: identification and analysis of the events, i.e., landslide events and warning events derived from available landslides and warnings databases; definition and computation of a duration matrix, whose elements report the time associated with the occurrence of landslide events in relation to the occurrence of warning events, in their respective classes; evaluation of the early warning model performance by means of performance criteria and indicators applied to the duration matrix. During the first step the analyst identifies and classifies the landslide and warning events, according to their spatial and temporal characteristics, by means of a number of model parameters. In the second step, the analyst computes a time-based duration matrix with a number of rows and columns equal to the number of classes defined for the warning and landslide events, respectively. In the third step, the analyst computes a series of model performance indicators derived from a set of performance criteria, which need to be defined by considering, once again, the features of the warning model. The applicability, potentialities and limitations of the EDuMaP method are tested and discussed using real landslides and warning data from the municipal early warning system operating in Rio de Janeiro (Brazil).

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“…EWSs are usually implemented at local scale, on single slopes (Clark et al 1996;Froese et al 2005;Ruch 2009;Michoud et al 2013;Gigli et al 2014;Froese and Moreno 2014), where in situ monitoring systems can be installed and operated. On the other hand, EWSs at basin or regional scale are typically developed for rainfall-induced landslides by exploiting records and forecasts of rainfall (Yu et al 2004;Guzzetti et al 2007;Capparelli and Tiranti 2010;Thiebes 2012;Lagomarsino et al 2013). The main limitation of the latter systems is that, contrary to kinematic parameters, rainfall is an indirect indicator of slope instabilities, which increases the risk of missed or false alarms (Lacasse and Nadim 2008;Intrieri et al 2012).…”

Section: Introductionmentioning

confidence: 99%