Rainfall thresholds for the forecasting of landslide occurrence at regional scale

Abstract

This paper concerns a regional scale warning system for landslides that relies on a decisional algorithm based on the comparison between rainfall recordings and statistically defined thresholds. The latter were based on the total amount of rainfall, which was cumulated considering different time intervals: 1-, 2-and 3-day cumulates took into account the critical rainfall influencing shallow movements, whilst a variable time interval cumulate (up to 240 days) was used to consider the triggering of deep-seated landslides in low permeability terrains. A prototypal version of the model was initially set up to define statistical thresholds. Then, thresholds were calibrated using a database of past georegistered and dated landslides. A validation procedure showed that the calibration highly improves the results and therefore the model was integrated in the regional warning system of Emilia Romagna (Italy) for civil protection purposes. The proposed methodology could be easily implemented in other similar regions and countries where a sufficiently organised meteorological network is present.Keywords Landslide . Optimization . Rainfall . Threshold Introduction In Italy, landsliding is a recurrent phenomenon responsible for casualties, destruction of assets and infrastructures and major economical loss (Guzzetti 2000). Since rainfall represents the most common triggering factor, many Italian civil protection agencies are setting up warning systems based on the interaction between rainfall and landslides. These agencies are responsible for large territories (e.g. regions or large subdivisions such as provinces), therefore they cannot rely on physically based approaches because of the difficulty of defining the exact spatial and temporal variation of the many involved factors (rainfall variation in space and in time, effect of vegetation, mechanic and hydraulic properties of both bedrock and soil layer). As a consequence, physically based approaches can effectively be applied only over small sites (Segoni et al. 2009), while at regional scale the most diffused methodology is the use of black box models based on empirical or statistical rainfall thresholds. The term 'black box' refers to a methodology in which the complex physical processes involved in landslide initiation are ignored (because too difficult to correctly calibrate over large areas) and a more simple and functional empirical correlation is found between the primarily cause (rainfall) and the effect (landslide). Amongst all the factors influencing the triggering of landslides, rainfall is-for instance-one of the most important and the easiest to correctly quantify, e.g. using rain gauges or radar measurements. The majority of the black box approaches are based on an empirical or statistical study of the rainfall characteristics that in the past led to landslides initiation (Caine 1980;Wieczorek 1996;Aleotti 2004;Guzzetti et al. 2008;Brunetti et al. 2010). Such study is aimed at deriving a mathematical equation which represents the threshold beyond whi...

A simple method to help determine landslide susceptibility from spaceborne InSAR data: the Montescaglioso case study

“…While this type of methodology might in all probability be less responsive in cases of landslides generally characterized by steady movements (e.g., soil creep, slow mudflows and earthflows), its use may rather be of particular advantage in the case of landslides with a behavior driven for the most part by rainfall intensity, like in the Montescaglioso case study. The dependence between water and slope movements surely recurs frequently in most of the Apennines and in many regions worldwide as well (Canuti et al 1985;Guzzetti et al 2002Guzzetti et al , 2007Martelloni et al 2012;Rosi et al 2012;Segoni et al 2014). On the other hand, a long time series is essential in order to determine representative mean and standard deviation of the incremental displacements.…”

Risk-based analysis of monitoring time intervals for landslide prevention

“…20 Different numbers of days have been considered and examined by researchers to find the most suitable correlation with landslide initiation (Aleotti, 2004;Polemio and Sdao, 1999;Zêzere et al, 2005). Of the issue, the researchers have proposed different numbers of days, however, only with local validity, which means that suggested rainfall thresholds are applicable to the respective study cases, and it also depends on the landside type (Jakob et al, 2006;Martelloni et al, 2012). Therefore, we referred to the domestic research results in that characteristics of local geology, soil and vegetation, as well as precipitation 25 patterns are different from the areas of other studies.…”

“…Despite the limitation on the accumulated landslide inventory data over the study region, the frequency of landslide occurrence was estimated by establishing a rainfall threshold. The selection of the rainfall threshold has been examined and proposed by various methodologies (Crozier, 2005;Guzzetti et al, 2007;Zêzere et 25 al., 2005;Frattini et al, 2009;Crosta and Frattini, 2003;Aleotti, 2004;Polemio and Sdao, 1999;Caine, 1980), and it has been shown that proposed rainfall thresholds are applicable to the respective study cases depending on the landside type with local validity (Jakob et al, 2006;Martelloni et al, 2012), so the criteria of cumulative precipitation and daily rainfall intensity for rainfall threshold setting were determined by referring to the local research results.…”

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

“…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).…”