Rainfall thresholds for triggering shallow landslides in Vara Valley (Liguria, Italy)

2016 ◽  
pp. 943-950 ◽  
Author(s):  
Y Galanti ◽  
R Giannecchini ◽  
G Avanzi ◽  
M Barsanti ◽  
G Benvenuto
Keyword(s):  
Shallow Landslides ◽  
Rainfall Thresholds

Topographic and Pedological Rainfall Thresholds for the Prediction of Shallow Landslides in Central Italy

2014 ◽  
pp. 299-304 ◽  
Author(s):  
Silvia Peruccacci ◽  
Maria Teresa Brunetti ◽  
Silvia Luciani ◽  
Maria Costanza Calzolari ◽  
Devis Bartolini ◽  
...  
Keyword(s):  
Central Italy ◽  
Shallow Landslides ◽  
Rainfall Thresholds

How to account for misclassification costs in shallow-landslide rainfall thresholds?

2021 ◽  
Author(s):  
Paolo Frattini ◽  
Gianluca Sala ◽  
Camilla Lanfranconi ◽  
Giulia Rusconi ◽  
Giovanni Crosta
Keyword(s):  
False Alarm ◽  
Rainfall Intensity ◽  
Rainfall Threshold ◽  
Shallow Landslides ◽  
False Alarms ◽  
Rainfall Thresholds ◽  
Rainfall Events ◽  
Misclassification Costs ◽  
Triggering Events ◽  
The Cost

<p>Rainfall is one of the most significant triggering factors for shallow landslides. The early warning for such phenomena requires the definition of a threshold based on a critical rainfall condition that may lead to diffuse landsliding. The developing of these thresholds is frequently done through empirical or statistical approaches that aim at identifying thresholds between rainfall events that triggered or non-triggered landslides. Such approaches present several problems related to the identification of the exact amount of rainfall that triggered landslides, the local geo-environmental conditions at the landslide site, and the minimum rainfall amount used to define the non-triggering events. Furthermore, these thresholds lead to misclassifications (false negative or false positive) that always induce costs for the society. The aim of this research is to address these limitations, accounting for classification costs in order to select the optimal thresholds for landslide risk management.</p><p>Starting from a database of shallow landslides occurred during five regional-scale rainfall events in the Italian Central Alps, we extracted the triggering rainfall intensities by adjusting rain gouge data with weather radar data. This adjustment significantly improved the information regarding the rainfall intensity at the landslide site and, although an uncertainty related to the exact timing of occurrence has still remained. Therefore, we identified the rainfall thresholds through the Receiver Operating Characteristic (ROC) approach, by identifying the optimal rainfall intensity that separates triggering and non-triggering events. To evaluate the effect related to the application of different minimum rainfall for non-triggering events, we have adopted three different values obtaining similar results, thus demonstrating that the ROC approach is not sensitive to the choice of the minimum rainfall threshold. In order to include the effect of misclassification costs we have developed cost-sensitive rainfall threshold curves by using cost-curve approach (Drummond and Holte 2000). As far as we know, this is the first attempt to build a cost-sensitive rainfall threshold for landslides that allows to explicitly account for misclassification costs. For the development of the cost-sensitive threshold curve, we had to define a reference cost scenario in which we have quantified several cost items for both missed alarms and false alarms. By using this scenario, the cost-sensitive rainfall threshold results to be lower than the ROC threshold to minimize the missed alarms, the costs of which are seven times greater than the false alarm costs. Since the misclassification costs could vary according to different socio-economic contexts and emergency organization, we developed different extreme scenarios to evaluate the sensitivity of misclassification costs on the rainfall thresholds. In the scenario with maximum false-alarm cost and minimum missed-alarm cost, the rainfall threshold increases in order to minimize the false alarms. Conversely, the rainfall thresholds decreases in the scenario with minimum false-alarm cost and maximum missed-alarm costs. We found that the range of variation between the curves of these extreme scenarios is as much as half an order of magnitude.</p>

Estimation of rainfall thresholds for shallow landslides in the Sierra Madre Oriental, northeastern Mexico

2020 ◽  
Vol 17 (7) ◽  
pp. 1565-1580
Author(s):  
Jorge A. Salinas-Jasso ◽  
Fernando Velasco-Tapia ◽  
Ignacio Navarro de León ◽  
Ricardo A. Salinas-Jasso ◽  
Efraín Alva-Niño
Keyword(s):  
Shallow Landslides ◽  
Rainfall Thresholds ◽  
Sierra Madre Oriental ◽  
Sierra Madre ◽  
Northeastern Mexico

Spatially distributed rainfall thresholds for the initiation of shallow landslides

2011 ◽  
Vol 61 (1) ◽  
pp. 229-245 ◽  
Author(s):  
Diana Salciarini ◽  
Claudio Tamagnini ◽  
Pietro Conversini ◽  
Silvia Rapinesi
Keyword(s):  
Shallow Landslides ◽  
Rainfall Thresholds ◽  
Spatially Distributed

scholarly journals Automated reconstruction of rainfall events responsible for shallow landslides

2014 ◽  
Vol 14 (9) ◽  
pp. 2399-2408 ◽  
Author(s):  
G. Vessia ◽  
M. Parise ◽  
M. T. Brunetti ◽  
S. Peruccacci ◽  
M. Rossi ◽  
...  
Keyword(s):  
Rainfall Intensity ◽  
Shallow Landslides ◽  
Threshold Values ◽  
Rainfall Thresholds ◽  
Rainfall Events ◽  
Mean Intensity ◽  
Landslide Occurrence ◽  
R Language ◽  
Rain Gauges ◽  
Rainfall Duration

Abstract. Over the last 40 years, many contributions have identified empirical rainfall thresholds (e.g. rainfall intensity (I) vs. rainfall duration (D), cumulated rainfall vs. rainfall duration (ED), cumulated rainfall vs. rainfall intensity (EI)) for the possible initiation of shallow landslides, based on local and global inventories. Although different methods to trace the threshold curves have been proposed and discussed in literature, a systematic study to develop an automated procedure to select the rainfall event responsible for the landslide occurrence has only rarely been addressed. Objective criteria for estimating the rainfall responsible for the landslide occurrence play a prominent role on the threshold values. In this paper, two criteria for the identification of the effective rainfall events are presented. The first criterion is based on the analysis of the time series of rainfall mean intensity values over 1 month preceding the landslide occurrence. The second criterion is based on the analysis of the trend in the time function of the cumulated mean intensity series calculated from the rainfall records measured through rain gauges. The two criteria have been implemented in an automated procedure that is written in the R language. A sample of 100 shallow landslides collected in Italy from 2002 to 2012 was used to calibrate the procedure. The cumulated event rainfall (E) and duration (D) of rainfall events that triggered the documented landslides are calculated through the new procedure and are fitted with power law in the D, E diagram. The results are discussed by comparing the D, E pairs calculated by the automated procedure and the ones by the expert method.

scholarly journals Rainfall thresholds for shallow landslide occurrence in Calabria, southern Italy

2014 ◽  
Vol 14 (2) ◽  
pp. 317-330 ◽  
Author(s):  
C. Vennari ◽  
S. L. Gariano ◽  
L. Antronico ◽  
M. T. Brunetti ◽  
G. Iovine ◽  
...  
Keyword(s):  
Southern Italy ◽  
Central Italy ◽  
Mediterranean Area ◽  
Shallow Landslide ◽  
Google Earth ◽  
Shallow Landslides ◽  
Rainfall Thresholds ◽  
Rainfall Events ◽  
Landslide Occurrence ◽  
Hourly Rainfall

Abstract. In many areas, rainfall is the primary trigger of landslides. Determining the rainfall conditions responsible for landslide occurrence is important, and may contribute to saving lives and properties. In a long-term national project for the definition of rainfall thresholds for possible landslide occurrence in Italy, we compiled a catalogue of 186 rainfall events that resulted in 251 shallow landslides in Calabria, southern Italy, from January 1996 to September 2011. Landslides were located geographically using Google Earth®, and were given a mapping and a temporal accuracy. We used the landslide information, and sub-hourly rainfall measurements obtained from two complementary networks of rain gauges, to determine cumulated event vs. rainfall duration (ED) thresholds for Calabria. For this purpose, we adopted an existing method used to prepare rainfall thresholds and to estimate their associated uncertainties in central Italy. The regional thresholds for Calabria were found to be nearly identical to previous ED thresholds for Calabria obtained using a reduced set of landslide information, and slightly higher than the ED thresholds obtained for central Italy. We segmented the regional catalogue of rainfall events with landslides in Calabria into lithology, soil regions, rainfall zones, and seasonal periods. The number of events in each subdivision was insufficient to determine reliable thresholds, but allowed for preliminary conclusions about the role of the environmental factors in the rainfall conditions responsible for shallow landslides in Calabria. We further segmented the regional catalogue based on administrative subdivisions used for hydro-meteorological monitoring and operational flood forecasting, and we determined separate ED thresholds for the Tyrrhenian and the Ionian coasts of Calabria. We expect the ED rainfall thresholds for Calabria to be used in regional and national landslide warning systems. The thresholds can also be used for landslide hazard and risk assessments, and for erosion and landscape evolution studies, in the study area and in similar physiographic regions in the Mediterranean area.

Rainfall thresholds for the activation of shallow landslides in the Italian Alps: the role of environmental conditioning factors

Geomorphology ◽  
2018 ◽  
Vol 303 ◽  
pp. 53-67 ◽  
Author(s):  
M.R. Palladino ◽  
A. Viero ◽  
L. Turconi ◽  
M.T. Brunetti ◽  
S. Peruccacci ◽  
...  
Keyword(s):  
Shallow Landslides ◽  
Italian Alps ◽  
Rainfall Thresholds ◽  
Conditioning Factors ◽  
Environmental Conditioning
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