In this paper, a methodology to automate and standardize the identification of rainfall intensity-duration thresholds for landslides triggering is presented. A newly developed software called MaCumBA (MAssive CUMulative Brisk Analyzer) can be used to analyze rain-gauge records, extract the intensities (I) and durations (D) of the rainstorms associated with the initiation of landslides, plot these values on a diagram and identify thresholds that define the lower bounds of the aforementioned I-D values. Because the methodology is automated, it is possible to process a relevant amount of data in short times, while allowing for user decision input. A back analysis using data from past events that did not trigger landslides can be used to identify the threshold conditions associated with the least amount of false alarms. We applied the methodology in two test sites. A validation procedure returned satisfactory results, demonstrating the potential utility of the proposed methodology in the development of landslide warning systems.
Landslides triggered by rainfall: A semi-automated procedure to define consistent intensity–duration thresholds / Segoni S.; Rossi G.; Rosi A.; Catani F.. - In: COMPUTERS & GEOSCIENCES. - ISSN 0098-3004. - ELETTRONICO. - 63:(2014), pp. 123-131. [10.1016/j.cageo.2013.10.009]
Landslides triggered by rainfall: A semi-automated procedure to define consistent intensity–duration thresholds
SEGONI, SAMUELE;ROSSI, GUGLIELMO;ROSI, ASCANIO;CATANI, FILIPPO
2014
Abstract
In this paper, a methodology to automate and standardize the identification of rainfall intensity-duration thresholds for landslides triggering is presented. A newly developed software called MaCumBA (MAssive CUMulative Brisk Analyzer) can be used to analyze rain-gauge records, extract the intensities (I) and durations (D) of the rainstorms associated with the initiation of landslides, plot these values on a diagram and identify thresholds that define the lower bounds of the aforementioned I-D values. Because the methodology is automated, it is possible to process a relevant amount of data in short times, while allowing for user decision input. A back analysis using data from past events that did not trigger landslides can be used to identify the threshold conditions associated with the least amount of false alarms. We applied the methodology in two test sites. A validation procedure returned satisfactory results, demonstrating the potential utility of the proposed methodology in the development of landslide warning systems.File | Dimensione | Formato | |
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