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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Landslides in the Mountain Region of Rio de Janeiro: A Proposal for the Semi-Automated Definition of Multiple Rainfall Thresholds

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Author(s):
Rosi, Ascanio [1] ; Canavesi, Vanessa [1, 2] ; Segoni, Samuele [1] ; Nery, Tulius Dias [2] ; Catani, Filippo [1] ; Casagli, Nicola [1]
Total Authors: 6
Affiliation:
[1] Univ Florence, Dept Earth Sci, Via Giorgio La Pira 4, I-50121 Florence - Italy
[2] Natl Ctr Monitoring & Early Warning Nat Disasters, Estr Doutor Altino Bondensan, BR-12209 Sao Jose Dos Campos, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: GEOSCIENCES; v. 9, n. 5 MAY 2019.
Web of Science Citations: 1
Abstract

In 2011 Brazil experienced the worst disaster in the country's history. There were 918 deaths and thousands made homeless in the mountainous region of Rio de Janeiro State due to several landslides triggered by heavy rainfalls. This area constantly suffers high volumes of rain and episodes of landslides. Due to these experiences, we used the MaCumBa (Massive CUMulative Brisk Analyser) software to identify rainfall intensity-duration thresholds capable of triggering landslides in the most affected municipalities of this region. More than 3000 landslides and rain data from a 10-year long dataset were used to define the thresholds and one year was used to validate the results. In this work, a set of three thresholds capable of defining increasing alert levels (moderate, high and very high) has been defined for each municipality. Results show that such thresholds may be used for early alerts. In the future, the same methodology can be replicated to other Brazilian municipalities with different datasets, leading to more accurate warning systems. (AU)

FAPESP's process: 14/50848-9 - INCT 2014: INCT for Climate Change
Grantee:Jose Antonio Marengo Orsini
Support type: Research Program on Global Climate Change - Thematic Grants