Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloStatistical approaches for the definition of landslide rainfall thresholds and their uncertainty using rain gauge and satellite data
Anno di pubblicazione2017
Formato
  • Elettronico
  • Cartaceo
Autore/iRossi, M.; Luciani, S.; Valigi, D.; Kirschbaum, D.; Brunetti, M. T.; Peruccacci, S.; Guzzetti, F.
Affiliazioni autoriCNR; Univ Perugia; NASA
Autori CNR e affiliazioni
  • MAURO ROSSI
  • SILVIA PERUCCACCI
  • MARIA TERESA BRUNETTI
  • FAUSTO GUZZETTI
Lingua/e
  • inglese
AbstractModels for forecasting rainfall-induced landslides are mostly based on the identification of empirical rainfall thresholds obtained exploiting rain gauge data. Despite their increased availability, satellite rainfall estimates are scarcely used for this purpose. Satellite data should be useful in ungauged and remote areas, or should provide a significant spatial and temporal reference in gauged areas. In this paper, the analysis of the reliability of rainfall thresholds based on rainfall remote sensed and rain gauge data for the prediction of landslide occurrence is carried out. To date, the estimation of the uncertainty associated with the empirical rainfall thresholds is mostly based on a bootstrap resampling of the rainfall duration and the cumulated event rainfall pairs (D,E) characterizing rainfall events responsible for past failures. This estimation does not consider the measurement uncertainty associated with D and E. In the paper, we propose (i) a new automated procedure to reconstruct ED conditions responsible for the landslide triggering and their uncertainties, and (ii) three new methods to identify rainfall threshold for the possible landslide occurrence, exploiting rain gauge and satellite data. In particular, the proposed methods are based on Least Square (IS), Quantile Regression (QR) and Nonlinear Least Square (NLS) statistical approaches. We applied the new procedure and methods to define empirical rainfall thresholds and their associated uncertainties in the Umbria region (central Italy) using both rain-gauge measurements and satellite estimates. We finally validated the thresholds and tested the effectiveness of the different threshold definition methods with independent landslide information. The NLS method among the others performed better in calculating thresholds in the full range of rainfall durations. We found that the thresholds obtained from satellite data are lower than those obtained from rain gauge measurements. This is in agreement with the literature, where satellite rainfall data underestimate the "ground" rainfall registered by rain gauges. (C) 2017 Elsevier B.V. All rights reserved.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da16
Pagine a27
Pagine totali12
RivistaGeomorphology (Amst.)
Attiva dal 1987
Editore: Elsevier - Oxford ;
Paese di pubblicazione: Paesi Bassi
Lingua: inglese
ISSN: 0169-555X
Titolo chiave: Geomorphology (Amst.)
Titolo proprio: Geomorphology. (Amst.)
Titolo abbreviato: Geomorphology (Amst.)
Numero volume della rivista285
Fascicolo della rivista-
DOI10.1016/j.geomorph.2017.02.001
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000405048500002)
Parole chiaveLandslide prediction, Rainfall threshold, Satellite rainfall estimates, Threshold uncertainty
Link (URL, URI)-
Titolo parallelo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • IRPI — Istituto di ricerca per la protezione idrogeologica
Moduli/Attività/Sottoprogetti CNR
  • TA.P05.005.005 : Applicazioni delle Osservazioni della Terra per il monitoraggio ambientale, il controllo del territorio e la protezione dai rischi: frane, fattori d'instabilità e caratteristiche dei sedimenti argillosi
  • DTA.AD003.216.001 : FRANE - Monitoraggio e modellazione per la valutazione della pericolosità da frana e la gestione del rischio
Progetti Europei-
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