Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides

To manage natural risks, an increasing effort is being put in the development of early warning systems (EWS), namely, approaches facing catastrophic phenomena by timely forecasting and alarm spreading throughout exposed population. Research efforts aimed at the development and implementation of...

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Main Authors: R. Greco, L. Pagano
Format: Article
Language:English
Published: Copernicus Publications 2017-12-01
Series:Natural Hazards and Earth System Sciences
Online Access:https://www.nat-hazards-earth-syst-sci.net/17/2213/2017/nhess-17-2213-2017.pdf
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spelling doaj-0762f87f7966429ebfba3a12720088202020-11-24T21:40:20ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812017-12-01172213222710.5194/nhess-17-2213-2017Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslidesR. Greco0L. Pagano1Dipartimento di Ingegneria Civile Design Edilizia e Ambiente, Universitá degli Studi della Campania “Luigi Vanvitelli”, Via Roma 9, 81031 Aversa (CE), ItalyDipartimento di Ingegneria Civile Edile e Ambientale, Universitá degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli, ItalyTo manage natural risks, an increasing effort is being put in the development of early warning systems (EWS), namely, approaches facing catastrophic phenomena by timely forecasting and alarm spreading throughout exposed population. Research efforts aimed at the development and implementation of effective EWS should especially concern the definition and calibration of the interpretative model. This paper analyses the main features characterizing predictive models working in EWS by discussing their aims and their features in terms of model accuracy, evolutionary stage of the phenomenon at which the prediction is carried out and model architecture. Original classification criteria based on these features are developed throughout the paper and shown in their practical implementation through examples of flow-like landslides and earth flows, both of which are characterized by rapid evolution and quite representative of many applications of EWS.https://www.nat-hazards-earth-syst-sci.net/17/2213/2017/nhess-17-2213-2017.pdf
collection DOAJ
language English
format Article
sources DOAJ
author R. Greco
L. Pagano
spellingShingle R. Greco
L. Pagano
Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides
Natural Hazards and Earth System Sciences
author_facet R. Greco
L. Pagano
author_sort R. Greco
title Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides
title_short Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides
title_full Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides
title_fullStr Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides
title_full_unstemmed Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides
title_sort basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides
publisher Copernicus Publications
series Natural Hazards and Earth System Sciences
issn 1561-8633
1684-9981
publishDate 2017-12-01
description To manage natural risks, an increasing effort is being put in the development of early warning systems (EWS), namely, approaches facing catastrophic phenomena by timely forecasting and alarm spreading throughout exposed population. Research efforts aimed at the development and implementation of effective EWS should especially concern the definition and calibration of the interpretative model. This paper analyses the main features characterizing predictive models working in EWS by discussing their aims and their features in terms of model accuracy, evolutionary stage of the phenomenon at which the prediction is carried out and model architecture. Original classification criteria based on these features are developed throughout the paper and shown in their practical implementation through examples of flow-like landslides and earth flows, both of which are characterized by rapid evolution and quite representative of many applications of EWS.
url https://www.nat-hazards-earth-syst-sci.net/17/2213/2017/nhess-17-2213-2017.pdf
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