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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2017-12-01
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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 |
work_keys_str_mv |
AT rgreco basicfeaturesofthepredictivetoolsofearlywarningsystemsforwaterrelatednaturalhazardsexamplesforshallowlandslides AT lpagano basicfeaturesofthepredictivetoolsofearlywarningsystemsforwaterrelatednaturalhazardsexamplesforshallowlandslides |
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1725926581320286208 |