Articles | Volume 17, issue 12
Nat. Hazards Earth Syst. Sci., 17, 2213–2227, 2017

Special issue: Landslide early warning systems: monitoring systems, rainfall...

Nat. Hazards Earth Syst. Sci., 17, 2213–2227, 2017

Research article 08 Dec 2017

Research article | 08 Dec 2017

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

Roberto Greco1 and Luca Pagano2 Roberto Greco and Luca Pagano
  • 1Dipartimento di Ingegneria Civile Design Edilizia e Ambiente, Universitá degli Studi della Campania “Luigi Vanvitelli”, Via Roma 9, 81031 Aversa (CE), Italy
  • 2Dipartimento di Ingegneria Civile Edile e Ambientale, Universitá degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli, Italy

Abstract. 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.

Short summary
The paper focuses on the main features characterizing predictive models working in early warning systems (EWS), by discussing their aims, the evolution stage of the phenomenon where they should be incardinated, and their architecture, regardless of the specific application field. With reference to flow-like landslide and earth flows, some alternative approaches to the development of the predictive tool and to its implementation in an EWS are described.
Final-revised paper