Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Nat. Hazards Earth Syst. Sci., 16, 2501-2510, 2016
http://www.nat-hazards-earth-syst-sci.net/16/2501/2016/
doi:10.5194/nhess-16-2501-2016
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
30 Nov 2016
Landslide forecasting and factors influencing predictability
Emanuele Intrieri and Giovanni Gigli Department of Earth Sciences, University of Studies of Firenze, via La Pira 4, 50121 Florence, Italy
Abstract. Forecasting a catastrophic collapse is a key element in landslide risk reduction, but it is also a very difficult task owing to the scientific difficulties in predicting a complex natural event and also to the severe social repercussions caused by a false or missed alarm. A prediction is always affected by a certain error; however, when this error can imply evacuations or other severe consequences a high reliability in the forecast is, at least, desirable.

In order to increase the confidence of predictions, a new methodology is presented here. In contrast to traditional approaches, this methodology iteratively applies several forecasting methods based on displacement data and, thanks to an innovative data representation, gives a valuation of the reliability of the prediction. This approach has been employed to back-analyse 15 landslide collapses. By introducing a predictability index, this study also contributes to the understanding of how geology and other factors influence the possibility of forecasting a slope failure. The results showed how kinematics, and all the factors influencing it, such as geomechanics, rainfall and other external agents, are key concerning landslide predictability.


Citation: Intrieri, E. and Gigli, G.: Landslide forecasting and factors influencing predictability, Nat. Hazards Earth Syst. Sci., 16, 2501-2510, doi:10.5194/nhess-16-2501-2016, 2016.
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Short summary
Forecasting a landslide collapse is a key element in risk reduction, but it is also a very difficult task due to scientific difficulties in predicting a complex natural event and the severe social repercussions caused by a false or missed alarm. In order to help decision makers, we propose a method of increasing the confidence when making landslide predictions. This study also helps understand how geology affects landslide predictability by introducing a predictability index.
Forecasting a landslide collapse is a key element in risk reduction, but it is also a very...
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