Landslide forecasting and factors influencing predictability

Abstract

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.

Satellite Interferometry as a Tool for Early Warning and Aiding Decision Making in an Open-Pit Mine

“…Here, we have wanted to show how Sentinel-1 used for open-pit mines can be regarded as a tool to formulate hypotheses that are strongly based on reliable data; however, the intrinsic limitations of satellite In-SAR still persist (LOS measurements, discontinuous spatial coverage, possibility of noise, phase wrapping); with respect to ground-based interferometric radar, commonly used to monitor landslides and quarries [7], [74]- [76], the lower frequency of acquisition of satellites allows for meaningful early warnings only for those landslides displaying a slower evolution (which are typically not small sized and not occurring in stiff rocks; [10], [70], [73]). Therefore, the high potential of Sentinel-1 in this matter should not dismiss the importance of field surveys and integrated monitoring to complete and verify such hypotheses.…”

“…This feature has been first harnessed by Saito [64] who used it to develop an empirical landslide forecasting method, from which a series of graphical solutions [36], [65], [66], methodologies and approaches [67]- [70] were then developed. The most popular method derived from the creep theory is the so-called inverse velocity method [36], [71], [72], according to which it is possible to extrapolate the time of failure of a landslide as the intersection between the inverse of the velocity (v −1 ) and the time axis, under the hypothesis that as the velocity increases and theoretically tends toward infinite at the time of collapse, its inverse will tend toward zero.…”

The Maoxian landslide as seen from space: detecting precursors of failure with Sentinel-1 data

“…If an early warning system was in place at the time, the evacuation of Xinmo village would have been highly advisable, even though Fukuzono's method is, naturally, subject to missed or false alarms. For a detailed dissertation upon the confidence of landslide forecasting methods refer to Intrieri and Gigli (2016).…”

Relationship between river bank stability and hydrological processes using in situ measurement data

“…However, to date, the direct effect of hydrological processes on movements and deformations of high river banks (e.g., Uchimura et al 2010;Bittelli et al 2012;Devoti et al 2015;Mentes 2017aMentes , 2017b were barely investigated. Since hydrological processes play a major role in development of landslides, the understanding of their role in determining the stability of high river banks is a significant research task for the development of early warning systems (e.g., Fathani et al 2016;Intrieri and Gigli 2016;Greco and Pagano 2017;Wen et al 2017).…”