INTEGRATING EMPIRICAL RAINFALL THRESHOLDS AND HYDROLOGIC MONITORING FOR DEVELOPING PRELIMINARY LANDSLIDE EARLY WARNING CRITERIA

2016 ◽  
Author(s):  
Benjamin B. Mirus ◽  
◽  
Joel B. Smith ◽  
Rex L. Baum
Keyword(s):  
Early Warning ◽  
Rainfall Thresholds ◽  
Landslide Early Warning ◽  
Warning Criteria ◽  
Hydrologic Monitoring

Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning

Landslides ◽  
2018 ◽  
Vol 15 (10) ◽  
pp. 1909-1919 ◽  
Author(s):  
Benjamin B. Mirus ◽  
Rachel E. Becker ◽  
Rex L. Baum ◽  
Joel B. Smith
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Rainfall Thresholds ◽  
Landslide Early Warning ◽  
Hydrologic Monitoring

scholarly journals Definition of 3D rainfall thresholds to increase operative landslide early warning system performances

Landslides ◽  
2020 ◽  
Author(s):  
Ascanio Rosi ◽  
Samuele Segoni ◽  
Vanessa Canavesi ◽  
Antonio Monni ◽  
Angela Gallucci ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Rainfall Thresholds ◽  
Landslide Early Warning ◽  
Definition Of

scholarly journals Brief communication: Using averaged soil moisture estimates to improve the performances of a regional-scale landslide early warning system

2018 ◽  
Vol 18 (3) ◽  
pp. 807-812 ◽  
Author(s):  
Samuele Segoni ◽  
Ascanio Rosi ◽  
Daniela Lagomarsino ◽  
Riccardo Fanti ◽  
Nicola Casagli
Keyword(s):  
Soil Moisture ◽  
Early Warning ◽  
Early Warning System ◽  
Preliminary Investigation ◽  
Regional Scale ◽  
Back Analysis ◽  
Warning System ◽  
False Alarms ◽  
Rainfall Thresholds ◽  
Landslide Early Warning

Abstract. We communicate the results of a preliminary investigation aimed at improving a state-of-the-art RSLEWS (regional-scale landslide early warning system) based on rainfall thresholds by integrating mean soil moisture values averaged over the territorial units of the system. We tested two approaches. The simplest can be easily applied to improve other RSLEWS: it is based on a soil moisture threshold value under which rainfall thresholds are not used because landslides are not expected to occur. Another approach deeply modifies the original RSLEWS: thresholds based on antecedent rainfall accumulated over long periods are substituted with soil moisture thresholds. A back analysis demonstrated that both approaches consistently reduced false alarms, while the second approach reduced missed alarms as well.

scholarly journals Satellite-derived rainfall thresholds for landslide early warning in Bogowonto Catchment, Central Java, Indonesia

2020 ◽  
Vol 89 ◽  
pp. 102093 ◽  
Author(s):  
Elias E. Chikalamo ◽  
Olga C. Mavrouli ◽  
Janneke Ettema ◽  
Cees J. van Westen ◽  
Agus S. Muntohar ◽  
...  
Keyword(s):  
Early Warning ◽  
Rainfall Thresholds ◽  
Central Java ◽  
Landslide Early Warning

scholarly journals Brief communication: Rainfall thresholds based on Artificial neural networks can improve landslide early warning

2021 ◽  
Author(s):  
Pierpaolo Distefano ◽  
David J. Peres ◽  
Pietro Scandura ◽  
Antonino Cancelliere
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Performance Improvement ◽  
Early Warning ◽  
Rainfall Intensity ◽  
Rainfall Event ◽  
Rainfall Thresholds ◽  
Event Duration ◽  
Landslide Early Warning ◽  
Artificial Neural

Abstract. In this communication we show how the use of artificial neural networks (ANNs) can improve the performance of the rainfall thresholds for landslide early warning. Results for Sicily (Italy), show how performance of a traditional rainfall event duration and depth power law threshold, yielding a true skill statistic (TSS) of 0.50, can be improved by ANNs (TSS = 0.59). Then we show how ANNs allow to easily add other variables, like peak rainfall intensity, with a further performance improvement (TSS = 0.64). This may stimulate more research on the use of this powerful tool for deriving landslide early warning thresholds.

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