Identification of hydro-meteorological thresholds for rainfall-induced landslide prediction with clustering techniques

Operational early warning systems for rainfall-induced landslides (LEWS) usually rely on simple empirical thresholds based on the statistical analysis of either triggering rainfall characteristics, e.g. intensity and duration (Guzzetti et al., 2007). The main pro of this simplified approach is that it requires only rainfall records, at the desired spatial and temporal resolution, and a database of landslides with known time and location. The effect of the hydrologic conditions of the slopes prior the onset of the triggering rainfall is usually neglected, limiting the performance of the LEWS, which often give rise to false and missing alarms. To address this issue, antecedent precipitation is sometimes included in the definition of the threshold, but the identification of the antecedent precipitation duration is doubtful, as this approach neglects non-linear hydrological processes affecting slope response. Hydro-meteorological thresholds, linking a variable accounting for the antecedent hydrologic conditions with a characteristic of the triggering rainfall, have been recently proposed (Bogaard and Greco, 2018).

In this study, hydro-meteorological thresholds for landslide prediction are identified for a slope in southern Italy, characterized by an unsaturated pyroclastic soil cover laying upon fractured limestone bedrock and subject to rainfall-induced shallow landslides. To this aim, a synthetic 1000 years long hourly point rainfall record is generated with the Neyman-Scott rectangular pulse stochastic model, calibrated thanks to available measured rainfall. The response of the slope to the synthetic rainfall record is simulated by means of a physically-based model, which couples unsaturated flow in the soil cover with a temporary perched aquifer in the limestone bedrock, and allows estimating all the terms of slope water balance (Greco et al., 2018). The stability of the slope is eventually assessed under the infinite slope hypothesis, allowing the identification of the occurrence of landslides.

The obtained synthetic dataset of rainfall and hydrologic variables has been exploited for the definition of hydro-meteorological thresholds. All the combinations of hydrologic variables with triggering rainfall height have been analyzed with several clustering techniques, so to identify the most effective combinations for landslide predictions.

 

References:

Bogaard TA, Greco R (2018). Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds, Nat Hazards Earth Syst Sci, 18: 31–39.

Greco R, Marino P, Santonastaso GF, Damiano E (2018). Interaction between Perched Epikarst Aquifer and Unsaturated Soil Cover in the Initiation of Shallow Landslides in Pyroclastic Soils, Water, 10: 948.

Guzzetti F, Peruccacci S, Rossi M, Stark CP (2007). Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorol Atmos Phys, 98: 239–267.