Abstract
Abstract. Assessment of landslide-triggering rainfall thresholds is useful for early warning in prone areas. In this paper, it is shown how stochastic rainfall models and hydrological and slope stability physically based models can be advantageously combined in a Monte Carlo simulation framework to generate virtually unlimited-length synthetic rainfall and related slope stability factor of safety data, exploiting the information contained in observed rainfall records and field-measurements of soil hydraulic and geotechnical parameters. The synthetic data set, dichotomized in triggering and non-triggering rainfall events, is analyzed by receiver operating characteristics (ROC) analysis to derive stochastic-input physically based thresholds that optimize the trade-off between correct and wrong predictions. Moreover, the specific modeling framework implemented in this work, based on hourly analysis, enables one to analyze the uncertainty related to variability of rainfall intensity within events and to past rainfall (antecedent rainfall). A specific focus is dedicated to the widely used power-law rainfall intensity–duration (I–D) thresholds. Results indicate that variability of intensity during rainfall events influences significantly rainfall intensity and duration associated with landslide triggering. Remarkably, when a time-variable rainfall-rate event is considered, the simulated triggering points may be separated with a very good approximation from the non-triggering ones by a I–D power-law equation, while a representation of rainfall as constant–intensity hyetographs globally leads to non-conservative results. This indicates that the I–D power-law equation is adequate to represent the triggering part due to transient infiltration produced by rainfall events of variable intensity and thus gives a physically based justification for this widely used threshold form, which provides results that are valid when landslide occurrence is mostly due to that part. These conditions are more likely to occur in hillslopes of low specific upslope contributing area, relatively high hydraulic conductivity and high critical wetness ratio. Otherwise, rainfall time history occurring before single rainfall events influences landslide triggering, determining whether a threshold based only on rainfall intensity and duration may be sufficient or it needs to be improved by the introduction of antecedent rainfall variables. Further analyses show that predictability of landslides decreases with soil depth, critical wetness ratio and the increase of vertical basal drainage (leakage) that occurs in the presence of a fractured bedrock.
Highlights
Rainfall thresholds indicating landslide triggering are useful for the development of early warning systems in prone areas
When a time-variable rainfall-rate event is considered, the simulated triggering points may be separated with a very good approximation from the non-triggering ones by a intensity– duration (I –D) powerlaw equation, while a representation of rainfall as constant– intensity hyetographs globally leads to non-conservative results. This indicates that the I –D power-law equation is adequate to represent the triggering part due to transient infiltration produced by rainfall events of variable intensity and gives a physically based justification for this widely used threshold form, which provides results that are valid when landslide occurrence is mostly due to that part
The approach synthesizes research findings in the fields of rainfall and landslide hydrological modeling to provide an output that is implemented in a early warning system, i.e., a landslide-triggering threshold, based on rainfall monitoring, of the same type that is commonly derived by direct empirical analysis of observed rainfall and landslide data
Summary
Rainfall thresholds indicating landslide triggering are useful for the development of early warning systems in prone areas (cf., e.g., Keefer et al, 1987; Fathani et al, 2009; Takara and Apip Bagiawan, 2009; Baum and Godt, 2010; Capparelli and Versace, 2011). Use of solely the duration and intensity pair (D, I ) in threshold formulation implies that the effect of initial wetness on triggering rainfall is neglected Regarding this issue, several authors have added to D and I antecedent rainfall as a control parameter, though the empirical analyses have not yet provided unequivocal indications on the role of antecedent rainfall and different researchers used diverse temporal horizons for its computation (Guzzetti et al, 2007). Because such thresholds were derived from a physically based model, this may be interpreted as an evidence that the use of the power-law form is not supported from a physically based standpoint In such studies the meteorological aspects were analyzed in a simplistic way, because the thresholds do not consider variability of rainfall intensity during events and the initial conditions are not computed as a function of rainfall time history preceding the current event. A sensitivity analysis on some of the most important control variables is carried out to analyze their effect on landslide-triggering thresholds and the associated uncertainty
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