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Prediction of the extent and probability of debris flow under rainfallconditions can contribute to precautionary activities through riskquantification. To this end, quantifying the debris-flow risk against rainfallinvolves three components: predicting the debris-flow initiation locationsunder rainfall conditions, setting appropriate physical parameters related todebris-flow transportation, and evaluating the affected area using numericalsimulation. In this study, we developed a logistic regression method thatincludes rainfall and topographic parameters as explanatory variables toquantify the probability of debris-flow initiation in an actual area withdisaster record. Moreover, an objective parameter-set selection was introducedby evaluating the agreement between the simulation results with multipleparameters and the erosion/deposition area determined using the aerial lightdetection and ranging difference data after debris flow. Finally, by combiningthese results, we conducted a predictive debris-flow transport simulation usingthe initiation datasets generated by the logistic model. Therefore, the spatialdistribution using the probability of the effects of debris-flow, which can beapplied for risk quantification and evacuation optimization, was successfullyobtained at 1-m resolution. Furthermore, a real-time hazard probabilityprediction system could be developed based on the presented simulation cost.

Prediction of spatial distribution of debris-flow hit probability considering the source-location uncertainty