  Prediction of the extent and probability of debris flow under rainfall
conditions can contribute to precautionary activities through risk
quantification. To this end, quantifying the debris-flow risk against rainfall
involves three components: predicting the debris-flow initiation locations
under rainfall conditions, setting appropriate physical parameters related to
debris-flow transportation, and evaluating the affected area using numerical
simulation. In this study, we developed a logistic regression method that
includes rainfall and topographic parameters as explanatory variables to
quantify the probability of debris-flow initiation in an actual area with
disaster record. Moreover, an objective parameter-set selection was introduced
by evaluating the agreement between the simulation results with multiple
parameters and the erosion/deposition area determined using the aerial light
detection and ranging difference data after debris flow. Finally, by combining
these results, we conducted a predictive debris-flow transport simulation using
the initiation datasets generated by the logistic model. Therefore, the spatial
distribution using the probability of the effects of debris-flow, which can be
applied for risk quantification and evacuation optimization, was successfully
obtained at 1-m resolution. Furthermore, a real-time hazard probability
prediction system could be developed based on the presented simulation cost.
