Debris flow triggered by rainfall that accompanies a volcanic eruption is a serious secondary impact of a volcanic disaster. The probability of debris flow events can be estimated based on the prior information of rainfall from historical and geomorphological data that are presumed to relate to debris flow occurrence. In this study, a debris flow disaster warning system was developed by applying the Naïve Bayes Classifier (NBC). The spatial likelihood of the hazard is evaluated at a small subbasin scale by including high-resolution rainfall measurements from X-band polarimetric weather radar, a topographic factor, and soil type as predictors. The study was conducted in the Gendol River Basin of Mount Merapi, one of the most active volcanoes in Indonesia. Rainfall and debris flow occurrence data were collected for the upper Gendol River from October 2016 to February 2018 and divided into calibration and validation datasets. The NBC was used to estimate the status of debris flow incidences displayed in the susceptibility map that is based on the posterior probability from the predictors. The system verification was performed by quantitative dichotomous quality indices along with a contingency table. Using the validation datasets, the advantage of the NBC for estimating debris flow occurrence is confirmed. This work contributes to existing knowledge on estimating debris flow susceptibility through the data mining approach. Despite the existence of predictive uncertainty, the presented system could contribute to the improvement of debris flow countermeasures in volcanic regions.

降雨伴随火山喷发引发的泥石流是火山灾害的严重次级影响。可以根据来自历史和地貌数据的降雨先验信息估算泥石流事件的概率，这些信息被认为与泥石流的发生有关。在这项研究中，通过应用朴素贝叶斯分类器（NBC）开发了泥石流灾害预警系统。通过包括来自X波段极化气象雷达的高分辨率降雨测量，地形因子和土壤类型作为预测因素，可以在较小的流域尺度上评估灾害的空间可能性。这项研究是在印度尼西亚最活跃的火山之一的默拉皮火山的热多尔河流域进行的。收集了2016年10月至2018年2月Gendol河上游的降雨和泥石流发生数据，并将其分为校准和验证数据集。NBC被用来估算在敏感性地图中显示的泥石流发生状况，该状况基于来自预测变量的后验概率。通过定量的二分质量指数和列联表进行系统验证。使用验证数据集，可以确定NBC在估算泥石流发生方面的优势。这项工作有助于通过数据挖掘方法来估计泥石流敏感性的现有知识。尽管存在预测不确定性，但所提出的系统可能有助于改善火山区泥石流对策。