A method for detecting rainfall that causes sediment disaster by applying the general state space model

Abstract

The accuracy rate of sediment disaster warning information in Japan is extremely low, around 5%. The first reason for this is that data consisting of hourly rainfall and soil water index are processed as independently generated data points, not as time series. The second reason is that the RBFN output values, which are threshold values calculated based on the independent data, are not linked to the occurrence of sediment disasters. Therefore, in order to improve the accuracy of this warning information, it is necessary to construct a statistical model with time series data of rainfall from the beginning of rainfall to the occurrence of a disaster, and then evaluate whether the output is associated with the occurrence of a disaster. This study presents a method for detecting the singular values included in the rainfall that causes sediment disasters using the general state space model as one of the proposals, and verifies the validity of the method.