EXTRACTION OF FILTERS APPLICABLE TO FLOOD FORECASTING MODEL AND PERFORMANCE EVALUATION BY INFORMATION CRITERION

Abstract

 There are various types of filters used for flood forecasting, including particle filters, but there has been no case in which the performance of filters is evaluated by employing an information criteria WAIC. Since particle degeneration is a problem in flood forecasting, five types of filters from the fields of moving object tracking, signal processing, image recognition, weather forecasting, that have the potential to work with degeneration were selected and used to evaluate the performance with WAIC. The filter performance was sufficient for all five types, but there was a slight difference in WAIC. In order to evaluate the significance of the WAIC difference, simulating the predicted rainfall error, analyzing the magnitude of the water level error, and estimating the ratio of the difference between filters to the water level error were conducted. As a result, it was found that the error between filters in the predicted water level was small, and the difference between the filters was also extremely small. Therefore, it was concluded that there was almost no difference in the performance between the five types of filters.