시간적 군집특성을 고려한 강우모의모형의 선정

Abstract

This study, a point rainfall process model, which could represent appropriately observed rainfall data, was to select. The point process models - rectangular pulses Poisson process model(RPPM), Neyman-Scott rectangular pulses Poisson process model(NS-RPPM), and modified Neyman-Scott rectangular pulses Poisson process model(modified NS-RPPM) - all based on Poisson process were considered as possible rainfall models, whose statistical analyses were performed with their simulation rainfall data. As results, simulated rainfall data using the NS-RPPM and the modified NS-RPPM represent appropriately statistics of observed data for several aggregation levels. Also, simulated rainfall data using the modified NS-RPPM shows similar characteristics of rainfall occurrence to the observed rainfall data. Especially, the modified NS-RPPM reproduces high-intensity rainfall events that contribute largely to occurrence of natural harzard such as flood and landslides most similarly. Also, the modified NS-RPPM shows the best results with respect to the total rainfall amount, duration, and inter-event time. In conclusions, the modified NS-RPPM was found to be the most appropriate model for the long-term simulation of rainfall.