Assessment of Risk of Rainfall Events with a Hybrid of ARFIMA-GARCH

Ibrahim Lawal Kane, Fadhilah Yusof


Hazardous situations related to rainfall events can be due to very intense rainfall, or to the persistence of rainfall over a long period of time. Such events may result to an exceedence of the capacity of drainage systems resulting in the heap of basements which may lead to landslides and flooding. This study assesses the persistence dependence of rainfall time series of Chui Chak, a station in Peninsular Malaysia that observed the highest rainfall event for the period 01/01/1975-31/12/2008. The persistence dependence of the rainfall time series was modelled via fractional ARIMA model augmented with the GARCH model. The Ljung-Box test for testing autocorrelation proves that the combined ARFIMA-GARCH model captures the temporal persistence behaviour in the Chui Chak rainfall time series data with persistence measure 0.839. This measure represents a relatively lasting persistence, that is, the process variability should return to the historical average after a relatively long period of time which may have a risk of extreme event.

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