Measuring volatility persistence on rainfall records with the hybrid of autoregressive fractional integrated moving average (ARFIMA) - Hidden Markov Model (HMM)

Abstract

Precarious circumstances related to rainfall events can be due to very intense or persistence of rainfall over a long period of time. Such events may give rise to an exceedence of the capacity of sewer systems resulting to landslides or flooding. One of the conventional ways of measuring such risk associated with persistence in rain is done through studies of long term persistence and volatility persistence. This work investigates the persistence level of Kuantan daily rainfall using the hybrid of autoregressive fractional integrated moving average (ARFIMA) and hidden Markov model (HMM). The result shows that the rainfall variability period returns quickly to its usual variability level which may not have a lasting period of extreme wet, hence relatively stable rainfall behavior is observed in Kuantan rainfall. This will enhance the understanding of the process for the successful development and implementation of water resource tools to assess engineering and environmental problems such as flood control.