Extreme rainfall prediction is a critical aspect in hydrological and climate research fields to estimate the probability of extreme events, such as heavy rainfall or floods. These extreme events occur all over the world and have a tremendous impact on human health, injury and illness, and the imbalance of the ecosystem. This paper aims to compare the prediction of extreme rainfall between generalized extreme value distribution (GEV) and generalized Pareto distribution (GPD) for 10 years return period. The daily rainfall data of northern region in Peninsular Malaysia were obtained from Department of Irrigation and Drainage Malaysia (DID) for 29 stations for the period 1999 to 2019 is used. The findings will be beneficial for hydrologists to improve understanding of the difference between the analysis of the standard data modeling with extreme data modeling as well as to understand the difference between two main approaches in extreme data analysis. Both models show Klinik Bkt. Bendera station will encounter the highest 10 years return level compared to the other stations. The maximum corresponding 10-years return value for GPD is 147.26mm while for GEV is 142.39mm. These values are reaching the very heavy category of rainfall intensity index in Malaysia.
