Modelling spatial variation of extreme precipitation over Ho Chi Minh City under nonstationary condition

Abstract

Understanding the magnitude and spatial variation of extreme rainfall events are required for decision making and adaptation strategies for flood risk. In Ho Chi Minh City (HCMC), heavy rainfall, which is considered as a main cause of floods, witnessed an increase in frequency and magnitude in last few decades. Although nonstationarity in extreme rainfall has been proved in many places of the world, research into nonstationarity feature in extreme rainfall in HCMC has not been paid attention thoroughly. In this study, the spatial variation of extreme precipitation over Ho Chi Minh City is modelled under nonstationary condition. The generalized extreme value (GEV) distribution with location made a nonlinear function of time is applied to annual maximum daily rainfall. The study results show that the nonstationary GEV model is found to be superior in capturing extreme precipitation events when compared to the stationary GEV model. The extreme rainfall estimates under the stationary condition are lower than those under the nonstationary condition in most stations. Besides, the spatial variation of extreme rainfall under nonstationary condition shows a significant difference in extreme estimates between the periods of 1980–1984 and 2010–2014 in study area.