Relationship between ENSO and Rainfall in the Central Plain of Thailand

Abstract

In this study, the response of monthly rainfall to the El Nino-southern oscillation (ENSO) was investigated by correlation analysis to determine the pattern and magnitude of the relationship, using rainfall datasets at four weather stations in the Central Plain of Thailand (Kanchanaburi, Lop Buri,
Nakhon Sawan, Suphan Buri). The rainfall data sets characterized by the standardized precipitation index (SPI) and the strengths of ENSO characterized by the multivariate ENSO index (MEI) were searched to get the best SPI-MEI subsets by step-wise multiple regression. Six SPI time scales: 1-, 2-,3-, 4-, 5-, and 6-months were chosen to form regression equations. The results indicated that the chosen statistical approach produced models that could be used to forecast SPI at least one fortnight ahead at 10% significance levels. It can be concluded from this study that the proposed models could contribute to irrigation water management and preparedness for water allocation planning during the dry period
from November to April. However, regional synthesis of the equations is necessary in order to apply the proposed model on a regional scale.