Drought prediction in Thailand using spatial analysis with bayesian generalized linear mixed models

Abstract

The objectives of this research were to propose a spatial analysis using Bayesian generalized linear mixed model for predicting drought in Thailand. The spatial effect was assumed to be a conditional autoregressive model (CAR model). The dependent variables was a drought or non-drought occurrence which was assumed to have a Bernolli distribution with logistic link function. Factors considered were rain, temperature, number of rainy days, number of large reservoirs and number of medium reservoirs. The results show that the rain, temperature, number of rainy days, number of large reservoirs and number of medium reservoirs influence on the drought occurrence. This study is useful for planning, making decision, preventing and remedying the drought problem.