Stochastic Rainfall Model for Irrigation Projects

Abstract

Stochastic rainfall models are concerned with the time of occurrence and depth of rainfall. Various rainfall models have been using different time scales. Daily rainfall models have gained wide applicability as being appropriate for use in detailed water balance and agricultural and environmental models. In this study a stochastic daily rainfall generation model was adapted for the Besut Irrigation Scheme located in Terengganu, Malaysia. The model simulates the sequence of rainfall occurrence using the method of transitional probability matrices, while daily rainfall amount was generated using a skewed normal distribution. Rainfall data from six meteorological stations located at the Besut Irrigation Scheme were used for this model. The model parameters were estimated from historical rainfall records. The model validation was then performed with a separate set of data. Results obtained showed that the model could be used to generate rainfall data satisfactorily.