TIME SERIES MODELING OF MONTHLY RAINFALL IN ARID AREAS: CASE STUDY FOR SAUDI ARABIA

Abstract

Stochastic techniques are essential in planning and management of water resources systems especially in arid and semi-arid areas where water is scarce. The forecasting of future events requires identifying proper stochastic models to be used in this process. For this purpose, a Periodic ARMA (PARMA) model and a temporal disaggregation models were used in this study to investigate weather they are appropriate for modeling the monthly rainfall data in Saudi Arabia. Results showed PARMA and temporal disaggregation models performed well in modeling the monthly rainfalls in Saudi Arabia. These models were able to preserve the basic seasonal statistics of the observed data well as preserving the seasonal correlation structure observed in the historical data. However, the PARMA model did not perform well at the annual level. In contrast, the disaggregation model performed well in preserving the correlation structure of the historical data at the annual level. Thus, these models can be used in modeling and forecasting of monthly rainfall in Arid and semi-arid areas.