Time Series Analysis Model for Rainfall Data in Jordan: Case Study for Using Time Series Analysis

Problem statement: Time series analysis and forecasting has become a major tool in different applications in hydrology and environmental management fields. Among the most effective approaches for analyzing time series data is the model introduced by Box and Jenkins, ARIMA (Autoregressive Integrated Moving Average). Approach: In this study we used Box-Jenkins methodology to build ARIMA model for monthly rainfall data taken for Amman airport station for the period from 1922-1999 with a total of 936 readings. Results: In this research, ARIMA (1, 0, 0) (0, 1, 1)12 model was developed. This model is used to forecasting the monthly rainfall for the upcoming 10 years to help decision makers establish priorities in terms of water demand management. Conclusion/Recommendations: An intervention time series analysis could be used to forecast the peak values of rainfall data.