An Application of Time Series Analysis in Modeling Monthly Rainfall Data for Maiduguri, North Eastern Nigeria

Abstract

Time series analysis and forecasting has become a major tool in different applications in meteorological phenomena such as rainfall, humidity, temperature, draught and so on; and environmental fields. Among the most effective approaches for analyzing time series data is the ARIMA (Autoregressive Integrated Moving Average) model introduced by Box and Jenkins. In this study, Box-Jenkins methodology was used to model monthly rainfall data taken from Maiduguri Airport Station for the period from 1981 to 2011 with a total of 372 readings. ARIMA (1, 1,0) model was developed. This model was used to forecast monthly rainfall for the upcoming 44 months (3 years 8 months) to help decision makers establish priorities in terms of water demand management and agriculture. Thus, ARIMA (1, 1,0) provides a good fit for the rainfall data of Maiduguri and is appropriate for short term forecast.Key Words: Time Series Analysis, Rainfall Model, Forecasting, ARIMA.