This study analyzes and forecasts rainfall patterns in Kano State, Nigeria, using a Seasonal Autoregressive Integrated Moving Average (SARIMA) model. A monthly rainfall dataset spanning January 2016 to December 2022 was obtained from the relevant government agency in Nigeria. Descriptive statistics from January 2016 to December 2022 reveal significant monthly rainfall
variations, with a mean of 70.23 mm and a maximum of 323.90 mm, highlighting pronounced seasonality. Time series decomposition confirms a strong annual cycle, with distinct wet and dry periods. The Augmented Dickey-Fuller (ADF) test indicates that the original rainfall series is non-stationary, necessitating seasonal differencing to achieve stationarity. Different ARIMA models were compared using the Akaike Information Criterion (AIC), with the ARIMA(0,0,1)(0,2,4)[12] model emerging as the best fit (AIC = 682.82). Parameter estimation and diagnostic checks confirm the model’s suitability, and residual analysis supports its predictive accuracy. Forecasting for the next year suggests continued seasonal rainfall patterns, aiding climate monitoring, agricultural planning, and water resource management in the region. The study underscores the effectiveness of SARIMA models in capturing seasonal trends and informing decision-making processes related to climate variability.
Adetunji K. Ilori, Olaiya O. O, Kole Emmanuel, and Toyosi Adebambo, “Kano State, Nigeria Rainfall Pattern: An Application of SARIMA Model,” International Journal of Multidisciplinary Research and Publications (IJMRAP), Volume 7, Issue 10, pp. 255-260, 2025.