Analysis of the Characteristics of Monthly Rainfall Pattern in Katsina

Abstract

Aims: This paper seeks to analyse the characteristics of monthly rainfall pattern in Katsina City in a view to unveiling the trends and describing its dynamics so that adequate recommendations can be made for its modelling.
 Study Design: The analysis involves a complete statistical, trend, spectral and nonlinear analysis of the monthly rainfall time series recorded in Katsina.
 Place and Duration of Study: Location: Katsina City, Katsina State, Nigeria from 1990 to 2015; a period of 26 years.
 Methodology: Secondary data of daily rainfall recorded in Katsina city from 1990 to 2015 was collected from the Nigerian Meteorological Agency (NiMet), and monthly averages were taken to obtain the monthly rainfall data. The data was then subjected to statistical, trend, spectral and nonlinear analysis techniques to reveal the behavioural patterns in the rainfall and also to reveal its underlying dynamics for its future modelling and prediction.
 Results: The outcome of this analysis indicates that the monthly rainfall in Katsina exhibits an increasing trend with high variance and right-skewed distribution requiring a maximum of 6 independent variables to model its dynamics. The correlation exponent plot reached a saturation value of 5.892 confirming that the monthly rainfall in Katsina over the last 26 years exhibits low dimensional chaotic behavior while the largest Lyapunov exponent for the monthly rainfall time series in Katsina was also computed and found to be positive, having a value of 0.006055/month confirming the presence of deterministic chaos dynamics and is predictable for the next 165 months.
 Conclusion: Since from the findings of this work it is confirmed that the rainfall in Katsina exhibits chaotic behavior with an increasing trend, it is recommended that more drainages and dams be built to provide steady supply of water for agricultural and domestic purposes as well as curtail the menace of flooding and drought which may occur as a result of global warming and climate change.