Extreme Rainfall Forecast and Flood Prediction in Equatorial Zone of West Africa: Port Harcourt, Nigeria in Focus

Abstract

Purpose: Rainfall is the most important element of climate in the tropics, it dictate human outdoor activities, recharge underground water and streams, dictate agricultural calendar and many cultural activities. More recently the incidence of extreme rainfall leading to urban flood in the city of Port Harcourt is increasingly becoming a looming disaster. Despite the importance of rainfall in the tropic, the fact that it varies significantly is worrisome to both scholars and the stakeholders. This study focused on extreme rainfall forecast and flood prediction in equatorial zone of West Africa especially in a humid tropic environment like Port Harcourt.
 Methodology: Statistical Time Series Model performed very well in rainfall forecast, but did better in flood prediction. Secondary data extracted from Nigeria Meteorological Agency, Oshodi, Lagos form 100/3 of the agency record servers as main source of data for this work. Descriptive statistics and inferential statistics were used, among which are mean, standard deviation, and coefficient of variation; Pearson product moment correlation and structural time series model.
 Findings: The study discovered that rainfall distribution has reduced over the years, besides the dry spell in the month of August has deduced gradually but steadily over the years. It also shown that flood cannot occur in the first 6 months of the year. Rainfall distribution varies significantly over the climatic period.
 Conclusion: There is a significant variation in rainfall distribution over Port Harcourt. August dry spell is steadily disappearing, giving raise to excessive run-off that triggers flood during late September to October. Flood will likely occur whenever the forecasted rainfall exceeds the generated level output during the seasonal peak. Structural Time Series Model performed well in flood prediction than in rainfall forecast.
 Recommendations: Extreme RF forecast by the authorities should be taken serious by inhabitants and warning be given and adhered to by residences. Also, structural time series model should be used for long time forecast since it performed very well, but this should be done with large data.