Statistical Evaluation of Rainfall Data in Owerri, Imo State, Nigeria

Abstract

This paper evaluated the monthly and yearly average the rainfall data of Owerri from 2000 to 2016. Two-Way ANOVA was employed in the data and the result showed that the average yearly rainfall in Owerri is not the same but the average monthly rainfall in Owerri is not is not significantly different over the years of study.

Introduction

I. INTRODUCTION

Rainfall is one of the climatologically data which is widely analyzed for a long time. Analysis of rainfall data is important as it facilitates policy decisions regarding the cropping pattern, sowing date, construction of roads and providing drinking water to urban and rural areas. Two season, wet and dry, are observed in the year.

The rainy season begins in April and last till October. Owerri as town in one the South Eastern region in Nigeria experiences climate variations following rainfall variability monthly and yearly. Every rainy season in Nigeria, wind gusts arising from tropical storms claim lives and property worth millions of naira across the country, Okorie et al (2014).stated that flash floods from Torrential rains wash away thousands of hectares of farmlands, Dam bursts were common following such floods.

Rainfall is one of the atmospheric driving forces responsible for climate variations and its effects in Imo State of Nigeria as in other parts of the world. Maduka (2009) indicated that 16% of the erosion in Owerri municipal of Imo state is caused by rainfall. Rainfall is a renewable resource, highly variable in space, time and subject to depletion or enhancement due to both natural and anthropogenic causes, Abaje (2010).

Climate is, with particular reference to rainfall, known to be changing worldwide and there has been growing concern as to the direction and effects of these changes on settlement and infrastructures, (Chaponniere and Smokhtin, (2006)). Many variations in rainfall have occurred for different climate regions and individual locations in Nigeria with associated disasters. These disasters which  had led to many loss of property and human lives, and also contributed to about 91% of mosquitoes breeding responsible for malaria cases in Owerri, Imo State, are attributed to rainfall variability which meaning that rainfall promotes mosquitoes breeding. The earth has experienced cycles of temperature and precipitation changes on a geographical scale. Flooding remains the most common of all environmental hazards worldwide.

Estimation of flood damage potential helps in flood risk management. Recently at Ibeneme Street, Relief Market Junction in Owerri, flood submerged many houses and destroyed property worth millions of naira. This was as a result of rain which lasted for hours and shortly resulted in a flood disaster.

More so, Economic activities suffered a great set back in Owerri due to a heavy downpour that submerged residents and shops in Amakohia area of Owerri. There are several studies on climate change and rainfall data using statistical methods, see for example, Stern and Coe (1984); Arvind, et al (2017);  El-Adlouni and Quarda (2010); Ologunorisa and Tersoo (2006); Gomathy, et al., (2022); Omar, (2022); Lana et al., (2001); Amjadi, et al (2021); Akinsanola and Ogunjobi (2014); Itiowe, et al (2019); Ogunride, et al (2019); Daramola, et al (2017); Animashaun, et al (2020) ; Igwenagu (2014); Shaharudin, et al (2020); Osarunwense (2013).  It is on this premise, therefore, that this study focuses on the statistical analysis of rainfall data from 2000-2016 in Owerri Imo State, Nigeria in order to examine the variability of rainfall over the years.

II. Materials and Method

A. Presentation of Data

The data presented in Table 3.1 was of secondary source from Owerri Municipal Council in Imo State, Nigeria comprising the available data of monthly and yearly rainfall pattern of between 2000 and 2016

Conclusion

From the findings of this paper, we observed that the average yearly rainfall in Owerri was not the same while the average monthly rainfall in Owerri was the same over the years meaning the months of November, February, December and January average monthly rainfall were not significantly different. We, therefore, conclude there were variations in the yearly rainfall but does not vary in the monthly rainfall.

References

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Copyright

Copyright © 2023 Chukwudi Anderson Ugomma. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.