A Markovian Model for Rainfall in Owerri Imo State, Nigeria

This book addresses a key gap in agro-meteorological planning: the lack of reliable probabilistic models for predicting monthly rainfall regimes. It quantifies the long-term distribution of dry, wet, and rainy months in Owerri, Imo State, Nigeria, using a three-state, first-order Markov chain model. Based on 36 years of monthly rainfall data, months are classified as dry ( 50 mm), wet (51-150 mm), or rainy (>150 mm). The dominance of rainy months suggests a persistently wet climate, with strong implications for agricultural scheduling. The book provides a stochastic framework to guide crop planning and water resource management in rain-fed systems. Root and perishable crop farmers are encouraged to use these insights to optimize output. It also estimates mean first passage times (MFPT) and mean first recurrence times (MFRT) for rainfall in Owerri. Statistical analysis of rainfall records is essential for understanding rainfall behavior and supporting agricultural and environmental planning.

Autorentext

Angel F. Ohaegbulem is a Statistician currently pursuing her Ph.D. in Nigeria. She's a data-driven, detail-oriented analyst and researcher with a strong academic and global mindset. She founded Gelo's Global Aid Foundation, a nonprofit supporting youth-especially young girls and mothers.