MODELING OF RAINFALL-RUNOFF RELATIONSHIP IN ABIA AND IMO STATE, NIGERIA

Abstract

Rainfall–runoff relationships play a critical role in hydrological analysis, flood prediction, erosion control, and water resources management, particularly in humid tropical environments such as Nigeria. This study evaluated the relationship between rainfall and runoff in Abia and Imo states, southeastern Nigeria, using long-term hydro-meteorological data spanning 25 years (1984–2009). Rainfall and associated climatological variables were analyzed, and runoff was estimated using two modelling approaches: linear regression analysis and fuzzy logic modelling. Monthly rainfall exhibited a distinct seasonal pattern, with peak values occurring between June and September, corresponding to higher runoff generation. Model performance assessment revealed that both approaches adequately simulated runoff responses; however, the fuzzy logic model demonstrated superior predictive capability with a lower average relative error of 13.40%, compared to 21.07% obtained from the regression model. The results confirm rainfall as the dominant factor influencing runoff generation in the study area and highlight the effectiveness of fuzzy logic techniques in capturing nonlinearity and uncertainty inherent in hydrological systems. The developed models provide a reliable framework for runoff prediction and can support erosion control planning, flood mitigation, and sustainable water resource management in southeastern Nigeria.