A model for Flood Prediction in Ibadan, Nigeria

• Authors: Oluwaferanmi Oladipupo Alalade , Felix Oluranti Okeowo , Oluwole Akinyele Agbede
• Languages of publication: EN

Abstracts

EN

Flooding in Ibadan has led to loss of life, property damage, uninhabitable dwellings, infrastructure destruction, crop loss, traffic congestion, and transportation disruption. This project focused on studying flooding in Ibadan by analysing flood events spanning 1981 to 2021, examining rainfall data, and developing a prediction model for estimating the return periods of peak monthly rainfalls in the city. In this project, rainfall data was obtained from NASA's website and analysed using Microsoft Excel for Exploratory Data Analysis. Three probability positions (Hazen, California, and Weibull) were utilized to estimate return periods of peak monthly rainfalls in Ibadan. Various linear regression models were generated at different scales and evaluated using the Coefficient of Determination. The best model was selected to predict the return period of peak monthly rainfall. Hourly discharges were also compared. In the Exploratory Data Analysis, the maximum annual rainfall and wettest month in Ibadan were identified. The prediction model for peak rainfall return period yielded a satisfactory coefficient of determination of 0.9389, making it suitable for predictions. The graph comparing Hourly Discharges over two days revealed that the discharge during the 2011 flood in Ibadan was three times higher than four days prior. The study shows that to manage the effect of future flood, a prediction model such as the one generated in this project is needed to allow for maximum preparation. Furthermore, the drainage channels need to be widened and deepened to allow them to carry any sudden increase in discharge from the Ogunpa river.

Keywords

EN

Flood; coefficient of determination; flood prediction; return period

Discipline

• ENVIRONMENT_&_ECOLOGY: ENVIRONMENT & ECOLOGY

• Publisher: Scientific Publishing House „DARWIN”
• Journal: World News of Natural Sciences
• Year: 2025
• Volume: 58
• Pages: 283-300

Contributors

author

Oluwaferanmi Oladipupo Alalade

• Department of Civil Engineering, Faculty of Technology, University of Ibadan, Ibadan, Nigeria

author

Felix Oluranti Okeowo

• State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China

author

Oluwole Akinyele Agbede

• Department of Civil Engineering, Faculty of Technology, University of Ibadan, Ibadan, Nigeria

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• Document Type: article