International Journal Of Imaging

Abstract

PREDICTING FLOOD EVENTS IN KEBBI STATE, NIGERIA: A MACHINE LEARNING APPROACH TO ENVIRONMENTAL MODELING

Author: L.Ashlesha,, B.Manohar,Shwejan Reddy,G.Prabakaran

Abstract:

Kebbi State has experienced significant flooding events over the years, largely due to seasonal rains and the overflow of rivers. Traditional flood management strategies relied on historical data and rudimentary forecasting methods. These approaches often lacked accuracy and timely response capabilities, leading to severe consequences for communities. To develop a machine learning model that accurately predicts flood events in Kebbi State, Nigeria, enhancing preparedness and response efforts. This approach aims to improve environmental modeling by leveraging data-driven insights for effective flood management. Before the adoption of machine learning or AI, flood prediction primarily relied on manual monitoring of weather patterns and river levels. Local authorities used simple tools like rain gauges and stream gauges to collect data, while community awareness campaigns provided limited information. Predictions were based on historical patterns and observational data, whi