IJEP 45(8): 720-727 : Vol. 45 Issue. 8 (August 2025)
University of Delhi, Device Modelling and Research Laboratory, Department of Electronics, Acharya Narendra Dev College, New Delhi – 110 019, India
Abstract
One of the worst forms of natural disaster, which has resulted in tremendous loss of human lives and has produced significant damage to flora, fauna and natural infrastructure across the globe over the past decade, is floods. Floods have led to deaths of roughly 12,000 people across the globe in 2023, out of which 656 loss of human lives were from India. This clearly shows that floods have affected almost every country in the world, particularly India, owing to its tropical climate. This is attributed to rapid urbanization along the floodplain coupled with global warming. This growing probability of occurrence of floods or extreme flood-like situations has emerged as one of the major social and economic challenges. The present work proposes a framework based on an machine learning (ML) algorithm that can accurately forecast rainfall and floods in any region/state/country in the world. By integrating this flood prediction model with a public warning/alert system, authorities can issue alerts to communities at risk of flooding. Additionally, the models also aid in assessing the impact caused by changes in rainfall patterns, enabling policymakers to make decisions regarding landuse, water resource management, agriculture and urban planning.
Keywords
Kerala flood 2018, Flood, Water level, Machine learning, Future forecasting, ARIMA model
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