Flood Forecasting Using Deep Learning

R M C Sekhar Koppisetty; Chandana Lingala; Baji Syed; Yogananda Sriram Prasad Lingeneni; Chandra Sekhar Reddy Gujjula

doi:10.36948/ijfmr.2026.v08i02.72522

Flood Forecasting Using Deep Learning

Author(s)	Mr. R M C Sekhar Koppisetty, Chandana Lingala, Baji Syed, Yogananda Sriram Prasad Lingeneni, Chandra Sekhar Reddy Gujjula
Country	India
Abstract	Floods are one of the most frequently occurring natural disasters, causing massive damage to property, agriculture, economy, and human life. Accurate and timely flood prediction remains a major challenge due to the dynamic and nonlinear interactions of hydrological variables such as rainfall intensity, river discharge, soil moisture, and seasonal climate changes. This paper proposes an enhanced Flood Forecasting Model (FFM) that integrates Federated Learning with multiple deep learning architectures to predict flood events while preserving data privacy. The proposed system trains Feed Forward Neural Networks (FFNN), Long Short-Term Memory (LSTM) networks, and two-dimensional Convolutional Neural Networks (CNN2D) locally across eighteen distributed stations and aggregates the models at a central server. An Ensemble Learning module combines the predictions of all three models using a weighted soft-voting mechanism to produce a more accurate and robust final forecast. The dataset comprises 4,588 records spanning from 1901 to 2024 across multiple Indian states and subdivisions. Experimental results demonstrate that FFNN achieves 88.71% accuracy, LSTM achieves 93.68% accuracy, and CNN2D achieves 98.13% accuracy. The Ensemble model achieves the highest accuracy of 98.84%, confirming the superiority of the combined approach. The system generates flood alerts with a five-day lead time, supporting early warning and disaster preparedness.
Keywords	Flood Forecasting, Federated Learning, Feed Forward Neural Network (FFNN), Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN2D), Ensemble Learning, Water Level Prediction, Natural Disaster Management
Field	Computer > Data / Information
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-03-27
DOI	https://doi.org/10.36948/ijfmr.2026.v08i02.72522

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Flood Forecasting Using Deep Learning

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