Flood forecasting has evolved from simple observational methods used by early civilizations to sophisticated AI-integrated systems that combine satellite remote sensing, sophisticated hydrological modelling, and citizen science. This literature review traces the historical development of flood forecasting methodologies through distinct chronological periods, examining technological breakthroughs and their impact on prediction accuracy. The review synthesizes current research on AI applications, satellite-based monitoring systems, and community-based approaches. The evolution demonstrates a clear trajectory from localized, experience-based methods to field applicable, data-driven systems that integrate multiple information sources for enhanced flood prediction capabilities.