Flooding is a pervasive natural disaster with profound social, economic, and environmental impacts, necessitating innovative solutions for prediction and management. As climate change and urbanization exacerbate flood risks, advanced technologies such as artificial intelligence (AI) have become increasingly vital in enhancing flood resilience. In this article, we focus on showing the recent advancements in AI-driven flood prediction, vulnerability assessment, damage mapping, infrastructure management, and real-time forecasting, highlighting their significance in improving disaster preparedness and response. We begin by emphasizing how AI techniques, including machine learning models like regression algorithms, decision trees, and neural networks, effectively process complex, heterogeneous datasets such as digital elevation models, land use patterns, rainfall records, satellite imagery, and social media reports to generate accurate and timely flood forecasts. These models facilitate early warning systems, enabling communities and authorities to undertake preventive measures before floodwaters inundate urban and rural areas. Furthermore, AI-driven vulnerability assessments integrate geospatial and socioeconomic data to identify high-risk zones, supporting targeted mitigation strategies and resource allocation. Damage assessment and inundation mapping, utilizing AI algorithms on satellite and aerial imagery, expedite post-disaster response efforts by quantifying affected areas and economic losses rapidly. The article also discusses how AI enhances infrastructure resilience through flood scenario simulations, failure prediction, and optimization of flood defense systems such as levees and drainage networks. Additionally, the integration of Explainable AI (XAI) improves transparency, stakeholder trust, and decision-making effectiveness during emergencies. Despite these promising developments, challenges such as data scarcity, high computational requirements, model interpretability, and institutional barriers remain obstacles to widespread adoption. Addressing these issues is crucial for harnessing AI's full potential in creating resilient, adaptive flood management systems. Overall, this review underscores the transformative role of AI in advancing flood prediction and mitigation, advocating for continued research and interdisciplinary collaboration to combat increasing flood hazards globally.
Marwan Al‐Raeei (2026) studied this question.