Scientific Study by the International University for Science and Technology Highlights the Latest Artificial Intelligence Applications in Flood Risk Management
As part of the International University for Science and Technology’s commitment to supporting scientific research and encouraging studies that address global challenges, one of the university’s researchers has completed a scientific study entitled “Revolutionizing Flood Risk Management Using Intelligent Artificial Intelligence Technologies.”
The study was published in the internationally peer-reviewed journal Progress in Disaster Science, published by Elsevier and available through ScienceDirect. The journal is indexed in Scopus, ranked in the first quartile (Q1), with an Impact Factor of 4.0 and a CiteScore of 6.5.
The study addresses one of today’s most pressing environmental challenges—the increasing risk of floods and their significant social, economic, and environmental impacts amid climate change and rapid urbanization. It explores the growing role of artificial intelligence (AI) in developing innovative solutions for flood prediction and risk management, enhancing disaster preparedness and reducing the impacts of flood events.
The research reviews the latest AI-driven applications in flood forecasting, vulnerability assessment, damage mapping, infrastructure management, and real-time prediction. It highlights the importance of these technologies in strengthening early warning systems, improving emergency response, and supporting timely and informed decision-making during disasters.
The study further demonstrates that machine learning models—including regression algorithms, decision trees, and artificial neural networks—are highly effective in analyzing complex and diverse datasets, such as digital elevation models, land-use patterns, rainfall records, satellite imagery, and social media data. These capabilities contribute to generating more accurate and reliable flood predictions.
In addition, the study shows that integrating geospatial data with socioeconomic indicators enables the identification of the most vulnerable areas, thereby supporting policymakers in developing effective risk reduction strategies and prioritizing resource allocation. AI technologies also facilitate rapid and accurate damage assessment and flood inundation mapping, contributing to more efficient disaster response and recovery efforts.
The research also examines the role of AI in enhancing infrastructure resilience through flood scenario simulations, predicting infrastructure failures, and optimizing the performance of protective systems such as dams and drainage networks. Furthermore, it emphasizes the value of Explainable Artificial Intelligence (XAI) in improving transparency, strengthening stakeholder confidence, and supporting higher-quality decision-making during crises.
Despite the rapid advancement of AI applications, the study notes that several challenges continue to limit their broader adoption, including limited data availability, high computational requirements, the limited interpretability of some AI models, and institutional barriers. It therefore calls for continued scientific research and interdisciplinary collaboration to maximize the benefits of AI technologies in disaster risk management.
This study reflects the International University for Science and Technology’s commitment to advancing scientific knowledge and publishing high-quality research in leading international journals, reinforcing its academic and research excellence while supporting global efforts to leverage emerging technologies in addressing environmental challenges and promoting sustainable development.