Climate change has become a major challenge for civil engineering infrastructure due to increasing incidents of extreme rainfall, flooding, heatwaves, sea-level rise, erosion, and changing hydrological conditions. These climate-related events affect the safety, durability, and performance of infrastructure systems such as roads, bridges, buildings, dams, and drainage networks. As the frequency and intensity of such events continue to rise, there is a growing need for advanced technologies that can improve prediction, planning, and infrastructure management.

Recent developments in artificial intelligence technologies, particularly advanced data-driven systems, have provided new opportunities for understanding and managing climate-related risks in civil engineering. These technologies can analyze large volumes of environmental and structural data to identify patterns, predict disasters such as floods and droughts, and support decision-making processes. Their applications also contribute to sustainable resource management, efficient infrastructure planning, and improved resilience against climate-induced hazards.

Despite these advantages, several challenges remain, including concerns related to data quality, transparency of predictive models, and ethical use of intelligent systems. Future research should focus on developing more reliable, interpretable, and multidisciplinary approaches that combine engineering knowledge with modern computational technologies. The integration of intelligent technologies into civil engineering infrastructure can support the development of safer, smarter, and more climate-resilient infrastructure systems in the future.

Keywords: Climate change, civil engineering infrastructure, floods, resilience, intelligent systems, sustainable infrastructure