Abstract
Climate change significantly impacts the distribution and availability of global water resources, increasing the frequency and intensity of extreme weather events such as droughts and floods. This complex issue poses a severe challenge to traditional water resource prediction methods. In recent years, artificial intelligence (AI) technology has gradually emerged as an essential tool for addressing climate change and water resource management problems due to its outstanding performance in big data processing and complex system modeling. This paper provides a comprehensive review of the latest advancements in AI applications for climate data processing, hydrological model optimization, climate impact prediction, and water resource risk warning. It focuses on the effectiveness and practical cases of AI in predicting extreme events such as droughts and floods. Through a systematic review of existing research, this paper summarizes the advantages of AI in improving prediction accuracy and decision-making efficiency, while also exploring key challenges in the field, including data quality assurance, model uncertainty evaluation, and the need for interdisciplinary collaboration. Finally, the paper outlines future directions for AI in water resource management under climate change, aiming to provide scientific references for academic research and policy-making to support global strategies for managing water resources in the face of climate change.
