AI大模型在山洪灾害风险辨识与预警中的应用探讨OA

Flash flood disasters are the main cause of fatalities among flood-related hazards in China.Risk identifica-tion and early warning represent crucial technologies for the proactive defense against flash floods.This paper system-atically reviews conventional techniques for flash flood risk identification and early warning both within China and abroad,providing a detailed analysis of the advantages,limitations and bottlenecks of various methods.By tracing the development of artificial intelligence(AI)and its role in transforming research paradigms in hydrological sci-ence,the study highlights the significant potential of AI in flash flood disaster prevention.It identifies six major chal-lenges confronting large AI models in the context of flash flood risk identification and early warning:data acquisition and quality,generalization and interpretability,balancing complexity with emergent capabilities,computational effi-ciency and parallel acceleration,and intelligent decision-making.Targeted solutions and future trends are discussed in response to these challenges.The paper proposes that future research should focus on big data governance,and the integration technology of AI and physical models.Additionally,efforts should focus on continuously improving hetero-geneous hybrid parallel computing framework and training strategies,advancing automated optimization of large model parameters and intelligent prediction,and enhancing learning capacity,generalization ability and risk predic-tion ability.The aim of these efforts is to provide both theoretical insights and practical guidance for the application of large AI models in flash flood risk identification and early warning.