中国防汛抗旱2026，Vol.36Issue(5)：1-6,6.DOI:10.16867/j.issn.1673-9264.2026154
基于多模态大模型的城市内涝短临预报方法探索
Exploration of urban waterlogging nowcasting method based on a multimodal large model
摘要
Abstract
Urban waterlogging nowcasting provides an essential basis for efficient disaster emergency response.Existing methods mostly rely on locally developed physics-based flood forecasting models,which face several limitations,including limited transferability of models and experience from other areas,complex processing of multi-source input data,and high computational cost.These limitations make it difficult to meet the requirements of rapid forecasting.Large models are capable of jointly processing multimodal data and rapidly generating results,offering potential for improving urban waterlogging forecasting.However,the types and organization of input information for this task remain insufficiently investigated.This study develops an urban waterlogging nowcasting method based on a multimodal large model.The method integrates inundation status,future rainfall,and terrain conditions to infer the evolution of water depth over future time periods.Using three monitoring points in Dalian as a case study,ablation experiments were conducted on different input conditions.The results show that the proposed method can accurately predict urban water depth,with a mean absolute error of 0.03 m under the optimal input condition.The incorporation of terrain conditions significantly improves the forecasting performance,reducing the error by 28.8%～69.1%.This study provides a new pathway for applying artificial intelligence to urban waterlogging nowcasting.关键词
城市内涝/短临预报/多模态大模型/智慧水利Key words
urban waterlogging/nowcasting/multimodal large model/smart water conservancy分类
建筑与水利引用本文复制引用
张峰瑞,李原至,吕恒,杨晨..基于多模态大模型的城市内涝短临预报方法探索[J].中国防汛抗旱,2026,36(5):1-6,6.基金项目
国家重点研发计划项目(2024YFC3213000) （2024YFC3213000）
国家自然科学基金项目(52309005). （52309005）
