水利学报2024，Vol.55Issue(9)：1009-1019,11.DOI:10.13243/j.cnki.slxb.20230687
基于机器学习降雨动态时空特征识别山丘区小流域洪水预报方法研究
Research on flood forecasting method in mountainous small watersheds based on machine learning for identifying rainfall dynamic spatiotemporal features
摘要
Abstract
The mountainous region experiences fast-flowing and highly destructive floods,posing challenges for accurate and timely forecasting.Enhancing the accuracy and lead time of flood prediction in mountainous areas is a pressing issue.Addressing this concern,this paper proposes an innovative flood forecasting method based on ma-chine learning technology.The approach identifies historical rainfall-flood events with the most similarity to the current dynamic spatiotemporal features of rainfall,employing a"learn from the past to predict the present"strate-gy.The results indicate that,in small watersheds with minimal human influence and a basin area of approximately 600 km2 in mountainous regions,the method not only predicts the overall trend of rainfall but also forecasts the asso-ciated mountainous flood processes under this rainfall trend.The average errors for peak flow,flood volume,and peak time are 8.33％,14.27％,and 1 hour,respectively,meeting the accuracy requirements for flood forecasting.Distinguished from traditional flood forecasting methods,this approach predicts mountainous floods from the per-spective of the overall rainfall trend,providing a targeted strategy for flood forecasting in small watersheds in hilly areas.关键词
人工智能/流形学习/降雨时空特征/山丘区小流域洪水预报Key words
artificial intelligence/manifold learning/spatiotemporal characteristics of rainfall/flood forecasting in small watersheds of mountainous regions分类
天文与地球科学引用本文复制引用
刘媛媛,刘业森,刘洋,刘正风,杨伟韬,胡文才..基于机器学习降雨动态时空特征识别山丘区小流域洪水预报方法研究[J].水利学报,2024,55(9):1009-1019,11.基金项目
国家自然科学基金重大基金项目(52394235) （52394235）
沂沭河流域超标准洪水防控能力提升措施建议(减JZ0145B042024) （减JZ0145B042024）
