A real-time probabilistic channel flood-forecasting model based on the Bayesian particle filter approach

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• 作者：Xingya Xu^a ; Xuesong Zhang^b ; ^c ; Hongwei Fang^a ; ^{fanghw@tsinghua.edu.cn} ; Ruixun Lai^d ; Yuefeng Zhang^a ; Lei Huang^a ; Xiaobo Liu^e
• 关键词：Channel flood forecasting ; Probabilistic forecast ; Particle filter ; Data assimilation ; Three Gorges Dam
• 刊名：Environmental Modelling & Software
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：88
• 期：Complete
• 页码：151-167
• 全文大小：5343 K
• 卷排序：88

文摘

A real-time flood-forecasting model is proposed by assimilating real-time stage observations into a hydraulic model. Particle filter is adopted as the data assimilation method to update/correct stage, discharge, and roughness coefficient. Synthetic experiments are employed to explore model settings and evaluate model performance. Model performance is compared with previous studies using Kalman Filter based methods. Probabilistic predictions provided by the model are more accurate and reliable.