DEVELOPMENT OF A REAL-TIME RIVER STAGE FORECASTING METHOD USING A PARTICLE FILTER
DEVELOPMENT OF A REAL-TIME RIVER STAGE FORECASTING METHOD USING A PARTICLE FILTER
复制标题
使用粒子滤波器的实时河位预报方法的开发
DOI：
10.2208/jscejhe.67.i_511
复制
发表时间：
2011
影响因子：
--
通讯作者：
Sunmin Kim
中科院分区：
文献类型：
--
作者：
Y. Tachikawa;Jyunichi Sudo;M. Shiiba;K. Yorozu;Sunmin Kim
提出了一种实时河段预报方法，旨在应用于没有等级曲线的河段。该方法采用粒子滤波与动态波模型相结合的方法。具有不同参数值和边界条件的若干动态波模型（粒子）并行运行；根据观测到的河流阶段，实时选择一组表现良好的粒子；并利用各观测时间步长的预测误差预测了未来数小时的河段。该方法应用于2004年台风23号造成的桂川河洪水。预报的河段与实际河段吻合较好。沿研究河段预测的最大河段也很好地解释了洪水标志。
A real-time river stage forecasting method is developed, which is aimed to apply to river sections where a rating curve does not exist. The method uses a particle filter combined with the dynamic wave model. A number of the dynamic wave models (particles) which have different parameter values and boundary conditions run in parallel; a set of well behaved particles are selected in real time according to the observed river stage; and several hours-ahead river stages are predicted with their prediction error at each observation time step. The method is applied to the Katsura River for the flood of the typhoon No. 23 in 2004. The predicted river stage shows a good agreement with the observed one. The predicted maximum river stages along the study river section also well explain the flood marks.