REAL-TIME PREDICTION ALGORITHM WITH A DISTRIBUTED HYDROLOGICAL MODEL USING KALMAN FILTER
REAL-TIME PREDICTION ALGORITHM WITH A DISTRIBUTED HYDROLOGICAL MODEL USING KALMAN FILTER
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基于卡尔曼滤波器的分布式水文模型实时预测算法
DOI：
10.2208/prohe.49.163
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
K. Takara
中科院分区：
文献类型：
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作者：
Sunmin Kim;Y. Tachikawa;K. Takara
卡尔曼滤波理论与分布式水文模型相结合，通过使用本文提出的几种技术来更新空间分布的状态变量。为了从出口流量观测中获得流域总蓄水量，采用Q-S曲线作为观测方程。在卡尔曼滤波更新总蓄水量后，引入比值法重新调整流域的分布式蓄水量，保持流域的空间分布格局。采用蒙特卡罗模拟来预测状态变量和误差方差传播。一个分布式模型与卡尔曼滤波理论相结合，给出了更新的模拟结果，提高了预测精度。
The Kalman filter theory is coupled with a distributed hydrological model to update spatially distributed state variables by using several techniques proposed here. To acquire the total water storages of a basin from discharge observations at the outlet, a Q-S curve is used as an observation equation. After updating total water storage with the Kalman filter, the ratio method is introduced to reset the distributed storage amount of a basin, maintaining the spatially distributed pattern. A Monte Carlo simulation is adopted to predict state variables and error variance propagations. A distributed model coupled with the Kalman filter theory gives updated simulation results with improved forecasting accuracy.
结合饱和-非饱和流动机制的阶段-流量关系方程的发展
DOI：
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发表时间：
2004
期刊：
Annual Journal of Hydraulic Engineering (JSCE) Vol.48
影响因子：
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作者：
Yasuto Tachikawa;Gen Nagatani;Kaoru Takara
通讯作者：
Kaoru Takara