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WATER QUALITY FORECAST OF THE TRIBUTARIES OF THREE-GORGE RESERVOIR

机译:三峡水库三峡水质预报

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摘要

Accurate and reliable flow forecasting form an important basis for efficient real-time fiver management, including flood control, flood warning and so on. In order to improve the accuracy of flow forecasting, gain matrix of Kalman filter was applied to real-time correction of hydraulic model for spatial distributing the system deviation (called "expected value of system noise" in Kalman filter). That means Kalman gain matrix is used to distribute model system deviation from measurement cross sections to the entire state of the river system. State functions of Kalman filter were set up based on discretization and linearization Saint-Venant equations by adopting four-point linear implicit form, and the spatial distribution system deviation method (SDM) was used for real-time correction. The calculation of flood forecasting for river section from Cuntan to Fengjie of Yangtze River verifies that SDM is useful in promoting the accuracy of real-time flood forecasting.
机译:准确可靠的流量预测,形成有效的实时纤维管理,包括防洪,洪水警告等的重要依据。为了提高流量预测的准确性,将Kalman滤波器的增益矩阵应用于液压模型的实时校正,用于在卡尔曼滤波器中的系统偏差(称为“系统噪声”的预期值“)。这意味着卡尔曼增益矩阵用于将模型系统偏差分配到河流系统的整个状态。通过采用四点线性隐式形式,基于离散化和线性化设置了卡尔曼滤波器的状态功能,并且使用空间分布系统偏差方法(SDM)进行实时校正。长江旗j凤剑河段洪水预报的计算验证了SDM可用于促进实时洪水预测的准确性。

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