A PILOT STUDY FOR AN ENHANCED ALGAL SPATIAL PATTERN PREDICTION USING RS IMAGES
Accurate and reliable flow forecasting form an important basis for efficient real-time river 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.
Kalman filter gain matriz real-time correction ezpected value of system noise
Hong Li Mijail Arias Anouk Blauw Steef Peters Arthur E.Mynett
UNESCO-IHE Institute for Water Education, 260IDA, Delft, Netherlands Delft University of Tecllnology UNESCO-IHE Institute for Water Education, 260IDA, Delft, Netherlands Delft University of Tecllnology, Faculty of CiTG, 2600 GA Delft, Netherlands Institute for Environmental Studies (IVM), Vrije Universiteit,1081 HV, Amsterdam, Netherlands UNESCO-IHE Institute for Water Education, 260IDA, Delft, Netherlands Delft University of Tecllnology
国际会议
第16届亚太地区国际水利学大会暨第3届水工水力学国际研讨会(16th IAHR-APD Congress and 3rd Symoposium of IAHR-ISHS)
南京
英文
738-743
2008-10-20（万方平台首次上网日期，不代表论文的发表时间）