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MATLAB algorithm to implement soil water data assimilation with the Ensemble Kalman Filter using HYDRUS

机译:使用HYDRUS与Ensemble Kalman滤波器实现土壤水分数据同化的MATLAB算法

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Data assimilation is becoming a promising technique in hydrologic modelling to update not only model states but also to infer model parameters, specifically to infer soil hydraulic properties in Richard-equation-based soil water models. The Ensemble Kalman Filter method is one of the most widely employed method among the different data assimilation alternatives. In this study the complete Matlab? code used to study soil data assimilation efficiency under different soil and climatic conditions is shown. The code shows the method how data assimilation through EnKF was implemented. Richards equation was solved by the used of Hydrus-1D software which was run from Matlab.?MATLAB routines are released to be used/modified without restrictions for other researchers?Data assimilation Ensemble Kalman Filter method code.?Soil water Richard equation flow solved by Hydrus-1D.
机译:数据同化正在成为水文建模中一种有前途的技术,它不仅可以更新模型状态,而且可以推断模型参数,特别是可以推断基于Richard方程的土壤水模型中的土壤水力特性。集合卡尔曼滤波方法是不同数据同化方法中使用最广泛的方法之一。在本研究中完整的Matlab?显示了用于研究不同土壤和气候条件下土壤数据同化效率的代码。该代码显示了如何实现通过EnKF进行数据同化的方法。通过使用Matlab运行的Hydrus-1D软件解决了Richards方程。MATLAB例程被发布以供其他研究人员使用/修改,而​​没有其他限制。数据同化集成Kalman滤波方法代码。 Hydrus-1D。

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