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Kalman filters for assimilating near-surface observations into the Richards equation-Part 3: Retrieving states and parameters from laboratory evaporation experiments

机译:用于将近地表观测吸收到Richards方程中的卡尔曼滤波器-第3部分:从实验室蒸发实验中检索状态和参数

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The purpose of this work is to evaluate the performance of a dual Kalman filter procedure in retrieving states and parameters of a one-dimensional soil water budget model based on the Richards equation, by assimilating near-surface soil water content values during evaporation experiments carried out under laboratory conditions. The experimental data set consists of simultaneously measured evaporation rates, soil water content and matric potential profiles. The parameters identified by assimilating the data measured at 1 and 2 cm soil depths are in very good agreement with those obtained by exploiting the observations carried out in the entire soil profiles. A reasonably good correspondence has been found between the parameter values obtained from the proposed assimilation technique and those identified by applying a non-sequential parameter estimation method. The dual Kalman filter also performs well in retrieving the water state in the porous system. Bias and accuracy of the predicted state profiles are affected by observation depth changes, particularly for the experiments involving low state vertical gradients. The assimilation procedure proved flexible and very stable in both experimental cases, independently from the selected initial conditions and the involved uncertainty.
机译:这项工作的目的是通过吸收进行的蒸发实验中的近地表土壤含水量值,评估双卡尔曼滤波程序在检索基于Richards方程的一维土壤水分收支模型的状态和参数方面的性能。在实验室条件下。实验数据集包括同时测量的蒸发速率,土壤含水量和基质势分布。通过吸收在1和2 cm土深处测得的数据而确定的参数与通过利用在整个土壤剖面中进行的观测所获得的参数非常吻合。从拟议的同化技术获得的参数值与通过应用非顺序参数估计方法确定的参数值之间找到了合理的良好对应关系。双卡尔曼滤波器在检索多孔系统中的水状态方面也表现出色。预测状态轮廓的偏差和准确性受观察深度变化的影响,特别是对于涉及低状态垂直梯度的实验。在两种实验情况下,同化过程都证明是灵活且非常稳定的,与所选的初始条件和所涉及的不确定性无关。

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