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基于残差重采样粒子滤波的土壤水分估算和水力参数同步优化

, PP. 1002-1016

Keywords: 数据同化,残差重采样,粒子滤波,微波亮温,土壤水分水力参数

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Abstract:

?陆面数据同化由于能将观测数据和模型模拟有机结合,已逐步发展为地球科学研究的重要方法之一.通过数据同化方法在模型中不断融入新的观测数据,一方面可以有效地校正陆面过程模型的预测轨迹,提高模型状态变量的估算精度,另一方面可以不断减小模型中的不确定因素,优化模型中的相关参数.在众多数据同化算法中,粒子滤波算法不受模型线性和误差高斯分布假设的约束,适用于任意非线性非高斯动态系统,逐渐成为当前数据同化算法研究的热点.本研究基于残差重采样粒子滤波算法发展了一个数据同化方案,将微波亮温数据同化到大尺度半分布式VIC(VariableInfiltrationCapacity)陆面水文模型中,对土壤水分进行估算,并对模型中的三个水力参数进行同步优化.最后设计了一系列对比实验并利用美国亚利桑那州在SMEX04(SoilMoistureExperiment2004)期间获取的一套完整的实验数据对该同化方案进行了验证.结果表明,该同化方案能够大幅度提高土壤水分估算精度,同时模型中的三个水力参数也得到了较好的优化,从而证明了该数据同化方案的有效性.

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