基于土壤水模型及站点资料的土壤湿度同化方法

基于非饱和土壤水模型和扩展卡尔曼滤波(Extended Kalman Filter)同化算法并结合陆面过程模型VIC发展了一个土壤湿度同化方案，并进行了理想试验及同化站点资料的同化试验。理想试验结果表明：扩展卡尔曼滤波方法能完整反演土壤湿度廓线，对土壤湿度的估计有较大改善；观测深度、观测层数和观测资料引入频率对同化结果有一定影响；加大观测频率，可以进一步改善同化效果。利用气象强迫驱动陆面模型VIC算出地表入渗条件而进行的同化站点资料的试验所得土壤湿度分布与观测资料基本吻合，反映了站点土壤湿度的月、季变化，表明该方案是合理的。

A Soil Moisture Assimilation Scheme With an Unsaturated Soil Water Flow Model and In-Site Observation

A soil moisture assimilation scheme based on the extended Kalman filter（EKF）and an unsaturated soil water flow model is developed and numerical experiments using synthetic data and numerical simulation with in-site observations are presented. The numerical experiments show that the assimilation scheme improve estimation of soil moisture, the frequency of observation, the depth and the layers at which observation is introduced have the influence on assimilation. The assimilation experiments with in-site observations and infiltration derived from meteorologic forcing condition and the land surface model VIC show the monthly and seasonal variation of soil moisture, which show that the assimilation scheme is reasonable.