基于集合卡尔曼滤波同化方法和HYDRUS-1D模型的土壤水分模拟  

Simulation of soil moisture based on ensemble Kalman filter assimilation method and HYDRUS-1D model

作　　者：王春娟 刘全明[1,2] 尹承深 王福强 WANG Chunjuan;LIU Quanming;YIN Chengshen;WANG Fuqiang(College of Water Conservancy and Civil Engineering,Inner Mongolia Agricultural University,Hohhot,Inner Mongolia 010018,China;Autonomous Regional Colluborative Innovation Center for Intergrated Management of Water Resources and Water Environment in the Inner Mongolia Reaches of the Yellow River,Hohhot,Inner Mongolia 010018,China)

机构地区：[1]内蒙古农业大学水利与土木建筑工程学院,内蒙古呼和浩特010018 [2]黄河流域内蒙段水资源与水环境综合治理自治区协同创新中心,内蒙古呼和浩特010018

出　　处：《干旱地区农业研究》2023年第2期141-149,共9页Agricultural Research in the Arid Areas

基　　金：国家自然科学基金(52069020)。

摘　　要：研究建立了一个基于集合卡尔曼滤波方法和HYDRUS-1D模型相结合的数据同化方案,利用2021年4月26日—10月5日内蒙古巴彦淖尔五原站0~80 cm的土壤水分观测数据进行模拟验证,以提高土壤水分的模拟精度。结果表明:(1)集合数大小和观测误差的选取对同化系统性能有较大影响。集合数在100以上,土壤含水量的同化精度不再有明显提高。观测误差越小土壤水分模拟精度越高,因此观测误差为0.025时的同化精度最高。(2)数据同化后,各层土壤水分模拟精度较同化前均有明显提高,各层土壤水分同化值与观测值间的相对误差、均方根误差、平均绝对误差分别减少至0.025~0.063、0.01~0.017 cm^(3)·cm^(-3)、0.008~0.016 cm^(3)·cm^(-3)。证明数据同化方法能够有效改善土壤水分模拟效果。(3)0~20 cm土壤水分同化效果最好,20~40 cm次之,40~80 cm土壤水分同化效果较差。模拟精度分析值优于同化预报值,同化预报值优于HYDRUS-1D预报值。In this study,a data assimilation scheme based on the combination of the ensemble Kalman filter method and HYDRUS-1D model was established.The soil moisture observation data of 0~80 cm from April 26 to October 5 in 2021 in Wuyuan Station of Bayannur were used for simulation verification,in order to improve the simulation accuracy of soil moisture.The results showed that:(1)The size of set number and the selection of observation error had great influence on the performance of assimilation system.The accuracy of soil moisture simulation on longer significantly improved when the set number was more than 100.The smaller the observation error was,the higher the simulation accuracy of soil moisture was,so the assimilation accuracy was the highest when the observation error was 0.025.(2)After data assimilation,the simulation accuracy of soil water in each layer was significantly improved compared with that before assimilation.The relative error,root mean square error and mean absolute error between the assimilation value and the observation value of soil water in each layer were reduced to 0.025~0.063,0.01~0.017 cm^(3)·cm^(-3),0.008~0.016 cm^(3)·cm^(-3),respectively.It is proved that the data assimilation can effectively improve simulation effect of soil moisture.(3)The soil water assimilation effect of 0~20cm was the best,followed by 20~40 cm,and the soil water assimilation effect of 40~80 cm was poor.In terms of simulation accuracy,the analysis value is better than the assimilation forecast value,and the assimilation forecast value was better than HYDRUS-1D forecast value.

关 键 词：土壤水分模拟 数据同化 HYDRUS-1D模型 集合卡尔曼滤波 

分 类 号：S157[农业科学—土壤学] S152.7[农业科学—农业基础科学]