摘要
通过数据同化技术用卡尔曼滤波算法对观测井所得水位监测资料进行同化计算,在得到较为精确水位观测值的基础上对主要取水层的渗透系数进行参数反演,并与前期室内试验获得的渗透系数对比,表明通过数据同化过滤之后进行的参数反演更精确有效。
Monitoring data of water level of observation wells are calculated by data assimilation technology and Caiman fil- tering algorithm. With this method, the permeability coefficient of the main aquifer is invcrsed base on the accurate water level values, and compared with the permeability coefficient obtained by test. The results show that the inversion parameter after data assimilation and filtering is more accurate and effective.
出处
《水科学与工程技术》
2017年第6期78-82,共5页
Water Sciences and Engineering Technology
关键词
数据同化
卡尔曼滤波
渗透系数
参数反演
data assimilation
Kalman filtering
permeability coefficient
parameter inversion
