Although the sounding results are reliable to estimate the stiffness of the ground, only the information of the point estimate is available. While, the geophysical exploration can present the spatially averaged information of the stiffness. In this study, two kinds of the test results are synthesized by the data assimilation technique, and the technique is applied to the identify the spatial distribution, namely random field of the stiffness. The surface wave method (SWM) and the sqrew weight sounding (SWS) are employed as a geophysical exploration method and a sounding test, respectively to identify the spatial distribution of the stiffness of an earth-fill dam in this study. The ensemble Kalman filter (EnKF) is used as a data assimilation technique. It can estimate the spatial distribution of the Young’s modulus as the stiffness of an earth-fill dam by assimilating the travel time to the first arrival of the surface waves. By the ensemble data assimilation, the measured data from the SWM is applied to simultaneously estimate the Young's modulus and evaluate the uncertainties. The SWS results are employed as the prior information to generate the initial ensemble through the sequential Gaussian simulation (sGs). In the experiments of assimilation, it has been shown that the reproducibility of the parameter field is enhanced by this initial ensemble generation method, and that the uncertainties of the identified parameters can be reduced by the assimilation. Consequently, it has been clarified the proposed approach could identify the random field of Young's modulus based on the numerical twin experiments, and could be available for the practical use from the results of applying to the measured SWM and SWS data in an earth-fill dam site.