Abstract: Reactive transport models are characterized by a large number of parameters and a variety of observations. Taking the TCE degradation model as an example, this article used the Ensemble Kalman Filter method to estimate the heterogeneous distribution of hydraulic conductivity field and storage coefficient field in order to compare the data values of different types of observations (i.e., only groundwater head, head and concentration) during the data assimilation. The results show that compared with only assimilating head data, jointly using head and concentration can improve the accuracy of parameter estimation and has a better performance in terms of data match and model prediction; the ensemble size and the number and location of observation wells will affect the results of the data assimilation, which is similar to the conclusions in other groundwater models such as the solute transport model and the unsaturated flow model. Better results and higher computational efficiency can be obtained by reasonably setting the layout of observation wells and choosing the ensemble size.