In order to solve the problem that the static model is often used in seepage safety evaluation with neglecting the dynamic change characteristics of index data, the functional data analysis theory is introduced into the scalable evaluation model where the discrete index data is transformed into the continuous function. A comprehensive index system of seepage safety was established including the basic index and the derivative index. Matter element analysis and correlation function construction method suitable for the functional data were proposed, and a dynamic and scalable evaluation model of dam seepage safety was established based on functional data analysis theory. In addition, the combination of analytic hierarchy process(AHP)and entropy weight method was used to determine the index weight. The time weights reflecting the importance of different time in dynamic evaluation were established. The seepage safety monitoring data of a concrete gravity dam in China was analyzed. The results show that the seepage safety state fluctuates from grade II to grade III, which is basically consistent with reality, indicating the effectiveness of proposed model.