An attractive, but very difficult research topic is automatic DEM deformation detection without control points. The technique is essential for multi-temporal remote sensing applied in, e.g., soil-erosion and debris flow disaster monitoring. This paper presents a differential model and a fully automatic method for multi-temporal DEMs deformation detection without control points based on Least Z-Difference (LZD) algorithm. Firstly, the corresponding points on both original DEM and ready matching DEM are paired using the criterion in the LZD algorithm, and then differential model can be constructed by arraying all Z-coordinate differences between corresponding points in line with their position. The weight of each observation (Z-difference) is set using the characteristics of differential model. The observation, whose weight is set to zero, is dropped from the matching process. Afterwards, all isolated observations are also removed. After processed through the above two steps, almost all of suspicious deformed observations, including some good observations, would be able be discarded from the objective function. Therefore, the DEM surface deformation can quantificationally be detected by the matched DEMs. A comparison study using multi-temporal DEMs on PUWAIGOU debris-flow valley shows that the presented method in this paper is more robust and has higher accuracy than ones of M-LZD and LMS-LZD algorithms. Moreover, the new method can detect that DEM data, whose deformation area is over 50%. Keywords3D matching, deformation detection, digital elevation model, differential model, Least Z-Difference Algorithm