The authors introduce a couple of prevailing gross error identification techniques adopted in the process of current dam safety monitoring data treatment and analyze their respective advantages & disadvantages as well as their application ranges. In combination with the shortcomings of those techniques, the gross error data were identified by using space-time identification technology and robustness-based technique. Space-time identification technology utilizes fully the basic space and time information of the data series and compare data with historical data or adjacent observation data to identify the gross error. The identification approach of robustness-based monitoring model overcomes the disadvantage of poor gross error interference immunity of traditional least square method and obtains robust estimation through iterative calculations with gradual weighted robustness. The estimation figures proved to be the most closely to the normal data without interfering by gross errors. The case analysis of safety monitoring data of Geheyan Dam verifies that the above approaches are capable of identifying gross errors outstandingly.