Abstract Interpolation process is essential whenever researchers are faced with a data shortage. Within the GIS, interpolation can be conducted using all kinds of environmental phenomena represented in the form of spatial data. Remote Sensing (RS) data represented in several Landsat ETM+ images, acquired in different dates, were processed by integration with the in-situ elevations data to achieve the interpolation process. As a result, this research aims to identify the best method for interpolating Lake Nubia's bed surface elevations, the Sudanese portion of Aswan High Dam Lake (AHDL). The three techniques tested in this study include Radial Base Function [RBF], Inverse Distance Weighting [IDW], and Ordinary Kriging [OK] technique. Also, this study focuses on estimating the accumulated sediment in Lake Nubia (LN) from 2004 to 2012 via the produced 3D profiles of the lake. Since the RBF provided the lowest values for both the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE), the findings clearly demonstrated the usefulness and superiority of the method. Moreover, results indicated that the amount of sediment calculated using the RBF method is close to that of the Aswan High Dam Authority (AHDA) using the cross-section method. These results indicate that the amount of sediment calculated using the RBF method is valid and reliable. It is recommended to apply this technique to efficiently create the 3D profiles of the lakes from the available elevations data using GIS/RS.