Topography plays a fundamental role in modulating land surface and atmospheric processes across a wide range of spatial scales (Hutchinson 2008). Thus digital elevation models (DEMs) have played a key role in supporting mesoscale representations of surface climate as well as in supporting finer scale representations of surface hydrology and catchment processes. The ANUDEM locally adaptive elevation gridding procedure (Hutchinson 1989, 2007) is commonly used to calculate these elevation models in regular grid form. Key features of the method include its computational efficiency, allowing it to be applied to very large data sets, and a range of locally adaptive features, including a drainage enforcement algorithm that attempts to maintain connected drainage structure in the interpolated DEM, and algorithms to incorporate data streamlines, lakes and cliffs. This paper describes current progress in the ANUDEM procedure to better represent lakes and to effectively process noisy, high resolution elevation data. Such data are becoming increasingly common. The underlying multi-grid interpolation procedure remains effective in effectively representing lakes and cliffs and in stably interpolating high resolution elevation data. Correlated errors in source elevation data can also be specifically accommodated. The multi-grid procedure also plays a crucial role in enabling the application of drainage enforcement and in initializing heights on data streamlines. This can prevent corruption of stream heights by noisy elevation values and improve the overall representation of drainage structure in the presence of dense noisy elevation source data.