The Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) has been a valuable resource for hydrological analysis, providing elevation data at a consistent resolution on a near-global scale. However, its resolution (3 arc-second or 90 m) is sometimes too low to obtain the desired level of accuracy and precision for hydrologic analysis. We evaluated the performance of several methods for interpolating SRTM 3 arc-second data to a 30 m resolution grid to better represent topography and derive terrain characteristics of the landscape. STRM data were interpolated to 30 m DEMs on a common grid using spline, inverse distance weighting, kriging, natural neighbor methods, and cubic convolution resampling. Accuracy of the methods was assessed by comparing interpolated and resampled 30 m grids with the reference data. Slope, aspect, sinks, and stream networks were derived for the 30 m grids and compared on a cell-by-cell basis to evaluate their performance in reproducing the derivatives. The comparisons identify spline and kriging as the most accurate interpolation methods, of which spline is preferred because of its relative simplicity. Inverse distance weighting provided the greatest bias in all methods with artifacts evident in slope and aspect maps. The performance of cubic convolution projection directly to a 30 m resolution was comparable to spline interpolation, thus is recommended as the most convenient method for interpolating SRTM to a higher resolution.