Water harvesting has a long history, but still plays an important role today by increasing crop productivity, combatting erosion, and improving water supplies. Geographical Information Systems (GIS) are used extensively to assess the suitability of sites for water harvesting but available tools fail to consider the synoptic topography of sites. Here, we report the creation of a novel, automated tool – “SiteFinder” – that evaluates potential locations by automatically calculating site-specific information, including structure parameters (height, length, and volume) and descriptors of the zone affected by the structure (storage capacity and area of influence) and the catchment area. Innovatively, compared to existing tools of this kind, SiteFinder works within a GIS environment. Thus, it allows the possibility of combining its outputs with larger Multi-Criteria Decision-Making processes to consider other bio-physical, socio-economic, and environmental factors. It utilises a Digital Elevation Model (DEM) and automatically analyses thousands of potential sites, computing site characteristics for different barrier heights that are dependent on the surrounding topography. It outputs values of eight parameters to aid planners in assessing the characteristics of sites as to their suitability for water harvesting. We conducted case studies using 30 × 30 m gridded DEMs to automatically evaluate several thousand sites and, by filtering the tool outputs, successfully identified sites with characteristics appropriate for scenarios at three spatial scales: large dams for nationally significant water supply reservoirs (383 sites analysed; 5 filtered sites with barriers up to 30 m in height); large gully erosion control dams for regional-scale interventions (4,586 sites analysed; 6 filtered sites with barriers up to 3.6 m in height); and local, community-based earth embankment projects (801 sites analysed; 6 filtered sites with barriers up to 2 m in height). A higher resolution (1 × 1 m) terrain elevation model, derived from open-source airborne survey data, was used to assess the veracity of these results. Correlations between the barrier length, impounded area and storage volume capacity derived from the two different resolution data sets were all strongly significant (Spearman’s rank correlation, p < 0.001); and normalised root mean square errors were 9%, 15% and 16% for these parameters, respectively.