Many traditional methods in hydrology require intensive field work. As a result these methods are expensive and are able to sample only a small portion of a study area. For instance, the paired watershed method involves installing flumes at the mouths of two similar watersheds, developing a regression relationship between them, treating the watersheds in some way, and finally determining how the treatment altered the calibration relationship. While this approach remains definitive and appropriate for many applications, it is also expensive. Perhaps more importantly this method can require several years to develop statistically viable regression equations if it is applied to water-limited systems and is therefore a slow process.
In contrast, synthesizing freely available geospatial data together with freely available hydrologic and meteorologic data that have often been collected regularly since the 1930's, it is possible to uncover the hydrologic effects of woody encroachment, tree die-off, or global warming at a fraction of the cost of traditional methods, over large areas , and rapidly since all of the data already exist and efforts are only required to synthesize and analyze these existing datasets. Therefore, a geospatial approach to hydrology is ideal for water resources planning to promote knowledge-based decision making and a secure water supply in the face of unprecedented threats due to global climate, land-use, and land-cover changes.