This report describes the creation of a large-scale watershed database for the lower Rio Grande/Rio Bravo Basin in Texas. The watershed database includes watersheds delineated to all 1:24,000-scale mapped stream confluences and other hydrologically significant points, selected watershed characteristics, and hydrologic derivative datasets. Computer technology allows generation of preliminary watershed boundaries in a fraction of the time needed for manual methods. This automated process reduces development time and results in quality improvements in watershed boundaries and characteristics. These data can then be compiled in a permanent database, eliminating the time-consuming step of data creation at the beginning of a project and providing a stable base dataset that can give users greater confidence when further subdividing watersheds. A standardized dataset of watershed characteristics is a valuable contribution to the understanding and management of natural resources. Vertical integration of the input datasets used to automatically generate watershed boundaries is crucial to the success of such an effort. The optimum situation would be to use the digital orthophoto quadrangles as the source of all the input datasets. While the hydrographic data from the digital line graphs can be revised to match the digital orthophoto quadrangles, hypsography data cannot be revised to match the digital orthophoto quadrangles. Revised hydrography from the digital orthophoto quadrangle should be used to create an updated digital elevation model that incorporates the stream channels as revised from the digital orthophoto quadrangle. Computer-generated, standardized watersheds that are vertically integrated with existing digital line graph hydrographic data will continue to be difficult to create until revisions can be made to existing source datasets. Until such time, manual editing will be necessary to make adjustments for man-made features and changes in the natural landscape that are not reflected in the digital elevation model data.