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Ecosystems which rely on either the surface expression or subsurface presence of groundwater are known as groundwater-dependent ecosystems ( GDEs). A comprehensive inventory of GDE locations at an appropriate management scale is a necessary first-step for sustainable management of supporting aquifers; however, this information is unavailable for most areas of concern. To address this gap, this study created a two-step algorithm which analyzed existing geospatial and remote sensing data to identify potential GDEs at both state/province and aquifer/basin scales. At the state/province scale, a geospatial information system ( GIS) database was constructed for Texas, including climate, topography, hydrology, and ecology data. From these data, a GDE index was calculated, which combined vegetative and hydrological indicators. The results indicated that central Texas, particularly the Edwards Aquifer region, had highest potential to host GDEs. Next, an aquifer/basin scale remote sensing-based algorithm was created to provide more detailed maps of GDEs in the Edwards Aquifer region. This algorithm used Landsat ETM+ and MODIS images to track the changes of NDVI for each vegetation pixel. The NDVI dynamics were used to identify the vegetation with high potential to use groundwater-such plants remain high NDVI during extended dry periods and also exhibit low seasonal and inter-annual NDVI changes between dry and wet seasons/years. The results indicated that 8% of natural vegetation was very likely using groundwater. Of the potential GDEs identified, 75% were located on shallow soil averaging 45 cm in depth. The dominant GDE species were live oak, ashe juniper, and mesquite. [ABSTRACT FROM AUTHOR]