Abstract

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.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call