Using Stable Isotope Tracers and Remote Sensing Data to Explain Seasonal Trends in Evapotranspiration in Watersheds in Orange County, CA Associated with Anthropogenic Water A Test of the "Urban Drool" HypoMasters Thesis

Urbanization is one of the most common forms of disturbance in southern California, and the corresponding increase in impervious surface cover is thought to contribute significant amounts of anthropogenic water to surrounding natural areas. In this study, stable isotope tracers were used to identify the presence of water from anthropogenic sources in streams throughout Orange County, CA in stream samples from May 2010 and September 2010. Additionally, remote sensing data were used to estimate corresponding changes in the evapotranspiration rates of vegetation communities within both the riparian zone and uphill areas of the watersheds in which the streams were located. Although isotope tracers have been used successfully in other studies, significant seasonal changes in measured isotope concentrations were not found in those analyses and the presence of supplemental water from human developments was not definitely proved. Normalized Difference Vegetation Index (NDVI) estimates were found to be higher during the spring sampling season than in the fall sampling season, and they were also higher in the riparian zones when compared to the uphill areas within each watershed during the spring sampling season compared to the fall. Finally, a series of linear regression models were created in an attempt to explain dry season NDVI measurements within riparian areas, as well as seasonal changes in riparian NDVI, as a function of changes in stable isotope concentrations and the amount of land within the watershed receiving supplemental water during the dry season. Stable isotope concentrations were found to be significant predictors of seasonal changes in NDVI, but not dry season NDVI. The proportion of land receiving dry season irrigation was not significant in any analyses. Further research is needed to determine which ecological variables are most important when describing and predicting seasonal changes in NDVI estimates.