Monitoring temporal dynamics of Great Artesian Basin wetland vegetation, Australia, using MODIS NDVI

The Great Artesian Basin springs (Australia) are unique groundwater dependent wetland ecosystems of great significance, but are endangered by anthropogenic water extraction from the underlying aquifers. Relationships have been established between the wetland area associated with individual springs and their discharge, providing a potential means of monitoring groundwater flow using measurements of vegetated wetland area. Previous attempts to use this relationship to monitor GAB springs have used aerial photography or high resolution satellite images and gave sporadic temporal information. These “snapshot” studies need to be placed within a longer and more regular context to better assess changes in response to aquifer draw-downs. In this study we test the potential of 8 years of Moderate Resolution Imaging Spectroradiometer Normalised Difference Vegetation Index data as a long-term tracer of the temporal dynamics of wetland vegetation at the Dalhousie Springs Complex of the Great Artesian Basin. NDVI time series were extracted from MODIS images and phenologies of the main wetland vegetation species defined. Photosynthetic activity within wetlands could be discriminated from surrounding land responses in this medium resolution imagery. The study showed good correlation between wetland vegetated area and groundwater flow over the 2002–2010 period, but also the important influence of natural species phenologies, rainfall, and anthropogenic activity on the observed seasonal and inter-annual vegetation dynamics. Declining trends in the extent (km2) of vegetated wetland areas were observed between 2002 and 2009 followed by a return of wetland vegetation since 2010. This study underlines the need to continue long-term medium resolution satellite studies of the GAB to fully understand variability and trends in the spring-fed wetlands. The MODIS record allows a good understanding of variability within the wetlands, and gives a high temporal-frequency context for less frequent higher spatial resolution studies, therefore providing a strong baseline for assessment of future changes.