This Geoscience Australia Record reports on Interferometric Synthetic Aperture Radar (InSAR) processing over the Great Artesian Basin (GAB) to support an improved understanding of the groundwater system and water balance across the region. InSAR is a geodetic technique that can identify ground surface movement from satellite data at a regional scale and is therefore a valuable and widely used technique for measuring patterns in surface movement over time; including the movement of fluids (i.e. water or gas) beneath the surface.
This Record is the one of two Geoscience Australia Records that describe ground surface movement monitoring Geoscience Australia have undertaken in the GAB in recent years. Namely;
1. Ground surface movement in the northern Surat Basin derived from campaign GPS measurements. (Garthwaite et al., 2022).
2. InSAR processing over the Great Artesian Basin and analysis over the western Eromanga Basin and northern Surat Basin (this Record).
We have produced ground surface motion data products, which cover about 90% of the GAB for the period of time between January 2016 and August 2020. The data products were created using Sentinel-1 Synthetic Aperture Radar (SAR) data and an InSAR processing workflow designed for large spatial scale processing. The large spatial scale InSAR processing workflow includes using GAMMA software to (i) pre-process SAR images to align the pixels, (ii) generate interferograms and short temporal baseline surface displacement maps and PyRate software to (iii) combine these outputs in an inversion to form pixel-wise time series ground surface displacement data and fit ground surface velocities to the displacement data. The raw SAR data and these subsequent data products of the workflow are partitioned into overlapping frames; the final stage of the large scale processing workflow is to combine the partitioned data into a single map using a mosaicking algorithm. The results of this processing chain demonstrate the feasibility of developing a regional scale ground surface movement reconnaissance tool (i.e. subsidence and uplift).
We provide a summary of the processing chain and data products and a focused assessment for two case study areas in the western Eromanga Basin (South Australia) and northern Surat Basin (Queensland). Over these case study areas we examine the relationship between the InSAR derived ground surface movement and available groundwater level data. We also assess how land use types may influence the InSAR derived ground surface motion data by comparing the InSAR data to the “land types” over the region which we classify using a machine learning algorithm with Sentinel-2 optical imagery data.
From our analysis we observe little ground surface motion over the western Eromanga Basin. The surface movement rate over the entire area is estimated to be mostly within ±10 mm/yr. Groundwater level time series data from well monitoring sites in the area did not appear to have any significant trends either. However, large and broad scale ground surface motion (both uplift and subsidence) was observed in the InSAR processing results over the northern Surat Basin. A 75 km x 150 km scale uplift signal, with rates of up to 20 mm/yr, was located over an area we classified as cultivated land, where InSAR signals are likely to be influenced by near-surface cultivation activities (such as irrigation) rather than subsurface groundwater level changes. Furthermore, two approximately 75km x 75 km areas were identified which had subsidence signals of up to -20 mm/yr. Over the same area, groundwater level time series data show long-term negative trends in the water head level. For a more direct comparison between the InSAR results and the well data, we fitted a first order poroelastic model to transform the InSAR derived ground surface motion rates into modelled pore-pressure decline/groundwater drawdown rates. We compared the model to the groundwater time series data in the Walloon Coal Measures, Surat Basin, and found good agreement, which indicates that the observed subsidence signals could be attributable to pore-pressure decline due to the falling water head level.
We finally provide some preliminary analysis comparing our InSAR results to the results from an Office of Groundwater Impact Assessment (OGIA) InSAR study and a Geoscience Australia GPS land movement study to assist in validating the Geoscience Australia InSAR results. Overall, the comparisons are encouraging, showing a high correlation against the OGIA InSAR results and GPS results. Further work, is required to further validate our results and reduce uncertainty in our analysis process.
