Remote Sensing and Hydrogeodesy

We process and interpret remote sensing and geodetic data for groundwater studies, supporting our assessments of regional-scale groundwater systems, of groundwater resource sustainability, and of impacts of groundwater extraction and injection.

Major types of remote sensing and geodetic technologies used in hydrogeology

Remote Sensing and hydrogeodesy play an important role in groundwater studies, allowing a transition of scales from ground-based observations of groundwater to aquifer scale, catchment scale, or even continental scale. They can also be sensitive to changes that are not visible: infrared, temperature, dielectric properties, subtle ground deformation and gravity.

Hydrogeologists take advantage of these measurements and of their scale for mapping surface geomorphology and aquifer boundaries, groundwater outflow and springs, groundwater-dependant vegetations and monitor groundwater storage change over time.

We can process and interpret most types of remote sensing and geodetic products valuable for groundwater studies: optical imagery, radar imagery and temporal gravity measurements.

Excess water estimates for the Cambrian Limestone Aquifer in northern Australia

Optical imagery

Optical imagery and its derived products are used to characterise floodplains and understand their relation to aquifers, delineating geomorphologic boundaries, identifying groundwater discharge zones, and mapping groundwater-dependent ecosystems.

For example, high-resolution optical imagery data was used to map areas of excess water, where groundwater discharge supports evapotranspiration in excess of precipitation. This was used to constrain estimates of groundwater recharge using the chloride mass balance in the Cambrian Limestone Aquifer in Northern Territory.

Mapping ground deformation related to groundwater extraction and injection using Interferometric radar data (InSAR).

Radar imagery

Radar imagery is used to create dry-period vegetation indices useful for detecting groundwater-dependent vegetation and groundwater discharge zones, similar to optical data. Combining vegetation indices derived from optical and radar sensors allows finer and more accurate identification of vegetation populations. For this application, the two sensing strategies can complement each other, as they both have inherent advantages and limitations.

Radar Interferometry (InSAR) compares the radar phase along a time-series of radar images. These phase shifts are used to track changes of distance between a satellite orbital track and the ground, which after applying proper corrections, can be interpreted as ground deformation. Because such deformation can originate from pressure changes in aquifers, its monitoring provides precious information for assessing groundwater resource sustainability and impacts from extraction or Managed Aquifer Recharge (MAR).

Temporal gravity time-series from GRACE (A) are separated into different contributing signals (B, C, D), which allows extraction of groundwater storage change estimates (D).

Temporal gravity sensing

Finally, temporal gravity data from GRACE satellites is the only remote, directly quantitative measurement of groundwater storage change. It uses changes in the gravity field to infer water mass changes; taking advantage that this relation is direct and requires no calibration. After extraction of non-groundwater storage via in situ data or modelling, the resulting groundwater storage change time-series have a unique value for groundwater sustainability studies.

GRACE data have been used to understand how climate cycles influence water storage across the Australian continent. By isolating the contributions from superficial and confined aquifers, GRACE temporal gravity data allows to monitor groundwater storage change in the Great Artesian Basin (GAB) and in each of its sub-basins (Fig. 4).

GRACE data can be used to constrain other types of remote sensing or geodetic imagery products. It allows, for example, identification of low or high water accumulation, which guides the selection of images used for observing contrasts between groundwater-dependent, drought-resilient vegetation and rainfall-dependent vegetation.