Groundwater is a critical resource for supporting human consumption, stock water, agricultural use, and mineral or energy extraction as well as the environment. However, the quality of groundwater varies enormously from potable to hyper-saline, particularly in the Australian context. To evaluate the suitability of a groundwater resource, the spatial distribution of salinity within an aquifer is typically estimated by measuring the electrical conductivity (EC) of groundwater sampled from boreholes. However, drilling is a logistically and economically challenging task, and hydrogeologists are usually left with a sparse set of measurements from which to infer groundwater salinity over large spatial extents. Airborne electromagnetic (AEM) surveying is a geophysical technique for estimating the bulk electrical conductivity of the near-surface. Where AEM bulk conductivity is well correlated with groundwater salinity in aquifers, AEM is a useful tool for modelling salinity in the data sparse areas between boreholes. We present a probabilistic method for modelling groundwater salinity and a case study from the Keep River Plains in the Northern Territory. Co-located probabilistic AEM inversions and EC measurements on pore fluids at coincident locations were fused to calculate an empirical joint probability density function. This function allowed us to estimate salinity away from the bores by sampling the ensemble of AEM conductivities. Unlike deterministic methods that provide a single estimate of salinity, our method generates an ensemble of estimates, which can be used to quantify predictive uncertainty. The results provided by our method can feed into decision making while accounting for uncertainty, allowing responsible management of land and water resources.

Open-Access Online Publication: March 03, 2023