Assessing groundwater-surface water connectivity using land and waterborne transient electromagnetic surveys

Lake Sibaya is the largest groundwater-fed freshwater lake in South Africa. In the past several decades the lake levels have declined substantially, largely due to drought, human water demands, and the expansion of eucalyptus plantations. These falling lake levels have resulted in the formation of isolated basins, most notably a northern main basin and a southern secondary basin, where water levels behave independently. The southern basin plays an important water resource and ecological role in the area, consequently, there is a need to better understand the groundwater-surface water connectivity and hydrogeological structure.

The area is characterized by a complex depositional system comprising dune and fluvial-deltaic sediments which makes understanding the groundwater and surface water connectivity non-trivial. To better understand the subsurface structure land and waterborne transient electromagnetic (TEM) surveys were conducted using a towed TEM system. The TEM method utilizes a transmitter and a receiver coil to estimate the subsurface resistivity distribution to depths of 50 – 70 m. Firstly, a primary electromagnetic field is generated by passing an electric current around the transmitter coil. The primary electromagnetic field induces currents in the subsurface which then generate a secondary electromagnetic field. The receiver coil then detects the secondary electromagnetic field. The rate of decay of this secondary electromagnetic field can be used to model the subsurface resistivity distribution. The resistivity models can be used with local borehole data to constrain geological boundaries in the survey area.

The resistivity models derived from the surveys, combined with borehole data, revealed distinct geological layers comprising organic sediments, sands, silts, and calcareous sandstones. Furthermore, whereas the northern basin is connected to the deeper aquifer, the southern basin is not. This work highlights the ability of high-productivity TEM methods to gain a better understanding of complex hydrogeological systems and provide context for their management.