The Palla Road well-field is located in the Central District of Botswana approximately 160 km from Gaborone and 50 km from Mahalapye. The aim of this project was to review and update the existing groundwater model developed in the late 1990s of the Palla Road well-field in order to assess the viability of long-term groundwater abstraction due to the increasing water demands in the region. The main hydrogeological units recognised in the project area comprise of aquifer systems developed in the Ntane Sandstone Formation and formations of the Middle Ecca Group with minor aquifers developed in Mosolotsane Formation and the Stormberg Basalt. The finite-difference model boundary covers an area of 3 702 km2 and was set-up as a three-dimensional semi-uniform grid comprising of four layers. Eight recharge and 14 hydraulic conductivity zones in accordance with the geological model were distinguished. Steady state calibration was accomplished by varying the hydraulic conductivity values, while keeping the recharge rates constant in order to achieve a unique solution. Transient calibration of the model covered three larger stress periods namely: (1) initial condition (pre-1988), (2) abstraction period (1988 to 2012) and (3) predicted model simulations (2013 to 2036).
The calibrated groundwater flow model was used to assess the impacts associated with the proposed abstraction scenarios for the Palla Road and Chepete well-fields with consideration of potential cumulative impacts due to the Kudumatse well-field. Three basic scenarios comprising certain sub-scenarios based on the future water demand for the Palla Road and Kudumatse region were considered. The model simulations show that the abstraction scenario 2a, namely simultaneous abstractions from the Chepete/Palla Road and Kudumatse well-fields, poses a risk to the sustainability of downstream water resources. The maximum simulated drawdown in the central and southern parts of the Palla Road well-field reach 14 m after six years of pumping. Although outflow diminishes after a six-year period, it is restored to approximately 80-90% after the simulated recovery period. The presented 3-D multi-layer model can be used as a tool to determine the optimal abstraction rates while giving cognisance to the sustainability of the resource.