Managed aquifer recharge focuses on increasing the availability of potable water within the subsurface. Under managed aquifer recharge, recycled or excess water is diverted into large infiltration basins that allow water to percolate into the subsurface thus increasing the volume of water within the shallow aquifer. Water can then be extracted during periods of increased demand and provided water security. This widely used technique has low energy costs and can significantly enhance the amount of groundwater recharge. However, infiltration rates can decrease as a result of clogging of sand grains within these infiltration basins and thus increase the percentage of water lost to evaporation. Rapid detection of decreases in infiltration can trigger remedial action in order to prevent further water loss. The research presented here focuses the development of passive thermal tomography; a new technology to (1) quantifying infiltration rates of managed aquifer recharge at meter scale resolution and (2) to determine aquifer heterogeneity within the subsurface. Passive thermal tomography uses temperature as a groundwater tracer to monitor infiltration rates over large areas, such as infiltration basins. The temperature of the surface water in infiltration basins fluctuates due to the daily solar heating and cooling cycle, and the resulting diel signal propagates down into the subsurface. As the rate of infiltration increases or decrease, the thermal signal produced at the land surface will shift at depth as a result of the advective transport of groundwater. Through the monitoring of shifts in the temperature signals at two discrete depths it is possible to quantify the rate of groundwater infiltration. By extracting the amplitude ratio or diel phase-shift at these two depths, recharge rates can be quantified across the infiltration basin. These methods assume vertical and steady flow of water, quasi-steady (cyclic) flow of heat, through homogeneous, isotropic, fully saturated sediments, and temperature measurements collected in a vertical profile. It should be noted that sensitivity analyses have demonstrated the uncertainty of flux calculations due to inaccurate thermal properties and sensor spacing. Uncertainties in both thermal properties and sensor spacing have been evaluated in this research using a fully coupled numerical model. Taking advantage of this natural passive signal, it is possible to detect temporal changes in the daily rate of groundwater recharge as well as seasonal changes, due to clogging of the pores. Using the calculated rates of groundwater infiltration, an inverse, fully coupled groundwater flow and heat transport model is run in order to determine heterogeneity in hydraulic conductivity within the aquifer. Using thermal and hydraulic boundary conditions at the surface and groundwater flux estimates based on the evaluation of amplitude/phase-shits in the thermal signature with depth, it is possible to determine a suite of hydraulic conductivity scenarios that match the true conditions within the aquifer. This inverse modeling approach using thermal tomography allows for the quantification of changes in hydraulic conductivity across the infiltration basin. While groundwater flux is based on a two dimensional grid, the inversion of the numerical model is able to represent a quasi three-dimensional change in hydraulic conductivity. Passive thermal tomography addresses the protection and management of groundwater resources through the quantification of artificial recharge. Current techniques to quantify artificial recharge are either based on point measurements or simple conservation of mass calculations. Through the use of this new technique it is possible to better monitor and maintain artificial infiltration basins in order to support sustainable and secure groundwater resources in Qatar.


Article metrics loading...

Loading full text...

Full text loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error