Groundwater models are essential for managing water resources, but they are hard to parameterize because subsurface data are sparse. Boreholes provide only point measurements, leaving the hydraulic properties of an aquifer poorly constrained. Airborne geophysical surveys offer a way to fill that gap by imaging resistivity across large areas, yet translating resistivity into hydraulic properties is not straightforward and carries its own uncertainty.
In a new paper highlighted by AGU's Water Resources Research, Scantlebury and Harter propose a probabilistic multi-texture framework that combines airborne electromagnetic resistivity models with borehole data. Their approach explicitly recognizes the uncertainty in resistivity–lithology relationships, producing hydraulic structure models that can be directly incorporated into a groundwater flow model.
The authors demonstrate the workflow on the Scott Valley aquifer system, showing that it can be applied over large spatial scales. According to the editors' highlight, such a workflow could significantly improve the use of large-scale geophysical data for reducing predictive uncertainty in groundwater models—a step toward more reliable water resource planning.