Exploring the Model Space of Airborne Electromagnetic Data to Delineate Large‐Scale Structure and Heterogeneity Within an Aquifer System

• Published in: Water resources research Vol. 57; no. 10
• Main Authors: Kang, S., Knight, R., Greene, T., Buck, C., Fogg, G.
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 01-10-2021
• Subjects: airborne electromagnetics; Aquifer systems; Aquifers; Connectivity; Data acquisition; Depth; Electrical resistivity; Gravel; Groundwater; Helicopters; Heterogeneity; Image acquisition; Interfaces; inversion; Inversions; Sand; Sediment; Sediments; Three dimensional models; Uncertainty; uncertainty quantification; vertical connectivity; Workflow; United States > US; California
• ISSN: 0043-1397; 1944-7973
• DOI: 10.1029/2021WR029699

Airborne electromagnetic (AEM) data can be inverted to recover models of the electrical resistivity of the subsurface; these, in turn, can be transformed to obtain models of sediment type. AEM data were acquired in Butte and Glenn Counties, California, USA to improve the understanding of the aquifer system. Around 800 line‐kilometers of high‐quality data were acquired, imaging to a depth of ∼300 m. We developed a workflow designed to obtain, from the AEM data, information about the large‐scale structure and heterogeneity of the aquifer system to better understand the vertical connectivity. Using six different inversions incorporating various forms of available information and posterior sampling of the recovered resistivity models, we produced 6,006 resistivity models. These models were transformed to models of sediment type and estimates of percentage of sand/gravel. Exploring the model space, containing the resistivity models and the derived models, allowed us to delineate the large‐scale structure of the aquifer system in a way that captures and communicates the uncertainty in the identified sediment type. The uncertainty increased, as expected, with depth, but also served to indicate, as areas of high uncertainty in sediment type, the location of both large‐scale and small‐scale interfaces between sediment types. A plan view map of the integrated percentage of sand/gravel, when compared to existing hydrographs, revealed the extent of lateral changes in vertical connectivity within the aquifer system throughout the study area.
Plain Language Summary
In studying and managing groundwater systems, it can be very difficult to get the information needed about the subsurface. The airborne electromagnetic (AEM) method uses a helicopter to move a geophysical system over the land surface to collect this needed information. In this study we acquired ∼800 line‐kilometers of high‐quality AEM data in an area of Butte and Glenn Counties in the Central Valley of California, USA. Acquisition of these data allowed us to obtain three‐dimensional (3D) resistivity models covering the region from the ground surface to a depth of about 300 m. Working with descriptions from wells, we were able to transform the 3D resistivity models into 3D sediment‐type models. These models allowed us to map out the large‐scale structure of the groundwater system and better understand the vertical connectivity within the system. Because of fundamental limitations in the AEM method, we obtained many different resistivity models and corresponding sediment‐type models. Exploring these models allowed us to quantify the uncertainty in our interpretation of the data. This not only assisted in our interpretation, but it also communicated, to the local water agency, our confidence in our interpretation.
Key Points
By incorporating various forms of available information in the inversion of airborne electromagnetic data, we designed a workflow that reduces and quantifies uncertainty in the derived sediment‐type models
Models of sediment type reveal the large‐scale architecture of the aquifer system
Models of the percentage of sand/gravel, when combined with hydrographs, provide information about the lateral variability in vertical connectivity within the aquifer system