Data from tomographic surveys make an inverse problem better posed in comparison to the data from a single excitation source. A tomographic survey provides different coverages and perspectives of subsurface heterogeneity: nonfully redundant information of the subsurface. Fusion of these pieces of information expands and enhances the capability of a conventional survey, provides cross validation of inverse solutions, and constrains inherently ill posed field-scale inverse problems. Basin-scale tomography requires energy sources of great strengths. Spatially and temporally varying natural stimuli are ideal energy sources for this purpose. In this study, we explore the possibility of using river stage variations for basin-scale subsurface tomographic surveys. Specifically, we use numerical models to simulate groundwater level changes in response to temporal and spatial variations of the river stage in a hypothetical groundwater basin. We then exploit the relation between temporal and spatial variations of well hydrographs and river stage to image subsurface heterogeneity of the basin. Results of the numerical exercises are encouraging and provide insights into the proposed river stage tomography. Using naturally recurrent stimuli such as river stage variations for characterizing groundwater basins could be the future of geohydrology. However, it calls for implementation of sensor networks that provide long-term and spatially distributed monitoring of excitation as well as response signals on the land surface and in the subsurface.
ASJC Scopus subject areas
- Water Science and Technology