In Earth sciences, the measurement of soil and rock moisture content is essential in improving our understanding of various hydrologic processes. Recently, the electrical resistivity method has been frequently used to estimate the moisture content in the field. The uncertainty associated with resistivity-estimated moisture content is mainly from two sources: regularized inversion and petrophysical interpretation. In this study, to reduce the uncertainty, we propose (1) to use subsurface structural information from seismic refraction measurements to relax the smoothness-based regularization at structural boundaries and (2) to use structural unit-specific petrophysical relationships to translate resistivity into moisture content. The proposed methods are tested on a synthetic subsurface model featuring three distinct layers of a granitic critical zone (CZ). The results of the synthetic example show that both the spatial pattern and the moisture content values estimated with the new method are very close to the true model with low uncertainty. Compared to the traditional method, the estimation is significantly improved, particularly at the CZ boundaries, such as the regolith-fractured bedrock interface. We also apply the new method to a granitic hillslope to estimate the moisture content distribution from field resistivity measurements. Although no ground truth is available for validation, the estimated moisture content distributions exhibit some typical hydrological features in hillslopes, such as the perched water at the soil/rock interface and preferential flow path in fractured rocks. Therefore, it is concluded that incorporating structural information in resistivity inversion and using structural unit-specific petrophysical models can improve moisture content estimation from field resistivity measurements.
This is an author-produced, peer-reviewed version of this article. © 2022, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International license. The final, definitive version of this document can be found online at Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2022.128343
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Chen, Hang and Niu, Qifei. (2022). "Improving Moisture Content Estimation from Field Resistivity Measurements with Subsurface Structure Information". Journal of Hydrology, 613(Part A), 128343. https://doi.org/10.1016/j.jhydrol.2022.128343
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