Hydrogeophysical inversion using a physics-based catchment model with hydrological and electromagnetic induction data

Authors: PLEASANTS, MARK - University Of Wyoming; KELLENERS, THIJS - University Of Wyoming; PARSEKIAN, ANDREW - University Of Wyoming; BEFUS, KEVIN - University Of Arkansas; Flerchinger, Gerald; SEYFRIED, MARK - Retired ARS Employee; CARR, BRADELY - University Of Wyoming

Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/6/2024
Publication Date: 11/19/2024
Citation: Pleasants, M., Kelleners, T., Parsekian, A., Befus, K., Flerchinger, G.N., Seyfried, M., Carr, B. 2024. Hydrogeophysical inversion using a physics-based catchment model with hydrological and electromagnetic induction data. Journal of Hydrology. 647. Article 132376. https://doi.org/10.1016/j.jhydrol.2024.132376.
DOI: https://doi.org/10.1016/j.jhydrol.2024.132376

Interpretive Summary: Accuracy of hydrologic models for predicting streamflow from mountain environments greatly depends on the data available to parameterize the model. Data used to parameterize the model can include hydrologic data (such as soil water content and groundwater levels) and geophysics surveys that identify properties of the geologic layers. This study explores differences in the accuracy of calibrated model results depending on which data is used. Results indicate that calibrated model results using geophysics data alone or combining with the hydrological data lead to more realistic values for model parameters while maintaining reasonably accurate predictions of all hydrological data sets. The geophysical data sets show potential to be used in place of hydrological data in conjunction with streamflow data during model calibration. This suggests that long-term collection of hydrologic data, such as soil water content, can be replaced a few geophysical surveys when calibrating hydrologic models.

Technical Abstract: Accuracy of hydrologic models for predicting streamflow from mountain environments greatly depends on the data available to parameterize the model. Data used to parameterize the model can include hydrologic data (such as soil water content and groundwater levels) and geophysics surveys that identify properties of the geologic layers. This study explores differences in the accuracy of calibrated model results depending on which data is used. Results indicate that calibrated model results using geophysics data alone or combining with the hydrological data lead to more realistic values for model parameters while maintaining reasonably accurate predictions of all hydrological data sets. The geophysical data sets show potential to be used in place of hydrological data in conjunction with streamflow data during model calibration. This suggests that long-term collection of hydrologic data, such as soil water content, can be replaced a few geophysical surveys when calibrating hydrologic models.