TY - JOUR

T1 - The application of electromagnetic induction methods to reveal the hydrogeological structure of a riparian wetland

AU - McLachlan, Paul

AU - Blanchy, Guillaume

AU - Chambers, Jonathan

AU - Sorensen, James

AU - Uhlemann, Sebastian

AU - Wilkinson, Paul

AU - Binley, Andrew

PY - 2021/6/30

Y1 - 2021/6/30

N2 - Understanding ecologically sensitive wetlands often require non-invasive methods to characterize their complex structure (e.g. deposit heterogeneity) and hydrogeological parameters (e.g. hydraulic conductivity). Here, electrical conductivities of a riparian wetland were obtained using frequency-domain electromagnetic induction (EMI) methods. The wetland was previously characterized by extensive intrusive measurements and 3D electrical resistivity tomography (ERT) and hence offers an ideal opportunity to objectively assess EMI methods. Firstly, approaches to obtain structural information (e.g. elevation and thickness of alluvium) from EMI data and models were assessed. Regularized and sharp inversion algorithms were investigated for ERT calibrated EMI data. Moreover, the importance of EMI errors in inversion was investigated. The hydrological information content was assessed using correlations with piezometric data and petrophysical models. It was found that EMI data were dominated by the thickness of peaty alluvial soils and relatively insensitive to topography and total alluvial thickness. Furthermore, although error weighting in the inversion improved the accuracy of alluvial soil thickness predictions, the multi-linear regression method performed the best. For instance, an iso-conductivity method to estimate the alluvial soil thickness in the regularized models had a normalized mean absolute difference (NMAD) of 21.4%, and although this performed better than the sharp inversion algorithm (NMAD = 65.3%), the multi-linear regression approach (using 100 intrusive observations) achieved a NMAD = 18.0%. In terms of hydrological information content, correlations between EMI results and piezometric data were poor, however robust relationships between petrophysically derived porosity and hydraulic conductivity were observed for the alluvial soils and gravels.

AB - Understanding ecologically sensitive wetlands often require non-invasive methods to characterize their complex structure (e.g. deposit heterogeneity) and hydrogeological parameters (e.g. hydraulic conductivity). Here, electrical conductivities of a riparian wetland were obtained using frequency-domain electromagnetic induction (EMI) methods. The wetland was previously characterized by extensive intrusive measurements and 3D electrical resistivity tomography (ERT) and hence offers an ideal opportunity to objectively assess EMI methods. Firstly, approaches to obtain structural information (e.g. elevation and thickness of alluvium) from EMI data and models were assessed. Regularized and sharp inversion algorithms were investigated for ERT calibrated EMI data. Moreover, the importance of EMI errors in inversion was investigated. The hydrological information content was assessed using correlations with piezometric data and petrophysical models. It was found that EMI data were dominated by the thickness of peaty alluvial soils and relatively insensitive to topography and total alluvial thickness. Furthermore, although error weighting in the inversion improved the accuracy of alluvial soil thickness predictions, the multi-linear regression method performed the best. For instance, an iso-conductivity method to estimate the alluvial soil thickness in the regularized models had a normalized mean absolute difference (NMAD) of 21.4%, and although this performed better than the sharp inversion algorithm (NMAD = 65.3%), the multi-linear regression approach (using 100 intrusive observations) achieved a NMAD = 18.0%. In terms of hydrological information content, correlations between EMI results and piezometric data were poor, however robust relationships between petrophysically derived porosity and hydraulic conductivity were observed for the alluvial soils and gravels.

KW - electromagnetic induction

KW - wetland

KW - riparian

KW - hydrogeophysics

U2 - 10.1029/2020WR029221

DO - 10.1029/2020WR029221

M3 - Journal article

VL - 57

JO - Water Resources Research

JF - Water Resources Research

SN - 0043-1397

IS - 6

M1 - e2020WR029221

ER -