Abstract
The integration of non-invasive geophysical technologies has been popular in recent years for hydro-geophysical applications. Electrical resistivity tomography (ERT) and surface nuclear magnetic resonance (surface NMR) are geophysical methods for classifying subsurface soil media up to 100 m below the soil's surface. The main focus of the present study is to estimate the seasonal changes in the subsurface aquifer properties like water content and hydraulic conductivity using the combination of 2D/3D ERT and surface NMR methods, and these results were compared with the pulse moment time inversion (QTI) scheme. It was observed that small-scale variability in aquifer properties was found in the ERT and surface inversions. However, these models were developed for the field scale. Thus, small-scale variability can be neglected. During the post-monsoon and monsoon seasons, the size of low resistivity (4–14Ohm-m) and very low resistivity (23–33Ohm-m) zones are as shown in Fig. 5. Similarly, surface NMR measurements revealed a significant increase in the water content during these seasons. The chi-square value for the QTI scheme was 1.0672, which was quite near to 1. As a result, the QTI model is considered to be accurate for this study. The subsurface soil samples particle size distribution curves were studied, and soil components were classified using the transverse relaxation time. Thus, the combination of ERT and surface NMR approach promises to be a powerful tool for estimating subsurface characterization.
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Singh, U., Sharma, P.K. Seasonal groundwater monitoring using surface NMR and 2D/3D ERT. Environ Earth Sci 81, 198 (2022). https://doi.org/10.1007/s12665-022-10325-9
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DOI: https://doi.org/10.1007/s12665-022-10325-9