Monitoring Soil Moisture Dynamics Using Electrical Resistivity Tomography under Homogeneous Field Conditions

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ID: 270216
2020
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Abstract
There is a gap between lab experiments where resistivity–soil moisture relations are generally very good and field studies in complex environmental settings where relations are always less good and complicated by many factors. An experiment was designed where environmental settings are more controlled, the best outside laboratory, to assess the transferability from lab to outdoor. A field experiment was carried out to evaluate the use of electric resistivity tomography (ERT) for monitoring soil moisture dynamics over a period of 67 days. A homogeneous site in the central part of The Netherlands was selected consisting of grass pasture on an aeolian sand soil profile. ERT values were correlated to gravimetric soil moisture samples for five depths at three different dates. Correlations ranged from 0.43 to 0.73 and were best for a soil depth of 90 cm. Resistivity patterns over time (time-lapse ERT) were analyzed and related to rainfall events where rainfall infiltration patterns could be identified. Duplicate ERT measurements showed that the noise level of the instrument and measurements is low and generally below 3% for the soil profile below the mixed layer but above the groundwater. Although the majority of the measured resistivity patterns could be well explained, some artefacts and dynamics were more difficult to clarify, even so in this homogeneous field situation. The presence of an oak tree with its root structure and a ditch with surface water with higher conductivity may have an impact on the resistivity pattern in the soil profile and over time. We conclude that ERT allows for detailed spatial measurement of local soil moisture dynamics resulting from precipitation although field experiments do not yield accuracies similar to laboratory experiments. ERT approaches are suitable for detailed spatial analyses where probe or sample-based methods are limited in reach or repeatability.
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jong2020sensorsmonitoring Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Steven M. de Jong;Renée A. Heijenk;Wiebe Nijland;Mark van der Meijde;de Jong, Steven M.;Heijenk, Renée A.;Nijland, Wiebe;van der Meijde, Mark;
Journal sensors
Year 2020
DOI
10.3390/s20185313
URL
https://doi.org/10.3390/s20185313
Keywords
surface water precipitation infiltration soil water content spatial dynamics time-lapse ert depth profile

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