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Ground Water. 2018 Sep;56(5):823-831. doi: 10.1111/gwat.12650. Epub 2018 Mar 31.

MoisturEC: A New R Program for Moisture Content Estimation from Electrical Conductivity Data.

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Hydrogeophysics Branch, Earth System Processes Division, U.S. Geological Survey, 11 Sherman Place, Unit 5015, Storrs, CT, 06269.
Environmental Chemistry Branch, Environmental Monitoring and Methods Division, National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, 944 E. Harmon Ave., Las Vegas, NV, 89119.


Noninvasive geophysical estimation of soil moisture has potential to improve understanding of flow in the unsaturated zone for problems involving agricultural management, aquifer recharge, and optimization of landfill design and operations. In principle, several geophysical techniques (e.g., electrical resistivity, electromagnetic induction, and nuclear magnetic resonance) offer insight into soil moisture, but data-analysis tools are needed to "translate" geophysical results into estimates of soil moisture, consistent with (1) the uncertainty of this translation and (2) direct measurements of moisture. Although geostatistical frameworks exist for this purpose, straightforward and user-friendly tools are required to fully capitalize on the potential of geophysical information for soil-moisture estimation. Here, we present MoisturEC, a simple R program with a graphical user interface to convert measurements or images of electrical conductivity (EC) to soil moisture. Input includes EC values, point moisture estimates, and definition of either Archie parameters (based on experimental or literature values) or empirical data of moisture vs. EC. The program produces two- and three-dimensional images of moisture based on available EC and direct measurements of moisture, interpolating between measurement locations using a Tikhonov regularization approach.


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