In agriculture, accurate hydrological information is crucial to infer water requirements for hydrological modeling, as well as for appropriate water management.
To achieve this purpose, geophysical frequency domain electromagnetic induction (FDEM) measurements are increasingly used for integration with traditional point-scale measurements to provide effective soil moisture estimations over large areas. The conversion of electromagnetic properties to soil moisture requires specific tools that must take into account the spatial variability of the two measurements and the data and model uncertainties. In a vineyard of about 4.5 ha located in Southern Italy, we tested an innovative assessment approach that uses a freeware code licensed from USGS, MoisturEC, to integrate electromagnetic data, collected with a CMD Mini-Explorer electromagnetic sensor, and point-scale soil moisture data.
About 30,000 data measurements of apparent electrical conductivity (sa) allowed us to build a 3D inverted electromagnetic model obtained via an inversion process. Soil properties at different depths were inferred from the FDEM model and confirmed through the ground truth sampling.
The data analysis tool allowed a more accurate estimation of the moisture distribution of the investigated area by combining the accuracy of the point-scale soil moisture measurements and the spatial coverage of the electrical conductivity (EC) data. The results confirmed the capability of the electromagnetic data to accurately map the moisture content of agricultural soils and, at the same time, the need to employ integrated analysis tools able to update such quantitative estimations in order to optimize soil and water management.