Comparison of Electromagnetic Induction Data with the Wireless Sensor Network at Wüstebach: An approach for non-invasively Characterisation of Soil Moisture Pattern in Conifer Forests

Abstract

Knowledge about spatial and temporal soil moisture distribution is one of the key elements in land and water management and supports the prediction of climate relevant events. Although information of soil moisture conditions is of utmost importance, it is still difficult to obtain reliable information over the field-scale. A possibility of filling that information gap is the indirect mapping of soil moisture by easily recordable physical variables, e.g. from the electric conductivity measured by electromagnetic induction (EMI) due to the (dependent) relationship between moisture and electric soil conditions. EMI has been an established tool for subsurface characterization for several decades and has the capacity to non-invasively map over larger spatial areas with low operation costs. However, the recorded electrical conductivity (EC) is an integrated value and includes the effects of clay and mineral properties, porosity and water content; hence, making an allocation to one of these qualities, in this case oil moisture, can be difficult. The Wireless Sensor Network SoilNet at Wüstebach catchment (approx. 27 ha) provides a reliable near-real-time monitoring of soil moisture at three different exploration depths (Bogena et al. 2010). However the SoilNet network is spatial limited, not portable and installation, monitoring and service are time and effort costly. A combination of the advantages of EMI measurement with these reliable moisture data could improve the allocation of the ECa signal to soil moisture values. This offers the deriving of moisture information from EMI maps recorded at areas outside of the network time and cost efficient. In this study we analysed EMI data from Wüstebach of two different exploration depths obtained during different weather condition / seasons. To separate the dynamic moisture signal from the geological background signal, we subtracted the temporal ECa values from the mean values and delineated so the relative changes at each depth as proxy for moisture changes. We also used the standard deviations estimated from the temporal ECa changes and identified therewith areas of higher and lower dynamic soil moisture changes. A comparison with the corresponding SoilNet data confirms similar areas of higher and lower soil moisture fluctuation and general trends, both spatial and temporal. The study demonstrates the ability of non-invasively hydrogeophysical measurement to reveal soil moisture pattern with relatively low effort. Thus the applied approach provides an adequate alternative to time and cost consuming invasive methods. The study also shows that the practice of EMI monitoring is not limited by areas with heterogeneous topography and / or complex accessibility appropriated for application within conifer forests