EGU22-9632
https://doi.org/10.5194/egusphere-egu22-9632
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Estimating the effect of maize crops on time-lapse horizontal crosshole GPR data

Lena Lärm1,2, Felix Bauer1,2, Jan van der Kruk1, Jan Vanderborght1, Harry Vereecken1, Andrea Schnepf1, and Anja Klotzsche1
Lena Lärm et al.
  • 1Forschungszentrum Jülich GmbH, Institute of Bio- and Geosciences Agrosphere (IBG-3), Germany (l.laerm@fz-juelich.de)
  • 2University of Bonn - Cluster of Excellence Phenorob

Investigating soil, roots and their interaction is important to optimize agricultural practices like irrigation and fertilization and therefore increase the sustainability and productivity of crop production. In this study, we are combining two methods to examine non-invasively, characterize and monitor the soil-root zone throughout crop growing seasons: crosshole ground penetrating radar (GPR) and root-images within horizontal mini-rhizotrons. Over three maize crop growing seasons, we acquired in-situ time-lapse crosshole ground penetrating radar data and time-lapse root images, at two mini-rhizotron facilities in Selhausen, Germany. These facilities allow to horizontally measure data at six different depths, ranging between 0.1 m - 1.2 m and below three different plots with varying agricultural treatments, such as irrigation, sowing density, sowing date and cultivars. The GPR measurements result in the dielectric permittivity slices by applying standard ray-based analysis to zero-offset measurements along a pair of rhizotubes. Such horizontal permittivity slices can be linked to soil water content using petro‑physical relationships. Additionally, the root images provide a root fraction per image, which is derived by using a workflow combining state-of-the-art software tools, deep neural networks and automated feature extraction. The dielectric permittivity slices suggest a permittivity variation along the horizontal and vertical axes, depending on atmospheric conditions, soil properties, and root architecture. To quantify the influence of the roots on the spatial and temporal distribution of dielectric permittivity, we used statistical methods to reduce the impacting factors like soil heterogeneity, tube deviations and changing atmospheric conditions, which results in the spatial and temporal variability. For verification these permittivity variabilities are compared to the root fraction values. In general, using the spatial and temporal permittivity variations, we can detect the presence of roots and additionally recognize a varying influence of the roots over the duration of the crop growing season. Using these first results, we demonstrate that GPR can be applied to improve the characterization of the root-soil system related to maize plants. This could be the first step towards developing proxies e.g. for irrigation and fertilization applications using this non-invasive method.

How to cite: Lärm, L., Bauer, F., van der Kruk, J., Vanderborght, J., Vereecken, H., Schnepf, A., and Klotzsche, A.: Estimating the effect of maize crops on time-lapse horizontal crosshole GPR data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9632, https://doi.org/10.5194/egusphere-egu22-9632, 2022.

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