Minimally invasive monitoring of root development and soil states (soil moisture, temperature) in undisturbed soils during a crop growing cycle is a challenging task. Minirhizotron (MR) tubes offer the possibility to view root development in situ with time. Two MR facilities were constructed in two different soils, stony vs. silty, to monitor root growth, root zone processes, and their dependence on soil water availability. To obtain a representative image of the root distribution, 7-m-long tubes were installed horizontally at 10-, 20-, 40-, 60-, 80-, and 120-cm depths. A homemade system was developed to install MR tubes in the silty soil in horizontally drilled straight holes. For the stony soil, the soil rhizotubes were installed in an excavated and subsequently backfilled pit. In both facilities, three subplots were established with different water treatments: rain sheltered, rainfed, and irrigated. To monitor soil moisture, water potential, and soil temperature, time domain reflectometer probes, tensiometers, and matrix water potential sensors were installed. Soil water content profiles in space and time were obtained between two MR tubes using cross-hole ground-penetrating radar along the tubes at different depths. Results from the first growing season of winter wheat (Triticum aestivum L.) after installation demonstrate that differences in root development, soil water, and temperature dynamics can be observed among the different soil types and water treatments. When combined with additional measurements of crop development and transpiration, these data provide key information that is essential to validate and parameterize root development and water uptake models in soil-vegetation-atmosphere transfer models.Abbreviations: CRIM, complex refraction index model; EMI, electromagnetic induction; GPR, ground-penetrating radar; MR, minirhizotron; SEM, standard error of the sample mean; SWC, soil water content; SWP, soil water potential; TDR, time domain reflectometry; ZOP, zero-offset profile.
Tremendous progress has been made with respect to ground penetrating radar (GPR) equipment, data acquisition, and processing since the establishment of GPR as a tool for soil water content determination in vadose zone hydrology about 25 yr ago. In this update, we aim to provide a critical overview of recent advances in vadose zone applications of GPR with a particular focus on new possibilities for multi-offset and borehole GPR measurements, the development of quantitative offground GPR methods, full-waveform inversion of GPR measurements, the potential of time-lapse GPR measurements for process investigations and hydrological parameter estimation, and recent improvements in GPR instrumentation. We hope that this update encourages the soil hydrology, groundwater, and critical zone community to embrace GPR as a viable tool for soil water content determination and the elucidation of subsurface hydrological processes.
Cross‐hole radar tomography is a useful tool for mapping shallow subsurface electrical properties viz. dielectric permittivity and electrical conductivity. Common practice is to invert cross‐hole radar data with ray‐based tomographic algorithms using first arrival traveltimes and first cycle amplitudes. However, the resolution of conventional standard ray‐based inversion schemes for cross‐hole ground‐penetrating radar (GPR) is limited because only a fraction of the information contained in the radar data is used. The resolution can be improved significantly by using a full‐waveform inversion that considers the entire waveform, or significant parts thereof. A recently developed 2D time‐domain vectorial full‐waveform cross‐hole radar inversion code has been modified in the present study by allowing optimized acquisition setups that reduce the acquisition time and computational costs significantly. This is achieved by minimizing the number of transmitter points and maximizing the number of receiver positions. The improved algorithm was employed to invert cross‐hole GPR data acquired within a gravel aquifer (4–10 m depth) in the Thur valley, Switzerland. The simulated traces of the final model obtained by the full‐waveform inversion fit the observed traces very well in the lower part of the section and reasonably well in the upper part of the section. Compared to the ray‐based inversion, the results from the full‐waveform inversion show significantly higher resolution images. At either side, 2.5 m distance away from the cross‐hole plane, borehole logs were acquired. There is a good correspondence between the conductivity tomograms and the natural gamma logs at the boundary of the gravel layer and the underlying lacustrine clay deposits. Using existing petrophysical models, the inversion results and neutron‐neutron logs are converted to porosity. Without any additional calibration, the values obtained for the converted neutron‐neutron logs and permittivity results are very close and similar vertical variations can be observed. The full‐waveform inversion provides in both cases additional information about the subsurface. Due to the presence of the water table and associated refracted/reflected waves, the upper traces are not well fitted and the upper 2 m in the permittivity and conductivity tomograms are not reliably reconstructed because the unsaturated zone is not incorporated into the inversion domain.
Heterogeneous small-scale high-contrast layers and spatial variabilities of soil properties can have a large impact on flow and transport processes in the critical zone. Because their characterization is difficult and critical, high-resolution methods are required. Standard ray-based approaches for imaging the subsurface consider only a small amount of the measured data and suffer from limited resolution. In contrast, full-waveform inversion (FWI) considers the full information content of the measured data and could yield higher resolution images in the subwavelength scale. In the past few decades, ground-penetrating radar (GPR) FWI and its application to experimental data have matured, which makes GPR FWI an established approach to significantly improve resolution. Several theoretical developments were achieved to improve the application to experimental data from crosshole GPR FWI. We have determined the necessary steps to perform FWI for experimental data to obtain reliable and reproducible high-resolution images. We concentrate on experimental crosshole GPR data from a test site in Switzerland to illustrate the challenges of applying FWI to experimental data and discuss the obtained results for different development steps including possible pitfalls. Thereby, we acknowledge out the importance of a correct time-zero correction of the data, the estimation of the effective source wavelet, and the effect of the choice of starting models. The reliability of the FWI results is investigated by analyzing the fit of the measured and modeled traces, the remaining gradients of the final models, and validating with independently measured logging data. Thereby, we found that special care needs to be taken to define the optimal inversion parameters to avoid overshooting of the inversion or truncation errors.
High-contrast layers caused by porosity or clay content changes can have a dominant effect on hydraulic processes within an aquifer. These layers can act as low-velocity waveguides for GPR waves. We used a field example from a hydrological test site in Switzerland to show that fullwaveform inversion of crosshole GPR signals could image a subwavelength thickness low-velocity waveguiding layer. We exploited the full information content of the data, whereas ray-based inversion techniques are not able to image such thin waveguide layers because they only exploit the first-arrival times and first-cycle amplitudes. This lowvelocity waveguide layer is caused by an increase in porosity and indicates a preferential flow path within the aquifer. The waveguide trapping causes anomalously high amplitudes and elongated wavetrains to be observed for a transmitter within the waveguide and receivers straddling the waveguide depth range. The excellent fit of amplitudes and phase between the measured and modeled data confirms its presence. This new method enables detailed aquifer characterization to accurately predict transport and flow and can be applied to a wide range of geologic, hydrological, and engineering investigations.
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