Khan Zaib Jadoon

Uniqueness and stability analysis of hydrogeophysical inversion for time‐lapse ground‐penetrating radar estimates of shallow soil hydraulic properties

Precise measurement of soil hydraulic properties at field scales is one of the prerequisites to simulate subsurface flow and transport processes, which is crucial in many research and engineering areas. In our study, we numerically analyze uniqueness and stability for integrated hydrogeophysical inversion of time-lapse, off-ground ground-penetrating radar (GPR) data in estimating the unsaturated soil hydraulic properties. In the inversion, hydrodynamic modeling based on the one-dimensional (1-D) Richards equation is used to physically constrain a full-waveform radar electromagnetic model. Synthetic GPR data, in terms of 3-D multilayered media Greens functions, were generated for three different textured soils (coarse, medium, and fine) and assuming different infiltration events. Inversion was performed iteratively to estimate three key soil hydraulic parameters (?, n, and Ks) of the Mualem-van Genuchten model using the global multilevel coordinate search optimization algorithm. For the coarse- and medium-textured soils, inversions converged to the actual solution for all scenarios. For the fine soil, estimation errors occurred, mainly because of the higher attenuation of the electromagnetic waves in such a soil (high electric conductivity). The procedure appeared to be generally stable with respect to possible errors in the hydrodynamic and petrophysical model parameterization. However, we found that particular attention should be given to an accurate estimation of the saturated water content and infiltration flux for real field applications. The results from our numerical experiments suggest that, in theory, the proposed method is promising for the noninvasive identification of the shallow soil hydraulic properties at the field scale with a high spatial resolution.

Mapping Field-Scale Soil Moisture With L-Band Radiometer and Ground-Penetrating Radar Over Bare Soil

Accurate estimates of surface soil moisture are essential in many research fields, including agriculture, hydrology, and meteorology. The objective of this study was to evaluate two remote-sensing methods for mapping the soil moisture of a bare soil, namely, L-band radiometry using brightness temperature and ground-penetrating radar (GPR) using surface reflection inversion. Invasive time-domain reflectometry (TDR) measurements were used as a reference. A field experiment was performed in which these three methods were used to map soil moisture after controlled heterogeneous irrigation that ensured a wide range of water content. The heterogeneous irrigation pattern was reasonably well reproduced by both remote-sensing techniques. However, significant differences in the absolute moisture values retrieved were observed. This discrepancy was attributed to different sensing depths and areas and different sensitivities to soil surface roughness. For GPR, the effect of roughness was excluded by operating at low frequencies (0.2-0.8 GHz) that were not sensitive to the field surface roughness. The root mean square (rms) error between soil moisture measured by GPR and TDR was 0.038 m3·m-3. For the radiometer, the rms error decreased from 0.062 (horizontal polarization) and 0.054 (vertical polarization) to 0.020 m3·m-3 (both polarizations) after accounting for roughness using an empirical model that required calibration with reference TDR measurements. Monte Carlo simulations showed that around 20% of the reference data were required to obtain a good roughness calibration for the entire field. It was concluded that relatively accurate measurements were possible with both methods, although accounting for surface roughness was essential for radiometry.

Quantifying field-scale surface soil water content from proximal GPR signal inversion in the time domain

We applied inverse modelling of zero-offset, air-raised ground-penetrating radar (GPR) data to measure soil surface water contents over a bare agricultural field. The GPR system consisted of a vector network analyser combined with a low-frequency 0.2–2.0 GHz off-ground monostatic horn antenna, thereby setting up an ultra-wideband stepped-frequency continuous-wave radar. A fully automated platform was created by mounting the radar system on a truck for real-time data acquisition. An antenna calibration experiment was performed by lifting the whole setup to different heights above a perfect electrical conductor. This calibration procedure allowed the flittering out of the antenna effects and antenna-soil interactions from the raw radar data in the frequency domain. To avoid surface roughness effects, only the lower frequency range of 0.2–0.8 GHz was used for signal processing. Inversions of the radar data using the Green’s functions were performed in the time domain, focusing on a time window containing the surface reflection. GPR measurements were conducted every 4 m along a transect of 100 m. In addition, five time-domain reflectometry measurements were randomly recorded within the footprint of the GPR antenna. A good agreement was observed between the GPR and time-domain reflectometry soil water content estimates, as compared to the previous study performed at the same test site using a higher frequency 0.8–1.6 GHz horn antenna. To monitor the dynamics of soil water content, a pair of time-domain reflectometry probes was installed at 8 cm depth near the footprint of the GPR antenna and both time-domain reflectometry and GPR measurements were carried out for a period of 20 days. A good agreement of the trend was observed between the time-domain reflectometry and GPR time-lapse data with respect to several precipitation events. The proposed method and truck-mounted setup appear to be promising for the real-time mapping and monitoring of surface soil moisture contents at the field scale.

Analysis of Horn Antenna Transfer Functions and Phase-Center Position for Modeling Off-Ground GPR

The antenna of a zero-offset off-ground ground-penetrating radar can be accurately modeled using a linear system of frequency-dependent complex scalar transfer functions under the assumption that the electric field measured by the antenna locally tends to a plane wave. First, we analyze to which extent this hypothesis holds as a function of the antenna height above a multilayered medium. Second, we compare different methods to estimate the antenna phase center, namely, 1) extrapolation of peak-to-peak reflection values in the time domain and 2) frequency-domain full-waveform inversion assuming both frequency-independent and -dependent phase centers. For that purpose, we performed radar measurements at different heights above a perfect electrical conductor. Two different horn antennas operating, respectively, in the frequency ranges 0.2-2.0 and 0.8-2.6 GHz were used and compared. In the limits of the antenna geometry, we observed that antenna modeling results were not significantly affected by the position of the phase center. This implies that the transfer function model inherently accounts for the phase-center positions. The results also showed that the antenna transfer function model is valid only when the antenna is not too close to the reflector, namely, the threshold above which it holds corresponds to the antenna size. The effect of the frequency dependence of the phase-center position was further tested for a two-layered sandy soil subject to different water contents. The results showed that the proposed antenna model avoids the need for phase-center determination for proximal soil characterization.

Estimation of soil salinity in a drip irrigation system by using joint inversion of multicoil electromagnetic induction measurements

Low frequency electromagnetic induction (EMI) is becoming a useful tool for soil characterization due to its fast measurement capability and sensitivity to soil moisture and salinity. In this research, a new EMI system (the CMD mini-Explorer) is used for subsurface characterization of soil salinity in a drip irrigation system via a joint inversion approach of multiconfiguration EMI measurements. EMI measurements were conducted across a farm where Acacia trees are irrigated with brackish water. In situ measurements of vertical bulk electrical conductivity (σb) were recorded in different pits along one of the transects to calibrate the EMI measurements and to compare with the modeled electrical conductivity (σ) obtained by the joint inversion of multiconfiguration EMI measurements. Estimates of σ were then converted into the universal standard of soil salinity measurement (i.e., electrical conductivity of a saturated soil paste extract – ECe). Soil apparent electrical conductivity (ECa) was repeatedly measured with the CMD mini-Explorer to investigate the temperature stability of the new system at a fixed location, where the ambient air temperature increased from 26°C to 46°C. Results indicate that the new EMI system is very stable in high temperature environments, especially above 40°C, where most other approaches give unstable measurements. In addition, the distribution pattern of soil salinity is well estimated quantitatively by the joint inversion of multicomponent EMI measurements. The approach of joint inversion of EMI measurements allows for the quantitative mapping of the soil salinity distribution pattern and can be utilized for the management of soil salinity.

Estimation of Hydraulic Properties of a Sandy Soil Using Ground-Based Active and Passive Microwave Remote Sensing

In this paper, we experimentally analyzed the feasibility of estimating soil hydraulic properties from 1.4 GHz radiometer and 0.8-2.6 GHz ground-penetrating radar (GPR) data. Radiometer and GPR measurements were performed above a sand box, which was subjected to a series of vertical water content profiles in hydrostatic equilibrium with a water table located at different depths. A coherent radiative transfer model was used to simulate brightness temperatures measured with the radiometer. GPR data were modeled using full-wave layered medium Greens functions and an intrinsic antenna representation. These forward models were inverted to optimally match the corresponding passive and active microwave data. This allowed us to reconstruct the water content profiles, and thereby estimate the sand water retention curve described using the van Genuchten model. Uncertainty of the estimated hydraulic parameters was quantified using the Bayesian-based DREAM algorithm. For both radiometer and GPR methods, the results were in close agreement with in situ time-domain reflectometry (TDR) estimates. Compared with radiometer and TDR, much smaller confidence intervals were obtained for GPR, which was attributed to its relatively large bandwidth of operation, including frequencies smaller than 1.4 GHz. These results offer valuable insights into future potential and emerging challenges in the development of joint analyses of passive and active remote sensing data to retrieve effective soil hydraulic properties.

Hydrogeology, water quality, and microbial assessment of a coastal alluvial aquifer in western Saudi Arabia: potential use of coastal wadi aquifers for desalination water supplies

Wadi alluvial aquifers located along coastal areas of the Middle East have been assumed to be suitable sources of feed water for seawater reverse osmosis facilities based on high productivity, connectedness to the sea for recharge, and the occurrence of seawater with chemistry similar to that in the adjacent Red Sea. An investigation of the intersection of Wadi Wasimi with the Red Sea in western Saudi Arabia has revealed that the associated predominantly unconfined alluvial aquifer divides into two sand-and-gravel aquifers at the coast, each with high productivity (transmissivity = 42,000 m2/day). This aquifer system becomes confined near the coast and contains hypersaline water. The hydrogeology of Wadi Wasimi shows that two of the assumptions are incorrect in that the aquifer is not well connected to the sea because of confinement by very low hydraulic conductivity terrigenous and marine muds and the aquifer contains hypersaline water as a result of a hydraulic connection to a coastal sabkha. A supplemental study shows that the aquifer system contains a diverse microbial community composed of predominantly of Proteobacteria with accompanying high percentages of Gammaproteobacteria, Alphaproteobacteria and Deltaproteobacteria.

Full-waveform modeling of ground-coupled GPR antennas for wave propagation in multilayered media: The problem solved?

We propose a full-waveform approach for modeling time and frequency domain, off-ground and on-ground radars for wave propagation in multilayered media. The radar antennas are modeled using an equivalent set of infinitesimal electric dipoles placed over the antenna aperture. The linear relations between the fields in the transmission line, the sources, and the backscattered fields over the antenna aperture are expressed in terms of frequency dependent, global reflection and transmission coefficients, which are characteristic to the antenna. The interactions between the antenna and the layered medium are thereby accounted for. Far-field and near-field measurements are used to determine these antenna coefficients. The fields over the antenna aperture are calculated using three-dimensional Greens functions. We validated the approach using measurements with a 900 MHz centre frequency transmitting and receiving antenna situated at different heights above a copper plane. For heights larger than the antenna, a single point source and receiver was sufficient for accurately modeling the radar data. For smaller distances, using six sources and receivers provided remarkably good results. Although some simplifications were made in this paper, the proposed method shows great promise for characterizing multilayered media using full-waveform inversion, with very limited computation time compared to numerical methods.

Full-Waveform Modelling and Inversion of Ground-Penetrating Radar Data for Non-invasive Characterisation of Soil Hydrogeophysical Properties

We present a new technique for real-time, proximal sensing of the soil hydrogeophysical properties using ground-penetrating radar (GPR). The radar system is based on international standard vector network analyser technology, thereby setting up stepped-frequency continuous-wave GPR. The radar is combined with an off-ground, ultra-wideband, and highly directional horn antenna acting simultaneously as transmitter and receiver. Full-waveform forward modelling of the radar signal includes antenna propagation phenomena through a system of linear transfer functions in series and parallel. The system takes into account antenna–soil interactions and assumes the air–subsurface compartments as a three-dimensional multilayered medium, for which Maxwell’s equations are solved exactly. We provide an efficient way for estimating the spatial Green’s function as a solution of Maxwell’s equations from its spectral counterpart by deforming the integration path in the complex plane of the integration variable. Signal inversion is formulated as a complex least squares problem and is solved iteratively using the global multilevel coordinate search optimisation algorithm combined with the local Nelder–Mead simplex method. The electromagnetic model has unprecedented accuracy for describing the GPR signal in controlled laboratory conditions, providing accurate estimates for both soil dielectric permittivity and electrical conductivity. The proposed method has been specifically designed for the retrieval of soil surface dielectric permittivity and correlated surface water content, which has been validated in field conditions. We also show that constraining the electromagnetic inverse problem using hydrodynamic modelling theoretically permits retrieval of the soil hydraulic properties and reconstruction of continuous vertical water content profiles from time-lapse GPR data. The proposed method shows great promise for field-scale, high-resolution digital soil mapping, and thereby for bridging the spatial-scale gap between ground truthing based on soil sampling or local probes and airborne and spaceborne remote sensing.

Estimation of the near surface soil water content during evaporation using air-launched ground-penetrating radar

Evaporation is an important process in the global water cycle and its variation affects the near surface soil water content, which is crucial for surface hydrology and climate modelling. Soil evaporation rate is often characterized by two distinct phases, namely, the energy limited phase (stage-I) and the soil hydraulic limited period (stage-II). In this paper, a laboratory experiment was conducted using a sand box filled with fine sand, which was subject to evaporation for a period of twenty three days. The setup was equipped with a weighting system to record automatically the weight of the sand box with a constant time-step. Furthermore, time-lapse air-launched ground penetrating radar (GPR) measurements were performed to monitor the evaporation process. The GPR model involves a full-waveform frequency-domain solution of Maxwell’s equations for wave propagation in three-dimensional multilayered media. The accuracy of the full-waveform GPR forward modelling with respect to three different petrophysical models was investigated. Moreover, full-waveform inversion of the GPR data was used to estimate the quantitative information, such as near surface soil water content. The two stages of evaporation can be clearly observed in the radargram, which indicates qualitatively that enough information is contained in the GPR data. The fullwaveform GPR inversion allows for accurate estimation of the near surface soil water content during extended evaporation phases, when a wide frequency range of GPR (0.8–5.0 GHz) is taken into account. In addition, the results indicate that the CRIM model may constitute a relevant alternative in solving the frequency-dependency issue for full waveform GPR modelling.