Marnik Vanclooster

Modeling of ground-penetrating Radar for accurate characterization of subsurface electric properties

The possibility to estimate accurately the subsurface electric properties from ground-penetrating radar (GPR) signals using inverse modeling is obstructed by the appropriateness of the forward model describing the GPR subsurface system. In this paper, we improved the recently developed approach of Lambot et al. whose success relies on a stepped-frequency continuous-wave (SFCW) radar combined with an off-ground monostatic transverse electromagnetic horn antenna. This radar configuration enables realistic and efficient forward modeling. We included in the initial model: 1) the multiple reflections occurring between the antenna and the soil surface using a positive feedback loop in the antenna block diagram and 2) the frequency dependence of the electric properties using a local linear approximation of the Debye model. The model was validated in laboratory conditions on a tank filled with a two-layered sand subject to different water contents. Results showed remarkable agreement between the measured and modeled Greens functions. Model inversion for the dielectric permittivity further demonstrated the accuracy of the method. Inversion for the electric conductivity led to less satisfactory results. However, a sensitivity analysis demonstrated the good stability properties of the inverse solution and put forward the necessity to reduce the remaining clutter by a factor 10. This may partly be achieved through a better characterization of the antenna transfer functions and by performing measurements in an environment without close extraneous scatterers.

Intraseasonal dynamics of soil moisture variability within a small agricultural maize cropped field

The spatio-temporal dynamics of soil water content was investigated within a small agricultural maize cropped field located in Belgium. Soil moisture measurements were intensively, made between May, 30 and September 13. 1999 on 28 sampling locations at different depths (from 0 to 125 cm) with both TDR and neutron probe. The adopted sampling scheme resulted in a comprehensive data set of nearly 8000 soil moisture measurements. Using this data set, we first probe the role of factors controlling the spatio-temporal soil moisture dynamics for the different considered soil depth. Special emphasis is thereby given to the role of the vegetation in the space-time relationships of soil Moisture. Secondly, we identify the temporal dynamics of the spatial structure of soil moisture pattern at different soil depth. Thirdly, we investigate the relationship between the mean soil moisture and the spatial variability across time, analysing through the season the optimal sampling strategies to adopt for providing the field areal soil moisture within a given predefined error limit. The result showed that the spatially variable within the held and subsequently through the process of evapotranspiration and the root Water Uptake, plays a non-negligible role in the temporal dynamics of the observed soil Moisture patterns for the superficial layers. The spatial structure of these soil moisture patterns,vas non-existent or only weakly marked. The study finally indicated that a negative correlation exists between the spatial variability and the mean soil moisture, implicitly suggesting that the sampling has to be more intensive for the drier conditions. Besides these results, this study reemphasises the importance of conducting, soil moisture spatial variability studies with measurements performed on the entire hydrological active zone and to adopt temporally unchanged sampling locations in order to progress in the thorough understanding of the physical processes generating the soil moisture spatial variability

A European test of pesticide-leaching models: methodology and major recommendations

Testing of pesticide-leaching models is important in view of their increasing use in pesticide registration procedures in the European Union. This paper presents the methodology and major conclusions of a test of pesticide-leaching models. Twelve models simulating the vertical one-dimensional movement of water, solute, heat, and, in particular, pesticides, through the soil profile were used by 36 different modellers. The adopted modelling codes differ in terms of modelling concepts and modelling hypothesis. Modellers were affiliated to industry and to the scientific community as well. Four quality datasets were identified to perform the analysis. The dataset included field and lysimeter data, collected in the Netherlands, Germany, Italy and the UK. As well, non-structured as structured soils were available in the dataset. To elucidate the ability to model correctly water transport, solute transport, heat transport and pesticide transport in soils, a stepwise evaluation approach was followed. Splitting up the experimental dataset enabled us to quantify the calibration capability and the prediction capability of the models. The simulations were performed by different model users enabling us also to characterise output variability in terms of user dependent interpretation of the model input and parameters. Recommendations are formulated for improving the quality of modelling datasets, and the process description of water, solute, and heat transport in a pesticide-leaching model, plus the process description of pesticide fate. Application of the principles of good modelling practice (GMP) is briefly described

Analysis of air-launched ground-penetrating radar techniques to measure the soil surface water content

We analyze the common surface reflection and full-wave inversion methods to retrieve the soil surface dielectric permittivity and correlated water content from air-launched ground-penetrating radar (GPR) measurements. In the full-wave approach, antenna effects are filtered out from the raw radar data in the frequency domain, and full-wave inversion is performed in the time domain, on a time window focused on the surface reflection. Synthetic experiments are performed to investigate the most critical hypotheses on which both techniques rely, namely, the negligible effects of the soil electric conductivity (?) and layering. In the frequency range 1–2 GHz we show that for ? > 0.1 Sm?1, significant errors are made on the estimated parameters, e.g., an absolute error of 0.10 in water content may be observed for ? = 1 Sm?1. This threshold is more stringent with decreasing frequency. Contrasting surface layering may proportionally lead to significant errors when the thickness of the surface layer is close to one fourth the wavelength in the medium, which corresponds to the depth resolution. Absolute errors may be >0.10 in water content for large contrasts. Yet we show that full-wave inversion presents valuable advantages compared to the common surface reflection method. First, filtering antenna effects may prevent absolute errors >0.04 in water content, depending of the antenna height. Second, the critical reference measurements above a perfect electric conductor (PEC) are not required, and the height of the antenna does not need to be known a priori. This averts absolute errors of 0.02–0.09 in water content when antenna height differences of 1–5 cm occur between the soil and the PEC. A laboratory experiment is finally presented to analyze the stability of the estimates with respect to actual measurement and modeling errors. While the conditions were particularly well suited for applying the common reflection method, better results were obtained using full-wave inversion.

A global multilevel coordinate search procedure for estimating the unsaturated soil hydraulic properties

We present a new inverse modeling procedure to characterize the hydraulic properties of partially saturated soils from soil moisture measurements during a natural transient flow experiment. The inversion of the governing one-dimensional Richards equation is carried out using the Global Multilevel Coordinate Search optimization algorithm in sequential combination with the local Nelder-Mead Simplex algorithm (GMCS-NMS). We introduce this optimization method in the area of unsaturated zone hydrology since it is adapted for solving accurately and efficiently complex nonlinear problems. Several numerical experiments have been conducted to evaluate the proposed inversion method using synthetic error-free and error-contaminated data for different textured soils. Inversion of the simulated error-free data and examination of the related response surfaces demonstrated the uniqueness of the inverse solution and the suitability of the GMCS-NMS strategy when identifying four key parameters of the hydraulic functions described by the Mualem-van Genuchten model. Inversion of the error-contaminated data proved further the good stability of the inverse solution that is consistent with the needs required by real experiments.

Effect of the sampling frequency of meteorological variables on the estimation of the reference evapotranspiration

In this paper, we quantify the effect of the temporal sampling frequency of commonly measured climatic variables on the estimation of the reference evapotranspiration. Using a set of data sampled on an intensive basis (i.e. one measurement each minute) during a period of 6 months, we first analyse the effect of the temporal sampling frequency on the estimation of the daily means of the shortwave solar radiation, the wind speed, the dry and wet temperatures, and on the estimation of the daily maximum and minimum dry temperature. Subsequently, a sensitivity analysis of a reference evapotranspiration model is carried out to determine the most sensible meteorological variables. The sensitivity coefficients were then combined with the errors due to the temporal sampling to quantify for each variable the impact of the sampling frequency on the estimation of daily ETo. The results showed that the solar radiation and the wind speed are the most sensitive to bias induced by inadequate temporal sampling frequency. Daily errors of 5.1 MJ m(-2) d(-1) or 41.05% for the solar radiation, and 0.45 m s(-1) or 18% for the wind speed may be obtained if these variables are inappropriately sampled. Moreover, the impact of inappropriate temporal sampling on the estimation of ETo can be significant with respective maximum bias of 0.61 mm d(-1) due to inappropriate solar radiation sampling and 0.36 mm d(-1) due to inappropriate maximum temperature sampling. A non-intensive hourly temporal sampling schedule of all meteorological variables may induce errors on the daily ETo so high as -0.76 mm d(-1) or -27%. Fortunately, the errors generated on the estimation of the long-term integrated evapotranspiration are clearly lower (3.8%). Our study clearly demonstrates the importance of scheduling appropriately the sampling frequency of climatic variables to correctly estimate land surfaces fluxes as well in fundamental as in more practically oriented research studies

Estimating solute transport in undisturbed soil columns using time-domain reflectometry

Time-domain reflectometry (TDR) was used to monitor solute breakthrough curves (BTCs) in 30 saturated undisturbed soil columns collected along a 35-m-long transect in the field. The BTCs were obtained by relating the bulk soil electrical conductivity, ECa, to the relative concentration of a KCl solute pulse applied to the soil surface. Values of ECa were estimated by measuring the soils impedance to an electromagnetic wave generated by a cable tester. Parallel two-rod TDR probes inserted horizontally at a depth of 10 cm were used to monitor the soils impedance during transport of the KCl solute pulse. Calculated experimental time moments indicated that the BTC data were very variable in time and space. This variability was attributed in part to the relatively small volume of soil sampled with the TDR probes, and in part to the natural heterogeneity of the sandy loam soil. The observed BTCs were classified into three groups. One group showed bell-shaped curves consistent with the classical convection-dispersion equation (CDE). A second group was characterized by early breakthrough and long tailing. The BTCs in this group could be described by a mobile-immobile transport model (MIM). A third group of BTCs showed irregular shapes with several peaks. Time moments were used to compare the estimated (from the moments), fitted (CDE and MIM) and independently measured pore-water velocities. The disparities between the observed and fitted velocities suggest that for structured soil several TDR probes may be necessary in order to obtain reasonable estimates of column-scale solute transport behaviour.

Hydrogeological investigations at the Membach station, Belgium, and application to correct long periodic gravity variations

[1] A comprehensive hydrogeological investigation regarding the influence of variations in local and regional water mass on superconducting gravity measurements is presented for observations taken near the geodynamic station of Membach, Belgium. Applying a regional water storage model, the gravity contribution due to the elastic deformation of the Earth was derived. In addition, the Newtonian gravity effect induced by the local water mass variations was calculated, using soil moisture observations taken at the ground surface (about 48 m above the gravimeters). The computation of the gravimetric effect is based on a digital elevation model with spatially discretized rectangular prisms. The obtained results are compared with the observations of a superconducting gravimeter (SG). We find that the seasonal variations can be reasonably well predicted with the regional water storage model and the local Newtonian effects. Shorter-period effects depend on the local changes in hydrology. This result shows the sensitivity of SG observations to very local water storage changes.

Estimating soil electric properties from monostatic ground‐penetrating radar signal inversion in the frequency domain

[1] A new integrated approach for identifying the shallow subsurface electric properties from ground-penetrating radar (GPR) signal is proposed. It is based on an ultrawide band (UWB) stepped frequency continuous wave (SFCW) radar combined with a dielectric filled transverse electric and magnetic (TEM) horn antenna to be used off the ground in monostatic mode; that is, a single antenna is used as emitter and receiver. This radar configuration is appropriate for subsurface mapping and allows for an efficient and more realistic modeling of the radar-antenna-subsurface system. Forward modeling is based on linear system response functions and on the exact solution of the three-dimensional Maxwell equations for wave propagation in a horizontally multilayered medium representing the subsurface. Subsurface electric properties, i.e., dielectric permittivity and electric conductivity, are estimated by model inversion using the global multilevel coordinate search optimization algorithm combined sequentially with the local Nelder-Mead simplex algorithm (GMCS-NMS). Inversion of synthetic data and analysis of the corresponding response surfaces proved the uniqueness of the inverse solution. Laboratory experiments on a tank filled with a homogeneous sand subject to different water content levels further demonstrated the stability and accuracy of the solution toward measurement and modeling errors, particularly those associated with the dielectric permittivity. Inversion for the electric conductivity led to less satisfactory results. This was mainly attributed to the characterization of the frequency response of the antenna and to the high frequency dependence of the electric conductivity.

Overview of inert tracer experiments in key belgian soil types: Relation between transport and soil morphological and hydraulic properties

To investigate relations between solute transport, soil properties, and experimental conditions, we summarize results from leaching experiments that we carried out in a range of soils, at different scales (column (0.3-1.0 m ID, 1.0 m length) and field plot scale), and using, different leaching rates (0.5-30 cm d(-1)). The lateral mixing regime and longitudinal dispersion were derived from time series of tracer concentrations at several depths in the soil. Field- and column-scale transport were similar in loam and silt loam soils. The mixing regime was related to soil morphological features, such as vertical tongues, stratification, macropores, and a water-repellent layer. The dispersion increased in all soils more than linearly with increasing leaching rate, implying that the dispersivity is not an intrinsic soil characteristic. The change of dispersivity with leaching rate was linked to the unsaturated hydraulic conductivity using a multidomain conceptualization of the pore space.