Measuring Water Content Heterogeneity Using Multifold GPR with Reflection Tomography

Bradford, John H.

doi:10.2136/vzj2006.0160

Cited by 83 publications

(32 citation statements)

References 31 publications

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“…Lunt et al (2005) studied temporal variation of soil water content along profiles with known reflector depths at a heterogeneous site with GPR reflections. Furthermore, without known reflector depths, the studies by Bradford (2008) and Steelman and Endres (2012) using common mid-point (CMP) soundings or similar measurements demonstrate that spatio-temporal soil water content variations can be obtained from GPR reflections at field conditions. In particular, a multi-channel GPR setup such as that proposed by Gerhards et al (2008) offers a quick and efficient imaging of soil water content and reflector depth.…”

Section: Pan Et Al: Estimating Field-scale Soil Water Dynamics Wimentioning

confidence: 96%

Estimating field-scale soil water dynamics at a heterogeneous site using multi-channel GPR

Xiong

Zhang

Huang

et al. 2012

Hydrol. Earth Syst. Sci.

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Abstract. We explore the feasibility to quantify the fieldscale soil water dynamics through time series of GPR (ground-penetrating radar) measurements, which bridge the gap between point measurements and field measurements. Working on a 40 m × 50 m area in a heterogeneous agricultural field, we obtain a time series of radargrams after a heavy rainfall event. The data are analysed to simultaneously yield (i) a three-dimensional representation of the subsurface architecture and (ii) the total soil water volume between the surface and a reflection boundary associated with the presence of paleo sand dunes or clay inclusions in a rather uniform sand matrix. We assess the precision and the accuracy of these quantities and conclude that the method is sensitive enough to capture the spatial structure of the changing soil water content in a three-dimensional heterogeneous soil during a short-duration infiltration event. While the sensitivity of the method needs to be improved, it already produced useful information to understand the observed patterns in crop height and it yielded insight into the dynamics of soil water content at this site including the effect of evaporation.

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Section: Pan Et Al: Estimating Field-scale Soil Water Dynamics Wimentioning

confidence: 96%

Estimating field-scale soil water dynamics at a heterogeneous site using multi-channel GPR

Xiong

Zhang

Huang

et al. 2012

Hydrol. Earth Syst. Sci.

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“…Analysis of the data from these surveys typically relies on normal-moveout (NMO) corrections (Fisher et al, 1992), however, which assumes idealized, locally continuous reflector geometries. To overcome these limitations, Bradford (2008) used reflection tomography to obtain improved velocity estimates and GPR reflection images in areas with significant lateral heterogeneity. The intensive surveying required to collect data for reflection tomography, however, makes the approach challenging to implement at the short time scales associated with the dynamics of individual soil hydrologic events, such as infiltration in response to rainfall.…”

Section: A R Mangel Et Al: Multi-offset Ground-penetrating Radar Imentioning

confidence: 99%

Multi-offset ground-penetrating radar imaging of a lab-scale infiltration test

Mangel

Moysey

Ryan

et al. 2012

Hydrol. Earth Syst. Sci.

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Abstract.A lab scale infiltration experiment was conducted in a sand tank to evaluate the use of time-lapse multi-offset ground-penetrating radar (GPR) data for monitoring dynamic hydrologic events in the vadose zone. Sets of 21 GPR traces at offsets between 0.44-0.9 m were recorded every 30 s during a 3 h infiltration experiment to produce a data cube that can be viewed as multi-offset gathers at unique times or common offset images, tracking changes in arrivals through time. Specifically, we investigated whether this data can be used to estimate changes in average soil water content during wetting and drying and to track the migration of the wetting front during an infiltration event. For the first problem we found that normal-moveout (NMO) analysis of the GPR reflection from the bottom of the sand layer provided water content estimates ranging between 0.10-0.30 volumetric water content, which underestimated the value determined by depth averaging a vertical array of six moisture probes by 0.03-0.05 volumetric water content. Relative errors in the estimated depth to the bottom of the 0.6 m thick sand layer were typically on the order of 2 %, though increased as high as 25 % as the wetting front approached the bottom of the tank. NMO analysis of the wetting front reflection during the infiltration event generally underestimated the depth of the front with discrepancies between GPR and moisture probe estimates approaching 0.15 m. The analysis also resulted in underestimates of water content in the wetted zone on the order of 0.06 volumetric water content and a wetting front velocity equal to about half the rate inferred from the probe measurements. In a parallel modeling effort we found that HYDRUS-1D also underestimates the observed average tank water content determined from the probes by approximately 0.01-0.03 volumetric water content, despite the fact that the model was calibrated to the probe data. This error suggests that the assumed conceptual model of laterally uniform, onedimensional vertical flow in a homogenous material may not be fully appropriate for the experiment. Full-waveform modeling and subsequent NMO analysis of the simulated GPR response resulted in water content errors on the order of 0.01-0.03 volumetric water content, which are roughly 30-50 % of the discrepancy between GPR and probe results observed in the experiment. The model shows that interference between wave arrivals affects data interpretation and the estimation of traveltimes. This is an important source of error in the NMO analysis, but it does not fully account for the discrepancies between GPR and the moisture probes observed in the experiment. The remaining discrepancy may be related to conceptual errors underlying the GPR analysis, such as the assumption of uniform one-dimensional flow, a lack of a sharply defined wetting front in the experiment, and errors in the petrophysical model used to convert dielectric constant to water content.

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“…When analysing multioffset data along a profile, a 2D velocity distribution of the subsurface and, thus, the water distribution can be deduced. This technique has been used successfully to map water content in the subsurface (e.g., Greaves et al, 1996;Bradford, 2008). …”

Section: Multioffset Measurementsmentioning

confidence: 99%

Basics and Application of Ground-Penetrating Radar as a Tool for Monitoring Irrigation Process

Takahashi¹,

Igel²,

Preetz³

et al. 2012

Problems, Perspectives and Challenges of Agricultural Water Management

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Measuring Water Content Heterogeneity Using Multifold GPR with Reflection Tomography

Cited by 83 publications

References 31 publications

Estimating field-scale soil water dynamics at a heterogeneous site using multi-channel GPR

Estimating field-scale soil water dynamics at a heterogeneous site using multi-channel GPR

Multi-offset ground-penetrating radar imaging of a lab-scale infiltration test

Basics and Application of Ground-Penetrating Radar as a Tool for Monitoring Irrigation Process

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