This title appears in the Scientific Report :
2017
Please use the identifier:
http://dx.doi.org/10.1002/2016WR019498 in citations.
Please use the identifier: http://hdl.handle.net/2128/16111 in citations.
High resolution aquifer characterization using crosshole GPR full-waveform tomography: Comparison with direct-push and tracer test data
High resolution aquifer characterization using crosshole GPR full-waveform tomography: Comparison with direct-push and tracer test data
Limited knowledge about the spatial distribution of aquifer properties typically constrains our ability to predict subsurface flow and transport. Here we investigate the value of using high resolution full-waveform inversion of cross-borehole ground penetrating radar (GPR) data for aquifer character...
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Personal Name(s): | Gueting, Nils (Corresponding author) |
---|---|
Vienken, Thomas / Klotzsche, Anja / van der Kruk, Jan / Vanderborght, Jan / Caers, Jef / Vereecken, Harry / Englert, Andreas | |
Contributing Institute: |
Agrosphäre; IBG-3 |
Published in: | Water resources research, 53 (2017) 1, S. 49–72 |
Imprint: |
[New York]
Wiley
2017
|
DOI: |
10.1002/2016WR019498 |
Document Type: |
Journal Article |
Research Program: |
Terrestrial Systems: From Observation to Prediction |
Link: |
OpenAccess OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://hdl.handle.net/2128/16111 in citations.
Limited knowledge about the spatial distribution of aquifer properties typically constrains our ability to predict subsurface flow and transport. Here we investigate the value of using high resolution full-waveform inversion of cross-borehole ground penetrating radar (GPR) data for aquifer characterization. By stitching together GPR tomograms from multiple adjacent crosshole planes, we are able to image, with a decimeter scale resolution, the dielectric permittivity and electrical conductivity of an alluvial aquifer along cross sections of 50 m length and 10 m depth. A logistic regression model is employed to predict the spatial distribution of lithological facies on the basis of the GPR results. Vertical profiles of porosity and hydraulic conductivity from direct-push, flowmeter and grain size data suggest that the GPR predicted facies classification is meaningful with regard to porosity and hydraulic conductivity, even though the distributions of individual facies show some overlap and the absolute hydraulic conductivities from the different methods (direct-push, flowmeter, grain size) differ up to approximately one order of magnitude. Comparison of the GPR predicted facies architecture with tracer test data suggests that the plume splitting observed in a tracer experiment was caused by a hydraulically low-conductive sand layer with a thickness of only a few decimeters. Because this sand layer is identified by GPR full-waveform inversion but not by conventional GPR ray-based inversion we conclude that the improvement in spatial resolution due to full-waveform inversion is crucial to detect small-scale aquifer structures that are highly relevant for solute transport. |