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Your search keyword '"Vereecken, Harry"' showing total 35 results
Start Over Author "Vereecken, Harry" Journal water resources research
35 results on '"Vereecken, Harry"'

2. On Infiltration and Infiltration Characteristic Times

Author

Rahmati, Mehdi, primary, Latorre, Borja, additional, Moret‐Fernández, David, additional, Lassabatere, Laurent, additional, Talebian, Nima, additional, Miller, Dane, additional, Morbidelli, Renato, additional, Iovino, Massimo, additional, Bagarello, Vincenzo, additional, Neyshabouri, Mohammad Reza, additional, Zhao, Ying, additional, Vanderborght, Jan, additional, Weihermüller, Lutz, additional, Jaramillo, Rafael Angulo, additional, Or, Dani, additional, Th. van Genuchten, Martinus, additional, and Vereecken, Harry, additional

Published
2022
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4. Invigorating Hydrological Research Through Journal Publications

Author

Quinn, Nevil, primary, Blöschl, Günter, additional, Bárdossy, András, additional, Castellarin, Attilio, additional, Clark, Martyn, additional, Cudennec, Christophe, additional, Koutsoyiannis, Demetris, additional, Lall, Upmanu, additional, Lichner, Lubomir, additional, Parajka, Juraj, additional, Peters‐Lidard, Christa D., additional, Sander, Graham, additional, Savenije, Hubert, additional, Smettem, Keith, additional, Vereecken, Harry, additional, Viglione, Alberto, additional, Willems, Patrick, additional, Wood, Andy, additional, Woods, Ross, additional, Xu, Chong‐Yu, additional, and Zehe, Erwin, additional

Published
2020
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20. High resolution aquifer characterization using crosshole GPRfull‐waveform tomography: Comparison with direct‐push and tracer test data

Author

Gueting, Nils, Vienken, Thomas, Klotzsche, Anja, van der Kruk, Jan, Vanderborght, Jan, Caers, Jef, Vereecken, Harry, and Englert, Andreas

Abstract

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. Highly resolved tomographic images of the subsurface are obtained from GPR full‐waveform inversionLogistic regression is used to translate GPR electrical properties into hydrogeological faciesThe distribution of GPR facies explains the plume splitting observed in a tracer experiment

Published
2017
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26. In situ determination of surface relaxivities for unconsolidated sediments.

Author

Brox, Timothy I., Pohlmeier, Andreas, Galvosas, Petrik, Vereecken, Harry, and Duschl, Markus

Subjects
NUCLEAR magnetic resonance, POROUS materials, SEDIMENTS, GAS absorption & adsorption, PORE fluids
Abstract

NMR relaxometry has developed into a method for rapid pore-size determination of natural porous media. Nevertheless, it is prone to uncertainties because of unknown surface relaxivities which depend mainly on the chemical composition of the pore walls as well as on the interfacial dynamics of the pore fluid. The classical approach for the determination of surface relaxivities is the scaling of NMR relaxation times by surface to volume ratios measured by gas adsorption or mercury intrusion. However, it is preferable that a method for the determination of average pore sizes uses the same substance, water, as probe molecule for both relaxometry and surface to volume measurements. One should also ensure that in both experiments the dynamics of the probe molecule takes place on similar length scales, which are in the order of some microns. Therefore, we employed NMR diffusion measurements with different observation times using bipolar pulsed field gradients and applied them to unconsolidated sediments (two purified sands, two natural sands, and one soil). The evaluation by Mitra's short-time model for diffusion in restricted environments yielded information about the surface to volume ratios which is independent of relaxation mechanisms. We point out that methods based on NMR diffusometry yield pore dimensions and surface relaxivities consistent with a pore space as sampled by native pore fluids via the diffusion process. This opens a way to calibrate NMR relaxation measurements with other NMR techniques, providing information about the pore-size distribution of natural porous media directly from relaxometry. [ABSTRACT FROM AUTHOR]

Published
2015
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35. Assimilation of Groundwater Level and Soil Moisture Data in an Integrated Land Surface‐Subsurface Model for Southwestern Germany

Author

Ching Pui Hung, Bernd Schalge, Gabriele Baroni, Harry Vereecken, Harrie‐Jan Hendricks Franssen, Hung, Ching Pui, Schalge, Bernd, Baroni, Gabriele, Vereecken, Harry, and Hendricks Franssen, Harrie‐Jan

Subjects
data assimilation, fully coupled hydrological models, ddc:550, Water Science and Technology
Abstract

Integrated terrestrial system models predict the coupled water, energy and biogeochemical cycles. Simulations with these models are affected by uncertainties of model parameters, initial and boundary conditions, atmospheric forcings and the biophysical processes. Data assimilation (DA) can quantify and reduce the uncertainty. This has been tested intensively for single compartment models, but far less for integrated models with multiple compartments. We constructed a virtual reality (VR) with a coupled land surface-subsurface model under the Terrestrial Systems Modeling Platform, which mimics the Neckar catchment in southern Germany. Soil moisture and groundwater level (GWL) data extracted from the simulated VR are used as measurements to be assimilated with state-only/state-hydraulic parameter estimation. Soil moisture DA improves soil moisture characterization in the vertical profile and the neighboring grid cells, with a 40 ∼ 60% reduction of root mean square error (RMSE) over the observation points. In spite of a small ensemble size of 64 members, assimilating soil moisture data improved saturated hydraulic conductivity estimation around the measurement locations. The characterization of evapotranspiration and river discharge only show limited improvements (1% at observation points and less than 0.1% in RMSE at 3 selected gauge locations respectively). GWL DA not only improves the GWL characterization (76 ∼ 88% RMSE reduction at observation locations) but also soil moisture for some cases. In addition, a clear improvement in GWL characterization is observed up to 8 km from the observations, and updating the model states of the saturated zone only instead of the complete domain gives better performance.

Published
2022

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