Articles | Volume 20, issue 5
https://doi.org/10.5194/hess-20-1925-2016
https://doi.org/10.5194/hess-20-1925-2016
Research article
 | 
13 May 2016
Research article |  | 13 May 2016

Testing alternative uses of electromagnetic data to reduce the prediction error of groundwater models

Nikolaj Kruse Christensen, Steen Christensen, and Ty Paul A. Ferre

Related authors

Voxel inversion of airborne electromagnetic data for improved groundwater model construction and prediction accuracy
Nikolaj Kruse Christensen, Ty Paul A. Ferre, Gianluca Fiandaca, and Steen Christensen
Hydrol. Earth Syst. Sci., 21, 1321–1337, https://doi.org/10.5194/hess-21-1321-2017,https://doi.org/10.5194/hess-21-1321-2017, 2017
Short summary

Related subject area

Subject: Groundwater hydrology | Techniques and Approaches: Uncertainty analysis
Data-driven estimates for the geostatistical characterization of subsurface hydraulic properties
Falk Heße, Sebastian Müller, and Sabine Attinger
Hydrol. Earth Syst. Sci., 28, 357–374, https://doi.org/10.5194/hess-28-357-2024,https://doi.org/10.5194/hess-28-357-2024, 2024
Short summary
Hierarchical sensitivity analysis for a large-scale process-based hydrological model applied to an Amazonian watershed
Haifan Liu, Heng Dai, Jie Niu, Bill X. Hu, Dongwei Gui, Han Qiu, Ming Ye, Xingyuan Chen, Chuanhao Wu, Jin Zhang, and William Riley
Hydrol. Earth Syst. Sci., 24, 4971–4996, https://doi.org/10.5194/hess-24-4971-2020,https://doi.org/10.5194/hess-24-4971-2020, 2020
Short summary
Interpretation of multi-scale permeability data through an information theory perspective
Aronne Dell'Oca, Alberto Guadagnini, and Monica Riva
Hydrol. Earth Syst. Sci., 24, 3097–3109, https://doi.org/10.5194/hess-24-3097-2020,https://doi.org/10.5194/hess-24-3097-2020, 2020
Short summary
Spatially distributed sensitivity of simulated global groundwater heads and flows to hydraulic conductivity, groundwater recharge, and surface water body parameterization
Robert Reinecke, Laura Foglia, Steffen Mehl, Jonathan D. Herman, Alexander Wachholz, Tim Trautmann, and Petra Döll
Hydrol. Earth Syst. Sci., 23, 4561–4582, https://doi.org/10.5194/hess-23-4561-2019,https://doi.org/10.5194/hess-23-4561-2019, 2019
Short summary
Multi-model approach to quantify groundwater-level prediction uncertainty using an ensemble of global climate models and multiple abstraction scenarios
Syed M. Touhidul Mustafa, M. Moudud Hasan, Ajoy Kumar Saha, Rahena Parvin Rannu, Els Van Uytven, Patrick Willems, and Marijke Huysmans
Hydrol. Earth Syst. Sci., 23, 2279–2303, https://doi.org/10.5194/hess-23-2279-2019,https://doi.org/10.5194/hess-23-2279-2019, 2019
Short summary

Cited articles

Abraham, J. D., Cannia, J. C., Bedrosian, P. A., Johnson, M. R., Ball, L. B., and Sibray, S. S.: Airborne Electromagnetic Mapping of the Base of Aquifer in Areas of Western Nebraska, in: US Geol. Surv. Sci. Investig. Rep. 2011–5219. http://pubs.usgs.gov/sir/2011/5219/ (last access: 4 January 2016), 2012.
Archie, G. E.: The Electrical Resistivity Log as an Aid in Determining Some Reservoir Characteristics, Trans. AIME, 146, 54–62, https://doi.org/10.2118/942054-G, 1942.
Árnason, K.: Consistent Discretization of Electromagnetic Fields and Transient Modeling, in: Geophysical Developments Series, edited by: Oristaglio, M. and Spies, B., Society of Exploration Geophysicists, 103–118, 1999.
Auken, E., Jørgensen, F., and Sørensen, K. I.: Large-scale TEM investigation for groundwater, Explor. Geophys., 34, 188–194, https://doi.org/10.1071/EG03188, 2003.
Auken, E., Christiansen, A. V., Westergaard, H. J., Kirkegaard, C., Foged, N., and Viezzoli, A.: An integrated processing scheme for high-resolution airborne electromagnetic surveys, the SkyTEM system, Explor. Geophys., 40, 184–192, https://doi.org/10.1071/EG08128, 2009.
Download
Short summary
Our primary objective in this study is to provide a virtual environment that allows users to determine the value of geophysical data and, furthermore, to investigate how best to use those data to develop groundwater models and to reduce their prediction errors. When this has been carried through for alternative data sampling, parameterization and inversion approaches, the best alternative can be chosen by comparison of prediction results between the alternatives.