Articles | Volume 20, issue 5
https://doi.org/10.5194/hess-20-1925-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-1925-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
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
CORRESPONDING AUTHOR
Department of Geoscience, Aarhus University,
Aarhus, Denmark
Steen Christensen
Department of Geoscience, Aarhus University,
Aarhus, Denmark
Ty Paul A. Ferre
Department of Hydrology and Water Resources, University of
Arizona, Tucson, USA
Related authors
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
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This study presents a new method for coupling a 3-D geophysical model with a 3-D groundwater model for improved groundwater model construction and prediction accuracy. The hydrological data consist of 35 hydraulic head measurements and one river discharge measurement, while the geophysical data set consists of 6300 measurement positions. The results demonstrate that the geophysical inversion strategy significantly affects the construction and prediction capability of the groundwater model.
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This study presents a new method for coupling a 3-D geophysical model with a 3-D groundwater model for improved groundwater model construction and prediction accuracy. The hydrological data consist of 35 hydraulic head measurements and one river discharge measurement, while the geophysical data set consists of 6300 measurement positions. The results demonstrate that the geophysical inversion strategy significantly affects the construction and prediction capability of the groundwater model.
Related subject area
Subject: Groundwater hydrology | Techniques and Approaches: Uncertainty analysis
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Multi-model approach to quantify groundwater-level prediction uncertainty using an ensemble of global climate models and multiple abstraction scenarios
Influence of input and parameter uncertainty on the prediction of catchment-scale groundwater travel time distributions
Numerical modeling and sensitivity analysis of seawater intrusion in a dual-permeability coastal karst aquifer with conduit networks
On the efficiency of the hybrid and the exact second-order sampling formulations of the EnKF: a reality-inspired 3-D test case for estimating biodegradation rates of chlorinated hydrocarbons at the port of Rotterdam
Groundwater flow processes and mixing in active volcanic systems: the case of Guadalajara (Mexico)
Analyses of uncertainties and scaling of groundwater level fluctuations
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Interpolation of groundwater quality parameters with some values below the detection limit
An approach to identify urban groundwater recharge
Assessment of conceptual model uncertainty for the regional aquifer Pampa del Tamarugal – North Chile
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
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It is still challenging to apply the quantitative and comprehensive global sensitivity analysis method to complex large-scale process-based hydrological models because of variant uncertainty sources and high computational cost. This work developed a new tool and demonstrate its implementation to a pilot example for comprehensive global sensitivity analysis of large-scale hydrological modelling. This method is mathematically rigorous and can be applied to other large-scale hydrological models.
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
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Permeability of natural systems exhibits heterogeneous spatial variations linked with the size of the measurement support scale. As the latter becomes coarser, the system appearance is less heterogeneous. As such, sets of permeability data associated with differing support scales provide diverse amounts of information. In this contribution, we leverage information theory to quantify the information content of gas permeability datasets collected with four diverse measurement support scales.
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
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Recently, the first global groundwater models were developed to better understand surface-water–groundwater interactions and human water use impacts. However, the reliability of model outputs is limited by a lack of data as well as model assumptions required due to the necessarily coarse spatial resolution. In this study we present the first global maps of model sensitivity according to their parameterization and build a foundation to improve datasets, model design, and model understanding.
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
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This study evaluates the effect of conceptual hydro(geo)logical model (CHM) structure, climate change and groundwater abstraction on future groundwater-level prediction uncertainty. If the current groundwater abstraction trend continues, groundwater level is predicted to decline quickly. Groundwater abstraction in NW Bangladesh should decrease by 60 % to ensure sustainable use. Abstraction scenarios are the dominant uncertainty source, followed by CHM uncertainty and climate model uncertainty.
Miao Jing, Falk Heße, Rohini Kumar, Olaf Kolditz, Thomas Kalbacher, and Sabine Attinger
Hydrol. Earth Syst. Sci., 23, 171–190, https://doi.org/10.5194/hess-23-171-2019, https://doi.org/10.5194/hess-23-171-2019, 2019
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We evaluated the uncertainty propagation from the inputs (forcings) and parameters to the predictions of groundwater travel time distributions (TTDs) using a fully distributed numerical model (mHM-OGS) and the StorAge Selection (SAS) function. Through detailed numerical and analytical investigations, we emphasize the key role of recharge estimation in the reliable predictions of TTDs and the good interpretability of the SAS function.
Zexuan Xu, Bill X. Hu, and Ming Ye
Hydrol. Earth Syst. Sci., 22, 221–239, https://doi.org/10.5194/hess-22-221-2018, https://doi.org/10.5194/hess-22-221-2018, 2018
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This study helps hydrologists better understand the parameters in modeling seawater intrusion in a coastal karst aquifer. Local and global sensitivity studies are conducted to evaluate a density-dependent numerical model of seawater intrusion. The sensitivity analysis indicates that karst features are critical for seawater intrusion modeling, and the evaluation of hydraulic conductivity is biased in continuum SEAWAT model. Dispervisity is no longer important in the advection-dominated aquifer.
Mohamad E. Gharamti, Johan Valstar, Gijs Janssen, Annemieke Marsman, and Ibrahim Hoteit
Hydrol. Earth Syst. Sci., 20, 4561–4583, https://doi.org/10.5194/hess-20-4561-2016, https://doi.org/10.5194/hess-20-4561-2016, 2016
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The paper addresses the issue of sampling errors when using the ensemble Kalman filter, in particular its hybrid and second-order formulations. The presented work is aimed at estimating concentration and biodegradation rates of subsurface contaminants at the port of Rotterdam in the Netherlands. Overall, we found that accounting for both forecast and observation sampling errors in the joint data assimilation system helps recover more accurate state and parameter estimates.
A. Hernández-Antonio, J. Mahlknecht, C. Tamez-Meléndez, J. Ramos-Leal, A. Ramírez-Orozco, R. Parra, N. Ornelas-Soto, and C. J. Eastoe
Hydrol. Earth Syst. Sci., 19, 3937–3950, https://doi.org/10.5194/hess-19-3937-2015, https://doi.org/10.5194/hess-19-3937-2015, 2015
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A conceptual model of groundwater flow processes and mixing was developed using a combination of hydrogeochemistry, isotopes and multivariate analysis. The implementation to the case of Guadalajara showed that groundwater was classified into four groups: cold groundwater, hydrothermal water, polluted groundwater and mixed groundwater. A multivariate mixing model was used to calculate the proportion of different fluids in sampled well water. The result helps authorities in decision making.
X. Y. Liang and Y.-K. Zhang
Hydrol. Earth Syst. Sci., 19, 2971–2979, https://doi.org/10.5194/hess-19-2971-2015, https://doi.org/10.5194/hess-19-2971-2015, 2015
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The error or uncertainty in head, obtained with an analytical or numerical solution, at an early time is mainly caused by the random initial condition. The error reduces with time, later reaching a constant error. The constant error at a later time is mainly due to the effects of the uncertain source/sink. The error caused by the uncertain boundary is limited to a narrow zone. Temporal scaling of head exists in most parts of a low permeable aquifer, mainly caused by recharge fluctuation.
X. He, T. O. Sonnenborg, F. Jørgensen, A.-S. Høyer, R. R. Møller, and K. H. Jensen
Hydrol. Earth Syst. Sci., 17, 3245–3260, https://doi.org/10.5194/hess-17-3245-2013, https://doi.org/10.5194/hess-17-3245-2013, 2013
A. Bárdossy
Hydrol. Earth Syst. Sci., 15, 2763–2775, https://doi.org/10.5194/hess-15-2763-2011, https://doi.org/10.5194/hess-15-2763-2011, 2011
E. Vázquez-Suñé, J. Carrera, I. Tubau, X. Sánchez-Vila, and A. Soler
Hydrol. Earth Syst. Sci., 14, 2085–2097, https://doi.org/10.5194/hess-14-2085-2010, https://doi.org/10.5194/hess-14-2085-2010, 2010
R. Rojas, O. Batelaan, L. Feyen, and A. Dassargues
Hydrol. Earth Syst. Sci., 14, 171–192, https://doi.org/10.5194/hess-14-171-2010, https://doi.org/10.5194/hess-14-171-2010, 2010
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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.
Our primary objective in this study is to provide a virtual environment that allows users to...
