Articles | Volume 23, issue 1
https://doi.org/10.5194/hess-23-171-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-171-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Jan 2019
Research article |
| 15 Jan 2019
| 15 Jan 2019
Influence of input and parameter uncertainty on the prediction of catchment-scale groundwater travel time distributions
Department of Computational Hydrosystems, UFZ – Helmholtz Centre
for Environmental Research, Permoserstr. 15, 04318 Leipzig, Germany
Institute of Geosciences, Friedrich Schiller University Jena,
Burgweg 11, 07749 Jena, Germany
Falk Heße
CORRESPONDING AUTHOR
Department of Computational Hydrosystems, UFZ – Helmholtz Centre
for Environmental Research, Permoserstr. 15, 04318 Leipzig, Germany
Rohini Kumar
Department of Computational Hydrosystems, UFZ – Helmholtz Centre
for Environmental Research, Permoserstr. 15, 04318 Leipzig, Germany
Olaf Kolditz
Department of Environmental
Informatics, UFZ – Helmholtz Centre for Environmental Research, Permoserstr.
15, 04318 Leipzig, Germany
Applied Environmental Systems Analysis,
Technische Universität Dresden, Dresden, Germany
Thomas Kalbacher
Department of Environmental
Informatics, UFZ – Helmholtz Centre for Environmental Research, Permoserstr.
15, 04318 Leipzig, Germany
Sabine Attinger
Department of Computational Hydrosystems, UFZ – Helmholtz Centre
for Environmental Research, Permoserstr. 15, 04318 Leipzig, Germany
Institute of
Earth and Environmental Sciences, University of Potsdam, Karl-Liebknecht-Str.
24–25, 14476 Potsdam, Germany
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This study shows quantitative and temporal offsets between nitrogen input and riverine output, using time series of three nested catchments in central Germany. The riverine concentrations show lagged reactions to the input, but at the same time exhibit strong inter-annual changes in the relationship between riverine discharge and concentration. The study found a strong retention of nitrogen that is dominantly assigned to a hydrological N legacy, which will affect future stream concentrations.
Stephan Thober, Matthias Cuntz, Matthias Kelbling, Rohini Kumar, Juliane Mai, and Luis Samaniego
Geosci. Model Dev., 12, 2501–2521, https://doi.org/10.5194/gmd-12-2501-2019, https://doi.org/10.5194/gmd-12-2501-2019, 2019
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We present a model that aggregates simulated runoff along a river
(i.e. a routing model). The unique feature of the model is that it
can be run at multiple resolutions without any modifications to the
input data. The model internally (dis-)aggregates all input data to
the resolution given by the user. The model performance does not
depend on the chosen resolution. This allows efficient model
calibration at coarse resolution and subsequent model application at
fine resolution.
Naoki Mizukami, Oldrich Rakovec, Andrew J. Newman, Martyn P. Clark, Andrew W. Wood, Hoshin V. Gupta, and Rohini Kumar
Hydrol. Earth Syst. Sci., 23, 2601–2614, https://doi.org/10.5194/hess-23-2601-2019, https://doi.org/10.5194/hess-23-2601-2019, 2019
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We find that Nash–Sutcliffe (NSE)-based model calibrations result in poor reproduction of high-flow events, such as the annual peak flows that are used for flood frequency estimation. The use of Kling–Gupta efficiency (KGE) results in annual peak flow estimates that are better than from NSE, with only a slight degradation in performance with respect to other related metrics.
Yoram Rubin, Ching-Fu Chang, Jiancong Chen, Karina Cucchi, Bradley Harken, Falk Heße, and Heather Savoy
Hydrol. Earth Syst. Sci., 22, 5675–5695, https://doi.org/10.5194/hess-22-5675-2018, https://doi.org/10.5194/hess-22-5675-2018, 2018
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This paper addresses questions related to the adoption of stochastic methods in hydrogeology, looking at factors such as environmental regulations, financial incentives, higher education, and the collective feedback loop involving these factors. We show that stochastic hydrogeology's blind spot is in focusing on risk while ignoring uncertainty, to the detriment of its potential clients. The imbalance between the treatments of risk and uncertainty is shown to be common to multiple disciplines.
Miao Jing, Falk Heße, Rohini Kumar, Wenqing Wang, Thomas Fischer, Marc Walther, Matthias Zink, Alraune Zech, Luis Samaniego, Olaf Kolditz, and Sabine Attinger
Geosci. Model Dev., 11, 1989–2007, https://doi.org/10.5194/gmd-11-1989-2018, https://doi.org/10.5194/gmd-11-1989-2018, 2018
Vimal Mishra, Reepal Shah, Syed Azhar, Harsh Shah, Parth Modi, and Rohini Kumar
Hydrol. Earth Syst. Sci., 22, 2269–2284, https://doi.org/10.5194/hess-22-2269-2018, https://doi.org/10.5194/hess-22-2269-2018, 2018
Andreas Marx, Rohini Kumar, Stephan Thober, Oldrich Rakovec, Niko Wanders, Matthias Zink, Eric F. Wood, Ming Pan, Justin Sheffield, and Luis Samaniego
Hydrol. Earth Syst. Sci., 22, 1017–1032, https://doi.org/10.5194/hess-22-1017-2018, https://doi.org/10.5194/hess-22-1017-2018, 2018
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Hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K). The multi-model ensemble results show that the change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean, while they increase in the Alpine and Northern regions. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. Adaptation should make use of change and uncertainty information.
Luis Samaniego, Rohini Kumar, Stephan Thober, Oldrich Rakovec, Matthias Zink, Niko Wanders, Stephanie Eisner, Hannes Müller Schmied, Edwin H. Sutanudjaja, Kirsten Warrach-Sagi, and Sabine Attinger
Hydrol. Earth Syst. Sci., 21, 4323–4346, https://doi.org/10.5194/hess-21-4323-2017, https://doi.org/10.5194/hess-21-4323-2017, 2017
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We inspect the state-of-the-art of several land surface (LSMs) and hydrologic models (HMs) and show that most do not have consistent and realistic parameter fields for land surface geophysical properties. We propose to use the multiscale parameter regionalization (MPR) technique to solve, at least partly, the scaling problem in LSMs/HMs. A general model protocol is presented to describe how MPR can be applied to a specific model.
Gabriele Baroni, Matthias Zink, Rohini Kumar, Luis Samaniego, and Sabine Attinger
Hydrol. Earth Syst. Sci., 21, 2301–2320, https://doi.org/10.5194/hess-21-2301-2017, https://doi.org/10.5194/hess-21-2301-2017, 2017
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Three methods are used to characterize the uncertainty in soil properties. The effect on simulated states and fluxes is quantified using a distributed hydrological model. Different impacts are identified as function of the perturbation method, of the model outputs and of the spatio-temporal resolution. The study underlines the importance of a proper characterization of the uncertainty in soil properties for a correct assessment of their role and further improvements in the model application.
Anne F. Van Loon, Rohini Kumar, and Vimal Mishra
Hydrol. Earth Syst. Sci., 21, 1947–1971, https://doi.org/10.5194/hess-21-1947-2017, https://doi.org/10.5194/hess-21-1947-2017, 2017
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Summer 2015 was extremely dry in Europe, hampering groundwater supply to irrigation and drinking water. For effective management, the groundwater situation should be monitored in real time, but data are not available. We tested two methods to estimate groundwater in near-real time, based on satellite data and using the relationship between rainfall and historic groundwater levels. The second method gave a good spatially variable representation of the 2015 groundwater drought in Europe.
Matthias Zink, Rohini Kumar, Matthias Cuntz, and Luis Samaniego
Hydrol. Earth Syst. Sci., 21, 1769–1790, https://doi.org/10.5194/hess-21-1769-2017, https://doi.org/10.5194/hess-21-1769-2017, 2017
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We discuss the estimation of a long-term, high-resolution, continuous and consistent dataset of hydro-meteorological variables for Germany. Here we describe the derivation of national-scale parameter sets and analyze the uncertainty of the estimated hydrologic variables (focusing on the parametric uncertainty). Our study highlights the role of accounting for the parametric uncertainty in model-derived hydrological datasets.
Falk Heße, Matthias Zink, Rohini Kumar, Luis Samaniego, and Sabine Attinger
Hydrol. Earth Syst. Sci., 21, 549–570, https://doi.org/10.5194/hess-21-549-2017, https://doi.org/10.5194/hess-21-549-2017, 2017
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Travel-time distributions are a comprehensive tool for the characterization of hydrological systems. In our study, we used data that were simulated by virtue of a well-established hydrological model. This gave us a very large yet realistic dataset, both in time and space, from which we could infer the relative impact of different factors on travel-time behavior. These were, in particular, meteorological (precipitation), land surface (land cover, leaf-area index) and subsurface (soil) properties.
Bernd Schalge, Jehan Rihani, Gabriele Baroni, Daniel Erdal, Gernot Geppert, Vincent Haefliger, Barbara Haese, Pablo Saavedra, Insa Neuweiler, Harrie-Jan Hendricks Franssen, Felix Ament, Sabine Attinger, Olaf A. Cirpka, Stefan Kollet, Harald Kunstmann, Harry Vereecken, and Clemens Simmer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-557, https://doi.org/10.5194/hess-2016-557, 2016
Manuscript not accepted for further review
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In this work we show how we used a coupled atmosphere-land surface-subsurface model at highest possible resolution to create a testbed for data assimilation. The model was able to capture all important processes and interactions between the compartments as well as showing realistic statistical behavior. This proves that using a model as a virtual truth is possible and it will enable us to develop data assimilation methods where states and parameters are updated across compartment.
Alraune Zech and Sabine Attinger
Hydrol. Earth Syst. Sci., 20, 1655–1667, https://doi.org/10.5194/hess-20-1655-2016, https://doi.org/10.5194/hess-20-1655-2016, 2016
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A new method is presented which allows interpreting pumping test in heterogeneous transmissivity fields. Based on radially dependent transmissivity, the effective well flow solution is derived for two cases: the ensemble mean of pumping tests and the drawdown at an individual heterogeneous transmissivity field. The analytical form of the solution allows inversely estimating the parameters of aquifer heterogeneity (mean, variance, and correlation length) from steady-state pumping test data.
Remko C. Nijzink, Luis Samaniego, Juliane Mai, Rohini Kumar, Stephan Thober, Matthias Zink, David Schäfer, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 20, 1151–1176, https://doi.org/10.5194/hess-20-1151-2016, https://doi.org/10.5194/hess-20-1151-2016, 2016
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The heterogeneity of landscapes in river basins strongly affects the hydrological response. In this study, the distributed mesoscale Hydrologic Model (mHM) was equipped with additional processes identified by landscapes within one modelling cell. Seven study catchments across Europe were selected to test the value of this additional sub-grid heterogeneity. In addition, the models were constrained based on expert knowledge. Generally, the modifications improved the representation of low flows.
Rohini Kumar, Jude L. Musuuza, Anne F. Van Loon, Adriaan J. Teuling, Roland Barthel, Jurriaan Ten Broek, Juliane Mai, Luis Samaniego, and Sabine Attinger
Hydrol. Earth Syst. Sci., 20, 1117–1131, https://doi.org/10.5194/hess-20-1117-2016, https://doi.org/10.5194/hess-20-1117-2016, 2016
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In a maiden attempt, we performed a multiscale evaluation of the widely used SPI to characterize local- and regional-scale groundwater (GW) droughts using observations at 2040 groundwater wells in Germany and the Netherlands. From this data-based exploratory analysis, we provide sufficient evidence regarding the inability of the SPI to characterize GW drought events, and stress the need for more GW observations and accounting for regional hydrogeological characteristics in GW drought monitoring.
T. Fischer, D. Naumov, S. Sattler, O. Kolditz, and M. Walther
Geosci. Model Dev., 8, 3681–3694, https://doi.org/10.5194/gmd-8-3681-2015, https://doi.org/10.5194/gmd-8-3681-2015, 2015
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We present a workflow to convert geological models into the open-source VTU format for usage in numerical simulation models. Tackling relevant scientific questions or engineering tasks often involves multidisciplinary approaches. Conversion workflows are needed between the diverse tools of the various disciplines. Our approach offers an open-source, platform-independent, robust, and comprehensible method that is potentially useful for a multitude of similar environmental studies.
W. He, C. Beyer, J. H. Fleckenstein, E. Jang, O. Kolditz, D. Naumov, and T. Kalbacher
Geosci. Model Dev., 8, 3333–3348, https://doi.org/10.5194/gmd-8-3333-2015, https://doi.org/10.5194/gmd-8-3333-2015, 2015
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This technical paper presents a new tool to simulate reactive transport processes in subsurface systems and which couples the open-source software packages OpenGeoSys and IPhreeqc. A flexible parallelization scheme was developed and implemented to enable an optimized allocation of computer resources. The performance tests of the coupling interface and parallelization scheme illustrate the promising efficiency of this generally valid approach to simulate reactive transport problems.
S. Gharari, M. Shafiei, M. Hrachowitz, R. Kumar, F. Fenicia, H. V. Gupta, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 18, 4861–4870, https://doi.org/10.5194/hess-18-4861-2014, https://doi.org/10.5194/hess-18-4861-2014, 2014
M. Bechmann, C. Schneider, A. Carminati, D. Vetterlein, S. Attinger, and A. Hildebrandt
Hydrol. Earth Syst. Sci., 18, 4189–4206, https://doi.org/10.5194/hess-18-4189-2014, https://doi.org/10.5194/hess-18-4189-2014, 2014
H. V. Gupta, C. Perrin, G. Blöschl, A. Montanari, R. Kumar, M. Clark, and V. Andréassian
Hydrol. Earth Syst. Sci., 18, 463–477, https://doi.org/10.5194/hess-18-463-2014, https://doi.org/10.5194/hess-18-463-2014, 2014
Related subject area
Subject: Groundwater hydrology | Techniques and Approaches: Uncertainty analysis
Data-driven estimates for the geostatistical characterization of subsurface hydraulic properties
Hierarchical sensitivity analysis for a large-scale process-based hydrological model applied to an Amazonian watershed
Interpretation of multi-scale permeability data through an information theory perspective
Spatially distributed sensitivity of simulated global groundwater heads and flows to hydraulic conductivity, groundwater recharge, and surface water body parameterization
Multi-model approach to quantify groundwater-level prediction uncertainty using an ensemble of global climate models and multiple abstraction scenarios
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
Testing alternative uses of electromagnetic data to reduce the prediction error of groundwater models
Groundwater flow processes and mixing in active volcanic systems: the case of Guadalajara (Mexico)
Analyses of uncertainties and scaling of groundwater level fluctuations
Analyzing the effects of geological and parameter uncertainty on prediction of groundwater head and travel time
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
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
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In this study, we have presented two different advances for the field of subsurface geostatistics. First, we present data of variogram functions from a variety of different locations around the world. Second, we present a series of geostatistical analyses aimed at examining some of the statistical properties of such variogram functions and their relationship to a number of widely used variogram model functions.
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.
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.
Nikolaj Kruse Christensen, Steen Christensen, and Ty Paul A. Ferre
Hydrol. Earth Syst. Sci., 20, 1925–1946, https://doi.org/10.5194/hess-20-1925-2016, https://doi.org/10.5194/hess-20-1925-2016, 2016
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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.
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
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.
We evaluated the uncertainty propagation from the inputs (forcings) and parameters to the...
