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  • 1
    Online-Ressource
    Online-Ressource
    Elsevier BV ; 2017
    In:  Journal of Hydrology Vol. 545 ( 2017-02), p. 42-54
    In: Journal of Hydrology, Elsevier BV, Vol. 545 ( 2017-02), p. 42-54
    Materialart: Online-Ressource
    ISSN: 0022-1694
    Sprache: Englisch
    Verlag: Elsevier BV
    Publikationsdatum: 2017
    ZDB Id: 240687-1
    ZDB Id: 1473173-3
    SSG: 13
    SSG: 14
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 2
    In: Geosciences, MDPI AG, Vol. 10, No. 11 ( 2020-11-16), p. 462-
    Kurzfassung: Pumping and tracer tests are site-investigation techniques frequently used to determine hydraulic conductivity. Tomographic test layouts, in which multiple tests with different combinations of injection and observation wells are performed, gain a better insight into spatial variability. While hydraulic tomography has repeatedly been applied in the field, tracer tomography lags behind. In a previous publication, we presented a synthetic study to investigate whether the ensemble Kalman Filter (EnKF) or the Kalman Ensemble Generator (KEG) performs better in inverting hydraulic- and tracer-tomographic data. In this work, we develop an experimental method for solute-tracer tomography using fluorescein as a conservative tracer. We performed hydraulic- and tracer-tomographic tests at the Lauswiesen site in Germany. We analyzed transient drawdown and concentration data with the EnKF and steady-state hydraulic heads and mean tracer arrival times with the KEG, obtaining more stable results with the KEG at lower computational costs. The spatial distribution of the estimated hydraulic conductivity field agreed with earlier descriptions of the aquifer at the site. This study narrows the gap between numerical studies and field applications for aquifer characterization at high resolution, showing the potential of combining ensemble-Kalman filter based methods with data collected from hydraulic and solute-tracer tomographic experiments.
    Materialart: Online-Ressource
    ISSN: 2076-3263
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2020
    ZDB Id: 2655946-8
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 3
    Online-Ressource
    Online-Ressource
    Springer Science and Business Media LLC ; 2020
    In:  Stochastic Environmental Research and Risk Assessment Vol. 34, No. 11 ( 2020-11), p. 1813-1830
    In: Stochastic Environmental Research and Risk Assessment, Springer Science and Business Media LLC, Vol. 34, No. 11 ( 2020-11), p. 1813-1830
    Kurzfassung: Ensemble-based uncertainty quantification and global sensitivity analysis of environmental models requires generating large ensembles of parameter-sets. This can already be difficult when analyzing moderately complex models based on partial differential equations because many parameter combinations cause an implausible model behavior even though the individual parameters are within plausible ranges. In this work, we apply Gaussian Process Emulators (GPE) as surrogate models in a sampling scheme. In an active-training phase of the surrogate model, we target the behavioral boundary of the parameter space before sampling this behavioral part of the parameter space more evenly by passive sampling. Active learning increases the subsequent sampling efficiency, but its additional costs pay off only for a sufficiently large sample size. We exemplify our idea with a catchment-scale subsurface flow model with uncertain material properties, boundary conditions, and geometric descriptors of the geological structure. We then perform a global-sensitivity analysis of the resulting behavioral dataset using the active-subspace method, which requires approximating the local sensitivities of the target quantity with respect to all parameters at all sampled locations in parameter space. The Gaussian Process Emulator implicitly provides an analytical expression for this gradient, thus improving the accuracy of the active-subspace construction. When applying the GPE-based preselection, 70–90% of the samples were confirmed to be behavioral by running the full model, whereas only 0.5% of the samples were behavioral in standard Monte-Carlo sampling without preselection. The GPE method also provided local sensitivities at minimal additional costs.
    Materialart: Online-Ressource
    ISSN: 1436-3240 , 1436-3259
    Sprache: Englisch
    Verlag: Springer Science and Business Media LLC
    Publikationsdatum: 2020
    ZDB Id: 1481263-0
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  • 4
    Online-Ressource
    Online-Ressource
    Elsevier BV ; 2019
    In:  Computers & Geosciences Vol. 126 ( 2019-05), p. 62-72
    In: Computers & Geosciences, Elsevier BV, Vol. 126 ( 2019-05), p. 62-72
    Materialart: Online-Ressource
    ISSN: 0098-3004
    RVK:
    Sprache: Englisch
    Verlag: Elsevier BV
    Publikationsdatum: 2019
    ZDB Id: 1499977-8
    SSG: 16,13
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 5
    Online-Ressource
    Online-Ressource
    Copernicus GmbH ; 2020
    In:  Hydrology and Earth System Sciences Vol. 24, No. 9 ( 2020-09-21), p. 4567-4574
    In: Hydrology and Earth System Sciences, Copernicus GmbH, Vol. 24, No. 9 ( 2020-09-21), p. 4567-4574
    Kurzfassung: Abstract. In global sensitivity analysis and ensemble-based model calibration, it is essential to create a large enough sample of model simulations with different parameters that all yield plausible model results. This can be difficult if a priori plausible parameter combinations frequently yield non-behavioral model results. In a previous study (Erdal and Cirpka, 2019), we developed and tested a parameter-sampling scheme based on active-subspace decomposition. While in principle this scheme worked well, it still implied testing a substantial fraction of parameter combinations that ultimately had to be discarded because of implausible model results. This technical note presents an improved sampling scheme and illustrates its simplicity and efficiency by a small test case. The new sampling scheme can be tuned to either outperform the original implementation by improving the sampling efficiency while maintaining the accuracy of the result or by improving the accuracy of the result while maintaining the sampling efficiency.
    Materialart: Online-Ressource
    ISSN: 1607-7938
    Sprache: Englisch
    Verlag: Copernicus GmbH
    Publikationsdatum: 2020
    ZDB Id: 2100610-6
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  • 6
    In: Geosciences, MDPI AG, Vol. 10, No. 7 ( 2020-07-17), p. 276-
    Kurzfassung: We compare two ensemble Kalman-based methods to estimate the hydraulic conductivity field of an aquifer from data of hydraulic and tracer tomographic experiments: (i) the Ensemble Kalman Filter (EnKF) and (ii) the Kalman Ensemble Generator (KEG). We generated synthetic drawdown and tracer data by simulating two pumping tests, each followed by a tracer test. Parameter updating with the EnKF is performed using the full transient signal. For hydraulic data, we use the standard update scheme of the EnKF with damping, whereas for concentration data, we apply a restart scheme, in which solute transport is resimulated from time zero to the next measurement time after each parameter update. In the KEG, we iteratively assimilate all observations simultaneously, here inverting steady-state heads and mean tracer arrival times. The inversion with the dampened EnKF worked well for the transient pumping-tests, but less for the tracer tests. The KEG produced similar estimates of hydraulic conductivity but at significantly lower costs. We conclude that parameter estimation in well-defined hydraulic tests can be done very efficiently by iterative ensemble Kalman methods, and ambiguity between state and parameter updates can be completely avoided by assimilating temporal moments of concentration data rather than the time series themselves.
    Materialart: Online-Ressource
    ISSN: 2076-3263
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2020
    ZDB Id: 2655946-8
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  • 7
    In: Earth System Science Data, Copernicus GmbH, Vol. 13, No. 9 ( 2021-09-14), p. 4437-4464
    Kurzfassung: Abstract. Coupled numerical models, which simulate water and energy fluxes in the subsurface–land-surface–atmosphere system in a physically consistent way, are a prerequisite for the analysis and a better understanding of heat and matter exchange fluxes at compartmental boundaries and interdependencies of states across these boundaries. Complete state evolutions generated by such models may be regarded as a proxy of the real world, provided they are run at sufficiently high resolution and incorporate the most important processes. Such a simulated reality can be used to test hypotheses on the functioning of the coupled terrestrial system. Coupled simulation systems, however, face severe problems caused by the vastly different scales of the processes acting in and between the compartments of the terrestrial system, which also hinders comprehensive tests of their realism. We used the Terrestrial Systems Modeling Platform (TerrSysMP), which couples the meteorological Consortium for Small-scale Modeling (COSMO) model, the land-surface Community Land Model (CLM), and the subsurface ParFlow model, to generate a simulated catchment for a regional terrestrial system mimicking the Neckar catchment in southwest Germany, the virtual Neckar catchment. Simulations for this catchment are made for the period 2007–2015 and at a spatial resolution of 400 m for the land surface and subsurface and 1.1 km for the atmosphere. Among a discussion of modeling challenges, the model performance is evaluated based on observations covering several variables of the water cycle. We find that the simulated catchment behaves in many aspects quite close to observations of the real Neckar catchment, e.g., concerning atmospheric boundary-layer height, precipitation, and runoff. But also discrepancies become apparent, both in the ability of the model to correctly simulate some processes which still need improvement, such as overland flow, and in the realism of some observation operators like the satellite-based soil moisture sensors. The whole raw dataset is available for interested users. The dataset described here is available via the CERA database (Schalge et al., 2020): https://doi.org/10.26050/WDCC/Neckar_VCS_v1.
    Materialart: Online-Ressource
    ISSN: 1866-3516
    Sprache: Englisch
    Verlag: Copernicus GmbH
    Publikationsdatum: 2021
    ZDB Id: 2475469-9
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  • 8
    Online-Ressource
    Online-Ressource
    Copernicus GmbH ; 2019
    In:  Hydrology and Earth System Sciences Vol. 23, No. 9 ( 2019-09-18), p. 3787-3805
    In: Hydrology and Earth System Sciences, Copernicus GmbH, Vol. 23, No. 9 ( 2019-09-18), p. 3787-3805
    Kurzfassung: Abstract. Integrated hydrological modeling of domains with complex subsurface features requires many highly uncertain parameters. Performing a global uncertainty analysis using an ensemble of model runs can help bring clarity as to which of these parameters really influence system behavior and for which high parameter uncertainty does not result in similarly high uncertainty of model predictions. However, already creating a sufficiently large ensemble of model simulation for the global sensitivity analysis can be challenging, as many combinations of model parameters can lead to unrealistic model behavior. In this work we use the method of active subspaces to perform a global sensitivity analysis. While building up the ensemble, we use the already-existing ensemble members to construct low-order meta-models based on the first two active-subspace dimensions. The meta-models are used to pre-determine whether a random parameter combination in the stochastic sampling is likely to result in unrealistic behavior so that such a parameter combination is excluded without running the computationally expensive full model. An important reason for choosing the active-subspace method is that both the activity score of the global sensitivity analysis and the meta-models can easily be understood and visualized. We test the approach on a subsurface-flow model including uncertain hydraulic parameters, uncertain boundary conditions and uncertain geological structure. We show that sufficiently detailed active subspaces exist for most observations of interest. The pre-selection by the meta-model significantly reduces the number of full-model runs that must be rejected due to unrealistic behavior. An essential but difficult part in active-subspace sampling using complex models is approximating the gradient of the simulated observation with respect to all parameters. We show that this can effectively and meaningfully be done with second-order polynomials.
    Materialart: Online-Ressource
    ISSN: 1607-7938
    Sprache: Englisch
    Verlag: Copernicus GmbH
    Publikationsdatum: 2019
    ZDB Id: 2100610-6
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  • 9
    Online-Ressource
    Online-Ressource
    Frontiers Media SA ; 2020
    In:  Frontiers in Earth Science Vol. 8 ( 2020-11-16)
    In: Frontiers in Earth Science, Frontiers Media SA, Vol. 8 ( 2020-11-16)
    Kurzfassung: Surface-water divides can be delineated by analyzing digital elevation models. They might, however, significantly differ from groundwater divides because the groundwater surface does not necessarily follow the surface topography. Thus, in order to delineate a groundwater divide, hydraulic-head measurements are needed. Because installing piezometers is cost- and labor-intensive, it is vital to optimize their placement. In this work, we introduce an optimal design analysis that can identify the best spatial configuration of piezometers. The method is based on formal minimization of the expected posterior uncertainty in localizing the groundwater divide. It is based on the preposterior data impact assessor, a Bayesian framework that uses a random sample of models (here: steady-state groundwater flow models) in a fully non-linear analysis. For each realization, we compute virtual hydraulic-head measurements at all potential well installation points and delineate the groundwater divide by particle tracking. Then, for each set of virtual measurements and their possible measurement values, we assess the uncertainty of the groundwater-divide location after Bayesian updating, and finally marginalize over all possible measurement values. We test the method mimicking an aquifer in South-West Germany. Previous works in this aquifer indicated a groundwater divide that substantially differs from the surface-water divide. Our analysis shows that the uncertainty in the localization of the groundwater divide can be reduced with each additional monitoring well. In our case study, the optimal configuration of three monitoring points involves the first well being close to the topographic surface water divide, the second one on the hillslope toward the valley, and the third one in between.
    Materialart: Online-Ressource
    ISSN: 2296-6463
    Sprache: Unbekannt
    Verlag: Frontiers Media SA
    Publikationsdatum: 2020
    ZDB Id: 2741235-0
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