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Browsing by Author "Wieprecht, Silke"

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    ItemOpen Access
    Bayesian calibration and validation of a large‐scale and time‐demanding sediment transport model
    (2020) Beckers, Felix; Heredia, Andrés; Noack, Markus; Nowak, Wolfgang; Wieprecht, Silke; Oladyshkin, Sergey
    This study suggests a stochastic Bayesian approach for calibrating and validating morphodynamic sediment transport models and for quantifying parametric uncertainties in order to alleviate limitations of conventional (manual, deterministic) calibration procedures. The applicability of our method is shown for a large‐scale (11.0 km) and time‐demanding (9.14 hr for the period 2002-2013) 2‐D morphodynamic sediment transport model of the Lower River Salzach and for three most sensitive input parameters (critical Shields parameter, grain roughness, and grain size distribution). Since Bayesian methods require a significant number of simulation runs, this work proposes to construct a surrogate model, here with the arbitrary polynomial chaos technique. The surrogate model is constructed from a limited set of runs (n=20) of the full complex sediment transport model. Then, Monte Carlo‐based techniques for Bayesian calibration are used with the surrogate model (105 realizations in 4 hr). The results demonstrate that following Bayesian principles and iterative Bayesian updating of the surrogate model (10 iterations) enables to identify the most probable ranges of the three calibration parameters. Model verification based on the maximum a posteriori parameter combination indicates that the surrogate model accurately replicates the morphodynamic behavior of the sediment transport model for both calibration (RMSE = 0.31 m) and validation (RMSE = 0.42 m). Furthermore, it is shown that the surrogate model is highly effective in lowering the total computational time for Bayesian calibration, validation, and uncertainty analysis. As a whole, this provides more realistic calibration and validation of morphodynamic sediment transport models with quantified uncertainty in less time compared to conventional calibration procedures.
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    Bayesian calibration points to misconceptions in three‐dimensional hydrodynamic reservoir modeling
    (2023) Schwindt, Sebastian; Callau Medrano, Sergio; Mouris, Kilian; Beckers, Felix; Haun, Stefan; Nowak, Wolfgang; Wieprecht, Silke; Oladyshkin, Sergey
    Three‐dimensional (3d) numerical models are state‐of‐the‐art for investigating complex hydrodynamic flow patterns in reservoirs and lakes. Such full‐complexity models are computationally demanding and their calibration is challenging regarding time, subjective decision‐making, and measurement data availability. In addition, physically unrealistic model assumptions or combinations of calibration parameters may remain undetected and lead to overfitting. In this study, we investigate if and how so‐called Bayesian calibration aids in characterizing faulty model setups driven by measurement data and calibration parameter combinations. Bayesian calibration builds on recent developments in machine learning and uses a Gaussian process emulator as a surrogate model, which runs considerably faster than a 3d numerical model. We Bayesian‐calibrate a Delft3D‐FLOW model of a pump‐storage reservoir as a function of the background horizontal eddy viscosity and diffusivity, and initial water temperature profile. We consider three scenarios with varying degrees of faulty assumptions and different uses of flow velocity and water temperature measurements. One of the scenarios forces completely unrealistic, rapid lake stratification and still yields similarly good calibration accuracy as more correct scenarios regarding global statistics, such as the root‐mean‐square error. An uncertainty assessment resulting from the Bayesian calibration indicates that the completely unrealistic scenario forces fast lake stratification through highly uncertain mixing‐related model parameters. Thus, Bayesian calibration describes the quality of calibration and correctness of model assumptions through geometric characteristics of posterior distributions. For instance, most likely calibration parameter values (posterior distribution maxima) at the calibration range limit or with widespread uncertainty characterize poor model assumptions and calibration.
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    Colmation: Unravelling physical interactions of surface and subsurface processes
    (Stuttgart : Universität Stuttgart, Institute for Modelling Hydraulic and Environmental Systems, 2024) Koca, Kaan; Haun, Stefan; Wieprecht, Silke; Noack, Markus
    Colmation, the infiltration and accumulation of fine sediment in gravel riverbeds, is a natural process in riverine ecosystems. However, when excessive amounts of fine sediments are transported into rivers due to human activities (e.g., intensive agriculture, mining), they can substantially clog the pores of the riverbed, reduce its hydraulic conductivity, usually leading to detrimental impacts on water quality and ecological health. Despite extensive research on colmation, considerable knowledge gaps exist regarding the spatio-temporal dynamics and interactions between near-bed and interstitial flow and processes governing colmation. This is mainly due to the lack of measurement methods that can be utilized at pore scale without disturbing the natural environment. To this end, we developed a novel smart sensor capable of monitoring and measuring sediment infiltration and deposition processes within the pores of the gravel bed. The developed sensor was compared to the industry standard gamma-ray computer tomography (Gamma CT), exhibiting good agreement across a range of infiltrating particle sizes, from sand to fine gravel. Flume experiments further demonstrated the reliability of the smart sensor in acquiring spatially-distributed information on sediment deposition dynamics at high temporal resolution and with reproducible results. While persistent technical malfunctions hindered the acquisition of interstitial flow measurements using an endoscopic PIV system, the developed sensor alone provides valuable insights into sediment accumulation processes, making it a promising tool for engineers, geomorphologists, and ecologists. A potential combination of our sensor with pore-scale velocity measurements and/or eddy-resolving simulations can be considered in the future to elucidate the interactions between local flow fields and progressive pore occlusion by fine sediments. In this respect, our contribution does not only fill a critical gap in our ability to non-destructively monitor sediment deposition process in the interstitial pore space, but also offers the potential for supporting development of more realistic, high-resolution numerical models, which are essential for understanding subsurface-surface interactions at larger scales and finally coming up with sustainable management strategies.
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    Combining field and laboratory measurements to determine the erosion risk of cohesive sediments best
    (2015) Noack, Markus; Gerbersdorf, Sabine Ulrike; Hillebrand, Gudrun; Wieprecht, Silke
    In contrast to non-cohesive sediments, the incipient motion of cohesive sediments is characterized by much more complex interactions between several sedimentary, biological, and chemical parameters. Thus, site-specific investigations are required to obtain information about the erosion stability of cohesive materials. This becomes even more relevant for contaminated sediments, stored in riverine sediments as a “burden of the past”, because of their remobilization potential during flood events. This article represents a twofold measuring strategy for the detection of erosion thresholds: an in situ device for determination of critical shear stresses in the field, and a laboratory approach where sediment cores are withdrawn and subsequently analyzed over depth. The combined measuring strategy was applied in the River Elbe and at selected sites of the catchment of the River Saale. The results show a great variety of erosion thresholds over depth, demonstrating the need to conduct vertical analyses, especially when addressing buried layers with contaminations. The latter is only possible in the laboratory but the in situ device revealed clear benefits in capturing the loose flocculent layer on top of the sediment that might be easily lost during sediment retrieval and transport. Consequently, it is ideal to combine both approaches for a comprehensive insight into sediment stability.
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    Comparison of local and global optimization methods for calibration of a 3D morphodynamic model of a curved channel
    (2020) Shoarinezhad, Vahid; Wieprecht, Silke; Haun, Stefan
    In curved channels, the flow characteristics, sediment transport mechanisms, and bed evolution are more complex than in straight channels, owing to the interaction between the centrifugal force and the pressure gradient, which results in the formation of secondary currents. Therefore, using an appropriate numerical model that considers this fully three-dimensional effect, and subsequently, the model calibration are substantial tasks for achieving reliable simulation results. The calibration of numerical models as a subjective approach can become challenging and highly time-consuming, especially for inexperienced modelers, due to dealing with a large number of input parameters with respect to hydraulics and sediment transport. Using optimization methods can notably facilitate and expedite the calibration procedure by reducing the user intervention, which results in a more objective selection of parameters. This study focuses on the application of four different optimization algorithms for calibration of a 3D morphodynamic numerical model of a curved channel. The performance of a local gradient-based method is compared with three global optimization algorithms in terms of accuracy and computational time (model runs). The outputs of the optimization methods demonstrate similar sets of calibrated parameters and almost the same degree of accuracy according to the achieved minimum of the objective function. Accordingly, the most efficient method concerning the number of model runs (i.e., local optimization method) is selected for further investigation by setting up additional numerical models using different sediment transport formulae and various discharge rates. The comparisons of bed topography changes in several longitudinal and cross-sections between the measured data and the results of the calibrated numerical models are presented. The outcomes show an acceptable degree of accuracy for the automatically calibrated models.
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    Einfluß des naturnahen Gewässerausbaus auf den Geschiebetransport
    (1993) Wieprecht, Silke; Kraus, Werner
    Nach einem naturnahen Ausbau des Unterlaufs der Weißach, einem Wildbach und Hauptzufluß des Tegernsees, lagerten sich beim Durchlauf einer Hochwasserwelle im Bereich eines Gefälleknicks große Geschiebemengen ab. In einem hydraulischen Modell mit beweglicher Sohle (Maßstab 1:20) wurden die vorhandenen Bedingungen und mögliche Verbesserungen zur Verhinderung von Auflandungen untersucht. Weiterhin wurden grundsätzliche Untersuchungen über den Einfluß von Sohleinbauten auf den Geschiebetransport und die Wassertiefen durchgeführt.
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    Enhancing hydrological model calibration through hybrid strategies in data‐scarce regions
    (2024) Anand, Vicky; Oinam, Bakimchandra; Wieprecht, Silke; Singh, Shailesh Kumar; Srinivasan, Raghavan
    Calibration of a hydrological model is a challenging task, especially in basins that are data scarce. With the incorporation of regional information and integration with satellite data, the parameters of hydrological models can be estimated for a basin with scant or no discharge records. The main objective of this study is to calibrate and validate a hydrological model based on a limited amount of in‐situ measured and remote sensing satellite datasets in a data‐sparse region. Multiple techniques were applied for the model calibration: (1) stage‐discharge curves using a spatial proximity approach, (2) Simplified Surface Energy Balance actual evapotranspiration, (3) river discharge using a physical similarity regionalization approach, and (4) a new hybrid approach by integrating remote sensing datasets along with field measured river bathymetry data to estimate the river discharge. To demonstrate the methodology, we employed the widely used Soil and Water Assessment Tool (SWAT) hydrological model in Manipur River Basin, India. The sensitivity, calibration, and validation of the SWAT model were carried out by using the Sequential Uncertainty Fitting Technique. During calibration, the coefficient of determination (R2) and the Kling Gupta Efficiency (KGE) were found to be in the range of 0.46-0.81 and 0.41-0.83, whereas during validation R2 and KGE were found to be in the range of 0.40-0.79 and 0.53-0.77 for the four different techniques. Among all the four techniques applied in this study, calibration based on (i) stage‐discharge curve using spatial proximity approach and (ii) new hybrid approach by integrating remote sensing datasets and river bathymetry were found as the better approaches as indicated by the statistical indices. The performance evaluation of the model through a new hybrid approach by integrating remote sensing and in‐situ measured datasets for rivers with narrow width represents a promising technique for use in a data sparse region.
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    Fuzzy map comparisons enable objective hydro‐morphodynamic model validation
    (2021) Negreiros, Beatriz; Schwindt, Sebastian; Haun, Stefan; Wieprecht, Silke
    Numerical modeling represents a state‐of‐the‐art technique to simulate hydro‐morphodynamic processes in river ecosystems. Numerical models are often validated based on observed topographic change in the form of pixel information on net erosion or deposition over a simulation period. When model validation is performed by a pixel‐by‐pixel comparison of exactly superimposed simulated and observed pixels, zero or negative correlation coefficients are often calculated, suggesting poor model performance. Thus, a pixel‐by‐pixel approach penalizes quantitative simulation errors, even if a model conceptually works well. To distinguish between reasonably well‐performing and non‐representative models, this study introduces and tests fuzzy map comparison methods. First, we use a fuzzy numerical map comparison to compensate for spatial offset errors in correlation analyses. Second, we add a level of fuzziness with a fuzzy kappa map comparison to additionally address quantitative inaccuracy in modeled topographic change by categorizing data. Sample datasets from a physical lab model and datasets from a 6.9 km long gravel-cobble bed river reach enable the verification of the relevance of fuzzy map comparison methods. The results indicate that a fuzzy numerical map comparison is a viable technique to compensate for model errors stemming from spatial offset. In addition, fuzzy kappa map comparisons are suitable for objectively expressing subjectively perceived correlation between two maps, provided that a small number of categories is used. The methods tested and the resulting spatially explicit comparison maps represent a significant opportunity to improve the evaluation and potential calibration of numerical models of river ecosystems in the future.
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    High spatio‐temporal resolution measurements of cohesive sediment erosion
    (2020) Beckers, Felix; Inskeep, Caleb; Haun, Stefan; Schmid, Gerhard; Wieprecht, Silke; Noack, Markus
    In this study, we present a novel approach to measure fundamental processes of cohesive sediment erosion. The experimental setup consists of a laboratory erosion flume (SETEG) and a photogrammetric method to detect sediment erosion (PHOTOSED). Detailed data are presented for three erosion experiments, which were conducted with a natural non‐cohesive/cohesive sediment mixture at increasing sediment depths (4, 8, 16 cm). In each experiment, the sediment was exposed to a set of incrementally increasing shear stresses and the erosion was measured dynamically, pixel‐based, and approximate to the process scale given the resolution of PHOTOSED. This enables us to distinguish between (i) individual emerging erosion spots caused by surface erosion and (ii) large holes torn open by detached aggregate chunks. Moreover, interrelated processes were observed, such as (iii) propagation of the erosion in the longitudinal and lateral direction leading to merging of disconnected erosion areas and (iv) progressive vertical erosion of already affected areas. By complementing the (bulk) erosion volume profiles with additional quantitative variables, which contain spatial information (erosion area, specific deepening, number of disconnected erosion areas), conclusions on the erosion behaviour (and the dominant processes) can be drawn without requiring qualitative information (such as visual observations). In addition, we provide figures indicating the spatio‐temporal erosion variability and the (bulk) erosion rates for selected time periods. We evaluate the variability by statistical quantities and show that significant erosion is mainly confined to only a few events during temporal progression, but then considerably exceeds the time‐averaged median of the erosion (factors between 7.0 and 16.0). Further, we point to uncertainties in using (bulk) erosion rates to assess cohesive sediment erosion and particularly the underlying processes. As a whole, the results emphasise the need to measure cohesive sediment erosion with high spatio‐temporal resolution to obtain reliable and robust information.
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    Influence of constructional elements on sediment transport
    (1994) Wieprecht, Silke; Bechteler, Wilhelm
    Efforts have recently been made to renaturalize the Weißach River which had previously been regulated in a schematic, monotonous manner. During the last flood period an aggradation of sediment occurred, which may provoke an overtopping of the dams. In a hydraulic model with movable bed (scale 1:20) the existing conditions and possible improvements were studied in order to prevent further aggradations. Furthermore, fundamental investigations were made with regard to the influence of constructional measures on sediment transport and water levels.
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    An interdisciplinary model chain quantifies the footprint of global change on reservoir sedimentation
    (2023) Mouris, Kilian; Schwindt, Sebastian; Pesci, María Herminia; Wieprecht, Silke; Haun, Stefan
    Global change alters hydro-climatic conditions, affects land use, and contributes to more frequent droughts and floods. Large artificial reservoirs may effectively alleviate hydro-climatic extremes, but their storage capacities are threatened by sedimentation processes, which in turn are exacerbated by land use change. Envisioning strategies for sustainable reservoir management requires interdisciplinary model chains to emulate key processes driving sedimentation under global change scenarios. Therefore, we introduce a model chain for the long-term prediction of complex three-dimensional (3d) reservoir sedimentation considering concurrent catchment, hydro-climatic, and land-use conditions. Applied to a mountainous Mediterranean catchment, the model chain predicts increased sediment production and decreased discharge for high and medium emission pathways. Increased winter precipitation, accompanied by a transition from snowfall to rainfall, is projected to aggravate reduced summer precipitation, emphasizing a growing need for reservoirs. Additionally, higher winter precipitation proliferates sediment production and reservoir sedimentation. Land use change can outweigh the increased reservoir sedimentation originating from hydro-climatic change, which highlights the significance of localized actions to reduce sediment production. Finally, a 3d hydro-morphodynamic model provides insights into interactions between global change and reservoir sedimentation with spatially explicit information on future sedimentation patterns facilitating the implementation of management strategies.
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    Interdisciplinary reservoir management : a tool for sustainable water resources management
    (2021) Daus, Milan; Koberger, Katharina; Koca, Kaan; Beckers, Felix; Encinas Fernández, Jorge; Weisbrod, Barbara; Dietrich, Daniel; Gerbersdorf, Sabine Ulrike; Glaser, Rüdiger; Haun, Stefan; Hofmann, Hilmar; Martin-Creuzburg, Dominik; Peeters, Frank; Wieprecht, Silke
    Reservoirs are a common way to store and retain water serving for a multitude of purposes like storage of drinking and irrigation water, recreation, flood protection, navigation, and hydropower production, and have been built since centuries. Today, few reservoirs serve only one purpose, which requires management of present demands and interests. Since each reservoir project will cause negative impacts alongside desired advantages both on a local, regional and global scale, it is even more urgent to develop a common management framework in an attempt to mitigate negative impacts, incorporate different demands and make them visible within the discourse in order to avoid conflicts from early on. The scientific publications on reservoirs are manifold, yet a comprehensive and integrative holistic tool about management of this infrastructure is not available. Therefore, a comprehensive and integrated conceptual tool was developed and proposed by the authors of this paper that can contribute to the sustainable management of existing reservoirs. The tool presented herein is based on the results from the interdisciplinary CHARM (CHAllenges of Reservoir Management) project as well as the condensed outcome of relevant literature to aid and enhance knowledge of reservoir management. The incorporated results are based on field, laboratory and empirical social research. The project CHARM focused on five different aspects related to existing reservoirs in southern Germany (Schwarzenbachtalsperre, Franconian Lake District), namely: sedimentation of reservoirs, biostabilisation of fine sediments, toxic cyanobacteria(l) (blooms), greenhouse gas emissions from reservoirs and social contestation, respectively consent. These five research foci contributed to the topics and setup of a conceptual tool, put together by the research consortium via delphi questioning, which can be found alongside this publication to provide insights for experts and laymen. Conceptualising and analysing the management in combination with quantitative and qualitative data in one descriptive tool presents a novelty for the case studies and area of research. The distribution within the scientific community and interested public will possibly make a positive contribution to the goal of sustainable water resources management in the future.
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    Introducing seasonal snow memory into the RUSLE
    (2022) Mouris, Kilian; Schwindt, Sebastian; Haun, Stefan; Morales Oreamuno, Maria Fernanda; Wieprecht, Silke
    Purpose: The sediment supply to rivers, lakes, and reservoirs has a great influence on hydro-morphological processes. For instance, long-term predictions of bathymetric change for modeling climate change scenarios require an objective calculation procedure of sediment load as a function of catchment characteristics and hydro-climatic parameters. Thus, the overarching objective of this study is to develop viable and objective sediment load assessment methods in data-sparse regions. Methods: This study uses the Revised Universal Soil Loss Equation (RUSLE) and the SEdiment Delivery Distributed (SEDD) model to predict soil erosion and sediment transport in data-sparse catchments. The novel algorithmic methods build on free datasets, such as satellite and reanalysis data. Novelty stems from the usage of freely available datasets and the introduction of a seasonal snow memory into the RUSLE. In particular, the methods account for non-erosive snowfall, its accumulation over months as a function of temperature, and erosive snowmelt months after the snow fell. Results: Model accuracy parameters in the form of Pearson’s r and Nash-Sutcliffe efficiency indicate that data interpolation with climate reanalysis and satellite imagery enables viable sediment load predictions in data-sparse regions. The accuracy of the model chain further improves when snow memory is added to the RUSLE. Non-erosivity of snowfall makes the most significant increase in model accuracy. Conclusion: The novel snow memory methods represent a major improvement for estimating suspended sediment loads with the empirical RUSLE. Thus, the influence of snow processes on soil erosion and sediment load should be considered in any analysis of mountainous catchments.
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    Model investigations into the influence of constructional elements on sediment transport
    (1994) Bechteler, Wilhelm; Vollmers, Hans-Joachim; Wieprecht, Silke
    Recently the attempt has been made to renaturalize the last section of the Weissach River before it flows into Lake Tegernsee. This part had been previously regulated in a schematic monotonous way. During the last flood period, an agglomeration of sediment has occurred, which may provoke an overtopping of the dams. In a hydraulic model with movable bed (scale 1:20) the existing conditions and possible improvements were studied in order to prevent agglomerations. Furthermore fundamental investigations were made about the influence of obstructions on sediment transport and water levels.
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    ItemOpen Access
    Model investigations into the influence of renaturalization on sediment transport
    (1994) Bechteler, Wilhelm; Vollmers, Hans-Joachim; Wieprecht, Silke
    Efforts have recently been made to renaturalize the Weißach River which had previously been regulated in a schematic, monotonous manner. During the last flood period an agglomeration of sediment occurred, which may provoke an overtopping of the dams. In a hydraulic model with movable bed (scale 1:20) the existing conditions and possible improvements were studied in order to prevent agglomerations. Furthermore, fundamental investigations were made with regard to the influence of constructional steps on sediment transport and water levels.
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    A multi‐parameter approach to quantify riverbed clogging and vertical hyporheic connectivity
    (2023) Negreiros, Beatriz; Aybar Galdos, Alcides; Seitz, Lydia; Noack, Markus; Schwindt, Sebastian; Wieprecht, Silke; Haun, Stefan
    Riverbed clogging is key to assessing vertical connectivity in the hyporheic zone and is often quantified using single-parameter or qualitative approaches. However, clogging is driven by multiple, interacting physical and bio-geochemical parameters, which do not allow for a conclusive assessment of hyporheic connectivity with single-parameter approaches. In addition, existing qualitative assessments lack transparency and repeatability. This study introduces a Multi-Parameter Approach to quantify Clogging and vertical hyporheic connectivity (MultiPAC), which builds on standardized measurements of physical (grain size characteristics, porosity, hydraulic conductivity) and bio-geochemical (interstitial dissolved oxygen) parameters. We apply MultiPAC at three gravel-bed rivers and show how the set of parameters provides a representative appreciation of physical riverbed clogging, thus quantifying vertical hyporheic connectivity. However, more parameters are required to fully characterize biological clogging. In addition, MultiPAC locates clogged layers in the hyporheic zone through multi-parameter vertical profiles over the riverbed depth. The discussion outlines the relevance of MultiPAC to guide field surveys.
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    Optimal exposure time in gamma-ray attenuation experiments for monitoring time-dependent densities
    (2022) Gonzalez-Nicolas, Ana; Bilgic, Deborah; Kröker, Ilja; Mayar, Assem; Trevisan, Luca; Steeb, Holger; Wieprecht, Silke; Nowak, Wolfgang
    Several environmental phenomena require monitoring time-dependent densities in porous media, e.g., clogging of river sediments, mineral dissolution/precipitation, or variably-saturated multiphase flow. Gamma-ray attenuation (GRA) can monitor time-dependent densities without being destructive or invasive under laboratory conditions. GRA sends gamma rays through a material, where they are attenuated by photoelectric absorption and then recorded by a photon detector. The attenuated intensity of the emerging beam relates to the density of the traversed material via Beer-Lambert’s law. An important parameter for designing time-variable GRA is the exposure time, the time the detector takes to gather and count photons before converting the recorded intensity to a density. Large exposure times capture the time evolution poorly (temporal raster error, inaccurate temporal discretization), while small exposure times yield imprecise intensity values (noise-related error, i.e. small signal-to-noise ratio). Together, these two make up the total error of observing time-dependent densities by GRA. Our goal is to provide an optimization framework for time-dependent GRA experiments with respect to exposure time and other key parameters, thus facilitating neater experimental data for improved process understanding. Experimentalists set, or iterate over, several experimental input parameters (e.g., Beer-Lambert parameters) and expectations on the yet unknown dynamics (e.g., mean and amplitude of density and characteristic time of density changes). We model the yet unknown dynamics as a random Gaussian Process to derive expressions for expected errors prior to the experiment as a function of key experimental parameters. Based on this, we provide an optimization framework that allows finding the optimal (minimal-total-error) setup and demonstrate its application on synthetic experiments.
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    Stability criteria for Bayesian calibration of reservoir sedimentation models
    (2023) Mouris, Kilian; Acuna Espinoza, Eduardo; Schwindt, Sebastian; Mohammadi, Farid; Haun, Stefan; Wieprecht, Silke; Oladyshkin, Sergey
    Modeling reservoir sedimentation is particularly challenging due to the simultaneous simulation of shallow shores, tributary deltas, and deep waters. The shallow upstream parts of reservoirs, where deltaic avulsion and erosion processes occur, compete with the validity of modeling assumptions used to simulate the deposition of fine sediments in deep waters. We investigate how complex numerical models can be calibrated to accurately predict reservoir sedimentation in the presence of competing model simplifications and identify the importance of calibration parameters for prioritization in measurement campaigns. This study applies Bayesian calibration, a supervised learning technique using surrogate-assisted Bayesian inversion with a Gaussian Process Emulator to calibrate a two-dimensional (2d) hydro-morphodynamic model for simulating sedimentation processes in a reservoir in Albania. Four calibration parameters were fitted to obtain the statistically best possible simulation of bed level changes between 2016 and 2019 through two differently constraining data scenarios. One scenario included measurements from the entire upstream half of the reservoir. Another scenario only included measurements in the geospatially valid range of the numerical model. Model accuracy parameters, Bayesian model evidence, and the variability of the four calibration parameters indicate that Bayesian calibration only converges toward physically meaningful parameter combinations when the calibration nodes are in the valid range of the numerical model. The Bayesian approach also allowed for a comparison of multiple parameters and found that the dry bulk density of the deposited sediments is the most important factor for calibration.
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    Using automatic model calibration for 3D morphological simulations : a case study of the Bodendorf reservoir flushing
    (2024) Shoarinezhad, Vahid; Olsen, Nils Reidar Bøe; Wieprecht, Silke; Haun, Stefan
    Reservoir sedimentation poses a significant challenge to water resource management. Improving the lifespan and productivity of reservoirs requires appropriate sediment management strategies, among which flushing operations have become more prevalent in practice. Numerical modeling offers a cost-effective approach to assessing the performance of different flushing operations. However, calibrating highly parametrized morphological models remains a complex task due to inherent uncertainties associated with sediment transport processes and model parameters. Traditional calibration methods require laborious manual adjustments and expert knowledge, hindering calibration accuracy and efficiency and becoming impractical when dealing with several uncertain parameters. A solution is to use optimization techniques that enable an objective evaluation of the model behavior by expediting the calibration procedure and reducing the issue of subjectivity. In this paper, we investigate bed level changes as a result of a flushing event in the Bodendorf reservoir in Austria by using a three-dimensional numerical model coupled with an optimization algorithm for automatic calibration. Three different sediment transport formulae (Meyer-Peter and Müller, van Rijn, and Wu) are employed and modified during the calibration, along with the roughness parameter, active layer thickness, volume fraction of sediments in bed, and the hiding-exposure parameter. The simulated bed levels compared to the measurements are assessed by several statistical metrics in different cross-sections. According to the goodness-of-fit indicators, the models using the formulae of van Rijn and Wu outperform the model calculated by the Meyer-Peter and Müller formula regarding bed patterns and the volume of flushed sediments.
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