Browsing by Author "Haun, Stefan"

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Open Access
Advanced methods for a sustainable sediment management of reservoirs
(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2022) Haun, Stefan; Wieprecht, Silke (Prof. Dr.-Ing.)
As a result of an increasing demand on storing water, sustainable reservoir management will become more and more important in the future. Minimizing, or in the best case avoiding, the loss of storage due to sedimentation is a challenging task because each reservoir has unique boundary conditions. Hence, not every management strategy is suitable for a given reservoir. Due to the combination of state of the art measurement methods and hydro‐morphodynamic models, reservoir sedimentation can be better predicted in the future and the success of sediment management strategies can be assessed. The development of advanced measurement methods makes it possible to obtain data with a high accuracy, but also with a high spatial and temporal resolution. The combination of recent measurement approaches with reliable hydro‐morphodynamic numerical prediction models, enhances a highly accurate prediction and understanding of governing processes. This opens new possibilities for an objective selection of important parameters, essential spatial domains as well as for the temporal resolution of measurements. This will finally lead to more reliable predictions about the future of reservoirs that provide water for human life, health and wealth. The presented scientific work gives an overview of recent developments to investigate hydromorphological processes in reservoirs.
Open Access
Advanced methods to investigate hydro‐morphological processes in open‐water environments
(2021) Haun, Stefan; Dietrich, Stephan
Hydro‐morphology describes the interactions between water and sediments in fluvial systems and the corresponding processes across all spatial and temporal scales. The results are natural and anthropogenically influenced bed structures and fluvial landforms. However, many of these hydro‐morphological processes cannot be described analytically yet, as a result of their stochastic behaviour and the multitude of processes involved across spatial and temporal scales. Deeper knowledge of these processes is essential, not only for understanding the system itself, but also for practical applications, which rely on correct and reliable investigations of these processes. During the European Geoscience Union (EGU) General Assembly (GA) 2018 in Vienna, Austria, the conveners of the session on “Measurements, monitoring and numerical modelling of sedimentary and hydro‐morphological processes in open‐water environments” had the idea of initiating a special issue, containing a collection of recent achievements in this research field. The aim of this extended introduction is twofold. First, an overview on research needs in investigating hydro‐morphological processes in open‐water environments is given in this article. Second, recently published studies that aim to improve the understanding of hydro‐morphological processes in rivers, lakes and reservoirs by innovative measurement approaches are discussed. In addition to submitted papers collected from the EGU GA in 2017, 2018 and 2019, related studies published in Earth Surface Processes and Landforms (ESPL) over the last two years are also incorporated into this special issue. The papers selected cover a wide range of studies with differing spatial and temporal resolutions. This broad spectrum of different scales clearly indicates the challenges associated with the development and use of advanced methods for investigating hydro‐morphological processes in open‐water environments.
Open Access
Assessment of uncertainties in a complex modeling chain for predicting reservoir sedimentation under changing climate
(2023) Pesci, María Herminia; Mouris, Kilian; Haun, Stefan; Förster, Kristian
Long-term predictions of reservoir sedimentation require an objective consideration of the preceding catchment processes. In this study, we apply a complex modeling chain to predict sedimentation processes in the Banja reservoir (Albania). The modeling chain consists of the water balance model WaSiM, the soil erosion and sediment transport model combination RUSLE-SEDD, and the 3d hydro-morphodynamic reservoir model SSIIM2 to accurately represent all relevant physical processes. Furthermore, an ensemble of climate models is used to analyze future scenarios. Although the capabilities of each model enable us to obtain satisfying results, the propagation of uncertainties in the modeling chain cannot be neglected. Hence, approximate model parameter uncertainties are quantified with the First-Order Second-Moment (FOSM) method. Another source of uncertainty for long-term predictions is the spread of climate projections. Thus, we compared both sources of uncertainties and found that the uncertainties generated by climate projections are 408% (for runoff), 539% (for sediment yield), and 272% (for bed elevation in the reservoir) larger than the model parameter uncertainties. We conclude that (i) FOSM is a suitable method for quantifying approximate parameter uncertainties in a complex modeling chain, (ii) the model parameter uncertainties are smaller than the spread of climate projections, and (iii) these uncertainties are of the same order of magnitude as the change signal for the investigated low-emission scenario. Thus, the proposed method might support modelers to communicate different sources of uncertainty in complex modeling chains, including climate impact models.
Open Access
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.
Open Access
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.
Open Access
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.
Open Access
Controlled reservoir drawdown : challenges for sediment management and integrative monitoring : an Austrian case study : part B: local scale
(2020) Hauer, Christoph; Holzapfel, Patrick; Flödl, Peter; Wagner, Beatrice; Graf, Wolfram; Leitner, Patrick; Haimann, Marlene; Holzer, Georg; Haun, Stefan; Habersack, Helmut; Schletterer, Martin
The present case study deals with a controlled drawdown beyond the operational level of the Gepatsch reservoir (Austria). Based on the awareness of potential ecological consequences, an advanced set of measures was conducted and an integrative monitoring design was implemented. This pre- and post-event monitoring included measurements regarding the cross sectional variability and habitat-related turbidity, freeze-core sampling to obtain knowledge on fine sediment infiltration and an evaluation of the macroinvertebrate communities as well as fish egg development (salmonid incubation). The results of the sedimentological as well as biological investigations show a negligible impact on the downstream located aquatic system due to the controlled drawdown of the Gepatsch reservoir. In addition, recommendations based on the findings from this study regarding possible methods for local scale monitoring can be given.
Open Access
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.
Open Access
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.
Open Access
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.
Open Access
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.
Open Access
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.
Open Access
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.
Open Access
Numerical study of discharge adjustment effects on reservoir morphodynamics and flushing efficiency : an outlook for the Unazuki Reservoir, Japan
(2021) Esmaeili, Taymaz; Sumi, Tetsuya; Kantoush, Sameh; Kubota, Yoji; Haun, Stefan; Rüther, Nils
The Unazuki Reservoir is located on the Kurobe River, which is influenced by a catchment with one of the highest sediment yields in Japan. Due to a sufficiently available discharge during flood events, annual sediment flushing with full water-level drawdown (i.e., free-flow sediment flushing) is conducted to preserve the effective storage capacity of the reservoir. Nevertheless, the upstream half of the reservoir (i.e., study segment) suffers from the excessive deposition of coarser sediments. Remobilization of these coarser materials and their transportation further downstream of the reservoir is a priority of reservoir owners for sustainable reservoir functions, such as flood-risk management and hydroelectric energy generation. In this paper, an already conducted sediment-flushing operation in the Unazuki Reservoir is simulated, and its effects on sediment scouring from the study segment of the reservoir together with changes in bed morphodynamics are presented. A fully 3D numerical model using the finite volume approach in combination with a wetting/drying algorithm was utilized to reproduce the hydrodynamics and bed changes using the available onsite data. Afterwards, the effects of discharge adjustment on the morphological bed changes and flushing efficiency were analysed in the study segment using an additional single-discharge pulse supplied from upstream reservoirs. Simulation results showed that an approximately 75% increase in the average discharge during the free-flow stage changed the dominant morphological process from deposition into an erosive mode in the study segment. If the increase in discharge reaches up to 100%, the flushed volume of sediments from the target segment can increase 2.9 times compared with the initiation of the erosive mode.
Open Access
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.
Open Access
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.