Calibration of river hydrodynamic models: Analysis from the dynamic component in roughness coefficients

Ferreira, Danieli Mara; Fernandes, Cristóvão Vicente Scapulatempo; Kaviski, Eloy; Bleninger, Tobias

doi:10.1016/j.jhydrol.2021.126136

Cited by 10 publications

(3 citation statements)

References 24 publications

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“…Despite this drawback, the MC calibration procedure has been shown to be able to identify good parameter sets if enough model trials are taken, and a selection of the 100 best parameter sets from a batch of 10'000 randomly generated has been shown to be sufficient for the parameter optimization (Konz and Seibert, 2010;Finger et al, 2011). Moreover, due to its simplicity, MC remains a frequently applied optimization technique in hydrology (Pool et al, 2017b;Finger, 2018;De Niet et al, 2020;Ferreira et al, 2021).…”

Section: The Hbv Modelmentioning

confidence: 99%

Improving the Pareto Frontier in multi-dataset calibration of hydrological models using metaheuristics

Stefnisdóttir

Sikorska‐Senoner

Ásgeirsson

et al. 2021

Preprint

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Abstract. Hydrological models are crucial tools in water and environmental resource management but they require careful calibration based on observed data. Model calibration remains a challenging task, especially if a multi-objective or multi-dataset calibration is necessary to generate realistic simulations of multiple flow components under consideration. In this study, we explore the value of three metaheuristics, i.e. (i) Monte Carlo (MC), (ii) Simulated Annealing (SA), and (iii) Genetic 5 Algorithm (GA), for a multi-data set calibration to simultaneously simulate streamflow, snow cover and glacier mass balances using the conceptual HBV model. Based on the results from a small glaciated catchment of the Rhone River in Switzerland, we show that all three metaheuristics can generate parameter sets that result in realistic simulations of all three variables. Detailed comparison of model simulations with these three metaheuristics reveals however that GA provides the most accurate simulations (with lowest confidence intervals) for all three variables when using both the 100 and the 10 best parameter sets for 10 each method. However, when considering the 100 best parameter sets per method, GA yields also some worst solutions from the pool of all methods’ solutions. The findings are supported by a reduction of the parameter equifinality and an improvement of the Pareto frontier for GA in comparison to both other metaheuristic methods. Based on our results, we conclude that GA-based multi-dataset calibration leads to the most reproducible and consistent hydrological simulations with multiple variables considered.

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Section: The Hbv Modelmentioning

confidence: 99%

Improving the Pareto Frontier in multi-dataset calibration of hydrological models using metaheuristics

Stefnisdóttir

Sikorska‐Senoner

Ásgeirsson

et al. 2021

Preprint

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“…The study of fluid mechanics mainly focuses on the power wave equation (i.e., the complete set of Saint-Venant equations). At present, various river and coastal hydrodynamic models based on the Saint-Venant equation, such as ISIS, MIKE 11, HEC-RAS, TUFLOW, and other general hydrodynamic models, are widely used for large-scale river flow and flood prediction [1][2][3][4]. However, it is difficult for these models to carry out secondary development.…”

Section: Introductionmentioning

confidence: 99%

Application of One-Dimensional Hydrodynamic Coupling Model in Complex River Channels: Taking the Yongding River as an Example

Lv,

Kong,

Chuo

et al. 2024

Water

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River conditions are complex and affected by human activities. Various hydraulic structures change the longitudinal slope and cross-sectional shape of the riverbed, which has a significant impact on the simulation of water-head evolution. With continuous population growth, the hydrological characteristics of the Yongding River Basin have undergone significant changes. Too little or too much water discharge may be insufficient to meet downstream ecological needs or lead to the wastage of water resources, respectively. It is necessary to consider whether the total flow in each key section can achieve the expected value under different discharge flows. Therefore, a reliable computer model is needed to simulate the evolution of the water head and changes in the water level and flow under different flow rates to achieve efficient water resource allocation. A one-dimensional hydrodynamic coupling model based on the Saint-Venant equations was established for the Yongding River Basin. Different coupling methods were employed to calibrate the coupling model parameters, using centralised water replenishment data for the autumn of 2022, and the simulation results were verified using centralised water replenishment data for the spring of 2023. The maximum error of the water-head arrival time between different river sections was 4 h, and the maximum error of the water-head arrival time from the Guanting Reservoir to each key cross-section was 6 h. The maximum flow error was less than 5 m3/s, and the changing trend of the flow over time was consistent with the measured data. The model effectively solved the problem of low accuracy of the water level and flow calculation results when using the traditional one-dimensional hydrodynamic model to simulate the flow movement of complex river channels in the Yongding River. The output results of the model include the time when the water head arrives at the key section, the change process of the water level and flow of each section, the change process of the water storage of lakes and gravel pits, and the change process of the total flow and water surface area of the key section. This paper reports data that support the development of an ecological water compensation scheme for the Yongding River.

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“…Refinement of the mesh in the main channel and in other hydraulically influential areas has been shown to have an overall effect on modeled results since coarse resolution meshes misrepresent the channel cross‐section, thus altering modeled velocities and total inundated area (Bilgili et al., 2023; Bomers et al., 2019; Bradley, 2023; Yu & Lane, 2006). Despite the overall effects that mesh and DEM resolutions have on models, they are usually not altered because calibration is typically done by altering the roughness values (Attari & Hosseini, 2019; Ballesteros et al., 2011; Bilgili et al., 2023; Ferreira et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

Lidar DEM and Computational Mesh Grid Resolutions Modify Roughness in 2D Hydrodynamic Models

Prior,

Michaelson,

Czuba

et al. 2024

Water Resources Research

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Topography and the computational mesh grid are fundamental inputs to all two‐dimensional (2D) hydrodynamic models, however their resolutions are often arbitrarily selected based on data availability. With the increasing use of drone technology, the end user can collect topographic data down to centimeter‐scale resolution. With this advancement comes the responsibility of choosing a resolution. In this study, we investigated how the choice of mesh grid and digital elevation model (DEM) resolutions affect 2D hydrodynamic modeling results, specifically water depths, velocities, and inundation extent. We made pairwise comparisons between simulations from a 2D HEC‐RAS model with varying mesh grid resolutions (1 and 2 m) and drone‐based lidar DEM resolutions (0.1, 0.25, 0.5, 1, and 2 m) over a 1.5 km reach of Stroubles Creek in Blacksburg, Virginia. The model was rerun for up to ±4% change in floodplain roughness to determine how the DEM and mesh grid changes relate to an equivalent change in roughness. We found that the modeled differences from resolution change were equivalent to altering floodplain roughness by up to 12% for depths and 44% for velocities. The largest differences in velocity were concentrated at the channel‐floodplain interface, whereas differences in depth occurred laterally throughout the floodplain and were not correlated with lidar ground point density. We also found that the inundation boundary is dependent on the DEM resolution. Our results suggest that modelers should carefully consider what resolution best represents the terrain while also resolving important riparian topographic features.

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Calibration of river hydrodynamic models: Analysis from the dynamic component in roughness coefficients

Cited by 10 publications

References 24 publications

Improving the Pareto Frontier in multi-dataset calibration of hydrological models using metaheuristics

Improving the Pareto Frontier in multi-dataset calibration of hydrological models using metaheuristics

Application of One-Dimensional Hydrodynamic Coupling Model in Complex River Channels: Taking the Yongding River as an Example

Lidar DEM and Computational Mesh Grid Resolutions Modify Roughness in 2D Hydrodynamic Models

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