Articles | Volume 10, issue 9
https://doi.org/10.5194/gmd-10-3411-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-10-3411-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Optimizing the parameterization of deep mixing and internal seiches in one-dimensional hydrodynamic models: a case study with Simstrat v1.3
Adrien Gaudard
CORRESPONDING AUTHOR
Eawag, Swiss Federal Institute of Aquatic Science and Technology,
Surface Waters, Research and Management, Seestrasse 79, 6047
Kastanienbaum, Switzerland
Robert Schwefel
École Polytechnique Fédérale de Lausanne, Physics of
Aquatic Systems Laboratory, Margaretha Kamprad Chair, EPFL-ENAC-IIE-APHYS,
1015 Lausanne, Switzerland
Love Råman Vinnå
École Polytechnique Fédérale de Lausanne, Physics of
Aquatic Systems Laboratory, Margaretha Kamprad Chair, EPFL-ENAC-IIE-APHYS,
1015 Lausanne, Switzerland
Martin Schmid
Eawag, Swiss Federal Institute of Aquatic Science and Technology,
Surface Waters, Research and Management, Seestrasse 79, 6047
Kastanienbaum, Switzerland
Alfred Wüest
Eawag, Swiss Federal Institute of Aquatic Science and Technology,
Surface Waters, Research and Management, Seestrasse 79, 6047
Kastanienbaum, Switzerland
École Polytechnique Fédérale de Lausanne, Physics of
Aquatic Systems Laboratory, Margaretha Kamprad Chair, EPFL-ENAC-IIE-APHYS,
1015 Lausanne, Switzerland
Eawag, Swiss Federal Institute of Aquatic Science and Technology,
Surface Waters, Research and Management, Seestrasse 79, 6047
Kastanienbaum, Switzerland
École Polytechnique Fédérale de Lausanne, Physics of
Aquatic Systems Laboratory, Margaretha Kamprad Chair, EPFL-ENAC-IIE-APHYS,
1015 Lausanne, Switzerland
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- Are surface temperature and chlorophyll in a large deep lake related? An analysis based on satellite observations in synergy with hydrodynamic modelling and in-situ data D. Bouffard et al. 10.1016/j.rse.2018.02.056
- An automatic lake-model application using near-real-time data forcing: development of an operational forecast workflow (COASTLINES) for Lake Erie S. Lin et al. 10.5194/gmd-15-1331-2022
- Fine-scale dynamics of calcite precipitation in a large hardwater lake N. Escoffier et al. 10.1016/j.scitotenv.2022.160699
- A hybrid empirical and parametric approach for managing ecosystem complexity: Water quality in Lake Geneva under nonstationary futures E. Deyle et al. 10.1073/pnas.2102466119
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- The thermal behaviour of French water bodies: From ponds to Lake Geneva J. Prats et al. 10.1016/j.jglr.2020.04.001
- Lake Water Temperature Modeling in an Era of Climate Change: Data Sources, Models, and Future Prospects S. Piccolroaz et al. 10.1029/2023RG000816
- Meteolakes: An operational online three-dimensional forecasting platform for lake hydrodynamics T. Baracchini et al. 10.1016/j.watres.2020.115529
- Toward an open access to high-frequency lake modeling and statistics data for scientists and practitioners – the case of Swiss lakes using Simstrat v2.1 A. Gaudard et al. 10.5194/gmd-12-3955-2019
- The vulnerability of lakes to climate change along an altitudinal gradient L. Råman Vinnå et al. 10.1038/s43247-021-00106-w
- Calcite precipitation: The forgotten piece of lakes’ carbon cycle G. Many et al. 10.1126/sciadv.ado5924
- Global warming affects nutrient upwelling in deep lakes R. Schwefel et al. 10.1007/s00027-019-0637-0
- Assessing vertical diffusion in a stratified lake using a three‐dimensional hydrodynamic model F. Dong et al. 10.1002/hyp.13653
- Tributaries affect the thermal response of lakes to climate change L. Råman Vinnå et al. 10.5194/hess-22-31-2018
- Alkalinity contributes at least a third of annual gross primary production in a deep stratified hardwater lake P. Perolo et al. 10.1002/lol2.10311
- Numerical Simulation of Ice Cover of Saline Lakes V. Stepanenko et al. 10.1134/S0001433819010092
- Improving a Multilevel Turbulence Closure Model for a Shallow Lake in Comparison With Other 1‐D Models L. Sun et al. 10.1029/2019MS001971
- An empirical parametrization of internal seiche amplitude including secondary effects R. de Carvalho Bueno et al. 10.1007/s10652-020-09767-1
- Internal wave analyzer for thermally stratified lakes R. de Carvalho Bueno et al. 10.1016/j.envsoft.2020.104950
- MFIT 1.0.0: Multi-Flow Inversion of Tracer breakthrough curves in fractured and karst aquifers J. Bodin 10.5194/gmd-13-2905-2020
- An automated calibration framework and open source tools for 3D lake hydrodynamic models T. Baracchini et al. 10.1016/j.envsoft.2020.104787
- Whiting Events in a Large Peri‐Alpine Lake: Evidence of a Catchment‐Scale Process N. Escoffier et al. 10.1029/2022JG006823
- A novel objective function DYNO for automatic multivariable calibration of 3D lake models W. Xia et al. 10.5194/hess-26-3651-2022
- Dynamic modelling provides new insights into development and maintenance of Lake Kivu's density stratification F. Bärenbold et al. 10.1016/j.envsoft.2021.105251
Latest update: 20 Nov 2024
Short summary
The study of lakes often uses numerical models to reproduce the processes occurring in nature as accurately as possible. Due to the complexity of natural systems, all numerical models need to leave aside or simplify many of the relevant processes. In this work, we improve the modelling of the impact of wind on the internal currents in deep lakes. This improves the reproduction of deep mixing, which influences the concentrations of oxygen and nutrients, with biological and chemical consequences.
The study of lakes often uses numerical models to reproduce the processes occurring in nature as...