Articles | Volume 13, issue 3
Geosci. Model Dev., 13, 1267–1284, 2020

Special issue: Modelling lakes in the climate system (GMD/HESS inter-journal...

Geosci. Model Dev., 13, 1267–1284, 2020

Development and technical paper 17 Mar 2020

Development and technical paper | 17 Mar 2020

Data assimilation of in situ and satellite remote sensing data to 3D hydrodynamic lake models: a case study using Delft3D-FLOW v4.03 and OpenDA v2.4

Theo Baracchini et al.

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Cited articles

Akella, S. and Navon, I. M.: Different approaches to model error formulation in 4D-Var: a study with high-resolution advection schemes, Tellus A, 61, 112–128, 2009. 
Anderson, L. A., Robinson, A. R., and Lozano, C. J.: Physical and biological modeling in the Gulf Stream region, Deep-Sea Res., 47, 1787–1827, 2000. 
Bannister, R. N.: A review of operational methods of variational and ensemble-variational data assimilation, Q. J. Roy. Meteor. Soc., 143, 607–633,, 2017. 
Baracchini, T.: OpenDA, available at:, last access: 9 March 2020. 
Baracchini, T., Verlaan, M., Cimatoribus, A., Wüest, A., and Bouffard, D.: Automated calibration of 3D lake hydrodynamic models using an open-source data assimilation platform, Environ. Modell. Softw., in review, 2019a. 
Short summary
Lake physical processes occur at a wide range of spatiotemporal scales. 3D hydrodynamic lake models are the only information source capable of solving those scales; however, they still need observations to be calibrated and to constrain their uncertainties. The optimal combination of a 3D hydrodynamic model, in situ measurements, and remote sensing observations is achieved through data assimilation. Here we present a complete data assimilation experiment for lakes using open-source tools.