EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Multi-basin calibration of the ECMWF land-surface model ECLand

Stephan Thober1, Robert Schweppe1, Matthias Kelbling1, Sebastian Müller1, Juliane Mai1, Christel Prudhomme2, Gianpaolo Balsamo2, and Luis Samaniego1
Stephan Thober et al.
  • 1Helmholtz Centre for Environmental Research - UFZ, Computational Hydrosystems, Leipzig, Germany
  • 2European Centre for Medium-Range Weather Forecasts, Reading, UK, Bologna, Italy, Bonn, Germany

Accurately and efficiently estimating parameters for spatially distributed environmental models is impossible without proper regularization of the parameter space. The Multiscale Parameter Regionalization (MPR, Samaniego et al. 2010) makes use of high-resolution physiographic data (i.e., physiographic data such as soil maps and land cover information) to translate local land surface properties into model parameters. MPR consists of two steps: first, the high-resolution model parameters are derived from physiographic data via transfer functions at the native resolution. Second, the model parameters are upscaled to the target resolution used by the environmental modelling application. MPR has been already successfully applied for the mesoscale hydrologic model (mHM, Samaniego et al. 2010, Kumar et al. 2013). The model agnostic, stand-alone version  implementation of MPR (Schweppe et al., 2022) allows applying this technique to any land-surface model or hydrological model.

In this study, we apply the MPR to optimize parameters for the land-surface model ECLand (Boussetta et al. 2021) of the ECMWF Integrated Forecasting System. Calibrating ECLand parameters at individual river basins leads to an improved representation of river discharge, i.e., an improved Kling-Gupta efficiency. In an ongoing effort, we explore model parameters optimization on multiple basins simultaneously to provide an improved representation of river discharge at a global scale. The calibration locations are chosen to cover different climates, soil, and land characteristics among other features.


Samaniego L., Kumar, R., and Attinger, S.: “Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale”, Water Resour. Res., 46, 2010.

Kumar, R., Samaniego, L., and Attinger, S.: “Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations”, Water Resources Res, 2013

Schweppe, R., Thober, S., Müller, S., Kelbling, M., Kumar, R., Attinger, S., and Samaniego, L.: MPR 1.0: a stand-alone multiscale parameter regionalization tool for improved parameter estimation of land surface models, Geosci. Model Dev., 15, 859–882,, 2022

Boussetta S, Balsamo G, Arduini G, Dutra E, McNorton J, Choulga M, Agustí-Panareda A, Beljaars A, Wedi N, Munõz-Sabater J, de Rosnay P, Sandu I, Hadade I, Carver G, Mazzetti C, Prudhomme C, Yamazaki D, Zsoter E. ECLand: The ECMWF Land Surface Modelling System. Atmosphere. 2021; 12(6):723.

How to cite: Thober, S., Schweppe, R., Kelbling, M., Müller, S., Mai, J., Prudhomme, C., Balsamo, G., and Samaniego, L.: Multi-basin calibration of the ECMWF land-surface model ECLand, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-9526,, 2023.