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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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HESS | Articles | Volume 24, issue 9
Hydrol. Earth Syst. Sci., 24, 4389–4411, 2020
https://doi.org/10.5194/hess-24-4389-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: Linking landscape organisation and hydrological functioning:...

Hydrol. Earth Syst. Sci., 24, 4389–4411, 2020
https://doi.org/10.5194/hess-24-4389-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 09 Sep 2020

Research article | 09 Sep 2020

Adaptive clustering: reducing the computational costs of distributed (hydrological) modelling by exploiting time-variable similarity among model elements

Uwe Ehret et al.

Data sets

Precipitation data Administration des services techniques de l'agriculture (ASTA) http://www.agrimeteo.lu/

Corine Land Cover (CLC) 2012 European Environment Agency (EEA) http://land.copernicus.eu/pan-european/corine-land-cover/clc-2012/view

Model code and software

KIT-HYD/SHM-Attert-Adaptive-Clustering: Release 1 (Version v1.0) Uwe Ehret https://doi.org/10.5281/zenodo.4017427

Publications Copernicus
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Short summary
In this paper we propose adaptive clustering as a new method for reducing the computational efforts of distributed modelling. It consists of identifying similar-acting model elements during the runtime, clustering them, running the model for just a few representatives per cluster, and mapping their results to the remaining model elements in the cluster. With the example of a hydrological model, we show that this saves considerable computation time, while largely maintaining the output quality.
In this paper we propose adaptive clustering as a new method for reducing the computational...
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