Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 10, 3001-3023, 2017
https://doi.org/10.5194/gmd-10-3001-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Model description paper
10 Aug 2017
lumpR 2.0.0: an R package facilitating landscape discretisation for hillslope-based hydrological models
Tobias Pilz, Till Francke, and Axel Bronstert Institute of Earth and Environmental Science, University of Potsdam, Potsdam, Germany
Abstract. The characteristics of a landscape pose essential factors for hydrological processes. Therefore, an adequate representation of the landscape of a catchment in hydrological models is vital. However, many of such models exist differing, amongst others, in spatial concept and discretisation. The latter constitutes an essential pre-processing step, for which many different algorithms along with numerous software implementations exist. In that context, existing solutions are often model specific, commercial, or depend on commercial back-end software, and allow only a limited or no workflow automation at all.

Consequently, a new package for the scientific software and scripting environment R, called lumpR, was developed. lumpR employs an algorithm for hillslope-based landscape discretisation directed to large-scale application via a hierarchical multi-scale approach. The package addresses existing limitations as it is free and open source, easily extendible to other hydrological models, and the workflow can be fully automated. Moreover, it is user-friendly as the direct coupling to a GIS allows for immediate visual inspection and manual adjustment. Sufficient control is furthermore retained via parameter specification and the option to include expert knowledge. Conversely, completely automatic operation also allows for extensive analysis of aspects related to landscape discretisation.

In a case study, the application of the package is presented. A sensitivity analysis of the most important discretisation parameters demonstrates its efficient workflow automation. Considering multiple streamflow metrics, the employed model proved reasonably robust to the discretisation parameters. However, parameters determining the sizes of subbasins and hillslopes proved to be more important than the others, including the number of representative hillslopes, the number of attributes employed for the lumping algorithm, and the number of sub-discretisations of the representative hillslopes.


Citation: Pilz, T., Francke, T., and Bronstert, A.: lumpR 2.0.0: an R package facilitating landscape discretisation for hillslope-based hydrological models, Geosci. Model Dev., 10, 3001-3023, https://doi.org/10.5194/gmd-10-3001-2017, 2017.
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Short summary
To discretise and transfer a landscape into a hydrological model, many different algorithms and software implementations exist. These are, however, often model specific, commercial, and allow for only a limited workflow automation. Overcoming these limitations, the software package lumpR was developed. It employs an hillslope-based discretisation algorithm directed at large-scale application. The software is demonstrated in a case study and crucial discretisation parameters are investigated.
To discretise and transfer a landscape into a hydrological model, many different algorithms and...
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