lumpR 2.0.0: an R package facilitating landscape discretisation for hillslope-based hydrological models
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 la...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-08-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://www.geosci-model-dev.net/10/3001/2017/gmd-10-3001-2017.pdf |
| Summary: | 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.
<br><br>
Consequently, a new package for the scientific software and scripting
environment R, called <i>lumpR</i>, 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.
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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. |
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| ISSN: | 1991-959X 1991-9603 |