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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 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, itThe 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.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Tobias PilzORCiD, Till FranckeORCiDGND, Axel BronstertORCiDGND
DOI:https://doi.org/10.5194/gmd-10-3001-2017
ISSN:1991-959X
ISSN:1991-9603
Titel des übergeordneten Werks (Englisch):Geoscientific model development : an interactive open access journal of the European Geosciences Union
Verlag:Copernicus
Verlagsort:Göttingen
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Jahr der Erstveröffentlichung:2017
Erscheinungsjahr:2017
Datum der Freischaltung:20.04.2020
Band:10
Seitenanzahl:23
Erste Seite:3001
Letzte Seite:3023
Fördernde Institution:Helmholtz graduate school GeoSim; Deutsche Forschungsgemeinschaft; University of Potsdam
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
Peer Review:Referiert
Name der Einrichtung zum Zeitpunkt der Publikation:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften
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