Articles | Volume 10, issue 8
https://doi.org/10.5194/gmd-10-3001-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-10-3001-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
10 Aug 2017
Model description paper |
| 10 Aug 2017
lumpR 2.0.0: an R package facilitating landscape discretisation for hillslope-based hydrological models
Institute of Earth and Environmental Science, University of Potsdam, Potsdam, Germany
Till Francke
Institute of Earth and Environmental Science, University of Potsdam, Potsdam, Germany
Axel Bronstert
Institute of Earth and Environmental Science, University of Potsdam, Potsdam, Germany
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Cited
22 citations as recorded by crossref.
- Mesoscale Mapping of Sediment Source Hotspots for Dam Sediment Management in Data-Sparse Semi-Arid Catchments A. Smetanová et al. https://doi.org/10.3390/w12020396
- Regional-scale seasonal forecast of surface water availability in a semi-arid environment: The case of Ceará State in Northeast of Brazil E. Rottler et al. https://doi.org/10.1016/j.ejrh.2024.102058
- glmGUI v1.0: an R-based graphical user interface and toolbox for GLM (General Lake Model) simulations T. Bueche et al. https://doi.org/10.5194/gmd-13-565-2020
- An effective strategy for combining variance- and distribution-based global sensitivity analysis G. Baroni & T. Francke https://doi.org/10.1016/j.envsoft.2020.104851
- Optimization of Hydrologic Response Units (HRUs) Using Gridded Meteorological Data and Spatially Varying Parameters D. Poblete et al. https://doi.org/10.3390/w12123558
- A comprehensive open-source course for teaching applied hydrological modelling in Central Asia B. Marti et al. https://doi.org/10.5194/hess-27-319-2023
- Decomposition of 2D polygons and its effect in hydrological models P. Sanzana et al. https://doi.org/10.2166/hydro.2018.031
- A Novel Algorithm to Delineate Surface Water Paths on Digital Elevation Model Image With Boundary Element Method A. Chantaveerod et al. https://doi.org/10.1109/ACCESS.2022.3180175
- A Novel Catchment Estimation for Super-Resolution DEM With Physically Based Algorithms: Surface Water Path Delineation and Specific Catchment Area Calculation A. Chantaveerod et al. https://doi.org/10.1109/ACCESS.2023.3293399
- Modeling the Effect of Multiple Reservoirs on Water and Sediment Dynamics in a Semiarid Catchment in Brazil G. Mamede et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001701
- Stability amidst variability: Four decades of hydrologic response in the Upper Snake River Basin, Wyoming, USA Z. Fang et al. https://doi.org/10.1016/j.ejrh.2026.103890
- Adaptive Physically Based Contour Framework for Robust and Efficient Catchment Estimation on Large-Scale Terrain Using Super-Resolution DEMs A. Chantaveerod et al. https://doi.org/10.1109/JSTARS.2025.3639901
- Distribution-based sensitivity analysis from a generic input-output sample F. Pianosi & T. Wagener https://doi.org/10.1016/j.envsoft.2018.07.019
- A multi-factor integrated method of calculation unit delineation for hydrological modeling in large mountainous basins B. Li et al. https://doi.org/10.1016/j.jhydrol.2021.126180
- How to Tailor My Process‐Based Hydrological Model? Dynamic Identifiability Analysis of Flexible Model Structures T. Pilz et al. https://doi.org/10.1029/2020WR028042
- Reduced-Complexity and Robust Surface Water Path Delineation for Large Real-World Terrain Using Boundary Element Method A. Chantaveerod et al. https://doi.org/10.1109/ACCESS.2024.3460762
- Unravelling the impact of spatial discretization and calibration strategies on event-based flood models V. Manikanta & N. Umamahesh https://doi.org/10.1007/s40808-023-01936-7
- Combining Machine Learning and Process-Based Modelling for Sediment Load Estimation in the Data-Scarce Kessie Watershed, Upper Blue Nile Basin K. Worku et al. https://doi.org/10.3390/w18141759
- Comparison and hydrological evaluation of different precipitation data for a large tropical region: the Blue Nile Basin in Ethiopia M. Zargar et al. https://doi.org/10.3389/frwa.2025.1536881
- Modelling infiltration and infiltration excess: The importance of fast and local processes A. Bronstert et al. https://doi.org/10.1002/hyp.14875
- Seasonal drought prediction for semiarid northeast Brazil: what is the added value of a process-based hydrological model? T. Pilz et al. https://doi.org/10.5194/hess-23-1951-2019
- Accounting for operational irrigation options in mesoscale hydrological modelling of dryland environments P. Voit et al. https://doi.org/10.1080/02626667.2023.2187296
22 citations as recorded by crossref.
- Mesoscale Mapping of Sediment Source Hotspots for Dam Sediment Management in Data-Sparse Semi-Arid Catchments A. Smetanová et al. https://doi.org/10.3390/w12020396
- Regional-scale seasonal forecast of surface water availability in a semi-arid environment: The case of Ceará State in Northeast of Brazil E. Rottler et al. https://doi.org/10.1016/j.ejrh.2024.102058
- glmGUI v1.0: an R-based graphical user interface and toolbox for GLM (General Lake Model) simulations T. Bueche et al. https://doi.org/10.5194/gmd-13-565-2020
- An effective strategy for combining variance- and distribution-based global sensitivity analysis G. Baroni & T. Francke https://doi.org/10.1016/j.envsoft.2020.104851
- Optimization of Hydrologic Response Units (HRUs) Using Gridded Meteorological Data and Spatially Varying Parameters D. Poblete et al. https://doi.org/10.3390/w12123558
- A comprehensive open-source course for teaching applied hydrological modelling in Central Asia B. Marti et al. https://doi.org/10.5194/hess-27-319-2023
- Decomposition of 2D polygons and its effect in hydrological models P. Sanzana et al. https://doi.org/10.2166/hydro.2018.031
- A Novel Algorithm to Delineate Surface Water Paths on Digital Elevation Model Image With Boundary Element Method A. Chantaveerod et al. https://doi.org/10.1109/ACCESS.2022.3180175
- A Novel Catchment Estimation for Super-Resolution DEM With Physically Based Algorithms: Surface Water Path Delineation and Specific Catchment Area Calculation A. Chantaveerod et al. https://doi.org/10.1109/ACCESS.2023.3293399
- Modeling the Effect of Multiple Reservoirs on Water and Sediment Dynamics in a Semiarid Catchment in Brazil G. Mamede et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001701
- Stability amidst variability: Four decades of hydrologic response in the Upper Snake River Basin, Wyoming, USA Z. Fang et al. https://doi.org/10.1016/j.ejrh.2026.103890
- Adaptive Physically Based Contour Framework for Robust and Efficient Catchment Estimation on Large-Scale Terrain Using Super-Resolution DEMs A. Chantaveerod et al. https://doi.org/10.1109/JSTARS.2025.3639901
- Distribution-based sensitivity analysis from a generic input-output sample F. Pianosi & T. Wagener https://doi.org/10.1016/j.envsoft.2018.07.019
- A multi-factor integrated method of calculation unit delineation for hydrological modeling in large mountainous basins B. Li et al. https://doi.org/10.1016/j.jhydrol.2021.126180
- How to Tailor My Process‐Based Hydrological Model? Dynamic Identifiability Analysis of Flexible Model Structures T. Pilz et al. https://doi.org/10.1029/2020WR028042
- Reduced-Complexity and Robust Surface Water Path Delineation for Large Real-World Terrain Using Boundary Element Method A. Chantaveerod et al. https://doi.org/10.1109/ACCESS.2024.3460762
- Unravelling the impact of spatial discretization and calibration strategies on event-based flood models V. Manikanta & N. Umamahesh https://doi.org/10.1007/s40808-023-01936-7
- Combining Machine Learning and Process-Based Modelling for Sediment Load Estimation in the Data-Scarce Kessie Watershed, Upper Blue Nile Basin K. Worku et al. https://doi.org/10.3390/w18141759
- Comparison and hydrological evaluation of different precipitation data for a large tropical region: the Blue Nile Basin in Ethiopia M. Zargar et al. https://doi.org/10.3389/frwa.2025.1536881
- Modelling infiltration and infiltration excess: The importance of fast and local processes A. Bronstert et al. https://doi.org/10.1002/hyp.14875
- Seasonal drought prediction for semiarid northeast Brazil: what is the added value of a process-based hydrological model? T. Pilz et al. https://doi.org/10.5194/hess-23-1951-2019
- Accounting for operational irrigation options in mesoscale hydrological modelling of dryland environments P. Voit et al. https://doi.org/10.1080/02626667.2023.2187296
Saved (final revised paper)
Latest update: 14 Oct 2026
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...
