Articles | Volume 13, issue 6
https://doi.org/10.5194/hess-13-779-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-13-779-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
16 Jun 2009
Identification and regionalization of dominant runoff processes – a GIS-based and a statistical approach
C. Müller
University of Trier, Faculty of Geosciences, Department of Soil Sciences, Trier, Germany
H. Hellebrand
Delft University of Technology, Faculty of Civil Engineering and Geosciences, Department of Watermanagement, Section of Hydrology, Delft, The Netherlands
M. Seeger
University & Research Center Wageningen, Department of Land Degradation and Development, Wageningen, The Netherlands
S. Schobel
Johann Heinrich von Thünen-Institute, Institute of Forest Ecology and Forest Inventory, Eberswalde, Germany
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Cited
22 citations as recorded by crossref.
- Research on machine learning hybrid framework by coupling grid-based runoff generation model and runoff process vectorization for flood forecasting C. Liu et al. 10.1016/j.jenvman.2024.121466
- How can expert knowledge increase the realism of conceptual hydrological models? A case study based on the concept of dominant runoff process in the Swiss Pre-Alps M. Antonetti & M. Zappa 10.5194/hess-22-4425-2018
- Ensemble flood forecasting considering dominant runoff processes – Part 1: Set-up and application to nested basins (Emme, Switzerland) M. Antonetti et al. 10.5194/nhess-19-19-2019
- Hydrological landscape classification: investigating the performance of HAND based landscape classifications in a central European meso-scale catchment S. Gharari et al. 10.5194/hess-15-3275-2011
- The dominant runoff processes on grassland versus bare soil hillslopes in a temperate environment - An experimental study G. Minea et al. 10.2478/johh-2019-0018
- Brixenbach research catchment: Quantification of runoff process proportions in a small Alpine catchment depending on soil moisture states and precipitation characteristics G. Meißl et al. 10.1002/hyp.14186
- Identifying Dominant Runoff Processes at a Regional Scale – A GIS - Based Approach F. Joseph et al. 10.1515/pesd-2017-0022
- Identification of the controlling factors for hydrological responses by artificial neural networks R. Hao et al. 10.1002/hyp.14420
- A process proof test for model concepts: Modelling the meso-scale H. Hellebrand et al. 10.1016/j.pce.2010.07.019
- Mapping dominant runoff processes: an evaluation of different approaches using similarity measures and synthetic runoff simulations M. Antonetti et al. 10.5194/hess-20-2929-2016
- Identifying dominant component of runoff yield processes: a case study in a sub-basin of the middle Yellow River L. Zhang et al. 10.2166/nh.2021.046
- Identification of runoff processes – The impact of different forest types and soil properties on runoff formation and floods M. Hümann et al. 10.1016/j.jhydrol.2011.08.067
- Exploring the Dominant Runoff Processes in Two Typical Basins of the Yellow River, China G. Ran et al. 10.3390/w12113055
- Topographic, pedologic and climatic interactions influencing streamflow generation at multiple catchment scales G. Ali et al. 10.1002/hyp.8416
- A method to employ the spatial organization of catchments into semi-distributed rainfall–runoff models H. Oppel & A. Schumann 10.5194/hess-21-4259-2017
- Improved Process Representation in the Simulation of the Hydrology of a Meso-Scale Semi-Arid Catchment A. Saraiva Okello et al. 10.3390/w10111549
- Spatial Evaluation of a Hydrological Model on Dominant Runoff Generation Processes Using Soil Hydrologic Maps H. Mohajerani et al. 10.3390/hydrology10030055
- Conceptual model building inspired by field-mapped runoff generation mechanisms A. Viglione et al. 10.2478/johh-2018-0010
- Process‐based hydrological modelling: The potential of a bottom‐up approach for runoff predictions in ungauged catchments M. Antonetti et al. 10.1002/hyp.11232
- Construction of a semi-distributed hydrological model considering the combination of saturation-excess and infiltration-excess runoff space under complex substratum Y. Xu et al. 10.1016/j.ejrh.2023.101642
- Improving the GIS-DRP Approach by Means of DelineatingRunoff Characteristics with New Discharge Relevant Parameters M. Hümann & C. Müller 10.3390/ijgi2010027
- Delineation of potential zones for groundwater recharge using integrated GIS-based AHP and CSI techniques in Ogun Waterside, Southwestern Nigeria G. Badmus et al. 10.2166/ws.2024.220
22 citations as recorded by crossref.
- Research on machine learning hybrid framework by coupling grid-based runoff generation model and runoff process vectorization for flood forecasting C. Liu et al. 10.1016/j.jenvman.2024.121466
- How can expert knowledge increase the realism of conceptual hydrological models? A case study based on the concept of dominant runoff process in the Swiss Pre-Alps M. Antonetti & M. Zappa 10.5194/hess-22-4425-2018
- Ensemble flood forecasting considering dominant runoff processes – Part 1: Set-up and application to nested basins (Emme, Switzerland) M. Antonetti et al. 10.5194/nhess-19-19-2019
- Hydrological landscape classification: investigating the performance of HAND based landscape classifications in a central European meso-scale catchment S. Gharari et al. 10.5194/hess-15-3275-2011
- The dominant runoff processes on grassland versus bare soil hillslopes in a temperate environment - An experimental study G. Minea et al. 10.2478/johh-2019-0018
- Brixenbach research catchment: Quantification of runoff process proportions in a small Alpine catchment depending on soil moisture states and precipitation characteristics G. Meißl et al. 10.1002/hyp.14186
- Identifying Dominant Runoff Processes at a Regional Scale – A GIS - Based Approach F. Joseph et al. 10.1515/pesd-2017-0022
- Identification of the controlling factors for hydrological responses by artificial neural networks R. Hao et al. 10.1002/hyp.14420
- A process proof test for model concepts: Modelling the meso-scale H. Hellebrand et al. 10.1016/j.pce.2010.07.019
- Mapping dominant runoff processes: an evaluation of different approaches using similarity measures and synthetic runoff simulations M. Antonetti et al. 10.5194/hess-20-2929-2016
- Identifying dominant component of runoff yield processes: a case study in a sub-basin of the middle Yellow River L. Zhang et al. 10.2166/nh.2021.046
- Identification of runoff processes – The impact of different forest types and soil properties on runoff formation and floods M. Hümann et al. 10.1016/j.jhydrol.2011.08.067
- Exploring the Dominant Runoff Processes in Two Typical Basins of the Yellow River, China G. Ran et al. 10.3390/w12113055
- Topographic, pedologic and climatic interactions influencing streamflow generation at multiple catchment scales G. Ali et al. 10.1002/hyp.8416
- A method to employ the spatial organization of catchments into semi-distributed rainfall–runoff models H. Oppel & A. Schumann 10.5194/hess-21-4259-2017
- Improved Process Representation in the Simulation of the Hydrology of a Meso-Scale Semi-Arid Catchment A. Saraiva Okello et al. 10.3390/w10111549
- Spatial Evaluation of a Hydrological Model on Dominant Runoff Generation Processes Using Soil Hydrologic Maps H. Mohajerani et al. 10.3390/hydrology10030055
- Conceptual model building inspired by field-mapped runoff generation mechanisms A. Viglione et al. 10.2478/johh-2018-0010
- Process‐based hydrological modelling: The potential of a bottom‐up approach for runoff predictions in ungauged catchments M. Antonetti et al. 10.1002/hyp.11232
- Construction of a semi-distributed hydrological model considering the combination of saturation-excess and infiltration-excess runoff space under complex substratum Y. Xu et al. 10.1016/j.ejrh.2023.101642
- Improving the GIS-DRP Approach by Means of DelineatingRunoff Characteristics with New Discharge Relevant Parameters M. Hümann & C. Müller 10.3390/ijgi2010027
- Delineation of potential zones for groundwater recharge using integrated GIS-based AHP and CSI techniques in Ogun Waterside, Southwestern Nigeria G. Badmus et al. 10.2166/ws.2024.220
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