Articles | Volume 6, issue 1
https://doi.org/10.5194/gmd-6-117-2013
© Author(s) 2013. 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-6-117-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
29 Jan 2013
Development and technical paper |
| 29 Jan 2013
Using multi-model averaging to improve the reliability of catchment scale nitrogen predictions
J.-F. Exbrayat
Climate Change Research Centre, University of New South Wales, Sydney, New South Wales, Australia
Institute for Landscape Ecology and Resources Management (ILR), Research Centre for BioSystems, Land Use and Nutrition (IFZ), Justus-Liebig-Universität Gießen, Germany
N. R. Viney
CSIRO Land and Water, Canberra, ACT, Australia
H.-G. Frede
Institute for Landscape Ecology and Resources Management (ILR), Research Centre for BioSystems, Land Use and Nutrition (IFZ), Justus-Liebig-Universität Gießen, Germany
L. Breuer
Institute for Landscape Ecology and Resources Management (ILR), Research Centre for BioSystems, Land Use and Nutrition (IFZ), Justus-Liebig-Universität Gießen, Germany
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Cited
14 citations as recorded by crossref.
- Examining soil carbon uncertainty in a global model: response of microbial decomposition to temperature, moisture and nutrient limitation J. Exbrayat et al. https://doi.org/10.5194/bg-10-7095-2013
- Relative model score: a scoring rule for evaluating ensemble simulations with application to microbial soil respiration modeling A. Elshall et al. https://doi.org/10.1007/s00477-018-1592-3
- Modeling the Effects of Environmental Conditions on HT2 and T2 Toxin Accumulation in Field Oat Grains X. Xu et al. https://doi.org/10.1094/PHYTO-03-13-0070-R
- A practical planning software program for desalination in agriculture - SPARE:WATERopt S. Multsch et al. https://doi.org/10.1016/j.desal.2016.11.012
- Toward “optimal” integration of terrestrial biosphere models C. Schwalm et al. https://doi.org/10.1002/2015GL064002
- Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties J. Exbrayat et al. https://doi.org/10.5194/esd-9-153-2018
- Reduction of predictive uncertainty in estimating irrigation water requirement through multi-model ensembles and ensemble averaging S. Multsch et al. https://doi.org/10.5194/gmd-8-1233-2015
- Addressing sources of uncertainty in runoff projections for a data scarce catchment in the Ecuadorian Andes J. Exbrayat et al. https://doi.org/10.1007/s10584-014-1160-x
- Development of majority voting combined model and application to coal calorific value prediction J. Chen et al. https://doi.org/10.1080/19392699.2025.2601698
- Capability and limitations of a simple grid-based model for simulating land use influences on stream nitrate concentrations S. Dunn et al. https://doi.org/10.1016/j.jhydrol.2013.10.016
- Combining Models is More Likely to Give Better Predictions than Single Models X. Hu et al. https://doi.org/10.1094/PHYTO-11-14-0315-R
- Developing logistic models to relate the accumulation of DON associated with Fusarium head blight to climatic conditions in Europe X. Xu et al. https://doi.org/10.1007/s10658-013-0280-x
- Identifying a robust method to build RCMs ensemble as climate forcing for hydrological impact models P. Olmos Giménez et al. https://doi.org/10.1016/j.atmosres.2016.01.012
- Toward a framework for the multimodel ensemble prediction of soil nitrogen losses K. Liao et al. https://doi.org/10.1016/j.ecolmodel.2021.109675
14 citations as recorded by crossref.
- Examining soil carbon uncertainty in a global model: response of microbial decomposition to temperature, moisture and nutrient limitation J. Exbrayat et al. https://doi.org/10.5194/bg-10-7095-2013
- Relative model score: a scoring rule for evaluating ensemble simulations with application to microbial soil respiration modeling A. Elshall et al. https://doi.org/10.1007/s00477-018-1592-3
- Modeling the Effects of Environmental Conditions on HT2 and T2 Toxin Accumulation in Field Oat Grains X. Xu et al. https://doi.org/10.1094/PHYTO-03-13-0070-R
- A practical planning software program for desalination in agriculture - SPARE:WATERopt S. Multsch et al. https://doi.org/10.1016/j.desal.2016.11.012
- Toward “optimal” integration of terrestrial biosphere models C. Schwalm et al. https://doi.org/10.1002/2015GL064002
- Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties J. Exbrayat et al. https://doi.org/10.5194/esd-9-153-2018
- Reduction of predictive uncertainty in estimating irrigation water requirement through multi-model ensembles and ensemble averaging S. Multsch et al. https://doi.org/10.5194/gmd-8-1233-2015
- Addressing sources of uncertainty in runoff projections for a data scarce catchment in the Ecuadorian Andes J. Exbrayat et al. https://doi.org/10.1007/s10584-014-1160-x
- Development of majority voting combined model and application to coal calorific value prediction J. Chen et al. https://doi.org/10.1080/19392699.2025.2601698
- Capability and limitations of a simple grid-based model for simulating land use influences on stream nitrate concentrations S. Dunn et al. https://doi.org/10.1016/j.jhydrol.2013.10.016
- Combining Models is More Likely to Give Better Predictions than Single Models X. Hu et al. https://doi.org/10.1094/PHYTO-11-14-0315-R
- Developing logistic models to relate the accumulation of DON associated with Fusarium head blight to climatic conditions in Europe X. Xu et al. https://doi.org/10.1007/s10658-013-0280-x
- Identifying a robust method to build RCMs ensemble as climate forcing for hydrological impact models P. Olmos Giménez et al. https://doi.org/10.1016/j.atmosres.2016.01.012
- Toward a framework for the multimodel ensemble prediction of soil nitrogen losses K. Liao et al. https://doi.org/10.1016/j.ecolmodel.2021.109675
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