Year |
Citation |
Score |
2020 |
Neill AJ, Tetzlaff D, Strachan NJC, Hough RL, Avery LM, Kuppel S, Maneta MP, Soulsby C. An agent-based model that simulates the spatio-temporal dynamics of sources and transfer mechanisms contributing faecal indicator organisms to streams. Part 1: Background and model description. Journal of Environmental Management. 270: 110903. PMID 32721338 DOI: 10.1016/J.Jenvman.2020.110903 |
0.349 |
|
2020 |
Knighton J, Kuppel S, Smith A, Soulsby C, Sprenger M, Tetzlaff D. Using Isotopes to Incorporate Tree Water Storage and Mixing Dynamics into a Distributed Ecohydrologic Modelling Framework Ecohydrology. 13: 2201. DOI: 10.1002/Eco.2201 |
0.321 |
|
2019 |
Peaucelle M, Bacour C, Ciais P, Vuichard N, Kuppel S, Peñuelas J, Belelli Marchesini L, Blanken PD, Buchmann N, Chen J, Delpierre N, Desai AR, Dufrene E, Gianelle D, Gimeno‐Colera C, et al. Covariations between plant functional traits emerge from constraining parameterization of a terrestrial biosphere model Global Ecology and Biogeography. 28: 1351-1365. DOI: 10.1111/Geb.12937 |
0.452 |
|
2019 |
Douinot A, Tetzlaff D, Maneta M, Kuppel S, Schulte-Bisping H, Soulsby C. Ecohydrological modelling with EcH2O‐iso to quantify forest and grassland effects on water partitioning and flux ages Hydrological Processes. 33: 2174-2191. DOI: 10.1002/Hyp.13480 |
0.35 |
|
2018 |
Bastrikov V, MacBean N, Bacour C, Santaren D, Kuppel S, Peylin P. Land surface model parameter optimisation using in-situ flux data:comparison of gradient-based versus random search algorithms Geoscientific Model Development Discussions. 1-26. DOI: 10.5194/Gmd-2018-160 |
0.434 |
|
2018 |
Bastrikov V, MacBean N, Bacour C, Santaren D, Kuppel S, Peylin P. Land surface model parameter optimisation using in situ flux data: comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2) Geoscientific Model Development. 11: 4739-4754. DOI: 10.5194/Gmd-11-4739-2018 |
0.413 |
|
2018 |
Kuppel S, Tetzlaff D, Maneta MP, Soulsby C. EcH 2 O-iso 1.0: water isotopes and age tracking in a process-based, distributed ecohydrological model Geoscientific Model Development. 11: 3045-3069. DOI: 10.5194/Gmd-11-3045-2018 |
0.357 |
|
2018 |
Kuppel S, Tetzlaff D, Maneta MP, Soulsby C. What can we learn from multi-data calibration of a process-based ecohydrological model? Environmental Modelling and Software. 101: 301-316. DOI: 10.1016/J.Envsoft.2018.01.001 |
0.308 |
|
2018 |
Houspanossian J, Kuppel S, Nosetto M, Bella CD, Oricchio P, Barrucand M, Rusticucci M, Jobbagy E. Long-lasting floods buffer the thermal regime of the Pampas Theoretical and Applied Climatology. 131: 111-120. DOI: 10.1007/S00704-016-1959-7 |
0.352 |
|
2017 |
Kuppel S, Fan Y, Jobbágy EG. Seasonal hydrologic buffer on continents: Patterns, drivers and ecological benefits Advances in Water Resources. 102: 178-187. DOI: 10.1016/J.Advwatres.2017.01.004 |
0.345 |
|
2016 |
Peylin P, Bacour C, MacBean N, Leonard S, Rayner P, Kuppel S, Koffi E, Kane A, Maignan F, Chevallier F, Ciais P, Prunet P. A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle Geoscientific Model Development. 9: 3321-3346. DOI: 10.5194/Gmd-9-3321-2016 |
0.579 |
|
2015 |
Kuppel S, Houspanossian J, Nosetto MD, Jobbágy EG. What does it take to flood the Pampas?: Lessons from a decade of strong hydrological fluctuations Water Resources Research. 51: 2937-2950. DOI: 10.1002/2015Wr016966 |
0.302 |
|
2014 |
Kuppel S, Peylin P, Maignan F, Chevallier F, Kiely G, Montagnani L, Cescatti A. Model-data fusion across ecosystems : From multisite optimizations to global simulations Geoscientific Model Development. 7: 2581-2597. DOI: 10.5194/Gmd-7-2581-2014 |
0.584 |
|
2012 |
Kuppel S, Chevallier F, Peylin P. Quantifying the model structural error in carbon cycle data assimilation systems Geoscientific Model Development. 6: 45-55. DOI: 10.5194/Gmd-6-45-2013 |
0.539 |
|
2012 |
Kuppel S, Peylin P, Chevallier F, Bacour C, Maignan F, Richardson AD. Constraining a global ecosystem model with multi-site eddy-covariance data Biogeosciences. 9: 3757-3776. DOI: 10.5194/Bg-9-3757-2012 |
0.581 |
|
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