Terrestrial water cycle Plant – water interactions Rock – water interactions Process-based modelling , conceptual modelling Modelling tools: EcH2O-iso, an ecohydrological model of the critical zone: online repository with case study and user guide.
Ackerer, J., Kuppel, S., Braud, I., Pasquet, S., Fovet, O., Probst, A., et al. . Exploring the critical zone heterogeneity and the hydrological diversity using an integrated ecohydrological model in three contrasted long-term observatories. Water Resources Research, 59, e2023WR035672. https://doi.org/10.1029/2023WR035672, 2023. Li, K., Kuppel, S., & Knighton, J.: Parameterizing vegetation traits with a process-based ecohydrological model and xylem water isotopic observations. Journal of Advances in Modeling Earth Systems, 15, e2022MS003263. https://doi.org/10.1029/2022MS003263, 2022. MacBean, N., Bacour, C., Raoult, N., Bastrikov, V., Koffi, E. N., Kuppel, S., … & Peylin, P.: Quantifying and reducing uncertainty in global carbon cycle predictions: lessons and perspectives from 15 years of data assimilation studies with the ORCHIDEE Terrestrial Biosphere Model. Global Biogeochemical Cycles, 36(7), e2021GB007177. 10.1029/2021GB007177, 2022. Arora, B., P. Sullivan, S. Kuppel, X. Yang, and J. Groh: The future of critical zone science: Call for papers, Eos, 102, https://doi.org/10.1029/2021EO157965, 2021. Fovet, O., A. Belemtougri, L. Boithias, I. Braud, J.-B. Charlier, M. Cottet, K. Daudin, G. Dramais, A. Ducharne, N. Folton, M. Grippa, B. Hector, S. Kuppel, J. Le Coz, L. Legal, P. Martin, F. Moatar, J. Molénat, A. Probst, J. Riotte, J.-P. Vidal, F. Vinatier, and T. Datry : Intermittent rivers and ephemeral streams: perspectives for critical zone sciences and research on socio-ecosystems, WIREs Water, 10.1002/wat2.1523, 2021. Giménez, R., J.L. Mercau, F.E. Bert, S. Kuppel, G. Baldi, J. Houspanossian, P.N. Magliano, and E.G Jobbágy : Hydrological and productive impacts of recent land‐use and land‐cover changes in the semiarid Chaco: Understanding novel water excess in water scarce farmlands. Ecohydrology, 13:e2243. https://doi.org/10.1002/eco.2243, 2020. Neill A.J., D. Tetzlaff, N.J.C. Strachan, R.L. Hough, L.M. Avery, S. Kuppel, M.P. Maneta, and C. Soulsby : 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, doi: 10.1016/j.jenvman.2020.110903, 2020. Kuppel, S., D. Tetzlaff, M.P. Maneta, and C. Soulsby : Critical zone storage controls on the water ages of ecohydrological outputs. Geophysical Research Letters, 47, e2020GL088897. https://doi.org/10.1029/2020GL088897, 2020. Knighton, J., S. Kuppel, A. Smith, M. Sprenger, C. Soulsby, and D. Tetzlaff : Using Isotopes to Incorporate Tree Water Storage and Mixing Dynamics into a Distributed Hydrologic Modeling Framework, Ecohydrology, doi:10.1002/eco.2201, 2020. Tague, C., S. Papuga, C. Gerlein-Safdi, S. Dymond, R. Morrison, E. Boyer, D. Riveros-Iregui, E. Agee, B. Arora, Y. Dialynas, A. Hansen, S. Krause, S. Kuppel, S.P Loheide II, S.J. Schymanski, S.C. Zipper : Adding our leaves: a community-wide perspective on research directions in ecohydrology, Hydrological Processes, doi:10.1002/hyp.13693, 2020. Peaucelle, M., C. Bacour, P. Ciais, N. Vuichard, S. Kuppel, J. Peñuelas, et al. : Covariations between plant functional traits emerge from constraining parameterization of a terrestrial biosphere model, Global Ecol. Biogeogr., doi:10.1111/geb.12937, 2019. Douinot, A., D. Tetzlaff, M.P. Maneta, S. Kuppel, H. Schulte-Bisping, and C. Soulsby : 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, 2019. Bastrikov, V., N. MacBean, C. Bacour, D. Santaren, S. Kuppel, and P. Peylin : Land surface model parameter optimisation using in-situ flux data: comparison of gradient-based versus random search algorithms, Geoscientific Model Development, 11, 4739–4754, doi:10.5194/gmd-11-4739-2018, 2018. Maneta, M.P., C. Soulsby, S. Kuppel, and D. Tetzlaff : Conceptualizing catchment storage dynamics and nonlinearities, Hydrological Processes (IF 3.2), 32, 3299–3303, doi:10.1002/hyp.13262, 2018. Kuppel, S., D. Tetzlaff, M.P. Maneta, and C. Soulsby : EcH2O-iso 1.0 : Water isotopes and age tracking implemented in a process-based, distributed ecohydrological model, Geoscientific Model Development, 11, 3045–3069, doi:10.5194/gmd-11-3045-2018, 2018. Kuppel, S., M.P. Maneta, D. Tetzlaff, and C. Soulsby : What can we learn from multi-data calibration of a process-based ecohydrological model ?, Environmental Modelling & Software (IF 4.6), 101, 301–316, doi:10.1016/j.envsoft.2018.01.001, 2018. Houspanossian, J., S. Kuppel, M.D. Nosetto, C. Di Bella, P. Oricchio, M. Barrucand, M. Rusticucci, and E.G. Jobbágy : The effect of long-lasting floods on the thermal regime of the Pampas. Theoretical and Applied Climatology, 131, 111–120, doi:10.1007/s00704-016-1959-7, 2018. Kuppel, S., Y. Fan, and E.G. Jobbágy : 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, 2017. Peylin, P., C. Bacour, N. MacBean, S. Leonard, P. J. Rayner, S. Kuppel, E. Koffi, A. Kane, F. Maignan, F. Chevallier, P. Ciais, and P. Prunet : A new step-wise 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, 2016. Kuppel, S., J. Houspanossian, M.D. Nosetto, and E.G. Jobbágy : 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, 2015. Kuppel, S., P. Peylin, F. Maignan, F. Chevallier, G. Kiely, L. Montagnani, and A. Cescatti : Model–data fusion across ecosystems : from multi-site optimizations to global simulations. Geoscientific Model Development, 7, 2581–2597, doi:10.5194/gmd-7-2581-2014, 2014. Kuppel, S., F. Chevallier, and P. Peylin : Quantifying the model structural error in Carbon Cycle Data Assimilation Systems. Geoscientific Model Development, 6, 45–55, doi:10.5194/gmd-6-45-2013, 2013. Kameyama, N., T. Fukuyama, S. Wada, S. Kuppel, K. Tsumori, H. Nakano et al. : Analysis of the H- ion emissive surface in the extraction region of negative ion sources. Review of Scientific Instruments, 83 (2), 02A721, doi:10.1063/1.3673495, 2012. Kuppel, S., P. Peylin, F. Chevallier, C. Bacour, F. Maignan, and A.D. Richardson: Constraining a global ecosystem model with multi-site eddy-covariance data. Biogeosciences, 9, 3757–3776, doi:10.5194/bg-9-3757-2012, 2012. Kuppel, S., D. Matsushita, A. Hatayama, and M. Bacal : Numerical analysis of electronegative plasma in the extraction region of negative hydrogen ion sources. Journal of Applied Physics, 109(1), 013305, doi:10.1063/1.3530454, 2011. Wada, S., S. Kuppel, T. Fukuyama, K. Miyamoto, A. Hatayama, and M. Bacal : Numerical analysis of the extraction of volume produced negative hydrogen ions in the extraction region of negative ion source, AIP Conference Proceedings, 1390 (1), 58-67, doi:10.1063/1.3637375, 2011. Kuppel, S., D. Matsushita, A. Hatayama, and M. Bacal : Influence of the electron cross-field diffusion in negative ion sources with the transverse magnetic field and the plasma-electrode bias, Review of Scientific Instruments, 81, 02B503, doi:10.1063/1.3259165, 2010. Zani, L., P.-E. Gille, C. Gonzales, S. Kuppel, and A. Torre: Code development and validation towards modeling and diagnosing current redistribution in an ITER-type superconducting cable subject to current imbalance, Fusion Science and Technology, 56(2), 690–694, doi:10.13182/FST09-A8989 , 2009. Matsushita, D., S. Kuppel, A. Hatayama, and M. Bacal : Modeling of the Plasma Electrode Bias in the Negative Ion Sources with 1D PIC Method. AIP Conference Proceedings, 1097, 38–46, doi:10.1063/1.3112536, 2009. Kuppel, S., D. Matsushita, A. Hatayama, and M. Bacal : Numerical analysis of electronegative plasma near the extraction grid in negative ion sources. AIP Conference Proceedings, 1097, 55–64, doi:10.1063/1.3112549, 2009.
Tracer-informed critical zone modelling to connect water ages with hydrological resources and solute exports [link], France-Berkely Fund, 2021-2022.