Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.240
IF5.240
IF 5-year value: 5.768
IF 5-year
5.768
CiteScore value: 8.9
CiteScore
8.9
SNIP value: 1.713
SNIP1.713
IPP value: 5.53
IPP5.53
SJR value: 3.18
SJR3.18
Scimago H <br class='widget-line-break'>index value: 71
Scimago H
index
71
h5-index value: 51
h5-index51
GMD | Articles | Volume 11, issue 7
Geosci. Model Dev., 11, 3045–3069, 2018
https://doi.org/10.5194/gmd-11-3045-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 11, 3045–3069, 2018
https://doi.org/10.5194/gmd-11-3045-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model evaluation paper 31 Jul 2018

Model evaluation paper | 31 Jul 2018

EcH2O-iso 1.0: water isotopes and age tracking in a process-based, distributed ecohydrological model

Sylvain Kuppel et al.

Related authors

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)
Vladislav Bastrikov, Natasha MacBean, Cédric Bacour, Diego Santaren, Sylvain Kuppel, and Philippe Peylin
Geosci. Model Dev., 11, 4739–4754, https://doi.org/10.5194/gmd-11-4739-2018,https://doi.org/10.5194/gmd-11-4739-2018, 2018
Short summary
A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle
Philippe Peylin, Cédric Bacour, Natasha MacBean, Sébastien Leonard, Peter Rayner, Sylvain Kuppel, Ernest Koffi, Abdou Kane, Fabienne Maignan, Frédéric Chevallier, Philippe Ciais, and Pascal Prunet
Geosci. Model Dev., 9, 3321–3346, https://doi.org/10.5194/gmd-9-3321-2016,https://doi.org/10.5194/gmd-9-3321-2016, 2016
Short summary
Model–data fusion across ecosystems: from multisite optimizations to global simulations
S. Kuppel, P. Peylin, F. Maignan, F. Chevallier, G. Kiely, L. Montagnani, and A. Cescatti
Geosci. Model Dev., 7, 2581–2597, https://doi.org/10.5194/gmd-7-2581-2014,https://doi.org/10.5194/gmd-7-2581-2014, 2014
Short summary
Quantifying the model structural error in carbon cycle data assimilation systems
S. Kuppel, F. Chevallier, and P. Peylin
Geosci. Model Dev., 6, 45–55, https://doi.org/10.5194/gmd-6-45-2013,https://doi.org/10.5194/gmd-6-45-2013, 2013

Related subject area

Hydrology
The latest improvements with SURFEX v8.0 of the Safran–Isba–Modcou hydrometeorological model for France
Patrick Le Moigne, François Besson, Eric Martin, Julien Boé, Aaron Boone, Bertrand Decharme, Pierre Etchevers, Stéphanie Faroux, Florence Habets, Matthieu Lafaysse, Delphine Leroux, and Fabienne Rousset-Regimbeau
Geosci. Model Dev., 13, 3925–3946, https://doi.org/10.5194/gmd-13-3925-2020,https://doi.org/10.5194/gmd-13-3925-2020, 2020
Short summary
A multirate mass transfer model to represent the interaction of multicomponent biogeochemical processes between surface water and hyporheic zones (SWAT-MRMT-R 1.0)
Yilin Fang, Xingyuan Chen, Jesus Gomez Velez, Xuesong Zhang, Zhuoran Duan, Glenn E. Hammond, Amy E. Goldman, Vanessa A. Garayburu-Caruso, and Emily B. Graham
Geosci. Model Dev., 13, 3553–3569, https://doi.org/10.5194/gmd-13-3553-2020,https://doi.org/10.5194/gmd-13-3553-2020, 2020
Short summary
MFIT 1.0.0: Multi-Flow Inversion of Tracer breakthrough curves in fractured and karst aquifers
Jacques Bodin
Geosci. Model Dev., 13, 2905–2924, https://doi.org/10.5194/gmd-13-2905-2020,https://doi.org/10.5194/gmd-13-2905-2020, 2020
Short summary
Simulator for Hydrologic Unstructured Domains (SHUD v1.0): numerical modeling of watershed hydrology with the finite volume method
Lele Shu, Paul A. Ullrich, and Christopher J. Duffy
Geosci. Model Dev., 13, 2743–2762, https://doi.org/10.5194/gmd-13-2743-2020,https://doi.org/10.5194/gmd-13-2743-2020, 2020
Short summary
HydroMix v1.0: a new Bayesian mixing framework for attributing uncertain hydrological sources
Harsh Beria, Joshua R. Larsen, Anthony Michelon, Natalie C. Ceperley, and Bettina Schaefli
Geosci. Model Dev., 13, 2433–2450, https://doi.org/10.5194/gmd-13-2433-2020,https://doi.org/10.5194/gmd-13-2433-2020, 2020
Short summary

Cited articles

Ala-aho, P., Tetzlaff, D., McNamara, J. P., Laudon, H., and Soulsby, C.: Using isotopes to constrain water flux and age estimates in snow-influenced catchments using the STARR (Spatially distributed Tracer-Aided Rainfall–Runoff) model, Hydrol. Earth Syst. Sci., 21, 5089–5110, https://doi.org/10.5194/hess-21-5089-2017, 2017. a, b, c, d, e
Albrektson, A.: Sapwood basal area and needle mass of Scots pine (Pinus sylvestris L.) trees in central Sweden, Forestry, 57, 35–43, 1984. a
Allison, G. B. and Leaney, F. W.: Estimation of isotopic exchange parameters, using constant-feed pans, J. Hydrol., 55, 151–161, https://doi.org/10.1016/0022-1694(82)90126-3, 1982. a
Barnes, C. J. and Bonell, M.: Application of unit hydrograph techniques to solute transport in catchments, Hydrol. Process., 10, 793–802, 1996. a
Benettin, P., Soulsby, C., Birkel, C., Tetzlaff, D., Botter, G., and Rinaldo, A.: Using SAS functions and high-resolution isotope data to unravel travel time distributions in headwater catchments, Water Resour. Res., 53, 1864–1878, 2017. a, b
Publications Copernicus
Download
Short summary
This paper presents a novel ecohydrological model in which both the fluxes of water and the relative concentration in stable isotopes (2H and 18O) can be simulated. Spatial heterogeneity, lateral transfers and plant-driven water use are incorporated. A thorough evaluation shows encouraging results using a wide range of in situ measurements from a Scottish catchment. The same modelling principles are then used to simulate how (and where) precipitation ages as water transits in the catchment.
This paper presents a novel ecohydrological model in which both the fluxes of water and the...
Citation