Impacts of the Soil Water Transfer Parameterization on the Simulation of Evapotranspiration over a 14-Year Mediterranean Crop Succession

S. Garrigues EMMAH, INRA, Université d’Avignon et des Pays de Vaucluse, Avignon, France

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A. Boone CNRM, UMR3589, Météo-France, CNRS, Toulouse, France

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B. Decharme CNRM, UMR3589, Météo-France, CNRS, Toulouse, France

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A. Olioso EMMAH, INRA, Université d’Avignon et des Pays de Vaucluse, Avignon, France

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C. Albergel CNRM, UMR3589, Météo-France, CNRS, Toulouse, France

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J.-C. Calvet CNRM, UMR3589, Météo-France, CNRS, Toulouse, France

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S. Moulin EMMAH, INRA, Université d’Avignon et des Pays de Vaucluse, Avignon, France

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S. Buis EMMAH, INRA, Université d’Avignon et des Pays de Vaucluse, Avignon, France

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E. Martin CNRM, UMR3589, Météo-France, CNRS, Toulouse, France
IRSTEA, UR RECOVER, Aix-en-Provence, France

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Abstract

This paper presents a comparison of two water transfer schemes implemented in land surface models: a three-layer bulk reservoir model based on the force–restore scheme (FR) and a multilayer soil diffusion scheme (DIF) relying on explicit mass‐diffusive equations and a root profile. The performances of each model at simulating evapotranspiration (ET) over a 14-yr Mediterranean crop succession are compared when the standard pedotransfer estimates versus the in situ values of the soil parameters are used. The Interactions between Soil, Biosphere, and Atmosphere (ISBA) generic land surface model is employed. When the pedotransfer estimates of the soil parameters are used, the best performance scores are obtained with DIF. DIF provides more accurate simulations of soil evaporation and gravitational drainage. It is less sensitive to errors in the soil parameters compared to FR, which is strongly driven by the soil moisture at field capacity. When the in situ soil parameters are used, the performance of the FR simulations surpasses those of DIF. The use of the proper maximum available water content for the plant removes the bias in ET and soil moisture over the crop cycle with FR, while soil water stress is simulated too early and the transpiration is underestimated with DIF. Increasing the values of the root extinction coefficient and the proportion of homogeneous root distribution slightly improves the DIF performance scores. Spatiotemporal uncertainties in the soil parameters generate smaller uncertainties in ET simulated with DIF compared to FR, which highlights the robustness of DIF for large-scale applications.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Sébastien Garrigues, sebastien.garrigues@inra.fr

Abstract

This paper presents a comparison of two water transfer schemes implemented in land surface models: a three-layer bulk reservoir model based on the force–restore scheme (FR) and a multilayer soil diffusion scheme (DIF) relying on explicit mass‐diffusive equations and a root profile. The performances of each model at simulating evapotranspiration (ET) over a 14-yr Mediterranean crop succession are compared when the standard pedotransfer estimates versus the in situ values of the soil parameters are used. The Interactions between Soil, Biosphere, and Atmosphere (ISBA) generic land surface model is employed. When the pedotransfer estimates of the soil parameters are used, the best performance scores are obtained with DIF. DIF provides more accurate simulations of soil evaporation and gravitational drainage. It is less sensitive to errors in the soil parameters compared to FR, which is strongly driven by the soil moisture at field capacity. When the in situ soil parameters are used, the performance of the FR simulations surpasses those of DIF. The use of the proper maximum available water content for the plant removes the bias in ET and soil moisture over the crop cycle with FR, while soil water stress is simulated too early and the transpiration is underestimated with DIF. Increasing the values of the root extinction coefficient and the proportion of homogeneous root distribution slightly improves the DIF performance scores. Spatiotemporal uncertainties in the soil parameters generate smaller uncertainties in ET simulated with DIF compared to FR, which highlights the robustness of DIF for large-scale applications.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Sébastien Garrigues, sebastien.garrigues@inra.fr
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  • Best, M. J., and Coauthors, 2011: The Joint UK Land Environment Simulator (JULES), Model description – Part 1: Energy and water fluxes. Geosci. Model Dev., 4, 677699, https://doi.org/10.5194/gmd-4-677-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Béziat, P., E. Ceschia, and G. Dedieu, 2009: Carbon balance of a three crop succession over two cropland sites in south west France. Agric. For. Meteor., 149, 16281645, https://doi.org/10.1016/j.agrformet.2009.05.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bhumralkar, C. M., 1975: Numerical experiments on the computation of ground surface temperature in an atmospheric general circulation model. J. Appl. Meteor., 14, 12461258, https://doi.org/10.1175/1520-0450(1975)014<1246:NEOTCO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blackadar, A. K., 1976: Modeling the nocturnal boundary layer. Preprints, Third Symp. on Atmospheric Turbulence, Diffusion and Air Quality, Raleigh, NC, Amer. Meteor. Soc., 46–49.

  • Blyth, E. M., and C. C. Daamen, 1997: The accuracy of simple soil water models in climate forecasting. Hydrol. Earth Syst. Sci., 1, 241248, https://doi.org/10.5194/hess-1-241-1997.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Boone, A., J.-C. Calvet, and J. Noilhan, 1999: Inclusion of a third soil layer in a land surface scheme using the force–restore method. J. Appl. Meteor., 38, 16111630, https://doi.org/10.1175/1520-0450(1999)038<1611:IOATSL>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Braud, I., J. Noilhan, P. Bessemoulin, P. Mascart, R. Haverkamp, and M. Vauclin, 1993: Bare ground surface heat and water exchanges under dry conditions: Observation and parameterization. Bound.-Layer Meteor., 66, 173200, https://doi.org/10.1007/BF00705465.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Braud, I., N. Varado, and A. Olioso, 2005: Comparison of root water uptake modules using either the surface energy balance or potential transpiration. J. Hydrol., 301, 267286, https://doi.org/10.1016/j.jhydrol.2004.06.033.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brooks, R. H., and A. T. Corey, 1966: Properties of porous media affecting fluid flow. J. Irrig. Drain. Div., Amer. Soc. Civ. Eng., 92, 6190.

    • Search Google Scholar
    • Export Citation
  • Calvet, J.-C., J. Noilhan, J.-L. Roujean, P. Bessemoulin, M. Cabelguenne, A. Olioso, and J.-P. Wigneron, 1998: An interactive vegetation SVAT model tested against data from six contrasting sites. Agric. For. Meteor., 92, 7395, https://doi.org/10.1016/S0168-1923(98)00091-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Calvet, J.-C., V. Rivalland, C. Picon-Cochard, and J.-M. Guehl, 2004: Modelling forest transpiration and CO2 fluxes—Response to soil moisture stress. Agric. For. Meteor., 124, 143156, https://doi.org/10.1016/j.agrformet.2004.01.007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Calvet, J.-C., S. Lafont, E. Cloppet, F. Souverain, V. Badeau, and C. Le Bas, 2012: Use of agricultural statistics to verify the interannual variability in land surface models: A case study over France with ISBA-A-gs. Geosci. Model Dev., 5, 3754, https://doi.org/10.5194/gmd-5-37-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Canal, N., J.-C. Calvet, B. Decharme, D. Carrer, S. Lafont, and G. Pigeon, 2014: Evaluation of root water uptake in the ISBA-A-gs land surface model using agricultural yield statistics over France. Hydrol. Earth Syst. Sci., 18, 49794999, https://doi.org/10.5194/hess-18-4979-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clapp, R., and G. Hornberger, 1978: Empirical equations for some soil hydraulic properties. Water Resour. Res., 14, 601604, https://doi.org/10.1029/WR014i004p00601.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dai, Y., and Coauthors, 2003: The Common Land Model. Bull. Amer. Meteor. Soc., 84, 10131023, https://doi.org/10.1175/BAMS-84-8-1013.

  • Deardorff, J. W., 1977: A parameterization of ground surface moisture content for use in atmospheric prediction models. J. Appl. Meteor., 16, 11821185, https://doi.org/10.1175/1520-0450(1977)016<1182:APOGSM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Decharme, B., A. Boone, C. Delire, and J. Noilhan, 2011: Local evaluation of the Interaction between Soil Biosphere Atmosphere soil multilayer diffusion scheme using four pedotransfer functions. J. Geophys. Res., 116, D20126, https://doi.org/10.1029/2011JD016002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Decharme, B., E. Martin, and S. Faroux, 2013: Reconciling soil thermal and hydrological lower boundary conditions in land surface models. J. Geophys. Res. Atmos., 118, 78197834, https://doi.org/10.1002/jgrd.50631.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Decharme, B., E. Brun, A. Boone, C. Delire, P. Le Moigne, and S. Morin, 2016: Impacts of snow and organic soils parameterization on northern Eurasian soil temperature profiles simulated by the ISBA land surface model. Cryosphere, 10, 853877, https://doi.org/10.5194/tc-10-853-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • de Rosnay, P., M. Bruen, and J. Polcher, 2000: Sensitivity of surface fluxes to the number of layers in the soil model used in GCMs. Geophys. Res. Lett., 27, 33293332, https://doi.org/10.1029/2000GL011574.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • de Rosnay, P., and Coauthors, 2009: AMMA Land Surface Model Intercomparison experiment coupled to the Community Microwave Emission Model: ALMIP‐MEM. J. Geophys. Res., 114, D05108, https://doi.org/10.1029/2008JD010724.

    • Search Google Scholar
    • Export Citation
  • Desborough, C. E., 1997: The impact of root weighting on the response of transpiration to moisture stress in land surface schemes. Mon. Wea. Rev., 125, 19201930, https://doi.org/10.1175/1520-0493(1997)125<1920:TIORWO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dewar, R. C., 2002: The Ball–Berry–Leuning and Tardieu–Davies stomatal models: Synthesis and extension within a spatially aggregated picture of guard cell function. Plant Cell Environ., 25, 13831398, https://doi.org/10.1046/j.1365-3040.2002.00909.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • dos Santos, M. A., Q. de Jong van Lier, J. C. van Dam, and A. H. Freire Bezerra, 2017: Benchmarking test of empirical root water uptake models. Hydrol. Earth Syst. Sci., 21, 473493, https://doi.org/10.5194/hess-21-473-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Egea, G., A. Verhoef, and P. L. Vidale, 2011: Towards an improved and more flexible representation of water stress in coupled photosynthesis–stomatal conductance models. Agric. For. Meteor., 151, 13701384, https://doi.org/10.1016/j.agrformet.2011.05.019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Faroux, S., A. T. Kaptué Tchuenté, J.-L. Roujean, V. Masson, E. Martin, and P. Le Moigne, 2013: ECOCLIMAP-II/Europe: A twofold database of ecosystems and surface parameters at 1 km resolution based on satellite information for use in land surface, meteorological and climate models. Geosci. Model Dev., 6, 563582, https://doi.org/10.5194/gmd-6-563-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Foken, T., M. Göckede, M. Mauder, L. Mahrt, B. Amiro, and W. Munger, 2004: Post-field data quality control. Handbook of Micrometeorology: A Guide for Surface Flux Measurement and Analysis, X. Lee, W. Massman, and B. E. Law, Eds., Atmospheric and Oceanographic Sciences Library Series, Vol. 29, Springer, 181–208.

    • Crossref
    • Export Citation
  • Garrigues, S., A. Olioso, D. Carrer, B. Decharme, J.-C. Calvet, E. Martin, S. Moulin, and O. Marloie, 2015a: Impact of climate, vegetation, soil and crop management variables on multi-year ISBA-A-gs simulations of evapotranspiration over a Mediterranean crop site. Geosci. Model Dev., 8, 30333053, https://doi.org/10.5194/gmd-8-3033-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garrigues, S., and Coauthors, 2015b: Evaluation of land surface model simulations of evapotranspiration over a 12-year crop succession: Impact of soil hydraulic and vegetation properties. Hydrol. Earth Syst. Sci., 19, 31093131, https://doi.org/10.5194/hess-19-3109-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gibelin, A.-L., J.-C. Calvet, J.-L. Roujean, L. Jarlan, and S. O. Los, 2006: Ability of the land surface model ISBA-A-gs to simulate leaf area index at the global scale: Comparison with satellites products. J. Geophys. Res., 111, D18102, https://doi.org/10.1029/2005JD006691.

    • Search Google Scholar
    • Export Citation
  • Goudriaan, J., H. H. van Laar, H. van Keulen, and W. Louwerse, 1985: Photosynthesis, CO2 and plant production. Wheat Growth and Modeling, W. Day and R. K. Atkin, Eds., NATO ASI Series A: Life Sciences, Vol. 86, Plenum Press, 107–122.

    • Crossref
    • Export Citation
  • Habets, F., A. Boone, and J. Noilhan, 2003: Simulation of a Scandinavian basin using the diffusion transfer version of ISBA. Global Planet. Change, 38, 137149, https://doi.org/10.1016/S0921-8181(03)00016-X.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Habets, F., and Coauthors, 2008: The SAFRAN-ISBA-MODCOU hydrometeorological model applied over France. J. Geophys. Res., 113, D06113, https://doi.org/10.1029/2007JD008548.

    • Search Google Scholar
    • Export Citation
  • Jackson, R. B., J. Canadell, J. R. Ehleringer, H. A. Mooney, O. E. Sala, and E. D. Schulze, 1996: A global analysis of root distributions for terrestrial biomes. Oecologia, 108, 389411, https://doi.org/10.1007/BF00333714.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jacobs, C. M. J., B. M. M. van den Hurk, and H. A. R. de Bruin, 1996: Stomatal behaviour and photosynthetic rate of unstressed grapevines in semi-arid conditions. Agric. For. Meteor., 80, 111134, https://doi.org/10.1016/0168-1923(95)02295-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jarvis, N. J., 2011: Simple physics-based models of compensatory plant water uptake: Concepts and eco-hydrological consequences. Hydrol. Earth Syst. Sci., 15, 34313446, https://doi.org/10.5194/hess-15-3431-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Javaux, M., V. Couvreur, J. Vanderborght, and H. Vereecken, 2013: Root water uptake: From three-dimensional biophysical processes to macroscopic modeling approaches. Vadose Zone J., 12, https://doi.org/10.2136/vzj2013.02.0042.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johnsson, H., and L.-C. Lundin, 1991: Surface runoff and soil water percolation as affected by snow and soil frost. J. Hydrol., 122, 141159, https://doi.org/10.1016/0022-1694(91)90177-J.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kutilek, M., and D. R. Nielsen, 1994: Soil Hydrology. Catena Verlag, 370 pp.

  • Mahfouf, J.-F., and J. Noilhan, 1991: Comparative study of various formulations of evaporations from bare soil using in situ data. J. Appl. Meteor., 30, 13541365, https://doi.org/10.1175/1520-0450(1991)030<1354:CSOVFO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mahfouf, J.-F., and J. Noilhan, 1996: Inclusion of gravitational drainage in a land surface scheme based on the force–restore method. J. Appl. Meteor., 35, 987992, https://doi.org/10.1175/1520-0450(1996)035<0987:IOGDIA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Manzi, A. O., and S. Planton, 1994: Implementation of the ISBA parameterization scheme for land surface processes in a GCM: An annual cycle experiment. J. Hydrol., 155, 353389, https://doi.org/10.1016/0022-1694(94)90178-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Masson, V., and Coauthors, 2013: The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes. Geosci. Model Dev., 6, 929960, https://doi.org/10.5194/gmd-6-929-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mauder, M., M. Cuntz, C. Drüe, A. Graf, C. Rebmann, H. P. Schmid, M. Schmidt, and R. Steinbrecher, 2013: A strategy for quality and uncertainty assessment of long-term eddy-covariance measurements. Agric. For. Meteor., 169, 122135, https://doi.org/10.1016/j.agrformet.2012.09.006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Metselaar, K., and Q. de Jong van Lier, 2007: The shape of the transpiration reduction function under plant water stress. Vadose Zone J., 6, 124139, https://doi.org/10.2136/vzj2006.0086.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Montaldo, N., and J. D. Albertson, 2001: On the use of the force–restore SVAT model formulation for stratified soils. J. Hydrometeor., 2, 571578, https://doi.org/10.1175/1525-7541(2001)002<0571:OTUOTF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moureaux, C., E. Ceschia, N. Arriga, P. Béziat, W. Eugster, W. L. Kutsch, and E. Pattey, 2012: Eddy covariance measurements over crops. Eddy Covariance: A Practical Guide to Measurement and Data Analysis, M. Aubinet, T. Vesala, and D. Papale, Eds., Springer Atmospheric Sciences Series, Vol. 2, Springer, 319–332.

    • Crossref
    • Export Citation
  • Noilhan, J., and S. Planton, 1989: A simple parameterization of land surface processes for meteorological models. Mon. Wea. Rev., 117, 536549, https://doi.org/10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Noilhan, J., and P. Lacarrère, 1995: GCM grid-scale evaporation from mesocale modeling. J. Climate, 8, 206223, https://doi.org/10.1175/1520-0442(1995)008<0206:GGSEFM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Noilhan, J., and J.-F. Mahfouf, 1996: The ISBA land surface parameterisation scheme. Global Planet. Change, 13, 145159, https://doi.org/10.1016/0921-8181(95)00043-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Olioso, A., and Coauthors, 2002: SVAT modeling over the Alpilles-ReSeDA experiment: Comparing SVAT models over wheat fields. Agron. J., 22, 651668, https://doi.org/10.1051/agro:2002054.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pan, H., and L. Mahrt, 1987: Interaction between soil hydrology and boundary layer development. Bound.-Layer Meteor., 38, 185202, https://doi.org/10.1007/BF00121563.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seneviratne, S. I., D. Lüthi, M. Litschi, and C. Schär, 2006: Land–atmosphere coupling and climate change in Europe. Nature, 443, 205209, https://doi.org/10.1038/nature05095.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sinclair, T. R., 2005: Theoretical analysis of soil and plant traits influencing daily plant water flux on drying soils. Agron. J., 97, 11481152, https://doi.org/10.2134/agronj2004.0286.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tardieu, F., and W. J. Davies, 1993: Integration of hydraulic and chemical signalling in the control of stomatal conductance and water status of droughted plants. Plant Cell Environ., 16, 341349, https://doi.org/10.1111/j.1365-3040.1993.tb00880.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van den Hurk, B., and Coauthors, 2016: LS3MIP (v1.0) contribution to CMIP6: The Land Surface, Snow and Soil moisture Model Intercomparison Project—Aims, setup and expected outcome. Geosci. Model Dev., 9, 28092832, https://doi.org/10.5194/gmd-9-2809-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vergnes, J.-P., B. Decharme, and F. Habets, 2014: Introduction of groundwater capillary rises using subgrid spatial variability of topography into the ISBA land surface model. J. Geophys. Res. Atmos., 119, 11 06511 086, https://doi.org/10.1002/2014JD021573.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Verhoef, A., and G. Egea, 2014: Modeling plant transpiration under limited soil water: Comparison of different plant and soil hydraulic parameterizations and preliminary implications for their use in land surface models. Agric. For. Meteor., 191, 2232, https://doi.org/10.1016/j.agrformet.2014.02.009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Viterbo, P., and A. C. M. Beljaars, 1995: An improved land surface parametrization scheme in the ECMWF model and its validation. J. Climate, 8, 27162748, https://doi.org/10.1175/1520-0442(1995)008<2716:AILSPS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vrugt, J. A., C. J. F. ter Braak, H. V. Gupta, and B. A. Robinson, 2009: Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling? Stochastic Environ. Res. Risk Assess., 23, 10111026, https://doi.org/10.1007/s00477-008-0274-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, S., R. A. Duursma, B. E. Medlyn, J. W. G. Kelly, and I. C. Prentice, 2013: How should we model plant responses to drought? An analysis of stomatal and non-stomatal responses to water stress. Agric. For. Meteor., 182–183, 204214, https://doi.org/10.1016/j.agrformet.2013.05.009.

    • Crossref
    • Search Google Scholar
    • Export Citation
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