Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements

Harper Anna B., Williams Karina E., McGuire Patrick C., Duran Rojas Maria Carolina, Hemming Debbie, Verhoef Anna, Huntingford Chris, Rowland Lucy, Marthews Toby, Breder Eller Cleiton, Mathison Camilla, Nobrega Rodolfo L. B., Gedney Nicola, Vidale Pier Luigi, Otu-Larbi Fred, Pandey Divya, Garrigues Sebastien, Wright Azin, Slevin Darren, De Kauwe Martin G., Blyth Eleanor, Ardö Jonas, Black Andrew, Bonal Damien, Buchmann Nina, Burban Benoit, Fuchs Kathrin, De Grandcourt Agnès, Mammarella Ivan, Merbold Lutz, Montagnani Leonardo, Nouvellon Yann, Restrepo-Coupe Natalia, Wohlfahrt Georg. 2021. Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements. GeoScientific Model Development, 14 : 3269-3294.

https://doi.org/10.5194/gmd-14-3269-2021

Article de revue ; Article de recherche ; Article de revue à facteur d'impact

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Url - jeu de données - Entrepôt autre : https://fluxnet.org/data/fluxnet2015-dataset/

Quartile : Q1, Sujet : GEOSCIENCES, MULTIDISCIPLINARY

Résumé : Drought is predicted to increase in the future due to climate change, bringing with it myriad impacts on ecosystems. Plants respond to drier soils by reducing stomatal conductance in order to conserve water and avoid hydraulic damage. Despite the importance of plant drought responses for the global carbon cycle and local and regional climate feedbacks, land surface models are unable to capture observed plant responses to soil moisture stress. We assessed the impact of soil moisture stress on simulated gross primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land Environment Simulator (JULES) vn4.9 on seasonal and annual timescales and evaluated 10 different representations of soil moisture stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high-latitude (cold-region) sites, while LE was best simulated in temperate and high-latitude (cold) sites. Errors that were not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savanna and deciduous forest sites. We found that three alternative approaches to calculating soil moisture stress produced more realistic results than the default parameterization for most biomes and climates. All of these involved increasing the number of soil layers from 4 to 14 and the soil depth from 3.0 to 10.8 m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation (the “soil14_psi” experiments), when the critical threshold value for inducing soil moisture stress was reduced (“soil14_p0”), and when plants were able to access soil moisture in deeper soil layers (“soil14_dr*2”). For LE, the biases were highest in the default configuration in temperate mixed forests, with overestimation occurring during most of the year. At these sites, reducing soil moisture stress (with the new parameterizations mentioned above) increased LE and increased model biases but improved the simulated seasonal cycle and brought the monthly variance closer to the measured variance of LE. Further evaluation of the reason for the high bias in LE at many of the sites would enable improvements in both carbon and energy fluxes with new parameterizations for soil moisture stress. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES or as a general way to improve land surface carbon and water fluxes in other models. In addition, using soil matric potential presents the opportunity to include plant functional type-specific parameters to further improve modeled fluxes.

Mots-clés Agrovoc : modélisation, modélisation environnementale, modèle de simulation, réponse de la plante, sécheresse, teneur en eau du sol, stress dû à la sécheresse

Mots-clés libres : Land Environment Simulator (JULES), Soil moisture stress, Gross primary productivity, Latent heat flux, Rooting depth

Classification Agris : F60 - Physiologie et biochimie végétale
H50 - Troubles divers des plantes
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 4 (2019-) - Santé des plantes, des animaux et des écosystèmes

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