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    Joël Léonard
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    Joël Léonard

    ORCID Scholar
    机构: INRAE, BioEcoAgro Joint Research Unit
    每年引用次数
    引用次数
    引用: 2,926
    H-指数: 24
    I10-指数 : 37
    出版物: 143
    标题
    引用次数
    年份
    A multi-model assessment of C cycling and soil C sequestration in grasslands and croplands

    Renata Sandor , Fiona Ehrhardt , Bruno Basso , Gianni Bellocchi
    6th International Symposium on Soil Organic Matter; Harpenden (Royaume Uni) 2 -2

    2017
    Short-term impacts of the summer 2019 heatwave on ecosystem functioning inferred from ICOS flux towers in France

    Pauline Buysse , R Fléchard Chris , Nicolas Martin-StPaul , Sébastien Lafont
    ICOS Science Conférence

    2020
    Quantification et modélisation de la production et des bilans C et N en systèmes de culture biologiques (AB)

    Nicolas Beaudoin , Bénédicte Autret , Lucia Rakotovololona , Aïcha Ronceux

    Modelling CO2 and N2O emissions from a tropical semi-arid parkland cultivated with groundnut and millet

    Yélognissè Agbohessou , Seydina Ba , Fabien Ferchaud , Joël Léonard
    EGU24 ( EGU24-7588)

    2024
    Modeling Denitrification: Can We Report What We Don't Know?

    B Grosz , Amanda Matson , K Butterbach‐Bahl , Timothy Clough
    AGU Advances 4 ( 6) e2023AV000990 -e2023AV000990

    3
    2023
    Sources of uncertainty in simulating crop N2O emissions under contrasting environmental conditions

    Sibylle Dueri , Joël Léonard , Florent Chlebowski , Pablo Rosso
    Agricultural and Forest Meteorology 340 109619 -109619

    2
    2023
    How modelers model: the overlooked social and human dimensions in model intercomparison studies

    Fabrizio Albanito , David McBey , Matthew Harrison , Pete Smith
    Environmental Science & Technology 56 ( 18) 13485 -13498

    7
    2022
    There is a growing realization that the complexity of model ensemble studies depends not only on the models used but also on the experience and approach used by modelers to calibrate and validate results, which remain a source of uncertainty. Here, we applied a multi-criteria decision-making method to investigate the rationale applied by modelers in a model ensemble study where 12 process-based different biogeochemical model types were compared across five successive calibration stages. The modelers shared a common level of agreement about the importance of the variables used to initialize their models for calibration. However, we found inconsistency among modelers when judging the importance of input variables across different calibration stages. The level of subjective weighting attributed by modelers to calibration data decreased sequentially as the extent and number of variables provided increased. In this context, the perceived importance attributed to variables such as the fertilization rate, irrigation regime, soil texture, pH, and initial levels of soil organic carbon and nitrogen stocks was statistically different when classified according to model types. The importance attributed to input variables such as experimental duration, gross primary production, and netecosystem exchange varied significantly according to the length of the modeler’s experience. We argue that the gradual access to input data across the five calibration stages negatively influenced the consistency of the interpretations made by the modelers, with cognitive bias in “trial-and-error” calibration routines. Our study highlights that overlooking human and social attributes is critical in the outcomes of modeling and model intercomparison studies. While complexity of the processes captured in the model algorithms and parameterization is important, we contend that (1) the modeler’s assumptions on the extent to which parameters should be altered and (2) modeler perceptions of the importance of model parameters are just as critical in obtaining a quality model calibration as numerical or analytical details.

    Fabrizio Albanito , David Mcbey , Matthew Harrison , Pete Smith

    2022
    Conceptual basis, formalisations and parameterization of the STICS crop model

    Nicolas Beaudoin , Dominique Ripoche , L Strullu , Bruno Mary
    iCROPM2020 Symposium-Crop Modelling for The Future 73 p. -73 p.

    6
    2020
    STICS: a generic and robust soil-crop model for modelling agrosystems response in various climatic conditions

    Nicolas Beaudoin , Samuel Buis , Dominique Ripoche , Eric Justes

    2015
    Evaluation of mitigation practices to attenuate N2O emission and increase soil C stock: a multi-model assessment in five croplands worldwide

    Marco Carozzi , Gianni Bellocchi , Fiona Ehrhardt , Lorenzo Brilli
    International Crop Modelling Symposium (iCROPM2020)

    2020
    Pan‐European Soil Erodibility Assessment

    Yves Le Bissonnais , Olivier Cerdan , Joël Léonard , Joël Daroussin
    Soil erosion in Europe 685 -693

    3
    2006
    Physical degradation of agricultural and forest soils due to compaction

    Jean Roger-Estrade , Dominique Arrouays , Vincent Adamiade , Edouard Baranger

    2011
    Revealing trade-offs in cropping systems sustainability by piecing together pedo-climatic datasets and agronomic knowledge with fuzzy logic

    Roberta Calone , Angela Fiore , Maria Luz Cayuela , Alessandra Lagomarsino
    EGU General Assembly Conference Abstracts EGU -13636

    2023
    Accuracy, robustness and behavior of the STICS soil–crop model for plant, water and nitrogen outputs: evaluation over a wide range of agro-environmental conditions in France

    Elsa Coucheney , Samuel Buis , Marie Launay , Julie Constantin
    Environmental Modelling & Software 64 177 -190

    203
    2015
    Multicriteria evaluation of the stics soil-crop model and implementation of an automated evaluation system

    Samuel Buis , Elsa Coucheney , Marie Launay , Patrice Lecharpentier
    iCROPM 2016 International Crop Modelling Symposium" Crop Modelling for Agriculture and Food Security under Global Change" 441 p. -441 p.

    2016
    A Preliminary Approach of 3D Simulation of Soil Surface Degradation by Rainfall.

    Gilles Valette , Michel Herbin , Laurent Lucas , Joël Léonard
    NPH 41 -49

    6
    2005
    A Non-Modular Cellular DEVS Model Of The Degradation Of A Cultivated Soil Surface By Rainfall

    Gilles Valette , Stéphanie Prévost , Laurent Lucas , Joël Léonard
    22nd Conference on Modelling and Simulation 285 -291

    2
    2008
    Simulation of rain splash using a genetic fuzzy system

    Gilles Valette , Stéphanie Prévost , Laurent Lucas , Joël Léonard
    11th IPMU International Conference. Paris

    1
    2006
    Review and analysis of strengths and weaknesses of agro-ecosystem models for simulating C and N fluxes

    Lorenzo Brilli , Luca Bechini , Marco Bindi , Marco Carozzi
    Science of The Total Environment 598 445 -470

    210
    2017
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