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    Global sensitivity analysis of crop yield and transpiration from the FAO-AquaCrop model for dryland environments

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    Type
    Article
    Authors
    Lu, Yang cc
    Chibarabada, Tendai P.
    McCabe, Matthew cc
    De Lannoy, Gabriëlle J.M.
    Sheffield, Justin
    KAUST Department
    Biological and Environmental Science and Engineering (BESE) Division
    Earth System Observation and Modelling
    Environmental Science and Engineering Program
    Water Desalination and Reuse Research Center (WDRC)
    KAUST Grant Number
    OSR-2017-CRG6
    Date
    2021-05-25
    Online Publication Date
    2021-05-25
    Print Publication Date
    2021-07
    Embargo End Date
    2023-05-25
    Submitted Date
    2020-06-19
    Permanent link to this record
    http://hdl.handle.net/10754/669278
    
    Metadata
    Show full item record
    Abstract
    The application of crop models towards improved local scale prediction and precision management requires the identification and description of the major factors influencing model performance. Such efforts are particularly important for dryland areas which face rapid population growth and increasing constraints on water supplies. In this study, a global sensitivity analysis on crop yield and transpiration was performed for 49 parameters in the FAO-AquaCrop model (version 6.0) across three dryland farming areas with different climatic conditions. The Morris screening method and the variance-based Extended Fourier Amplitude Sensitivity Test (EFAST) method were used to evaluate the parameter sensitivities of several staple crops (maize, soybean or winter wheat) under dry, normal and wet scenarios. Results suggest that parameter sensitivities vary with the target model output (e.g., yield, transpiration) and the wetness condition. By synthesizing parameter sensitivities under different scenarios, the key parameters affecting model performance under both high and low water stress were identified for the three crops. Overall, factors relevant to root development tended to have large impacts under high water stress, while those controlling maximum canopy cover and senescence were more influential under low water stress. Parameter sensitivities were also shown to be stage-dependent from a day-by-day analysis of canopy cover and biomass simulations. Subsequent comparison with AquaCrop version 5.0 suggests that AquaCrop version 6.0 is less sensitive to uncertainties in soil properties.
    Citation
    Lu, Y., Chibarabada, T. P., McCabe, M. F., De Lannoy, G. J. M., & Sheffield, J. (2021). Global sensitivity analysis of crop yield and transpiration from the FAO-AquaCrop model for dryland environments. Field Crops Research, 269, 108182. doi:10.1016/j.fcr.2021.108182
    Sponsors
    This work was partly funded through the ‘A new paradigm in precision agriculture: assimilation of ultra-fine resolution data into a crop-yield forecasting model’ project, supported by the King Abdullah University of Science and Technology, grant number OSR-2017-CRG6, and through the ‘Building REsearch Capacity for sustainable water and food security In drylands of sub-saharan Africa (BRECcIA)’ project, which is supported by UK Research and Innovation as part of the Global Challenges Research Fund, grant number NE/P021093/1. Matthew McCabe was funded by KAUST. G. De Lannoy was funded by EU project SHui GA 773903. The authors thank Dr. Francesca Pianosi from University of Bristol for her help in performing the sensitivity analysis.
    Publisher
    Elsevier BV
    Journal
    Field Crops Research
    DOI
    10.1016/j.fcr.2021.108182
    Additional Links
    https://linkinghub.elsevier.com/retrieve/pii/S0378429021001283
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.fcr.2021.108182
    Scopus Count
    Collections
    Articles; Biological and Environmental Science and Engineering (BESE) Division; Environmental Science and Engineering Program; Water Desalination and Reuse Research Center (WDRC)

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