Global Sensitivity Analysis of WOFOST Model Parameters for Maize and Wheat Yield Simulation

Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
The dynamical simulation model of WOFOST is widely used for yield estimation at farm and regional scales as well as different climate conditions. In modelling processes, there are lots of parameters which have to be estimated (calibrated) and also in the other hand there are limitations for providing enough observational data. Therefor it is required to choose sensitive parameters for model calibration. In this study, a global sensitivity analysis has presented for maize and wheat simulation in WOFOST model. Global sensitivity analysis methods are useful tools to rank the model parameters based on their influence on model outputs and considering the entire range of parameters. In other words, these methods consider the influence of a unique parameter as well as the influence of its combinations with the other parameters. In this paper, Regional Sensitivity Analysis (RSA) method is applied as a global method and its results are discussed. The variations of sensitivity index for the two crops are obtained from minimum 0.006 (insensitive) to 0.37 (high sensitive). Furthermore, Results for maize crop showed that the parameters which are related to temperature process (TSUMAM, TSUMEA) and absorbed radiation (SLA, AMAX, EFF) are among the most influential parameters in simulation of maize crop yield. In case of wheat crop, only the parameters which are related to absorbed radiation process (SLA, RGRLAI, AMAX, and EFF) are identified as most influential parameters.
Language:
Persian
Published:
Iranian Journal of Soil and Water Research, Volume:49 Issue: 4, 2018
Pages:
831 to 839
https://www.magiran.com/p1857108  
سامانه نویسندگان
  • Shafiei، Mojtaba
    Corresponding Author (1)
    Shafiei, Mojtaba
    Researcher Hydrology and Water Management, مرکز پژوهشی آب و محیط زیست شرق
  • Ghahreman، Bijan
    Author (2)
    Ghahreman, Bijan
    Full Professor Water Engineering, Ferdowsi University, مشهد, Iran
  • Davary، Kamran
    Author (4)
    Davary, Kamran
    Professor water sciences & engineering, Ferdowsi University, مشهد, Iran
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