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Sensitivity analysis of simulated Lycium barbarum L. yield in the WOFOST model under different climate conditions

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  • Wang, Zhaoyang
  • Shi, Yinfang
  • Hou, Cheng
  • Zhang, Puhan

Abstract

Calibrating process-based crop models in a timely manner is often challenging due to the extensive range of parameters involved. Sensitivity analysis (SA) is a useful practice for analyzing model uncertainty in these parameters. In this study, the Morris and extended Fourier Amplitude Sensitivity Test (E-FAST) methods were employed in sub-model level experiments. The yield outputs of WOFOST model under different climate conditions were used to evaluate the impact of altering model parameters in the modeling of Lycium barbarum L. The results indicate that parameters associated with CO2 assimilation rate, leaf area expansion and thermal time during specific periods have a significant impact on the simulated yield. The sensitive parameter rankings obtained from E-FAST exhibited good concordance across each planting site, and both SA methods consistently revealed similar rankings. This study provided a strategy to efficiently verify the applicability of new crop model parameters in different regions.

Suggested Citation

  • Wang, Zhaoyang & Shi, Yinfang & Hou, Cheng & Zhang, Puhan, 2024. "Sensitivity analysis of simulated Lycium barbarum L. yield in the WOFOST model under different climate conditions," Ecological Modelling, Elsevier, vol. 488(C).
    • Handle: RePEc:eee:ecomod:v:488:y:2024:i:c:s0304380023003320
    DOI: 10.1016/j.ecolmodel.2023.110602
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    References listed on IDEAS

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    1. Paleari, Livia & Movedi, Ermes & Zoli, Michele & Burato, Andrea & Cecconi, Irene & Errahouly, Jabir & Pecollo, Eleonora & Sorvillo, Carla & Confalonieri, Roberto, 2021. "Sensitivity analysis using Morris: Just screening or an effective ranking method?," Ecological Modelling, Elsevier, vol. 455(C).
    2. Confalonieri, R. & Bellocchi, G. & Bregaglio, S. & Donatelli, M. & Acutis, M., 2010. "Comparison of sensitivity analysis techniques: A case study with the rice model WARM," Ecological Modelling, Elsevier, vol. 221(16), pages 1897-1906.
    3. Shi, Yinfang & Wang, Zhaoyang & Hou, Cheng & Zhang, Puhan, 2022. "Yield estimation of Lycium barbarum L. based on the WOFOST model," Ecological Modelling, Elsevier, vol. 473(C).
    4. Li, Zhibin & Feng, Bianbian & Wang, Wei & Yang, Xi & Wu, Pute & Zhuo, La, 2022. "Spatial and temporal sensitivity of water footprint assessment in crop production to modelling inputs and parameters," Agricultural Water Management, Elsevier, vol. 271(C).
    5. de Wit, Allard & Boogaard, Hendrik & Fumagalli, Davide & Janssen, Sander & Knapen, Rob & van Kraalingen, Daniel & Supit, Iwan & van der Wijngaart, Raymond & van Diepen, Kees, 2019. "25 years of the WOFOST cropping systems model," Agricultural Systems, Elsevier, vol. 168(C), pages 154-167.
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