Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications

PLoS One. 2017 Nov 6;12(11):e0187485. doi: 10.1371/journal.pone.0187485. eCollection 2017.

Abstract

Process-based models can be usefully employed for the assessment of field and regional-scale impact of drought on crop yields. However, in many instances, especially when they are used at the regional scale, it is necessary to identify the parameters and input variables that most influence the outputs and to assess how their influence varies when climatic and environmental conditions change. In this work, two different crop models, able to represent yield response to water, Aquacrop and SAFYE, were compared, with the aim to quantify their complexity and plasticity through Global Sensitivity Analysis (GSA), using Morris and EFAST (Extended Fourier Amplitude Sensitivity Test) techniques, for moderate to strong water limited climate scenarios. Although the rankings of the sensitivity indices was influenced by the scenarios used, the correlation among the rankings, higher for SAFYE than for Aquacrop, assessed by the top-down correlation coefficient (TDCC), revealed clear patterns. Parameters and input variables related to phenology and to water stress physiological processes were found to be the most influential for Aquacrop. For SAFYE, it was found that the water stress could be inferred indirectly from the processes regulating leaf growth, described in the original SAFY model. SAFYE has a lower complexity and plasticity than Aquacrop, making it more suitable to less data demanding regional scale applications, in case the only objective is the assessment of crop yield and no detailed information is sought on the mechanisms of the stress factors affecting its limitations.

MeSH terms

  • Agricultural Irrigation*
  • Climate
  • Crops, Agricultural*
  • Models, Theoretical*
  • Triticum*
  • Water*

Substances

  • Water

Grants and funding

PhD scholarship to Paolo Cosmo Silvestro under European Space Agency contract 4000110311/14/I-BG; European Space Agency Dragon 3 Project ID 10448 (https://dragon3.esa.int); Agreement on scientific cooperation between Consiglio Nazionale delle Ricerche and China Academy of Science 2014-2016; Chinese National Science and Technology Support Program grant 2012BAH29B00 to Guijun Yang; Chinese State Key Basic Project grant 2013CB733404 to Hao Yang; University of Tuscia funding to Paolo Cosmo Silvestro. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.