4.6 Article

Towards a more flexible representation of water stress effects in the nonlinear Jarvis model

Journal

JOURNAL OF INTEGRATIVE AGRICULTURE
Volume 16, Issue 1, Pages 210-220

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/S2095-3119(15)61307-7

Keywords

summer maize; stomatal conductance; water status; recovery compensation; water stress indicators; Jarvis model

Funding

  1. Programme of Introducing Talents of Discipline to Universities, China [B12007]
  2. National Natural Science Foundation of China [51179162]
  3. National Key Technoloies R&D Program of China [2011BAD29B01]

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To better interpret summer maize stomatal conductance (g(s)) variation under conditions of changing water status at different growth stages, three water stress indicators, soil water content (SWC), leaf-air temperature difference (Delta T) and leaf level water stress index (CWSIL) were employed in Jarvis model, which were J(s), J(T) and J(C) models respectively. Measurements of g(s) were conducted in a summer maize field experiment during the year 2012-2013. In the insufficient irrigation experiment, three levels of irrigation amount were applied at four different growth stages of summer maize. We constructed three scenarios to evaluate the performance of the three water stress indicators for estimating maize g(s) in a modified Jarvis model. Results showed that J(T) and J(C) models had, better simulation accuracy than the model, especially at the late growth stage (Scenario 1) or considering the plant recovery compensation effects (Scenario 2). Scenario 3 indicated that the more environmental factors were adopted, the better prediction performance would be for J(S) model. While for J(T) model, two environmental factors (photosynthesis active radiation (PAR), and vapor pressure deficit (VPD)) seemed good enough to obtain a reliable simulation. When there were insufficient environmental data, CWSIL would be the bet option. This study can be useful to understand the response of plant stomatal to changing water conditions and will further facilitate the application of the Jarvis model in various environments.

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