Improvements to the Hybrid-Maize model for simulating maize yields in harsh rainfed environments
2017
Yang, Haishun | Grassini, Patricio | Cassman, Kenneth G. | Aiken, Robert M. | Coyne, Patrick I.
This paper reports revisions in formulation and new features of the Hybrid-Maize model (released as HM2016), to better simulate yields in harsh rainfed environments. Revisions include updated subroutines for root growth and distribution within the soil profile, greater sensitivity of canopy expansion and senescence to water deficits, an expanded kernel setting period, and soil evaporation as influenced by surface cover with crop residues. The updated model also includes routines for simulating surface runoff and estimating soil water content at sowing based on simulation of soil water balance during the preceding fallow period. Revisions of model functions were based on recent advances in understanding and quantification of maize response to environmental factors and management practices, as well as characteristics of new maize hybrids. More robust simulation of maize yield was obtained with the updated model under rainfed conditions, especially in years and locations with severe drought or on soils with limited water holding capacity. Capability to quantify soil water content at sowing and to perform batch simulations makes HM2016 more useful for pre-season yield projections in years with below-normal soil water recharge and for in-season yield forecasting across a wide range of environments. Revisions to routines governing root distribution and kernel setting make HM2016 a more powerful tool for evaluating hybrid-specific traits and crop management practices for ability to mitigate yield loss from water deficits and for identifying management options for individual production fields.
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