Optimality-based modelling of wheat sowing dates globally

Wheat sowing dates are currently used as an input for crop models that simulated wheat production. However, the optimal time for planting wheat will be affected by climate changes and human adaptations to these changes. In this paper, we present an optimality-based modelling approach, with additional constraints from low temperature and precipitation intensity, to estimate wheat sowing dates globally. This approach assumes that wheat could be sown at any time when the climate conditions are suitable, but the optimal sowing date that would be adopted by farmers would be that which maximises overall grain yields. We therefore run the model starting on every possible sowing date as determined by the climate constraints and then select the date which gives the highest yield in each location. We compare the modelled optimal sowing dates with an updated version of observed sowing dates created by merging census-based datasets and local agronomic information. Cold season temperatures are the major determinant of sowing dates in the extra-tropics, whereas the seasonal cycle of monsoon rainfall plays an important role in determining sowing dates in the tropics. The model captures the timing of reported sowing dates, with difference between estimated and observed sowing dates of less than one month (< 30 days) over much of the world; maximum errors in tropical regions with large altitudinal gradients, such as Ethiopia, Bolivia and Peru, are up to two months. Discrepancies between the predictions and observations are larger in tropical regions than temperate and cold regions. Our approach for estimating optimal wheat sowing dates provides a way to examine human management decisions could mitigate the impacts of climate change on crop systems.