Project
Assessment of realistic climate change impacts on start and length of cropping season in the Netherlands
One of the main adaptation strategies adopted by the farmers to face climate change is to shift sowing (and, therefore, emergence) and harvest dates. Mechanistic crop models enable researchers to simulate future climate impacts on crop growth and development. However, setting sowing/emergence and harvest dates (input values) in such simulations remains often at the user’s discretion. Modelers can account for climate change adaptation by using rule-based approaches to estimate optimal sowing and emergence dates, usually basing this assessment on a few meteorological variables (e.g. air temperature and rainfall in a given period), while harvest dates are usually set at crop maturity (modeled). This approach rarely mimics what happens in reality, where the farmer’s decision is more complex and non-optimal[1], and includes considerations on soil trafficability, bolting risk, preceding crop/catch crop, weed competition, weather forecasts, workforce organization, etc [1] van Oort et al. (2012) doi:10.1016/j.eja.2012.02.005
The project aims to predict realistic emergence and harvest dates of the main seasonal crops under future climate in the Netherlands, using innovative AI models and data sources obtained through a collaboration of science groups within WUR. The outputs will help crop modelers to set a realistic start and length of cropping seasons (deliverable: dataset and spatial data) in their studies of climate impacts on crop growth and development, and will provide to a broader public a visual representation of the predicted changes in cropping seasons under future climate (deliverable: interactive app), broadening and strengthening WUR climate solutions portfolio.