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Improving cereal yield forecasts in Europe – The impact of weather extremes
- Pagani, Valentina, Guarneri, Tommaso, Fumagalli, Davide, Movedi, Ermes, Testi, Luca, Klein, Tommy, Calanca, Pierluigi, Villalobos, Francisco, Lopez-Bernal, Alvaro, Niemeyer, Stefan, Bellocchi, Gianni, Confalonieri, Roberto
- European journal of agronomy 2017 v.89 pp. 97-106
- Mediterranean climate, cold, cold stress, crop production, drought, flowering, frost, grain crops, heat, heat stress, leaf development, models, monitoring, production technology, rain, spring barley, Poland
- The impact of extreme events (such as prolonged droughts, heat waves, cold shocks and frost) is poorly represented by most of the existing yield forecasting systems. Two new model-based approaches that account for the impact of extreme weather events on crop production are presented as a way to improve yield forecasts, both based on the Crop Growth Monitoring System (CGMS) of the European Commission. A first approach includes simple relations – consistent with the degree of complexity of the most generic crop simulators – to explicitly model the impact of these events on leaf development and yield formation. A second approach is a hybrid system which adds selected agro-climatic indicators (accounting for drought and cold/heat stress) to the previous one. The new proposed methods, together with the CGMS-standard approach and a system exclusively based on selected agro-climatic indicators, were evaluated in a comparative fashion for their forecasting reliability. The four systems were assessed for the main micro- and macro-thermal cereal crops grown in highly productive European countries. The workflow included the statistical post-processing of model outputs aggregated at national level with historical series (1995–2013) of official yields, followed by a cross-validation for forecasting events triggered at flowering, maturity and at an intermediate stage. With the system based on agro-climatic indicators, satisfactory performances were limited to microthermal crops grown in Mediterranean environments (i.e. crop production systems mainly driven by rainfall distribution). Compared to CGMS-standard system, the newly proposed approaches increased the forecasting reliability in 94% of the combinations crop×country×forecasting moment. In particular, the explicit simulation of the impact of extreme events explained a large part of the inter-annual variability (up to +44% for spring barley in Poland), while the addition of agro-climatic indicators to the workflow mostly added accuracy to an already satisfactory forecasting system.