Data di Pubblicazione:
2017
Citazione:
Improving cereal yield forecast in Europe - the impact of weather extremes / V. Pagani, T. Guarneri, D. Fumagalli, E. Movedi, L. Testi, T. Klein, P. Calanca, F. Villalobos, A. Lopez-Bernal, S. Niemeyer, G. Bellocchi, R. Confalonieri. - In: EUROPEAN JOURNAL OF AGRONOMY. - ISSN 1161-0301. - 89:(2017 Sep), pp. 97-106. [10.1016/j.eja.2017.06.010]
Abstract:
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 agroclimatic indicators to the workflow mostly added accuracy to an already satisfactory forecasting system.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
agro-climatic indicators; CGMS; crop model; extreme weather events; WOFOST; yield forecasting
Elenco autori:
V. Pagani, T. Guarneri, D. Fumagalli, E. Movedi, L. Testi, T. Klein, P. Calanca, F. Villalobos, A. Lopez-Bernal, S. Niemeyer, G. Bellocchi, R. Confalonieri
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