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Título: | Improving cereal yield forecasts in Europe – The impact of weather extremes |
Autor: | Pagani, Valentina; Guarneri, Tommaso; Fumagalli, Davide; Movedi, Ermes; Testi, Luca CSIC ORCID ; Klein, Tommy; Calanca, Pierluigi; Villalobos, Francisco J. CSIC ORCID ; López-Bernal, Álvaro CSIC ORCID; Niemeyer, Stefano; Bellocchi, Gianni; Confalonieri, Roberto | Palabras clave: | Agro-climatic indicators CGMS Crop model Extreme weather events WOFOST Yield forecasting |
Fecha de publicación: | sep-2017 | Editor: | Elsevier | Citación: | European Journal of Agronomy 89: 97-106 (2017) | Resumen: | 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. | Versión del editor: | https://doi.org/10.1016/j.eja.2017.06.010 | URI: | http://hdl.handle.net/10261/166838 | DOI: | 10.1016/j.eja.2017.06.010 | ISSN: | 1161-0301 |
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