Can Agrometeorological Indices of Adverse Weather Conditions Help to Improve Yield Prediction by Crop Models? (CROSBI ID 211896)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Lalić, Branislava ; Eitzinger, Josef ; Thaler, Sabina ; Vučetić, Višnjica ; Nejedlik, Pavol ; Eckersten, Henrik ; Jačimović, Goran ; Nikolić-Đorić, Emilija
engleski
Can Agrometeorological Indices of Adverse Weather Conditions Help to Improve Yield Prediction by Crop Models?
Extreme weather event (EWE) impact on crop production is random in time and space and depends on factors such as severity, previous agrometeorological conditions and plant vulnerability at a specific crop development stage. Any exclusion or improper treatment of any of these factors for yield prediction by crop models can produce significant under- or over-estimation of yield. Inherent uncertainty of soil-plant-atmosphere system increases in presence of EWE implying only consideration of probability of yield realisation scenario instead of certain event itself. Assessment of errors and level of uncertainties in simulations can therefore lead to more efficient use of crop models in presence of EWE, rather than its reduction or elimination. However, a completely statistical "event scenario" approach, based on correlations between agrometeorological indices and long term crop yield and EWE data series, can produce typical scenarios for certain location, crop type and EWE pattern and therefore improve yield forecasting in presence of EWE.
extreme weather event; crop models; plant vulnerability; yields
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