Seasonal forecasting of green water components and crop yield of summer crops in Serbia and Austria. (14th February 2018)

• Record Type: Journal Article
• Authors: Lalić, B.; Firanj Sremac, A.; Eitzinger, J.; Stričević, R.; Thaler, S.; Maksimović, I.; Daničić, M.; Perišić, D.; Dekić, Lj.
• Is Part Of: Journal of agricultural science. Volume 156:Number 5(2018)
• Page Start: 658
• Page End: 672
• Publication Date: 2018-02-14
• Subjects: Ensembles of crop model output estimates, -- green water, -- seasonal weather forecast, -- staple food crops, -- water footprint; Agriculture -- Periodicals; 630.5
• DOI: 10.1017/S0021859618000047
• Languages: English
• ISSNs: 0021-8596

Abstract

Abstract: A probabilistic crop forecast based on ensembles of crop model output estimates, presented here, offers an ensemble of possible realizations and probabilistic forecasts of green water components, crop yield and green water footprints (WFs) on seasonal scales for selected summer crops. The present paper presents results of an ongoing study related to the application of ensemble forecasting concepts in crop production. Seasonal forecasting of crop water use indicators (evapotranspiration (ET), water productivity, green WF) and yield of rainfed summer crops (maize, spring barley and sunflower), was performed using the AquaCrop model and ensemble weather forecast, provided by The European Centre for Medium-range Weather Forecast. The ensemble of estimates obtained was tested with observation-based simulations to assess the ability of seasonal weather forecasts to ensure that accuracy of the simulation results was the same as for those obtained using observed weather data. Best results are obtained for ensemble forecast for yield, ET, water productivity and green WF for sunflower in Novi Sad (Serbia) and maize in Groß-Enzersdorf (Austria) – average root mean square error (2006–2014) was <10% of observation-based values of selected variables. For variables yielding a probability distribution, capacity to reflect the distribution from which their outcomes will be drawn was tested using an Ignorance score. Average Ignorance score, for all locations, crops and variables varied from 1.49 (spring barley ET in Groß-Enzersdorf) to 3.35 (sunflower water productivity in Groß-Enzersdorf).