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Seasonal forecasting of green water components and crop yield of summer crops in Serbia and Austria
- Source :
- The Journal of Agricultural Science, Journal of Agricultural Science
-
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
- Subjects :
- 010504 meteorology & atmospheric sciences
Mean squared error
Distribution (economics)
Atmospheric sciences
01 natural sciences
Crop
Evapotranspiration
staple food crops
Genetics
green water
0105 earth and related environmental sciences
2. Zero hunger
Ensemble forecasting
business.industry
Crop yield
04 agricultural and veterinary sciences
Seasonal forecasting, ensembles of crop model output estimates
Sunflower
Ensembles of crop model output estimates
water footprint
seasonal weather forecast
Crops and Soils Research Paper
040103 agronomy & agriculture
0401 agriculture, forestry, and fisheries
Environmental science
Animal Science and Zoology
business
Agronomy and Crop Science
Water use
Subjects
Details
- Language :
- English
- ISSN :
- 14695146 and 00218596
- Volume :
- 156
- Issue :
- 5
- Database :
- OpenAIRE
- Journal :
- The Journal of Agricultural Science
- Accession number :
- edsair.doi.dedup.....d66c1b159db4647ee2b393d831444105
- Full Text :
- https://doi.org/10.1017/s0021859618000047