<div class="csl-bib-body">
<div class="csl-entry">Büechi, P. E., Fischer, M., Crocetti, L., Trnka, M., Grlj, A., Zappa, L., & Dorigo, W. (2023). Crop yield anomaly forecasting in the Pannonian basin using gradient boosting and its performance in years of severe drought. <i>Agricultural and Forest Meteorology</i>, <i>340</i>, Article 109596. https://doi.org/10.1016/j.agrformet.2023.109596</div>
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dc.identifier.issn
0168-1923
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/187761
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dc.description.abstract
The increasing frequency and intensity of severe droughts over recent decades have led to substantial crop yield losses in the Pannonian Basin in southeastern Europe. Their socioeconomic consequences can be minimized by accurate crop yield forecasts, but such forecasts often underestimate the impact of severe droughts on crop yields. We developed a gradient-boosting-based crop yield anomaly forecasting system for the Pannonian Basin and examined its performance, with a focus on drought years. Winter wheat and maize yield anomalies are forecasted for 42 regions in the Pannonian Basin using predictor datasets from Earth observation and reanalysis describing vegetation state, weather, and soil moisture conditions.
Our results show that crop yield anomaly estimates in the two months preceding harvest have better performance (maize errors 14–17%, wheat 13–14%) than earlier in the year (maize errors 21%, wheat 17%). The forecast models can satisfactorily capture the interannual yield anomalies, but spatial yield variability is only partially reproduced. In years of severe drought, the wheat model performs better than under average conditions with errors below 12%. The errors of the maize forecasts in drought years are larger than average forecast skill: 31% two months ahead and 20% one month ahead. However, for both crops the yield losses remain underestimated by the forecasts in severe drought years. The feature importance analysis shows that during the last two months before harvest, wheat yield anomalies are controlled by temperature and evaporation and maize by the combined effects of temperature and water availability as expressed by several drought indices. In severe drought years, during the two months before harvest the seasonal temperature forecast becomes the most important predictor for the wheat forecasts and soil moisture for the maize model. Overall, this study provides in-depth insights into the impact of droughts on crop yield forecasts in the Pannonian Basin.
en
dc.description.sponsorship
ESA-ESRIN
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dc.description.sponsorship
European Commission
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dc.language.iso
en
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dc.publisher
Elsevier
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dc.relation.ispartof
Agricultural and Forest Meteorology
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
Crop yield forecast
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dc.subject
Remote sensing
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dc.subject
Machine learning
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dc.subject
XGBoost
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dc.subject
Drought
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dc.title
Crop yield anomaly forecasting in the Pannonian basin using gradient boosting and its performance in years of severe drought
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dc.type
Article
en
dc.type
Artikel
de
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.rights.license
Creative Commons Attribution 4.0 International
en
dc.contributor.affiliation
Czech Academy of Sciences, Czech Republic
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dc.contributor.affiliation
ETH Zürich, Switzerland
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dc.contributor.affiliation
Czech Academy of Sciences, Czech Republic
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dc.contributor.affiliation
SPACE-SI, Slovenian Centre of Excellence for Space Sciences and Technologies, Slovenia