Measuring extremes-driven direct biophysical impacts in agricultural drought damages

Mansi Nagpal, Jasmin Heilemann, Luis Samaniego, Bernd Klauer, Erik Gawel, and Christian Klassert

Supplement

https://doi.org/10.5194/nhess-25-2115-2025-supplement

Data sets

National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data (2017, 2018 and 2019) Lukas Blickensdörfer et al. https://doi.org/10.5281/zenodo.5153047

Regionaldatenbank Deutschland, 41141-02-02-4: Anbau auf dem Ackerland in landwirtschaftlichen Betrieben nach Fruchtarten, 2010-2020 Statistisches Bundesamt (Destatis) https://www.regionalstatistik.de/genesis/online?operation=table&code=41141-02-02-4#astructure

Regionaldatenbank Deutschland. 41241-01-03-4: Erträge ausgewählter Feldfrüchte - Jahressumme Statistisches Bundesamt (Destatis) https://www.regionalstatistik.de/genesis//online?operation=table&code=41241-01-03-4&bypass=true&levelindex=1&levelid=1677842497003#abreadcrumb

Dürremonitor Deutschland Helmholtz Centre for Environmental Research https://www.ufz.de/index.php?de=37937

Model code and software

LASSO-crop-yield-projection Jasmin Heilemann https://git.ufz.de/heileman/lasso-crop-yield-projection

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Short summary

This study measures the direct effects of droughts in association with other extreme weather events on agriculture in Germany at the district level. Using a statistical yield model, we quantify the direct damage of extremes on crop yields and farm revenue. Extreme events during drought cause an average annual damage of EUR 781 million, accounting for 45 % of reported revenue losses. The insights herein can help develop better strategies for managing and mitigating the effects of future climate extremes.