Measuring extremes-driven direct biophysical impacts in agricultural drought damages
-д хадгалсан:
| -д хэвлэсэн: | Natural Hazards and Earth System Sciences vol. 25, no. 6 (2025), p. 2115 |
|---|---|
| Үндсэн зохиолч: | |
| Бусад зохиолчид: | , , , , |
| Хэвлэсэн: |
Copernicus GmbH
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| Нөхцлүүд: | |
| Онлайн хандалт: | Citation/Abstract Full Text Full Text - PDF |
| Шошгууд: |
Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!
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MARC
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| 100 | 1 | |a Nagpal, Mansi |u Department of Economics, Helmholtz Centre for Environmental Research – UFZ, 04318 Leipzig, Germany | |
| 245 | 1 | |a Measuring extremes-driven direct biophysical impacts in agricultural drought damages | |
| 260 | |b Copernicus GmbH |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Assessing the economic implications of droughts has become increasingly important due to their substantial impacts on agriculture. Existing empirical analyses for drought damages are often conducted on a national scale without spatially distributed data, which might bias estimates. Furthermore, the cumulative effects of multiple weather extremes, such as heat or preceded frost co-occurring with drought, are often overlooked. Measuring the direct biophysical impacts of such extremes on agriculture is essential for more precise risk assessment. This study presents a comprehensive approach to measure the cumulative economic damages of droughts and other hydrometeorological extremes on agriculture, focusing on eight major field crops in Germany. By utilizing a statistical yield model, we isolate the effects of multiple extremes on crop yields from other influencing factors (such as pests and diseases or farm management) and analyse their contribution to revenue losses during droughts at the district level from 2016–2022. Our findings indicate that the average annual direct biophysical damage caused by extremes under drought conditions during this period amounts to EUR 781 million (sensitivity range: EUR 766 million–EUR 812 million) across Germany. The study also reveals that biophysical impacts of extremes alone account for 60 % of reported revenue damages during widespread drought years. For maize, direct biophysical damage explains up to 97 % (2018) of revenue losses. Additionally, comparison of national level damage estimates using aggregated and spatially disaggregated data shows that the aggregated data matches overall results, but diverges for maize and wheat, highlighting the importance of spatially distributed damage assessment. In this paper, we provide detailed estimates of extremes-driven direct biophysical damages at the district level, offering a high-resolution understanding of the spatial and temporal variability of these impacts. Assessing the extent of revenue losses resulting from these extremes alone can provide valuable insights for the development of effective drought mitigation programmes and guide policy planning at local and national levels to enhance the resilience of the agricultural sector against future climate extremes. Future integration of routine drought damage estimation into operational monitoring and forecasting systems would enhance early warning capabilities, improve economic preparedness against increasing weather extremes, and support more proactive adaptation strategies. | |
| 651 | 4 | |a Germany | |
| 653 | |a Extreme weather | ||
| 653 | |a Food security | ||
| 653 | |a Agricultural industry | ||
| 653 | |a Crop yield | ||
| 653 | |a Drought damage | ||
| 653 | |a Water shortages | ||
| 653 | |a Estimates | ||
| 653 | |a Early warning systems | ||
| 653 | |a Agriculture | ||
| 653 | |a Drought | ||
| 653 | |a Climatic extremes | ||
| 653 | |a Crops | ||
| 653 | |a Damage assessment | ||
| 653 | |a Agricultural drought | ||
| 653 | |a Risk assessment | ||
| 653 | |a Climate change | ||
| 653 | |a Farm management | ||
| 653 | |a Damage | ||
| 653 | |a Economics | ||
| 653 | |a Precipitation | ||
| 653 | |a Regions | ||
| 653 | |a Corn | ||
| 653 | |a Weather effects | ||
| 653 | |a Temporal variability | ||
| 653 | |a Agricultural production | ||
| 653 | |a Weather | ||
| 653 | |a Hydrology | ||
| 653 | |a Drought conditions | ||
| 653 | |a Empirical analysis | ||
| 653 | |a Statistical models | ||
| 653 | |a Temporal variations | ||
| 653 | |a Hydrometeorology | ||
| 653 | |a Temperature | ||
| 653 | |a Pests | ||
| 653 | |a Future climates | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Heilemann, Jasmin |u Department of Economics, Helmholtz Centre for Environmental Research – UFZ, 04318 Leipzig, Germany | |
| 700 | 1 | |a Samaniego, Luis |u Department of Computational Hydrosystems (CHS), Helmholtz Center for Environmental Research – UFZ, 04318 Leipzig, Germany; Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany | |
| 700 | 1 | |a Klauer, Bernd |u Department of Economics, Helmholtz Centre for Environmental Research – UFZ, 04318 Leipzig, Germany | |
| 700 | 1 | |a Gawel, Erik |u Department of Economics, Helmholtz Centre for Environmental Research – UFZ, 04318 Leipzig, Germany; Faculty of Economics and Business Management, University of Leipzig, 04109 Leipzig, Germany | |
| 700 | 1 | |a Klassert, Christian |u Department of Economics, Helmholtz Centre for Environmental Research – UFZ, 04318 Leipzig, Germany | |
| 773 | 0 | |t Natural Hazards and Earth System Sciences |g vol. 25, no. 6 (2025), p. 2115 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3225785254/abstract/embedded/ZKJTFFSVAI7CB62C?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3225785254/fulltext/embedded/ZKJTFFSVAI7CB62C?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3225785254/fulltextPDF/embedded/ZKJTFFSVAI7CB62C?source=fedsrch |