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1000 Titel
  • Probabilistic modeling of crop-yield loss risk under drought: a spatial showcase for sub-Saharan Africa
1000 Autor/in
  1. Kamali, Bahareh |
  2. Jahanbakhshi, Farshid |
  3. Dogaru, Diana |
  4. Dietrich, Jörg |
  5. Nendel, Claas |
  6. AghaKouchak, Amir |
1000 Erscheinungsjahr 2022
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2022-02-11
1000 Erschienen in
1000 Quellenangabe
  • 17:024028
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2022
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1088/1748-9326/ac4ec1 |
1000 Ergänzendes Material
  • https://iopscience.iop.org/article/10.1088/1748-9326/ac4ec1#erlac4ec1s5 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Assessing the risk of yield loss in African drought-affected regions is key to identify feasible solutions for stable crop production. Recent studies have demonstrated that Copula-based probabilistic methods are well suited for such assessment owing to reasonably inferring important properties in terms of exceedance probability and joint dependence of different characterization. However, insufficient attention has been given to quantifying the probability of yield loss and determining the contribution of climatic factors. This study applies the Copula theory to describe the dependence between drought and crop yield anomalies for rainfed maize, millet, and sorghum crops in sub-Saharan Africa (SSA). The environmental policy integrated climate model, calibrated with Food and Agriculture Organization country-level yield data, was used to simulate yields across SSA (1980–2012). The results showed that the severity of yield loss due to drought had a higher magnitude than the severity of drought itself. Sensitivity analysis to identify factors contributing to drought and high-temperature stresses for all crops showed that the amount of precipitation during vegetation and grain filling was the main driver of crop yield loss, and the effect of temperature was stronger for sorghum than for maize and millet. The results demonstrate the added value of probabilistic methods for drought-impact assessment. For future studies, we recommend looking into factors influencing drought and high-temperature stresses as individual/concurrent climatic extremes.
1000 Sacherschließung
lokal drought stress
lokal crop model
lokal risk
lokal Copula theory
lokal joint probability
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0002-8070-0175|https://orcid.org/0000-0002-8428-0171|https://orcid.org/0000-0002-7474-6273|https://orcid.org/0000-0002-1742-8025|https://orcid.org/0000-0001-7608-9097|https://orcid.org/0000-0003-4689-8357
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1000 Erstellt am 2022-03-10T09:18:41.749+0100
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