Probabilistic modeling of crop-yield loss risk under drought: A spatial showcase for sub-Saharan Africa

Research output: Contribution to journalArticleResearchpeer review

Authors

  • Bahareh Kamali
  • Farshid Jahanbakhshi
  • Diana Dogaru
  • Jörg Dietrich
  • Claas Nendel
  • Amir Aghakouchak

External Research Organisations

  • Leibniz Centre for Agricultural Landscape Research (ZALF)
  • University of Bonn
  • Yazd University
  • Romanian Academy
  • University of Potsdam
  • University of California at Irvine
View graph of relations

Details

Original languageEnglish
Article number024028
JournalEnvironmental research letters
Volume17
Issue number2
Publication statusPublished - 11 Feb 2022

Abstract

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.

Keywords

    Copula theory, crop model, drought stress, joint probability, risk

ASJC Scopus subject areas

Sustainable Development Goals

Cite this

Probabilistic modeling of crop-yield loss risk under drought: A spatial showcase for sub-Saharan Africa. / Kamali, Bahareh; Jahanbakhshi, Farshid; Dogaru, Diana et al.
In: Environmental research letters, Vol. 17, No. 2, 024028, 11.02.2022.

Research output: Contribution to journalArticleResearchpeer review

Kamali B, Jahanbakhshi F, Dogaru D, Dietrich J, Nendel C, Aghakouchak A. Probabilistic modeling of crop-yield loss risk under drought: A spatial showcase for sub-Saharan Africa. Environmental research letters. 2022 Feb 11;17(2):024028. doi: 10.1088/1748-9326/ac4ec1
Kamali, Bahareh ; Jahanbakhshi, Farshid ; Dogaru, Diana et al. / Probabilistic modeling of crop-yield loss risk under drought : A spatial showcase for sub-Saharan Africa. In: Environmental research letters. 2022 ; Vol. 17, No. 2.
Download
@article{35b3628c0990499bbd10bf0ffb44f1b0,
title = "Probabilistic modeling of crop-yield loss risk under drought: A spatial showcase for sub-Saharan Africa",
abstract = "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. ",
keywords = "Copula theory, crop model, drought stress, joint probability, risk",
author = "Bahareh Kamali and Farshid Jahanbakhshi and Diana Dogaru and J{\"o}rg Dietrich and Claas Nendel and Amir Aghakouchak",
year = "2022",
month = feb,
day = "11",
doi = "10.1088/1748-9326/ac4ec1",
language = "English",
volume = "17",
journal = "Environmental research letters",
issn = "1748-9318",
publisher = "IOP Publishing Ltd.",
number = "2",

}

Download

TY - JOUR

T1 - Probabilistic modeling of crop-yield loss risk under drought

T2 - A spatial showcase for sub-Saharan Africa

AU - Kamali, Bahareh

AU - Jahanbakhshi, Farshid

AU - Dogaru, Diana

AU - Dietrich, Jörg

AU - Nendel, Claas

AU - Aghakouchak, Amir

PY - 2022/2/11

Y1 - 2022/2/11

N2 - 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.

AB - 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.

KW - Copula theory

KW - crop model

KW - drought stress

KW - joint probability

KW - risk

UR - http://www.scopus.com/inward/record.url?scp=85125463802&partnerID=8YFLogxK

U2 - 10.1088/1748-9326/ac4ec1

DO - 10.1088/1748-9326/ac4ec1

M3 - Article

AN - SCOPUS:85125463802

VL - 17

JO - Environmental research letters

JF - Environmental research letters

SN - 1748-9318

IS - 2

M1 - 024028

ER -

By the same author(s)