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Copula-based agricultural drought risk of rainfed cropping systems

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  • Ribeiro, Andreia F.S.
  • Russo, Ana
  • Gouveia, Célia M.
  • Páscoa, Patrícia

Abstract

In a future climate, warmer and drier conditions are expected, and the associated negative impacts in agricultural productions are a major issue. Assessing the risk of drought hazard on agricultural systems is, therefore, of main importance in decision-making, with the aim of mitigating drought-related crop losses. In this study the agricultural drought risk is defined as the conditional probability of occurring crop-losses under drought conditions. We use the copula theory to estimate joint probability distributions describing the amount of dependence between drought conditions and crop yield anomalies of two major rainfed cereals in the Iberian Peninsula (wheat and barley), in the period 1986–2016. Further conditional probability distributions of the crop yield anomalies under different drought levels are obtained using the Standardized Precipitation Evapotranspiration Index (SPEI) and the satellite derived indices Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). The results suggest that, in general, the joint behaviour of yield anomalies and drought conditions exhibits a dependence between the extreme values, whereas barley exhibits greater probabilities of joint extreme low values of yield and drought indicators. Moreover, while TCI is mainly used in copula models indicating greater probabilities of joint extreme high values of wheat and drought indicators (gumbel models), VCI and SPEI are mainly associated to copula models indicating greater probabilities of joint extreme low values (clayton models). The estimated conditional probabilities of occurrence of crop-loss are illustrated at the province level and suggest that agricultural drought risk increases with drought severity in most of the provinces.

Suggested Citation

  • Ribeiro, Andreia F.S. & Russo, Ana & Gouveia, Célia M. & Páscoa, Patrícia, 2019. "Copula-based agricultural drought risk of rainfed cropping systems," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    • Handle: RePEc:eee:agiwat:v:223:y:2019:i:c:70
    DOI: 10.1016/j.agwat.2019.105689
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    References listed on IDEAS

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    1. Ying Li & Wei Gu & Weijia Cui & Zhiyun Chang & Yingjun Xu, 2015. "Exploration of copula function use in crop meteorological drought risk analysis: a case study of winter wheat in Beijing, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(2), pages 1289-1303, June.
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    6. Sosheel S. Godfrey & Thomas Nordblom & Ryan H. L. Ip & Susan Robertson & Timothy Hutchings & Karl Behrendt, 2021. "Drought Shocks and Gearing Impacts on the Profitability of Sheep Farming," Agriculture, MDPI, vol. 11(4), pages 1-19, April.
    7. Elaheh Motevali Bashi Naeini & Ali Mohammad Akhoond-Ali & Fereydoun Radmanesh & Jahangir Abedi Koupai & Shahrokh Soltaninia, 2021. "Comparison of the Calculated Drought Return Periods Using Tri-variate and Bivariate Copula Functions Under Climate Change Condition," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(14), pages 4855-4875, November.
    8. Zhang, Shuo & Kang, Yan & Gao, Xuan & Chen, Peiru & Cheng, Xiao & Song, Songbai & Li, Lingjie, 2023. "Optimal reservoir operation and risk analysis of agriculture water supply considering encounter uncertainty of precipitation in irrigation area and runoff from upstream," Agricultural Water Management, Elsevier, vol. 277(C).
    9. Ihsan F. Hasan & Rozi Abdullah, 2022. "Agricultural Drought Characteristics Analysis Using Copula," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 5915-5930, December.
    10. Karen A. McKinnon & Andrew Poppick, 2020. "Estimating Changes in the Observed Relationship Between Humidity and Temperature Using Noncrossing Quantile Smoothing Splines," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(3), pages 292-314, September.
    11. Zhang, Yu & Hao, Zengchao & Feng, Sifang & Zhang, Xuan & Xu, Yang & Hao, Fanghua, 2021. "Agricultural drought prediction in China based on drought propagation and large-scale drivers," Agricultural Water Management, Elsevier, vol. 255(C).
    12. Mubenga-Tshitaka, Jean-Luc & Muteba Mwamba, John W. & Dikgang, Johane & Gelo, Dambala, 2021. "Risk spillover between climate variables and the agricultural commodity market in East Africa," EconStor Preprints 243160, ZBW - Leibniz Information Centre for Economics.
    13. Zhang, Fan & Cui, Ningbo & Guo, Shanshan & Yue, Qiong & Jiang, Shouzheng & Zhu, Bin & Yu, Xiuyun, 2023. "Irrigation strategy optimization in irrigation districts with seasonal agricultural drought in southwest China: A copula-based stochastic multiobjective approach," Agricultural Water Management, Elsevier, vol. 282(C).
    14. Zhang, Yu & Hao, Zengchao & Feng, Sifang & Zhang, Xuan & Hao, Fanghua, 2022. "Changes and driving factors of compound agricultural droughts and hot events in eastern China," Agricultural Water Management, Elsevier, vol. 263(C).
    15. Jun Yin & Zhe Yuan & Ting Li, 2021. "The Spatial-Temporal Variation Characteristics of Natural Vegetation Drought in the Yangtze River Source Region, China," IJERPH, MDPI, vol. 18(4), pages 1-24, February.
    16. Dongxing Zhang & Dang Luo, 2022. "Assessment of agricultural drought loss using a skewed grey cloud ordered clustering model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 2787-2810, December.

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