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Event-based approach for probabilistic agricultural drought risk assessment under rainfed conditions

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Listed:
  • Juan Quijano
  • Miguel Jaimes
  • Marco Torres
  • Eduardo Reinoso
  • Luisarturo Castellanos
  • Jesús Escamilla
  • Mario Ordaz

Abstract

An event-based approach for the probabilistic risk assessment of agricultural drought under rainfed conditions to estimate the economic impact is proposed. The risk parameters are evaluated in an event-based probabilistic framework for a set of hazard events; these results are probabilistically integrated including, in a formal way, all uncertainties related to every part of the process. The hazard is defined as a stochastic or historic set of events, collectively exhaustive and mutually exclusive, that describes the spatial distribution, the annual frequency, and the randomness of the hazard intensity. The risk is expressed in different economic terms: the average annual loss (or pure risk premium) and the loss exceedance curve; these metrics are of particular importance for risk retention (financing) schemes or risk transfer instruments. As an illustrative example, this approach is applied to probabilistic drought risk assessment of maize under rainfed conditions in Mexico. These results are the base of further studies in defining strategies for financial protection against agricultural losses and disasters. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Juan Quijano & Miguel Jaimes & Marco Torres & Eduardo Reinoso & Luisarturo Castellanos & Jesús Escamilla & Mario Ordaz, 2015. "Event-based approach for probabilistic agricultural drought risk assessment under rainfed conditions," 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. 76(2), pages 1297-1318, March.
    • Handle: RePEc:spr:nathaz:v:76:y:2015:i:2:p:1297-1318
    DOI: 10.1007/s11069-014-1550-4
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    References listed on IDEAS

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    1. Ana Paulo & Luis Pereira, 2007. "Prediction of SPI Drought Class Transitions Using Markov Chains," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(10), pages 1813-1827, October.
    2. Hong Wu & Donald Wilhite, 2004. "An Operational Agricultural Drought Risk Assessment Model for Nebraska, USA," 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. 33(1), pages 1-21, September.
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    Cited by:

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    2. M. C. Marulanda & J. C. Llera & G. A. Bernal & O. D. Cardona, 2021. "Epistemic uncertainty in probabilistic estimates of seismic risk resulting from multiple hazard models," 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. 108(3), pages 3203-3227, September.
    3. Mario A. Salgado-Gálvez & Daniela Zuloaga & Sebastian Henao & Gabriel A. Bernal & Omar-Darío Cardona, 2018. "Probabilistic assessment of annual repair rates in pipelines and of direct economic losses in water and sewage networks: application to Manizales, Colombia," 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. 93(1), pages 5-24, September.
    4. 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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