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Probabilistic Characteristics of Drought Propagation from Meteorological to Hydrological Drought in South Korea

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  • Muhammad Nouman Sattar

    (Hanyang University)

  • Jin-Young Lee

    (Hanyang University)

  • Ji-Yae Shin

    (Hanyang University)

  • Tae-Woong Kim

    (Hanyang University)

Abstract

A reliable understanding of propagation from meteorological to hydrological drought is necessary for accurate forecasting of hydrological droughts. Our current understanding of drought propagation is limited because the characteristics of each drought and the lag time between droughts are uneven due to spatial variability in underlying conditions and climatic variables. The objective of this study is to identify the probabilistic relationship between lag time and the occurrence of different classes of hydrological drought in South Korea while considering propagation factors and using a Bayesian network model. The results show that the propagation rate varied from 27% to 60% and the maximum value of the lag time was projected to be 4 to 10 weeks. For moderate intensity of meteorological drought, the occurrence probability of lag time was high and decreased when the intensity changed to severe and extreme. In addition, the probability for each class of hydrological drought intensity varied with space and increased as the intensity of propagated meteorological drought class changed from moderate to extreme. The observed probabilistic characteristics of hydrological drought may be useful in decision-making strategies for mitigating water shortage.

Suggested Citation

  • Muhammad Nouman Sattar & Jin-Young Lee & Ji-Yae Shin & Tae-Woong Kim, 2019. "Probabilistic Characteristics of Drought Propagation from Meteorological to Hydrological Drought in South Korea," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(7), pages 2439-2452, May.
    • Handle: RePEc:spr:waterr:v:33:y:2019:i:7:d:10.1007_s11269-019-02278-9
    DOI: 10.1007/s11269-019-02278-9
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    References listed on IDEAS

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    1. Ali Tabrizi & Davar Khalili & Ali Kamgar-Haghighi & Shahrokh Zand-Parsa, 2010. "Utilization of Time-Based Meteorological Droughts to Investigate Occurrence of Streamflow Droughts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(15), pages 4287-4306, December.
    2. Huang, Shengzhi & Huang, Qiang & Chang, Jianxia & Leng, Guoyong & Xing, Li, 2015. "The response of agricultural drought to meteorological drought and the influencing factors: A case study in the Wei River Basin, China," Agricultural Water Management, Elsevier, vol. 159(C), pages 45-54.
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    Cited by:

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    5. Saeed Azimi & Erfan Hassannayebi & Morteza Boroun & Mohammad Tahmoures, 2020. "Probabilistic Analysis of Long-Term Climate Drought Using Steady-State Markov Chain Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(15), pages 4703-4724, December.
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    7. Kiyoumars Roushangar & Roghayeh Ghasempour & Farhad Alizadeh, 2022. "Uncertainty Assessment of the Integrated Hybrid Data Processing Techniques for Short to Long Term Drought Forecasting in Different Climate Regions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(1), pages 273-296, January.

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