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Study on the Probability of Meteorological-to-Hydrological Drought Propagation Based on a Bayesian Network

Author

Listed:
  • Xiangyang Zhang

    (School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China)

  • Huiliang Wang

    (School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China)

  • Zhilei Yu

    (School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China)

  • Dengming Yan

    (Yellow River Engineering Consulting Co., Ltd., Zhengzhou 450003, China)

  • Ruxue Liu

    (Yellow River Conservancy Commission Hydrology and Water Resources Bureau of Henen, Zhengzhou 450003, China)

  • Simin Liu

    (China National Forestry-Grassland Development Research Center, Beijing 100714, China)

  • Yujia Zhu

    (School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China
    Yanqing Water Authority of Beijing, Beijing 102100, China)

  • Yifan Chen

    (Yellow River Conservancy Technical Institute, North China University of Water Resources and Electric Power, Kaifeng 475004, China)

  • Zening Wu

    (School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China)

Abstract

With accelerating climate change, droughts have increased in frequency and exerted a substantial influence on socioeconomic factors. Under conditions of insufficient precipitation and high temperatures, meteorological droughts have the potential to develop into more intense hydrological droughts, and the independent impact of temperature factors on drought propagation has not been considered separately. This study constructed a Standardized Temperature Index (STI) and, combined with time-series datasets of standardized indices of precipitation and runoff (SPI and SRI), based on Bayesian network principles, analyzed the probabilistic characteristics of drought propagation from meteorology to hydrology due to the influence of single or dual factors in the Yiluo River Basin (1961–2020). It also explored the transmission mechanisms of temperature and precipitation that drive and affect meteorological and hydrological drought. The results showed that propagation of meteorological to hydrological droughts increased with rising temperatures, and the propagation probability to severe and extreme hydrological drought increased by approximately 5%. Under the most adverse circumstances (high temperature and precipitation shortage scenarios), the likelihood of meteorological droughts progressing into intense hydrological drought events rose to 80%. Increasing temperature is expected to lead to more severe hydrological droughts. This study offers a theoretical foundation for drought prevention and mitigation.

Suggested Citation

  • Xiangyang Zhang & Huiliang Wang & Zhilei Yu & Dengming Yan & Ruxue Liu & Simin Liu & Yujia Zhu & Yifan Chen & Zening Wu, 2025. "Study on the Probability of Meteorological-to-Hydrological Drought Propagation Based on a Bayesian Network," Land, MDPI, vol. 14(3), pages 1-24, February.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:3:p:445-:d:1596063
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    References listed on IDEAS

    as
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    3. 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.
    4. Chunyi Wang & Hans W. Linderholm & Yanling Song & Fang Wang & Yanju Liu & Jinfeng Tian & Jinxia Xu & Yingbo Song & Guoyu Ren, 2020. "Impacts of Drought on Maize and Soybean Production in Northeast China During the Past Five Decades," IJERPH, MDPI, vol. 17(7), pages 1-10, April.
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