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Integrated assessment for hydrometeorological drought based on Markov chain model

Author

Listed:
  • Jie Yang

    (Xi’an University of Technology)

  • Yimin Wang

    (Xi’an University of Technology)

  • Jianxia Chang

    (Xi’an University of Technology)

  • Jun Yao

    (Hanjiang - to - Weihe River Water Diversion Project Construction Co. Ltd.)

  • Qiang Huang

    (Xi’an University of Technology)

Abstract

Drought assessment based on a single index cannot comprehensively reflect the characteristics of a drought affected by multiple factors. Therefore, the main purpose of this study is to accurately assess the drought by constructing an integrated drought assessment method (PDSI-SDI) that can combine the meteorological drought and hydrological drought at the same time. To better evaluate and forecast the drought, the Markov chain model is employed in this study to calculate the expected residence time, return period and transition probabilities of the drought. Furthermore, the Mann–Kendall method is adopted to predict the trend of the drought. The Weihe River Basin is selected as the study area, and according to the distribution characteristics of the water system, it is divided into five districts in order to better assess the drought. Results indicate that: (1) spatially, drought probabilities increase from south to north and west to east. (2) Temporally, probabilities of spring droughts are the highest, followed by summer droughts and autumn droughts, winter droughts have the lowest probabilities, extreme droughts are more likely to occur in autumn. (3) Drought preferentially transfers within the same scenario, except scenario 4 (meteorological drought with no hydrological drought) in autumn is prone to shift to scenario 1 (no meteorological drought with no hydrological drought). (4) There is a significant drying trend of the drought in the Weihe River Basin at the significance level of 95 %. The integrated drought assessment method and other methods adopted in this study can be applied in other regions as well.

Suggested Citation

  • Jie Yang & Yimin Wang & Jianxia Chang & Jun Yao & Qiang Huang, 2016. "Integrated assessment for hydrometeorological drought based on Markov chain 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. 84(2), pages 1137-1160, November.
    • Handle: RePEc:spr:nathaz:v:84:y:2016:i:2:d:10.1007_s11069-016-2480-0
    DOI: 10.1007/s11069-016-2480-0
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    References listed on IDEAS

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    Cited by:

    1. Wentao Yang & Min Deng & Jianbo Tang & Rui Jin, 2020. "On the use of Markov chain models for drought class transition analysis while considering spatial effects," 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. 103(3), pages 2945-2959, September.

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