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Drought Occurrence Probability Analysis Using Multivariate Standardized Drought Index and Copula Function Under Climate Change

Author

Listed:
  • Kimia Naderi

    (Arak University)

  • Mahnoosh Moghaddasi

    (Arak University
    Arak University)

  • Ashkan shokri

    (Bureau of Meteorology)

Abstract

This study aims to investigate the effect of climate change on the probability of drought occurrence in central Iran. To this end, a new drought index called Multivariate Standardized Drought Index (MSDI) was developed, which is composed of the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Soil Moisture Index (SSI). The required data included precipitation, temperature (from CRU TS), and soil moisture (from the ESA CCA SM product) on a monthly time scale for the 1980–2016 period. Moreover, future climate data were downloaded from CMIP6 models under the latest SSPs-RCPs emission scenarios (SSP1-2.6 and SSP5-8.5) for the 2020–2056 period. Based on the normalized root mean square error (NRMSE), Cramer-von mises statistic (Sn), and Nash Sutcliffe (NS) evaluation criteria, the Galambos and Clayton functions were selected to derive copula-based joint distribution functions in both periods. The results showed that more severe and longer droughts will occur in the future compared to the historical period and in particular under the SSP5-8.5 scenario. From the derived joint return period, a drought event with defined severity or duration will happen in a shorter return period as compared with the historical period. In other words, the joint return period indicated a higher probability of drought occurrence in the future period. Moreover, the joint return period analysis revealed that the return period of mild droughts will remain the same, while it will decrease for extreme droughts in the future.

Suggested Citation

  • Kimia Naderi & Mahnoosh Moghaddasi & Ashkan shokri, 2022. "Drought Occurrence Probability Analysis Using Multivariate Standardized Drought Index and Copula Function Under Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2865-2888, June.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:8:d:10.1007_s11269-022-03186-1
    DOI: 10.1007/s11269-022-03186-1
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    References listed on IDEAS

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    Cited by:

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    2. Tugrul Varol & Ayhan Atesoglu & Halil Baris Ozel & Mehmet Cetin, 2023. "Copula-based multivariate standardized drought index (MSDI) and length, severity, and frequency of hydrological drought in the Upper Sakarya Basin, Turkey," 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. 116(3), pages 3669-3683, April.
    3. Zahra Sadat Hosseini & Mahnoosh Moghaddasi & Shahla Paimozd, 2023. "Simultaneous Monitoring of Different Drought Types Using Linear and Nonlinear Combination Approaches," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1125-1151, February.
    4. Amirhossein Salimi & Amir Noori & Isa Ebtehaj & Tadros Ghobrial & Hossein Bonakdari, 2024. "Advancing Spatial Drought Forecasts by Integrating an Improved Outlier Robust Extreme Learning Machine with Gridded Data: A Case Study of the Lower Mainland Basin, British Columbia, Canada," Sustainability, MDPI, vol. 16(8), pages 1-27, April.

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