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Projected Changes of Future Extreme Drought Events under Numerous Drought Indices in the Heilongjiang Province of China

Author

Listed:
  • Muhammad Imran Khan

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

  • Dong Liu

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

  • Qiang Fu

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

  • Qaisar Saddique

    (Northwest A&F University)

  • Muhammad Abrar Faiz

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

  • Tianxiao Li

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

  • Muhammad Uzair Qamar

    (University of Agriculture)

  • Song Cui

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

  • Chen Cheng

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

Abstract

Effective drought prediction methods are essential for the mitigation of adverse effects of severe drought events. This study utilizes the Reconnaissance Drought Index, Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index to assess the occurrence of future drought events in the study area of the Heilongjiang province of China over a period of 2016–2099. The drought indices were computed from the meteorological data (temperature, precipitation) generated by the global climate model (HadCM3A2). Moreover, Mann-Kendall trend test was applied for the assessment of future climatic trends and detecting probable differences in the behaviour of various drought indices. Drought forecasting periods has been divided into three categories: the early phase (1916–2030), middle phase (2031–2060) and late phase (2061–2099). The occurrence of future droughts is also ranked according to their intensity (mild, moderate, severe and extreme drought). Based on the drought results, more number of drought events are expected to occur during 12-month drought analysis are, RDI during 2084–2098 (DD = 14, DS = −1.38), SPEI during 2084–2098 (DD = 14, DS = −1.33) and SPI during 2084–2095 (DD = 12, DS = −1.19). The 1st and 2nd months of the years studied predicted a warming trend, while the 7th, 8th, and 9th months predicted a wetter trend. Finally, it was observed that RDI is more sensitive to drought and indicated a high percentage of years under severe and extreme drought conditions during the drought frequency analysis. Conclusively, this study provides a strategies for water resources management and monitoring of droughts, in which drought indices like RDI can play a central role.

Suggested Citation

  • Muhammad Imran Khan & Dong Liu & Qiang Fu & Qaisar Saddique & Muhammad Abrar Faiz & Tianxiao Li & Muhammad Uzair Qamar & Song Cui & Chen Cheng, 2017. "Projected Changes of Future Extreme Drought Events under Numerous Drought Indices in the Heilongjiang Province of China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(12), pages 3921-3937, September.
  • Handle: RePEc:spr:waterr:v:31:y:2017:i:12:d:10.1007_s11269-017-1716-4
    DOI: 10.1007/s11269-017-1716-4
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    References listed on IDEAS

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    1. Davar Khalili & Tohid Farnoud & Hamed Jamshidi & Ali Kamgar-Haghighi & Shahrokh Zand-Parsa, 2011. "Comparability Analyses of the SPI and RDI Meteorological Drought Indices in Different Climatic Zones," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(6), pages 1737-1757, April.
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    3. Muhammad Imran Khan & Dong Liu & Qiang Fu & Shuhua Dong & Umar Waqas Liaqat & Muhammad Abrar Faiz & Yuxiang Hu & Qaisar Saddique, 2016. "Recent Climate Trends and Drought Behavioral Assessment Based on Precipitation and Temperature Data Series in the Songhua River Basin of China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4839-4859, October.
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    5. Harris Vangelis & Mike Spiliotis & George Tsakiris, 2011. "Drought Severity Assessment Based on Bivariate Probability Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(1), pages 357-371, January.
    6. Alireza Shokoohi & Reza Morovati, 2015. "Basinwide Comparison of RDI and SPI Within an IWRM Framework," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 2011-2026, April.
    7. Seyed Banimahd & Davar Khalili, 2013. "Factors Influencing Markov Chains Predictability Characteristics, Utilizing SPI, RDI, EDI and SPEI Drought Indices in Different Climatic Zones," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(11), pages 3911-3928, September.
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    2. Ayşegül Kuzucu & Gülay Onuşluel Gül, 2023. "Analysis of Drought Dynamics over Annual Maximum Drought Severity Series Based on Daily Index Definitions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1421-1436, February.
    3. Qaisar Saddique & Huanjie Cai & Jiatun Xu & Ali Ajaz & Jianqiang He & Qiang Yu & Yunfei Wang & Hui Chen & Muhammad Imran Khan & De Li Liu & Liang He, 2020. "Analyzing adaptation strategies for maize production under future climate change in Guanzhong Plain, China," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(8), pages 1523-1543, December.
    4. Quang-Tuong Vo & Jae-Min So & Deg-Hyo Bae, 2020. "An Integrated Framework for Extreme Drought Assessments Using the Natural Drought Index, Copula and Gi* Statistic," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(4), pages 1353-1368, March.

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