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Multivariate Drought Assessment Considering the Antecedent Drought Conditions

Author

Listed:
  • Muhammad Waseem

    (Hanyang University)

  • Muhammad Ajmal

    (Hanyang University
    University of Engineering and Technology)

  • Joo Heon Lee

    (Joongbu University)

  • Tae-Woong Kim

    (Hanyang University)

Abstract

Several drought indices have been developed based on a single variable or multiple variables using very complex calculations. Antecedent conditions are quite significant for analyzing physical processes involved in the conceptual rainfall-runoff modeling and for proper assessment of drought. However, not much attention has been paid to these conditions in the development of drought indices. Hence, we developed an alternative index for drought assessment, i.e., the antecedent condition-based multivariate drought index (AMDI), by taking into consideration all of the forms of drought, including meteorological, agricultural, and hydrological drought, in combination with the antecedent drought conditions. By comparing the AMDI with the standardized precipitation index (SPI) and reconnaissance drought index (RDI), it was revealed that in most cases, the drought trend was more or less the same. However, some discrepancies were also observed. Moreover, by considering additional factors, i.e., the antecedent soil moisture conditions and balance, an approximately 6 % difference in the drought frequency was observed compared to that of the SPI and RDI results, leading to a significant and proper drought assessment. The AMDI was also identified as a multi-scalar, multivariate index, which aggregates the effects of multiple drought forms by maintaining the continuity during month-to-month transitions. Hence, we concluded that the AMDI could be considered as an alternative tool for significant drought assessment.

Suggested Citation

  • Muhammad Waseem & Muhammad Ajmal & Joo Heon Lee & Tae-Woong Kim, 2016. "Multivariate Drought Assessment Considering the Antecedent Drought Conditions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4221-4231, September.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:12:d:10.1007_s11269-016-1416-5
    DOI: 10.1007/s11269-016-1416-5
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    References listed on IDEAS

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    Cited by:

    1. Si Chen & Waseem Muhammad & Joo-Heon Lee & Tae-Woong Kim, 2018. "Assessment of Probabilistic Multi-Index Drought Using a Dynamic Naive Bayesian Classifier," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(13), pages 4359-4374, October.
    2. Mohammad Ghabaei Sough & Hamid Zare Abyaneh & Abolfazl Mosaedi, 2018. "Assessing a Multivariate Approach Based on Scalogram Analysis for Agricultural Drought Monitoring," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(10), pages 3423-3440, August.
    3. Junfei Chen & Menghua Deng & Lu Xia & Huimin Wang, 2017. "Risk Assessment of Drought, Based on IDM-VFS in the Nanpan River Basin, Yunnan Province, China," Sustainability, MDPI, vol. 9(7), pages 1-16, June.

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