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Propagation of the Multi-Scalar Aggregative Standardized Precipitation Temperature Index and its Application

Author

Listed:
  • Zulfiqar Ali

    (Quaid-i-Azam University)

  • Ijaz Hussain

    (Quaid-i-Azam University)

  • Muhammad Faisal

    (University of Bradford
    Bradford Teaching Hospitals NHS Foundation Trust)

  • Dost Muhammad Khan

    (Abdul Wali Khan University Mardan)

  • Rizwan Niaz

    (Quaid-i-Azam University)

  • Elsayed Elsherbini Elashkar

    (King Saud University)

  • Alaa Mohamd Shoukry

    (King Saud University
    KSA workers University)

Abstract

Nowadays, drought monitoring with various probabilistic indices has become common. However, the interpretation and applicability issues of multi-scalar drought indices are the main problems in establishing accurate drought mitigation policies. In addition, the spatial structure of environmental variables such as rainfall, and the spatial distribution of meteorological stations have a vital role in the precise and accurate analysis. In this paper, a comprehensive drought index “the Multi-Scalar Aggregative Standardized Precipitation Temperature Index (MASPTI)” is proposed. In MASPTI procedure, temporal vectors of various time scales of SPTI index are accumulated by giving long term transient weights. These weights are determined from the steady state probabilities of drought classification states in each time scale. Application of the proposed index is based on spatio-temporal data of SPTI index at its various time scales. However, before proceeding to evaluate MASPTI, we first observed the spatial relevancy of important time scale of SPTI index using the machine learning wrapper Boruta algorithm. The preliminary evaluation of MASPTI is based on four meteorological stations located in different homogeneous climatic clusters in Pakistan. The comparative analysis includes the ordinal association, where historical qualitative series of drought classes attained from MASPTI are compared with existing SPTI time scales. Outcomes show that MASPTI has the ability to capture joint characterization of drought by incorporating long term probabilities as a transient weight.

Suggested Citation

  • Zulfiqar Ali & Ijaz Hussain & Muhammad Faisal & Dost Muhammad Khan & Rizwan Niaz & Elsayed Elsherbini Elashkar & Alaa Mohamd Shoukry, 2020. "Propagation of the Multi-Scalar Aggregative Standardized Precipitation Temperature Index and its Application," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 699-714, January.
    • Handle: RePEc:spr:waterr:v:34:y:2020:i:2:d:10.1007_s11269-019-02469-4
    DOI: 10.1007/s11269-019-02469-4
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    References listed on IDEAS

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    1. Javad Bazrafshan & Somayeh Hejabi & Jaber Rahimi, 2014. "Drought Monitoring Using the Multivariate Standardized Precipitation Index (MSPI)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(4), pages 1045-1060, March.
    2. Kursa, Miron B. & Rudnicki, Witold R., 2010. "Feature Selection with the Boruta Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i11).
    3. Zuliqar Ali & Ijaz Hussain & Muhammad Faisal & Hafiza Mamona Nazir & Mitwali Abd-el Moemen & Tajammal Hussain & Sadaf Shamsuddin, 2017. "A Novel Multi-Scalar Drought Index for Monitoring Drought: the Standardized Precipitation Temperature Index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 4957-4969, December.
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