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A New Regional Drought Index under X-bar Chart Based Weighting Scheme – The Quality Boosted Regional Drought Index (QBRDI)

Author

Listed:
  • Zulfiqar Ali

    (University of the Punjab)

  • Sadia Qamar

    (University of Sargodha)

  • Nasrulla Khan

    (University of the Punjab)

  • Muhammad Faisal

    (Rawalpindi Cantt)

  • Saad Sh. Sammen

    (University of Diyala)

Abstract

Unlike other natural hazards, drought has severe consequences on numerous aspects of life. After the industrial revolution, drought is prevailing in most parts of the world. Likewise, global warming and climate change have increased the recurrent occurrences of extreme values and the short-distance variability in precipitation. Therefore, accurate and effective reporting of drought characteristics at the regional level is one of the most challenging tasks in hydrology. This research aims to improve the accuracy and quality of drought characterization and its continuous monitoring at the regional level. This article develops a new drought indicator by integrating unequal weights under an X-bar chart with the regional aggregation precipitation data. We called the new index– the Quality Boosted Regional Drought Index (QBRDI). In application, the northern region of Pakistan is considered to assess and evaluate QBRDI. In comparison, the study includes a pairwise comparison of QBRDI and Regional Standardized Precipitation Index (RSPI) using the Pearson correlation coefficient. Comparative to RSPI, a significantly low Coefficient of Variation between the correlations of QBRDI with other meteorological stations reveals that QBRDI has more regional characteristics than RSPI. These outcomes endorse the rationality of using QBRDI for regional drought analysis. In addition, the methodology of QBRDI provides a new way to minimize the impact of outliers and extreme values in the regional aggregation of precipitation data.

Suggested Citation

  • Zulfiqar Ali & Sadia Qamar & Nasrulla Khan & Muhammad Faisal & Saad Sh. Sammen, 2023. "A New Regional Drought Index under X-bar Chart Based Weighting Scheme – The Quality Boosted Regional Drought Index (QBRDI)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(5), pages 1895-1911, March.
    • Handle: RePEc:spr:waterr:v:37:y:2023:i:5:d:10.1007_s11269-023-03461-9
    DOI: 10.1007/s11269-023-03461-9
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    References listed on IDEAS

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    1. Kim Phuc Tran, 2022. "Introduction to Control Charts and Machine Learning for Anomaly Detection in Manufacturing," Springer Series in Reliability Engineering, in: Kim Phuc Tran (ed.), Control Charts and Machine Learning for Anomaly Detection in Manufacturing, pages 1-6, Springer.
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    4. Rizwan Niaz & Mohammed M. A. Almazah & Xiang Zhang & Ijaz Hussain & Muhammad Faisal & Alireza Amirteimoori, 2021. "Prediction for Various Drought Classes Using Spatiotemporal Categorical Sequences," Complexity, Hindawi, vol. 2021, pages 1-11, November.
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    Cited by:

    1. Alina Mukhtar & Aamina Batool & Zulfiqar Ali & Sadia Qamar & Saba Riaz & Saad Sh. Sammen, 2024. "A New Hybrid Weighted Regional Drought Index to Improve Regional Drought Assessment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(14), pages 5541-5558, November.

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