IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v37y2023i5d10.1007_s11269-023-03461-9.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-023-03461-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-023-03461-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    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.
    2. Sedigheh Mohamadi & Saad Sh. Sammen & Fatemeh Panahi & Mohammad Ehteram & Ozgur Kisi & Amir Mosavi & Ali Najah Ahmed & Ahmed El-Shafie & Nadhir Al-Ansari, 2020. "Zoning map for drought prediction using integrated machine learning models with a nomadic people optimization algorithm," 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. 104(1), pages 537-579, October.
    3. Phuong Hanh Tran & Adel Ahmadi Nadi & Thi Hien Nguyen & Kim Duc Tran & Kim Phuc Tran, 2022. "Application of Machine Learning in Statistical Process Control Charts: A Survey and Perspective," Springer Series in Reliability Engineering, in: Kim Phuc Tran (ed.), Control Charts and Machine Learning for Anomaly Detection in Manufacturing, pages 7-42, Springer.
    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.
    5. Guo, Honggang & Wang, Jianzhou & Li, Zhiwu & Jin, Yu, 2022. "A multivariable hybrid prediction system of wind power based on outlier test and innovative multi-objective optimization," Energy, Elsevier, vol. 239(PE).
    6. 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.
    7. Gustavo Naumann & Carmelo Cammalleri & Lorenzo Mentaschi & Luc Feyen, 2021. "Increased economic drought impacts in Europe with anthropogenic warming," Nature Climate Change, Nature, vol. 11(6), pages 485-491, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Muhammad Shakeel & Zulfiqar Ali, 2024. "Integration of Exponential Weighted Moving Average Chart in Ensemble of Precipitation of Multiple Global Climate Models (GCMs)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(3), pages 935-949, February.
    2. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ethel García & Rita Peñabaena-Niebles & Maria Jubiz-Diaz & Angie Perez-Tafur, 2022. "Concurrent Control Chart Pattern Recognition: A Systematic Review," Mathematics, MDPI, vol. 10(6), pages 1-31, March.
    2. Wilson Rojas-Preciado & Mauricio Rojas-Campuzano & Purificación Galindo-Villardón & Omar Ruiz-Barzola, 2023. "Control Chart T2Qv for Statistical Control of Multivariate Processes with Qualitative Variables," Mathematics, MDPI, vol. 11(12), pages 1-32, June.
    3. Xu, Yingying & Lü, Haishen & Yagci, Ali Levent & Zhu, Yonghua & Liu, Di & Wang, Qimeng & Xu, Haiting & Pan, Ying & Su, Jianbin, 2024. "Influence of groundwater on the propagation of meteorological drought to agricultural drought during crop growth periods: A case study in Huaibei Plain," Agricultural Water Management, Elsevier, vol. 305(C).
    4. Arthur Charpentier & Molly James & Hani Ali, 2021. "Predicting Drought and Subsidence Risks in France," Papers 2107.07668, arXiv.org.
    5. Guimbeau, Amanda & Ji, Xinde James & Menon, Nidhiya, 2024. "Climate Shocks, Intimate Partner Violence, and the Protective Role of Climate-Resilience Projects," IZA Discussion Papers 17529, Institute of Labor Economics (IZA).
    6. Jianmin Zhang & Renguang Wu & Xiaojing Jia, 2025. "Interdecadal changes in persistent drought over Asia under phase transitions of the Atlantic Multidecadal Oscillation," Climatic Change, Springer, vol. 178(5), pages 1-19, May.
    7. Zhang, Haipeng & Wang, Jianzhou & Qian, Yuansheng & Li, Qiwei, 2024. "Point and interval wind speed forecasting of multivariate time series based on dual-layer LSTM," Energy, Elsevier, vol. 294(C).
    8. Nadjib Haied & Atif Foufou & Samira Khadri & Adel Boussaid & Mohamed Azlaoui & Nabil Bougherira, 2023. "Spatial and Temporal Assessment of Drought Hazard, Vulnerability and Risk in Three Different Climatic Zones in Algeria Using Two Commonly Used Meteorological Indices," Sustainability, MDPI, vol. 15(10), pages 1-25, May.
    9. Farman Ali & Bing-Zhao Li & Zulfiqar Ali, 2021. "Strengthening Drought Monitoring Module by Ensembling Auxiliary Information Based Varying Estimators," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(10), pages 3235-3252, August.
    10. Xiong, Yanfei & Zhang, Anlu & Liu, Mengba & Zhang, Xue & Cheng, Qi, 2024. "Drought risk assessment for citrus and its mitigation resistance under climate change and crop specialization: A case study of southern Jiangxi, China," Agricultural Water Management, Elsevier, vol. 306(C).
    11. Wu, Chunying & Wang, Jianzhou & Hao, Yan, 2022. "Deterministic and uncertainty crude oil price forecasting based on outlier detection and modified multi-objective optimization algorithm," Resources Policy, Elsevier, vol. 77(C).
    12. Dongxing Zhang & Dang Luo, 2022. "Assessment of agricultural drought loss using a skewed grey cloud ordered clustering model," 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. 114(3), pages 2787-2810, December.
    13. Simon Hoeg, 2024. "Potential Amplifiers of Hydrological Drought: A Deep Dive into the Seasonal Variations of New, Young, and Old Water Fractions in the Stream Discharge of a Pre-Alpine Catchment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(15), pages 6191-6212, December.
    14. Xu, Zhenheng & Sun, Hao & Zhang, Tian & Xu, Huanyu & Wu, Dan & Gao, JinHua, 2023. "Evaluating established deep learning methods in constructing integrated remote sensing drought index: A case study in China," Agricultural Water Management, Elsevier, vol. 286(C).
    15. André S. Ballarin & Yannis Markonis & Oldrich Rakovec & Simon Michael Papalexiou, 2025. "How likely is Ukraine to experience an extreme drought in the near future?," Climatic Change, Springer, vol. 178(6), pages 1-14, June.
    16. 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.
    17. Raphael Calel & David A. Stainforth, 2025. "Little floods everywhere: what will climate change mean for you?," Climatic Change, Springer, vol. 178(1), pages 1-9, January.
    18. Geng, Donghan & Zhang, Yongkang & Zhang, Yunlong & Qu, Xingchuang & Li, Longfei, 2025. "A hybrid model based on CapSA-VMD-ResNet-GRU-attention mechanism for ultra-short-term and short-term wind speed prediction," Renewable Energy, Elsevier, vol. 240(C).
    19. Wang, Hao & Ye, Jingzhen & Huang, Linxuan & Wang, Qiang & Zhang, Haohua, 2023. "A multivariable hybrid prediction model of offshore wind power based on multi-stage optimization and reconstruction prediction," Energy, Elsevier, vol. 262(PA).
    20. Okan Mert Katipoğlu, 2023. "Prediction of Streamflow Drought Index for Short-Term Hydrological Drought in the Semi-Arid Yesilirmak Basin Using Wavelet Transform and Artificial Intelligence Techniques," Sustainability, MDPI, vol. 15(2), pages 1-24, January.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:37:y:2023:i:5:d:10.1007_s11269-023-03461-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.