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

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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.

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The data and materials used in this study are available upon reasonable request from the corresponding author.

References

  • Abramowitz M, Stegun IA (Eds.) (1948) Handbook of mathematical functions with formulas, graphs, and mathematical tables (Vol. 55). US Government printing office

  • Aghelpour P, Bahrami-Pichaghchi H, Varshavian V (2021) Hydrological drought forecasting using multi-scalar streamflow drought index, stochastic models and machine learning approaches, in northern Iran. Stoch Env Res Risk Assess 35(8):1615–1635

    Article  Google Scholar 

  • Ahmed K, Shahid S, Chung ES, Wang XJ, Harun SB (2019) Climate change uncertainties in seasonal drought severity-area-frequency curves: Case of arid region of Pakistan. J Hydrol 570:473–485

    Article  Google Scholar 

  • Ali Z, Almanjahie IM, Hussain I, Ismail M, Faisal M (2020a) A novel generalized combinative procedure for Multi-Scalar standardized drought Indices-The long average weighted joint aggregative criterion. Tellus A Dyn Meteorol Oceanogr 72(1):1–23

    Google Scholar 

  • Ali Z, Hussain I, Faisal M, Elashkar EE, Gani S, Shehzad MA (2019) Selection of appropriate time scale with Boruta algorithm for regional drought monitoring using multi-scaler drought index. Tellus A: Dyn Meteorol Oceanogr 71(1):1604057

  • Ali Z, Hussain I, Grzegorczyk MA, Ni G, Faisal M, Qamar S, Al-Deek FF (2020b) Bayesian network based procedure for regional drought monitoring: the seasonally combinative regional drought indicator. J Environ Manag 276:111296

    Article  Google Scholar 

  • Ali F, Li BZ, Ali Z (2021a) Strengthening drought monitoring module by ensembling auxiliary information based varying estimators. Water Resour Manag 35(10):3235–3252

  • Ali F, Li BZ, Ali Z (2022a) A new weighting scheme for diminishing the effect of extreme values in regional drought analysis. Water Resour Manag 1–16

  • Ali F, Riaz S, Ali Z, Qamar S, Li BZ, Khan MA (2022b) The spatiotemporal weighted efficient drought index (STWEDI)‐a new generalized procedure of regional drought indicator. Ecohydrology e2454

  • Ali Z, Ellahi A, Hussain I, Nazeer A, Qamar S, Ni G, Faisal M (2021b) Reduction of errors in hydrological drought monitoring–a novel statistical framework for spatio-temporal assessment of drought. Water Resour Manag 35(13):4363–4380

  • Ali Z, Hussain I, Faisal M, Nazir HM, Moemen MAE, Hussain T, Shamsuddin S (2017) A novel multi-scalar drought index for monitoring drought: the standardized precipitation temperature index. Water Resour Manag 31(15):4957–4969

    Article  Google Scholar 

  • Alsafadi K, Mohammed S, Ayugi AB, Sharaf M, Harsanyi E (2020) Spatial–temporal evolution of drought characteristics over Hungary between 1961 and 2010. Pure Appl Geophys 177:1–18

    Article  Google Scholar 

  • Balti H, Abbes AB, Mellouli N, Sang Y, Farah IR, Lamolle M, Zhu Y (2021) Big data based architecture for drought forecasting using LSTM, ARIMA, and Prophet: Case study of the Jiangsu Province, China. In 2021 International Congress of Advanced Technology and Engineering (ICOTEN) (pp. 1–8). IEEE

  • Cheng H (2020) Future earth and sustainable developments. Innovation 1(3)

  • da Silva GJ, Borges AC, Moreira MC, Rosa AP (2022) Statistical process control in assessing water quality in the Doce river basin after the collapse of the Fundão dam (Mariana, Brazil). J Environ Manag 317:115402

    Article  Google Scholar 

  • Danandeh Mehr A, Rikhtehgar Ghiasi A, Yaseen ZM, Sorman AU, Abualigah L (2022) A novel intelligent deep learning predictive model for meteorological drought forecasting. J Ambient Intell Hum Comput 1–15

  • Fallah Zolleh S, Ildoromi A, Nouri H (2021) Predicting the effect f climate change on drought indices (SPI) and (SDI) in Malayer watershed using ARIMA time series model. Geogr Plan 25(77):205–218

    Google Scholar 

  • Guo H, Wang J, Li Z, Jin Y (2022) A multivariable hybrid prediction system of wind power based on outlier test and innovative multi-objective optimization. Energy 239:122333

    Article  Google Scholar 

  • Kaur A, Sood SK (2019) Artificial intelligence-based model for drought prediction and forecasting. Comput J. https://doi.org/10.1093/comjnl/bxz105

    Article  Google Scholar 

  • Li Z, Ali Z, Cui T, Qamar S, Ismail M, Nazeer A, Faisal M (2022a) A comparative analysis of pre-and post-industrial spatiotemporal drought trends and patterns of Tibet Plateau using Sen slope estimator and steady-state probabilities of Markov Chain. Nat Hazards 1–30

  • Li Z, Riaz S, Qamar S, Ali Z, Abbasi JN, Fayyaz R (2022b) Development of adaptive standardized precipitation index and its application in the Tibet Plateau region. Stoch Environ Res Risk Assess 1–19

  • Liu Z, Chen S, Wu H, He R, Hao L (2018) A Student’st mixture probability hypothesis density filter for multi-target tracking with outliers. Sensors 18(4):1095

    Article  Google Scholar 

  • McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. Proc Conf Appl Climatol 17(22):179–183

    Google Scholar 

  • Mohamadi S, Sammen SS, Panahi F et al (2020) Zoning map for drought prediction using integrated machine learning models with a nomadic people optimization algorithm. Nat Hazards 104:537–579. https://doi.org/10.1007/s11069-020-04180-9

    Article  Google Scholar 

  • Montgomery DC (2020) Introduction to statistical quality control. John Wiley & Sons

  • Mukherjee S, Mishra A, Trenberth KE (2018) Climate change and drought: a perspective on drought indices. Curr Clim Change Rep 4(2):145–163

    Article  Google Scholar 

  • Naumann G, Cammalleri C, Mentaschi L, Feyen L (2021) Increased economic drought impacts in Europe with anthropogenic warming. Nat Clim Chang 11(6):485–491

    Article  Google Scholar 

  • Nelson LS (1984) The Shewhart control chart—tests for special causes. J Qual Technol 16(4):237–239

    Article  Google Scholar 

  • Niaz R, Almazah M, Hussain I, Al-Ansari N, Sammen SS (2022a) Assessing the probability of drought severity in a homogeneous region. Complexity. https://doi.org/10.1155/2022/3139870

    Article  Google Scholar 

  • Niaz R, Almazah MM, Hussain I, Faisal M, Al-Rezami AY, Naser MA (2022b) A new comprehensive approach for regional drought monitoring. PeerJ 10:e13377

    Article  Google Scholar 

  • Niaz R, Almazah MM, Zhang X, Hussain I, Faisal M (2021) Prediction for various drought classes using spatiotemporal categorical sequences. Complexity 2021:1–11

  • Niaz R, Hussain I, Ali Z, Faisal M, Elashkar EE, Shoukry AM, Al-Deek FF (2020) A novel spatially weighted accumulative procedure for regional drought monitoring. Tellus A Dyn Meteorol Oceanogr 72(1):1–13

    Google Scholar 

  • Page ES (1954) Continuous inspection schemes. Biometrika 41(1–2):100–115

    Article  Google Scholar 

  • Perkasa L (2021) Benefit using statistical process control (SPC) for process control in textile manufacturing: A Review. J Mech Sci Eng 8(1):023–028

    Article  Google Scholar 

  • Ponnamperuma N, Rajapakse L (2021) Comparison of time series forecast models for rainfall and drought prediction. In 2021 Moratuwa Engineering Research Conference (MERCon) (pp. 626–631). IEEE

  • Raza A, Hussain I, Ali Z, Faisal M, Elashkar EE, Shoukry AM, Gani S (2021) A seasonally blended and regionally integrated drought index using Bayesian network theory. Meteorol Appl 28(3):e1992

    Article  Google Scholar 

  • Roberts SW (1959) Control chart tests based on geometric moving averages. Technometrics (3):239–250

  • Shahgedanova M (2021) Climate change and melting glaciers. In The Impacts of Climate Change (pp. 53–84). Elsevier

  • Shamsuzzaman M, Shamsuzzoha A, Maged A, Haridy S, Bashir H, Karim A (2021) Effective monitoring of carbon emissions from industrial sector using statistical process control. Appl Energy 300:117352

    Article  Google Scholar 

  • Stagge JH, Tallaksen LM, Gudmundsson L, Van Loon AF, Stahl K (2015) Candidate distributions for climatological drought indices (SPI and SPEI). Int J Climatol 35(13):4027–4040

    Article  Google Scholar 

  • Surdam RC (2013) Geological observations supporting dynamic climatic changes. In Geological CO2 Storage Characterization (pp. 1–13). Springer, New York, NY

  • Svoboda MD, Fuchs BA (2016) Handbook of drought indicators and indices (pp. 1–44). Geneva, Switzerland: World Meteorological Organization

  • Svoboda MD (2018) The national drought mitigation center: Translating the science of drought to the public and policy makers. In AGU Fall Meeting Abstracts (Vol. 2018, pp. PA34A-09)

  • Tran PH, Ahmadi Nadi A, Nguyen TH, Tran KD, Tran KP (2022) Application of machine learning in statistical process control charts: A survey and perspective. In Control Charts and Machine Learning for Anomaly Detection in Manufacturing (pp. 7–42). Springer, Cham

  • Tsakiris G, Nalbantis I, Vangelis H, Verbeiren B, Huysmans M, Tychon B, Batelaan O (2013) A system-based paradigm of drought analysis for operational management. Water Resour Manag 27:5281–5297

    Article  Google Scholar 

  • Xu D, Zhang Q, Ding Y, Zhang D (2022) Application of a hybrid ARIMA-LSTM model based on the SPEI for drought forecasting. Environ Sci Pollut Res 29(3):4128–4144

    Article  Google Scholar 

  • Yang P, Xia J, Luo X, Meng L, Zhang S, Cai W, Wang W (2021) Impacts of climate change-related flood events in the Yangtze River Basin based on multi-source data. Atmos Res 263:105819

    Article  Google Scholar 

Download references

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Contributions

Zulfiqar Ali and Sadia Qamar conceived the presented idea. Zulfiqar Ali developed the theory and performed the computations. Nasrullah Khan and Muhammad Faisal verified the analytical methods and computations. Saad Shauket Sammen encouraged Sadia Qamar and Zulfiqar Ali to investigate the consistency of the studies and supervised the findings of this work. All authors discussed the results and contributed to the final manuscript.

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Correspondence to Zulfiqar Ali.

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Ali, Z., Qamar, S., Khan, N. et al. A New Regional Drought Index under X-bar Chart Based Weighting Scheme – The Quality Boosted Regional Drought Index (QBRDI). Water Resour Manage 37, 1895–1911 (2023). https://doi.org/10.1007/s11269-023-03461-9

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