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Water Resources Management

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22-07-2022

A New Weighting Scheme for Diminishing the Effect of Extreme Values in Regional Drought Analysis

Authors: Farman Ali, Bing-Zhao Li, Zulfiqar Ali

Published in: Water Resources Management | Issue 11/2022

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Abstract

Climate warming has increased the risk of recurrent drought hazards. Previous research has indicated potential associations between climate warming and extreme climate events. Due to short distance spatial variability in meteorological variables, the prevalence of extreme values may result in biased inferences or reduce the scope of regional drought analysis. Therefore, precise inferences of spatiotemporal characteristics of regional drought are challenging. In this study, we provide a new weighting scheme to diminish the effect of extreme values for the regional aggregation of precipitation data. We used K – Components Gaussian Mixture Models (K–CGMM) based on the standardization procedure to achieve maximum computational accuracy. Consequently, the article proposes a new regional drought index – the Bias Diminished Weighted Regional Drought Index (BDWRDI). We assessed the performance of BDWRDI by calculating the Standardized Precipitation Index (SPI) using data from six meteorological stations in the Northern area of Pakistan. We found that the proposed weighting scheme can greatly diminish the effect of extreme values during the spatiotemporal aggregation of precipitation data. In addition, the strong positive correlation of BDWRDI with individual SPIs endorses the proposed weighting scheme and the proposed drought indicator for regional drought analysis.

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

Adedeji O, Olusola A, James G, Shaba HA, Orimoloye IR, Singh SK, Adelabu S (2020) Early warning systems development for agricultural drought assessment in Nigeria. Environ Monit Assess 192(12):1–21CrossRef

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

Ali Z, Ellahi A, Hussain I, Nazeer A, Qamar S, Ni G, Faisal M (2021a) Reduction of Errors in Hydrological Drought Monitoring–A Novel Statistical Framework for Spatio-Temporal Assessment of Drought. Water Resour Manage 35(13):4363–4380CrossRef

Allan RP, Soden BJ (2008) Atmospheric warming and the amplification of precipitation extremes. Science 321(5895):1481–1484CrossRef

Arumugam P, Saranya R (2018) Outlier detection and missing value in seasonal ARIMA model using rainfall data. Materials Today: Proceedings, 5(1), 1791–1799

Azadi H, Keramati P, Taheri F, Rafiaani P, Teklemariam D, Gebrehiwot K, Witlox F (2018) Agricultural land conversion: Reviewing drought impacts and coping strategies. Int J disaster risk Reduct 31:184–195CrossRef

Bahinipati CS (2020) Assessing the costs of droughts in rural India: a comparison of economic and non-economic loss and damage. Curr Sci 118(11):1832CrossRef

Balti H, Abbes AB, Mellouli N, Farah IR, Sang Y, Lamolle M (2020) A review of drought monitoring with big data: Issues, methods, challenges and research directions. Ecol Inf 60:101136CrossRef

Başakın EE, Ekmekcioğlu Ö (2020) Comment on “Comparison of the ability of ARIMA, WNN and SVM models for drought forecasting in the Sanjiang Plain, China” by Yuhu Zhang, Huirong Yang, Hengjian Cui, and Qiuhua Chen, in Natural Resources Research. Nat Resour Res 29(2):1465–1467CrossRef

Bong CHJ, Richard J (2020) Drought and climate change assessment using standardized precipitation index (SPI) for Sarawak River Basin. J Water Clim Change 11(4):956–965CrossRef

Byers EA, Coxon G, Freer J, Hall JW (2020) Drought and climate change impacts on cooling water shortages and electricity prices in Great Britain. Nat Commun 11(1):1–12CrossRef

Chevuturi A, Klingaman NP, Turner AG, Hannah S (2018) Projected changes in the Asian-Australian monsoon region in 1.5° C and 2.0° C global‐warming scenarios. Earth’s Future 6(3):339–358CrossRef

Delignette-Muller ML, Dutang C (2013) fitdistrplus: An R package for fitting distributions. J Stat Softw 64(4):1–34

Gampe D, Zscheischler J, Reichstein M, O’Sullivan M, Smith WK, Sitch S, Buermann W (2021) Increasing impact of warm droughts on northern ecosystem productivity over recent decades. Nat Clim Change 11(9):772–779CrossRef

Giorgi F, Raffaele F, Coppola E (2019) The response of precipitation characteristics to global warming from climate projections. Earth Sys Dyn 10(1):73–89CrossRef

Gregersen IB, Sørup HJD, Madsen H, Rosbjerg D, Mikkelsen PS, Arnbjerg-Nielsen K (2013) Assessing future climatic changes of rainfall extremes at small spatio-temporal scales. Clim Change 118(3):783–797CrossRef

Hao Z, AghaKouchak A (2013) Multivariate standardized drought index: a parametric multi-index model. Adv Water Resour 57:12–18CrossRef

Huang J, Zhuo W, Li Y, Huang R, Sedano F, Su W, Zhang X (2020) Comparison of three remotely sensed drought indices for assessing the impact of drought on winter wheat yield. Int J Digit Earth 13(4):504–526CrossRef

Kao SC, Govindaraju RS (2010) A copula-based joint deficit index for droughts. J Hydrol 380(1–2):121–134CrossRef

Kamruzzaman M, Cho J, Jang MW, Hwang S (2019) Comparative evaluation of standardized precipitation index (SPI) and effective drought index (EDI) for meteorological drought detection over Bangladesh. J Korean Soc Agricultural Eng 61(1):145–159

Khan MMH, Muhammad NS, El-Shafie A (2020) Wavelet based hybrid ANN-ARIMA models for meteorological drought forecasting. J Hydrol 590:125380CrossRef

Liu Y, Zhou R, Wen Z, Khalifa M, Zheng C, Ren H, Wang Z (2021) Assessing the impacts of drought on net primary productivity of global land biomes in different climate zones. Ecol Ind 130:108146CrossRef

Magalhães AR, Magalhães MC (2019) Drought preparedness and livelihood implications in developing countries: what are the options?—Latin America and Northeast Brazil. Current directions in water scarcity research, vol 2. Elsevier, pp 55–66

McKee TB, Doesken NJ, Kleist J (1993), January The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology (Vol. 17, No. 22, pp. 179–183)

Mishra AK, Singh VP (2011) Drought modeling–A review. J Hydrol 403(1–2):157–175CrossRef

Nkemelang T, New M, Zaroug M (2018) Temperature and precipitation extremes under current, 1.5 C and 2.0 C global warming above pre-industrial levels over Botswana, and implications for climate change vulnerability. Environ Res Lett 13(6):065016CrossRef

Papalexiou SM, Montanari A (2019) Global and regional increase of precipitation extremes under global warming. Water Resour Res 55(6):4901–4914CrossRef

Tsakiris G, Pangalou D, Vangelis H (2007) Regional drought assessment based on the Reconnaissance Drought Index (RDI). Water Resour Manage 21(5):821–833CrossRef

Rasul G, Chaudhry QZ, Mahmood A, Hyder KW, Dahe Q (2011) Glaciers and glacial lakes under changing climate in Pakistan.Pakistan Journal of Meteorology, 8(15)

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. Meteorological Applications, 28(3), e1992

Salvador C, Nieto R, Linares C, Díaz J, Gimeno L (2020) Short-term effects of drought on daily mortality in Spain from 2000 to 2009. Environ Res 183:109200CrossRef

Spiess AN (2018) Propagation of Uncertainty Using Higher-. Order Taylor Expansion and Monte Carlo Simulation

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):4027–4040CrossRef

Sugg M, Runkle J, Leeper R, Bagli H, Golden A, Handwerger LH, Woolard S (2020) A scoping review of drought impacts on health and society in North America.Climatic Change,1–19

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

Tabari H (2020) Climate change impact on flood and extreme precipitation increases with water availability. Sci Rep 10(1):1–10CrossRef

Vicente-Serrano SM, Beguería S, López-Moreno JI (2010) A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Clim 23(7):1696–1718CrossRef

Wei W, Zhang J, Zhou L, Xie B, Zhou J, Li C (2021) Comparative evaluation of drought indices for monitoring drought based on remote sensing data. Environ Sci Pollut Res 28(16):20408–20425CrossRef

Yaduvanshi A, Nkemelang T, Bendapudi R, New M (2021) Temperature and rainfall extremes change under current and future global warming levels across Indian climate zones. Weather and Climate Extremes 31:100291CrossRef

Zhang Y, Li Y, Ge J, Li G, Yu Z, Niu H (2018) Correlation analysis between drought indices and terrestrial water storage from 2002 to 2015 in China. Environ Earth Sci 77(12):1–12

Zhang Y, Yang H, Cui H, Chen Q (2020) Comparison of the ability of ARIMA, WNN and SVM models for drought forecasting in the Sanjiang Plain, China. Nat Resour Res 29(2):1447–1464CrossRef

Title: A New Weighting Scheme for Diminishing the Effect of Extreme Values in Regional Drought Analysis
Authors: Farman Ali
Bing-Zhao Li
Zulfiqar Ali
Publication date: 22-07-2022
Publisher: Springer Netherlands
Published in: Water Resources Management / Issue 11/2022
Print ISSN: 0920-4741
Electronic ISSN: 1573-1650
DOI: https://doi.org/10.1007/s11269-022-03243-9

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