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A Monte Carlo Simulation-Based Approach to Evaluate the Performance of three Meteorological Drought Indices in Northwest of Iran

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Abstract

Although meteorological drought indices are considered as important tools for drought monitoring, they are embedded with different theoretical and experimental structures. Regarding the different geographic and climatic conditions around the world, the most meteorological drought indices have been commonly applied for drought monitoring in different parts of the world. Interestingly, it is observed that such indices in the published studies on drought monitoring have usually yielded inconsistent performance. On the other hand, most studies on drought monitoring as well as the performance of drought indices has been based on short-term historical data (less than 50 years). Therefore, this study aimed to analyze and compare the performance of three common indices of SPI, RAI and PNPI to predict long-term drought events using the Monte Carlo procedure and historical data. To do this end, the 50-year recorded or historical rainfall data across 11 synoptic stations in the Northwest of Iran were employed to generate 1000 synthetic data series so that the characteristics of long-term drought might be determined and the performance of those three indices might be analyzed and compared. The results indicated a very high comparative advantage of the SPI in terms of yielding a satisfactory and detailed analysis to determine the characteristics of long-term drought. Also, the RAI indicated significant deviations from normalized natural processes. However, these results could not reasonably and sufficiently predict long-term drought. Finally, the PNPI was determined as the most uncertain and spatial index (depending on average or coefficient of variation of rainfall data) in drought monitoring.

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References

  • Adeloye AJ, Montaseri M (2002) Preliminary streamflow data analyses prior to water resources planning study. Hydrolog Sci J 47(5):679–692

    Article  Google Scholar 

  • Aksoy H, Unal NE, Alexandrov V, Dakova S, Yoon J (2008) Hydrometeorological analysis of northwestern Turkey with links to climate change. Int J Climatol 28:1047–1060

    Article  Google Scholar 

  • Amirataee B, Montaseri M, Sanikhani H (2016) The analysis of trend variations of reference evapotranspiration via eliminating the significance effect of all autocorrelation coefficients. Theor Appl Climatol 126(1):131–139

  • Angelidis P, Maris F, Kotsovinos N, Hrissanthou V (2012) Computation of drought index SPI with alternative distribution functions. Water Resour Manag 26(9):2453–2473

    Article  Google Scholar 

  • Barua S, Ng AWM, Perera BJC (2011) Comparative evaluation of drought indices: a case study on the Yarra river catchment in Australia. J Water Res Pl-ASCE 137(2):215–226

    Article  Google Scholar 

  • Cancelliere A, Di Mauro G, Bonaccorso B, Rossi G (2006) Drought forecasting using the standardized precipitation index. Water Resour Manag 21(5):801–819

    Article  Google Scholar 

  • Douglas H (2000) How to measure anything: finding the value of intangibles in business. John Wiley and Sons, Inc., Hoboken

    Google Scholar 

  • Dracup JA, Lee KS, Paulson EG (1980) On the statistical characteristics of drought events. Water Resour Res 16(2):289–296

    Article  Google Scholar 

  • Gibbs WJ, Maher JV (1967) Rainfall deciles as drought indicators. Bureau of Meteorology, Bulletin, No.48, Commonwealth of Australia, Melbourne

  • Guttman NB (1998) Comparing the palmer drought severity index and the standardized precipitation index. J Amer Water Res Ass 34(1):113–121

    Article  Google Scholar 

  • Hamed KH, Rao AR (1998) A modified Mann–Kendall trend test for autocorrelated data. J Hydrol 204:182–196

    Article  Google Scholar 

  • Heim J (2002) A review of twentieth-century drought indices used in the United States. B Am Meteorol Soc 83(8):1149–1166

    Article  Google Scholar 

  • Jain V, Pandey R, Jain M, Byun HR (2015) Comparison of drought indices for appraisal of drought characteristics in the Ken River basin. Weather Clim Extrem 8:1–11

    Article  Google Scholar 

  • Ju XS, Yang XW, Chen LJ, Wang YM (1997) Research on determination of indices and division of regional flood/drought grades in China (in Chinese). Q J Appl Meteorol 8(1):26–33

    Google Scholar 

  • Keyantash J, Dracup JA (2002) The quantification of drought: an evaluation of drought indices. B Am Meteorol Soc 83(8):1167–1180

    Article  Google Scholar 

  • Khalili D, Farnoud T, Jamshidi H, Kamgar-Haghighi A, Zand-Parsa S (2011) Comparability analyses of the SPI and RDI meteorological drought indices in different climatic zones. Water Resour Manag 25:1737–1757

    Article  Google Scholar 

  • Loucks DP, Stedinger JR, Haith DA (1981) Water resources system planning and analysis. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Loukas A, Vasiliades L, Dalezios NR (2003) Inter comparison of meteorological drought indices for drought assessment and monitoring in Greece. Paper presented at the 8th International Conference on Environmental Science and Technology Lemons Island, 484–491

  • McGhee JW (1985) Introductory statistics. West Publishing Co., New York

    Google Scholar 

  • McGuire JK, Palmer WC (1957) The 1957 drought in the eastern United States. Mon Weather Rev 85(9):305–314

    Article  Google Scholar 

  • Mckee TB, Doesken NY, Kleist Y (1993) The relationship of drought frequency and duration to time scales. Paper presented at the. In: 8th conference on applied climatology, Anaheim, pp 179–184

    Google Scholar 

  • McMahon TA, Adeloye AJ (2005) Water resources yield. Water Resources Publications, LLC

    Google Scholar 

  • McMahon TA, Vogel RM, Peel MC, Pegram GGS (2007) Global streamflows—part 1: characteristics of annual streamflows. J Hydrol 347:243–259

    Article  Google Scholar 

  • Mishra AK, Singh VP (2010) A review of drought concepts. J Hydrol 391:202–216

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Mishra AK, Singh VP, Desai VR (2009) Drought characterization: a probabilistic approach. Stoch Env Res Risk A 23(1):41–55

    Article  Google Scholar 

  • Montaseri M, Adeloye A (1999) Critical period of reservoir systems for planning purposes. J Hydrol 224(3–4):115–136

    Article  Google Scholar 

  • Montaseri M, Adeloye A (2004) A graphical rule for volumetric evaporation loss correction in reservoir capacity-yield-performance planning in Urmia region, Iran. Water Resour Manag 18(1):55–74

    Article  Google Scholar 

  • Montaseri M, Amirataee B (2017) Comprehensive stochastic assessment of meteorological drought indices. Int J Climatol 37(2):998-1013

  • Moreira EE, Coelho CA, Paulo AA, Pereira LS, Mexia JT (2008) SPI-based drought category prediction using loglinear models. J Hydrol 354:116–130

    Article  Google Scholar 

  • Morid S, Smakhtin V, Moghaddasi M (2006) Comparison of seven meteorological indices for drought monitoring in Iran. Int J Climatol 26:971–985

    Article  Google Scholar 

  • Nitzche MH, Silva BB, Martinez AS (1985) Indicativo de ano seco e chuvoso. Sociedade Brasileira de Agrometeorologia, Londrina-PR, pp 307–314

    Google Scholar 

  • Oladipo EO (1985) A comparative performance analysis of three meteorological drought indices. J Climatol 5:655–664

    Article  Google Scholar 

  • Palmer WC (1965) Meteorological drought. Weather bureau research paper no. 45. US Deptartment of Commerce, Washington, DC, p 58

    Google Scholar 

  • Palmer WC (1968) Keeping track of crop moisture conditions, nationwide: the new crop moisture index. Weatherwise 21:156–161

    Article  Google Scholar 

  • Panu US, Sharma TC (2002) Challenge in drought research: some perspectives and future directions. Hydrolog Sci J 47:19–30

    Article  Google Scholar 

  • Quiring SM, Papakryiakou TN (2003) An evaluation of agricultural drought indices for the Canadian prairies. Agric For Meteorol 118(1–2):49–62

    Article  Google Scholar 

  • Salas JD (1993) Analysis and Modeling of Hydrologic Time Series. In handbook of hydrology, Edited by Maidment. McGrow-Hill book Co.: New York.

  • Santos EG, Salas JD (1992) Stepwise disaggregation scheme for synthetic hydrology. J Hydraul Eng-ASCE 118(5):765–784

    Article  Google Scholar 

  • Sayari N, Bannayan M, Alizadeh A, Farid A (2013) Using drought indices to assess climate change impacts on drought conditions in the northeast of Iran (case study: Kashafrood basin). Met Apps 20:115–127

    Article  Google Scholar 

  • Tsakiris G, Vangelis H (2004) Towards a drought watch system based on spatial SPI. Water Resour Manag 18(1):1–12

    Article  Google Scholar 

  • Tsakiris G, Vangelis H (2005) Establishing a drought index incorporating evapotranspiration. Eur Water 9(10):3–11

    Google Scholar 

  • Tsakiris G, Pangalou D, Vangelis H (2007) Regional drought assessment based on the reconnaissance drought index (RDI). Water Resour Manag 21:821–833

    Article  Google Scholar 

  • Valencia D, Schaake JC (1973) Disaggregation processes in stochastic hydrology. Water Resour Res 9(3):580–585

    Article  Google Scholar 

  • Van Rooy MP (1965) A rainfall anomaly index independent of time and space. Notes 14:43–48

    Google Scholar 

  • Vogel RM, Kroll CN (1989) Low flow frequency analysis using probability plot correlation coefficients. J Water Res Pl-ASCE 115(3):338–357

    Article  Google Scholar 

  • Vogel RM, Wilson I (1996) Probability distribution of annual maximum mean and minimum streamflows in the United States. J Hydrol Eng 1(2):69–76

    Article  Google Scholar 

  • Wilhite DA (2000) Drought: a global assessment. Volume I. Rutledge Press: London and New York

  • Willeke G, Hosking JRM, Wallis JR, Guttman NB (1994) The national drought atlas. Institute for Water Resources Report 94-NDs-4, U.S Army Crops of Engineers

  • Wu H, Hayes MJ, Welss A, Hu Q (2001) An evaluation the standardized precipitation index, the China-z index and the statistical z-score. Int J Climatol 21:745–758

    Article  Google Scholar 

  • Yevjevich V (1967) An objective approach to definitions and investigation of continental hydrological droughts. Hydrology Paper 23. Colorado State University, Fort Collins, CO

  • Yue SH, Hashino M (2007) Probability distribution of annual, seasonal and monthly precipitation in Japan. Hydrolog Sci J 52(5):863–877

    Article  Google Scholar 

  • Zargar A, Sadiq R, Naser G, Khan F (2011) A review of drought indices. Environ Rev 19:333–349

    Article  Google Scholar 

Download references

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Montaseri, M., Amirataee, B. & Nawaz, R. A Monte Carlo Simulation-Based Approach to Evaluate the Performance of three Meteorological Drought Indices in Northwest of Iran. Water Resour Manage 31, 1323–1342 (2017). https://doi.org/10.1007/s11269-017-1580-2

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