Advertisement

Water Resources Management

, Volume 31, Issue 4, pp 1323–1342 | Cite as

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

  • Majid Montaseri
  • Babak Amirataee
  • Rizwan Nawaz
Article

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.

Keywords

Data generation models Drought Drought indices Monte Carlo simulation 

References

  1. Adeloye AJ, Montaseri M (2002) Preliminary streamflow data analyses prior to water resources planning study. Hydrolog Sci J 47(5):679–692CrossRefGoogle Scholar
  2. Aksoy H, Unal NE, Alexandrov V, Dakova S, Yoon J (2008) Hydrometeorological analysis of northwestern Turkey with links to climate change. Int J Climatol 28:1047–1060CrossRefGoogle Scholar
  3. 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):131–139Google Scholar
  4. Angelidis P, Maris F, Kotsovinos N, Hrissanthou V (2012) Computation of drought index SPI with alternative distribution functions. Water Resour Manag 26(9):2453–2473CrossRefGoogle Scholar
  5. 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):215–226CrossRefGoogle Scholar
  6. Cancelliere A, Di Mauro G, Bonaccorso B, Rossi G (2006) Drought forecasting using the standardized precipitation index. Water Resour Manag 21(5):801–819CrossRefGoogle Scholar
  7. Douglas H (2000) How to measure anything: finding the value of intangibles in business. John Wiley and Sons, Inc., HobokenGoogle Scholar
  8. Dracup JA, Lee KS, Paulson EG (1980) On the statistical characteristics of drought events. Water Resour Res 16(2):289–296CrossRefGoogle Scholar
  9. Gibbs WJ, Maher JV (1967) Rainfall deciles as drought indicators. Bureau of Meteorology, Bulletin, No.48, Commonwealth of Australia, MelbourneGoogle Scholar
  10. Guttman NB (1998) Comparing the palmer drought severity index and the standardized precipitation index. J Amer Water Res Ass 34(1):113–121CrossRefGoogle Scholar
  11. Hamed KH, Rao AR (1998) A modified Mann–Kendall trend test for autocorrelated data. J Hydrol 204:182–196CrossRefGoogle Scholar
  12. Heim J (2002) A review of twentieth-century drought indices used in the United States. B Am Meteorol Soc 83(8):1149–1166CrossRefGoogle Scholar
  13. 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 8:1–11CrossRefGoogle Scholar
  14. 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):26–33Google Scholar
  15. Keyantash J, Dracup JA (2002) The quantification of drought: an evaluation of drought indices. B Am Meteorol Soc 83(8):1167–1180CrossRefGoogle Scholar
  16. 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 25:1737–1757CrossRefGoogle Scholar
  17. Loucks DP, Stedinger JR, Haith DA (1981) Water resources system planning and analysis. Prentice-Hall, Englewood CliffsGoogle Scholar
  18. 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, 484–491Google Scholar
  19. McGhee JW (1985) Introductory statistics. West Publishing Co., New YorkGoogle Scholar
  20. McGuire JK, Palmer WC (1957) The 1957 drought in the eastern United States. Mon Weather Rev 85(9):305–314CrossRefGoogle Scholar
  21. 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 179–184Google Scholar
  22. McMahon TA, Adeloye AJ (2005) Water resources yield. Water Resources Publications, LLCGoogle Scholar
  23. McMahon TA, Vogel RM, Peel MC, Pegram GGS (2007) Global streamflows—part 1: characteristics of annual streamflows. J Hydrol 347:243–259CrossRefGoogle Scholar
  24. Mishra AK, Singh VP (2010) A review of drought concepts. J Hydrol 391:202–216CrossRefGoogle Scholar
  25. Mishra AK, Singh VP (2011) Drought modeling – a review. J Hydrol 403(1–2):157–175CrossRefGoogle Scholar
  26. Mishra AK, Singh VP, Desai VR (2009) Drought characterization: a probabilistic approach. Stoch Env Res Risk A 23(1):41–55CrossRefGoogle Scholar
  27. Montaseri M, Adeloye A (1999) Critical period of reservoir systems for planning purposes. J Hydrol 224(3–4):115–136CrossRefGoogle Scholar
  28. 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):55–74CrossRefGoogle Scholar
  29. Montaseri M, Amirataee B (2017) Comprehensive stochastic assessment of meteorological drought indices. Int J Climatol 37(2):998-1013Google Scholar
  30. Moreira EE, Coelho CA, Paulo AA, Pereira LS, Mexia JT (2008) SPI-based drought category prediction using loglinear models. J Hydrol 354:116–130CrossRefGoogle Scholar
  31. Morid S, Smakhtin V, Moghaddasi M (2006) Comparison of seven meteorological indices for drought monitoring in Iran. Int J Climatol 26:971–985CrossRefGoogle Scholar
  32. Nitzche MH, Silva BB, Martinez AS (1985) Indicativo de ano seco e chuvoso. Sociedade Brasileira de Agrometeorologia, Londrina-PR, pp 307–314Google Scholar
  33. Oladipo EO (1985) A comparative performance analysis of three meteorological drought indices. J Climatol 5:655–664CrossRefGoogle Scholar
  34. Palmer WC (1965) Meteorological drought. Weather bureau research paper no. 45. US Deptartment of Commerce, Washington, DC, p 58Google Scholar
  35. Palmer WC (1968) Keeping track of crop moisture conditions, nationwide: the new crop moisture index. Weatherwise 21:156–161CrossRefGoogle Scholar
  36. Panu US, Sharma TC (2002) Challenge in drought research: some perspectives and future directions. Hydrolog Sci J 47:19–30CrossRefGoogle Scholar
  37. Quiring SM, Papakryiakou TN (2003) An evaluation of agricultural drought indices for the Canadian prairies. Agric For Meteorol 118(1–2):49–62CrossRefGoogle Scholar
  38. Salas JD (1993) Analysis and Modeling of Hydrologic Time Series. In handbook of hydrology, Edited by Maidment. McGrow-Hill book Co.: New York.Google Scholar
  39. Santos EG, Salas JD (1992) Stepwise disaggregation scheme for synthetic hydrology. J Hydraul Eng-ASCE 118(5):765–784CrossRefGoogle Scholar
  40. 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 20:115–127CrossRefGoogle Scholar
  41. Tsakiris G, Vangelis H (2004) Towards a drought watch system based on spatial SPI. Water Resour Manag 18(1):1–12CrossRefGoogle Scholar
  42. Tsakiris G, Vangelis H (2005) Establishing a drought index incorporating evapotranspiration. Eur Water 9(10):3–11Google Scholar
  43. Tsakiris G, Pangalou D, Vangelis H (2007) Regional drought assessment based on the reconnaissance drought index (RDI). Water Resour Manag 21:821–833CrossRefGoogle Scholar
  44. Valencia D, Schaake JC (1973) Disaggregation processes in stochastic hydrology. Water Resour Res 9(3):580–585CrossRefGoogle Scholar
  45. Van Rooy MP (1965) A rainfall anomaly index independent of time and space. Notes 14:43–48Google Scholar
  46. Vogel RM, Kroll CN (1989) Low flow frequency analysis using probability plot correlation coefficients. J Water Res Pl-ASCE 115(3):338–357CrossRefGoogle Scholar
  47. Vogel RM, Wilson I (1996) Probability distribution of annual maximum mean and minimum streamflows in the United States. J Hydrol Eng 1(2):69–76CrossRefGoogle Scholar
  48. Wilhite DA (2000) Drought: a global assessment. Volume I. Rutledge Press: London and New YorkGoogle Scholar
  49. 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 EngineersGoogle Scholar
  50. 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 21:745–758CrossRefGoogle Scholar
  51. Yevjevich V (1967) An objective approach to definitions and investigation of continental hydrological droughts. Hydrology Paper 23. Colorado State University, Fort Collins, COGoogle Scholar
  52. Yue SH, Hashino M (2007) Probability distribution of annual, seasonal and monthly precipitation in Japan. Hydrolog Sci J 52(5):863–877CrossRefGoogle Scholar
  53. Zargar A, Sadiq R, Naser G, Khan F (2011) A review of drought indices. Environ Rev 19:333–349CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Majid Montaseri
    • 1
  • Babak Amirataee
    • 1
  • Rizwan Nawaz
    • 2
  1. 1.Department of Water EngineeringUrmia UniversityUrmiaIran
  2. 2.School of GeographyUniversity of LeedsLeedsUK

Personalised recommendations