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Factors Influencing Markov Chains Predictability Characteristics, Utilizing SPI, RDI, EDI and SPEI Drought Indices in Different Climatic Zones

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  • Seyed Banimahd
  • Davar Khalili

Abstract

Comparability analyses were carried out to investigate behavioural aspects of effective drought index (EDI), standardized precipitation index (SPI), reconnaissance drought index (RDI) and standardized precipitation evapotranspiration index (SPEI), considering 3-month, 6-month and annual time periods. Investigations included parametric/non-parametric correlation analysis among indices, climatic zone influence, record length impacts and evapotranspiration role (RDI and SPEI) on Markov chains predictability characteristics. Except for the EDI, all indices/cases (all climatic zones) showed significant correlation. In arid/semi-arid climates, the 3-month and 6-month maximum drought severities were detected by the RDI and annual maximum drought severities were detected by the SPEI, emphasizing the evapotranspiration influence. In all climatic zones, the EDI values for wet (dry) periods were higher (lower), compared to other indices. First order dependency was detected for the EDI (all cases) and the SPI (most cases), over entire period (1951–2011) and sub-periods [(1951–1981), (1982–2011)]. The largest number of second order dependency was detected by the SPEI, followed by a relatively large number of such cases by the RDI (3-month time period), for the 61-year data period. This research showed that several factors influence Markov chains predictability characteristics in drought studies, particularly the impact of record length and evapotranspiration (RDI and SPEI) were confirmed. Copyright Springer Science+Business Media Dordrecht 2013

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  • Seyed Banimahd & Davar Khalili, 2013. "Factors Influencing Markov Chains Predictability Characteristics, Utilizing SPI, RDI, EDI and SPEI Drought Indices in Different Climatic Zones," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(11), pages 3911-3928, September.
    • Handle: RePEc:spr:waterr:v:27:y:2013:i:11:p:3911-3928
    DOI: 10.1007/s11269-013-0387-z
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    1. Ali Tabrizi & Davar Khalili & Ali Kamgar-Haghighi & Shahrokh Zand-Parsa, 2010. "Utilization of Time-Based Meteorological Droughts to Investigate Occurrence of Streamflow Droughts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(15), pages 4287-4306, December.
    2. Davar Khalili & Tohid Farnoud & Hamed Jamshidi & Ali Kamgar-Haghighi & Shahrokh Zand-Parsa, 2011. "Comparability Analyses of the SPI and RDI Meteorological Drought Indices in Different Climatic Zones," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(6), pages 1737-1757, April.
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    6. Tayeb Raziei & Isabella Bordi & Luis Pereira, 2013. "Regional Drought Modes in Iran Using the SPI: The Effect of Time Scale and Spatial Resolution," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(6), pages 1661-1674, April.
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    14. Arash Modaresi Rad & Davar Khalili & Ali Akbar Kamgar-Haghighi & Shahrokh Zand-Parsa & Seyed Adib Banimahd, 2016. "Assessment of seasonal characteristics of streamflow droughts under semiarid conditions," 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. 82(3), pages 1541-1564, July.
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