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Quantifying Changes in Reconnaissance Drought Index using Equiprobability Transformation Function

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  • Abolfazl Mosaedi
  • Hamid Zare Abyaneh
  • Mohammad Ghabaei Sough
  • S. Samadi

Abstract

The Reconnaissance Drought Index (RDI) is obtained by fitting a lognormal probability density function (PDF) to the ratio of accumulated precipitation over potential evapotranspiration values (α k ) at different time scales. This paper aims to address the question of how a probability distribution may fit better to the α k values than a lognormal distribution and how RDI values may change in shorter (i.e.,3-month, and 6-month) and longer (i.e., 9-month, and annual) time scales during 1960–2010 period over various climate conditions (arid, semi-arid, and humid) in Iran. For this purpose, the series of RDI were initially computed by fitting a lognormal PDF to the α k values and the Kolmogorov–Smirnov (K-S) test was implemented to choose the best probability function in different window sizes from 3 to 12-months. The corresponding RDI values for the best distribution were then deriven based on an equiprobability transformation function. The differences between RDI values (the lognormal (RDI log ) and the best (RDI App ) distributions) were compared based on Nash-Sutcliffe efficiency (NSE) criterion. The results of goodness of fit test based on threshold value in the K-S test showed that the goodness of fit in the lognormal distribution may not be rejected at 0.01 and 0.05 significance levels while may only be rejected in a short term (Apr.-Jun.) period at humid station (Rasht station), and three-month (Oct.-Dec. and Apr.-Jun.) and six-month (Apr.-Sep.) periods in semi-arid station (Shiraz station) at significance levels of 0.10 and 0.20, correspondingly. Further a difference between RDI log and RDI App performed that RDI values may change if the best distribution employs and this may therefore lead to significant discrepant and/or displacement of drought severity classes in the RDI estimation. Copyright Springer Science+Business Media Dordrecht 2015

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  • Abolfazl Mosaedi & Hamid Zare Abyaneh & Mohammad Ghabaei Sough & S. Samadi, 2015. "Quantifying Changes in Reconnaissance Drought Index using Equiprobability Transformation Function," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2451-2469, June.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:8:p:2451-2469
    DOI: 10.1007/s11269-015-0944-8
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    References listed on IDEAS

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    1. Panagiotis Angelidis & Fotios Maris & Nikos Kotsovinos & Vlassios Hrissanthou, 2012. "Computation of Drought Index SPI with Alternative Distribution Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(9), pages 2453-2473, July.
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    6. 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.
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    1. Valipour, Mohammad & Gholami Sefidkouhi, Mohammad Ali & Raeini−Sarjaz, Mahmoud, 2017. "Selecting the best model to estimate potential evapotranspiration with respect to climate change and magnitudes of extreme events," Agricultural Water Management, Elsevier, vol. 180(PA), pages 50-60.
    2. Mohammad Ghabaei Sough & Hamid Zare Abyaneh & Abolfazl Mosaedi, 2018. "Assessing a Multivariate Approach Based on Scalogram Analysis for Agricultural Drought Monitoring," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(10), pages 3423-3440, August.
    3. Abdelaaziz Merabti & Mohamed Meddi & Diogo S. Martins & Luis S. Pereira, 2018. "Comparing SPI and RDI Applied at Local Scale as Influenced by Climate," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(3), pages 1071-1085, February.

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