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Regional Drought Modes in Iran Using the SPI: The Effect of Time Scale and Spatial Resolution

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  • Tayeb Raziei
  • Isabella Bordi
  • Luis Pereira

Abstract

In the present paper, regional drought modes in Iran are identified applying the Principal Component Analysis (PCA) and Varimax rotation to the Standardized Precipitation Index (SPI) computed on different time scales. Data used include gridded monthly precipitation covering the period 1951–2007 retrieved from the Global Precipitation Climatology Centre (GPCC) archive with different spatial resolutions (2.5, 1 and 0.5° resolution). The objective of the study is twofold: (i) Investigate the stability of drought spatial modes as a function of the SPI time scales used for monitoring the different kinds of drought, (ii) Evaluate the impact of the spatial resolution of gridded data on drought regionalization. For the coarse spatial resolution of 2.5°, results show four drought modes of distinct variability, which remain quite stable when the SPI time scale is varied from 1- to 24-month. Differently, for higher spatial resolutions drought modes appear more sensitive to the index time scale and become less spatially homogeneous as the time scale is increased. Moreover, the number of identified modes (sub-regions) may reduce to three or two, but in all cases the most well defined sub-region appears to be the southern one. This suggests that both the spatial resolution of precipitation data and the time scale may affect drought regionalization, i.e. the number of drought modes and their spatial homogeneity. Copyright Springer Science+Business Media B.V. 2013

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:27:y:2013:i:6:p:1661-1674
    DOI: 10.1007/s11269-012-0120-3
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    References listed on IDEAS

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    1. B. Bonaccorso & I. Bordi & A. Cancelliere & G. Rossi & A. Sutera, 2003. "Spatial Variability of Drought: An Analysis of the SPI in Sicily," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 17(4), pages 273-296, August.
    2. Donald Wilhite & Mark Svoboda & Michael Hayes, 2007. "Understanding the complex impacts of drought: A key to enhancing drought mitigation and preparedness," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 763-774, May.
    3. Tayeb Raziei & Isabella Bordi & Luis Pereira, 2011. "An Application of GPCC and NCEP/NCAR Datasets for Drought Variability Analysis in Iran," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(4), pages 1075-1086, March.
    4. repec:ucp:bkecon:9780226316529 is not listed on IDEAS
    5. Sergio Vicente-Serrano, 2006. "Differences in Spatial Patterns of Drought on Different Time Scales: An Analysis of the Iberian Peninsula," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(1), pages 37-60, February.
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    2. Brunella Bonaccorso & David Peres & Antonio Castano & Antonino Cancelliere, 2015. "SPI-Based Probabilistic Analysis of Drought Areal Extent in Sicily," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(2), pages 459-470, January.
    3. Afiq Hipni & Ahmed El-shafie & Ali Najah & Othman Karim & Aini Hussain & Muhammad Mukhlisin, 2013. "Daily Forecasting of Dam Water Levels: Comparing a Support Vector Machine (SVM) Model With Adaptive Neuro Fuzzy Inference System (ANFIS)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(10), pages 3803-3823, August.
    4. 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.
    5. Javad Bazrafshan & Somayeh Hejabi & Jaber Rahimi, 2014. "Drought Monitoring Using the Multivariate Standardized Precipitation Index (MSPI)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(4), pages 1045-1060, March.
    6. Milan Gocic & Slavisa Trajkovic, 2014. "Drought Characterisation Based on Water Surplus Variability Index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 3179-3191, August.
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