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Uncertainty-Driven Characterization of Climate Change Effects on Drought Frequency Using Enhanced SPI

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  • Amin Zargar
  • Rehan Sadiq
  • Faisal Khan

Abstract

The Standardized Precipitation Index (SPI) is a well-established drought index that is based on transforming the interannual distribution of precipitation to a standard normal distribution. Because of its robust statistical basis, SPI is readily applicable to different regions making comparisons between locations and time windows possible. Nevertheless, the usability of SPI results is undermined by shortcomings that are partly resultant from data and model uncertainties. One such shortcoming is the inability of the existing SPI model to include change in variability of interannual precipitation from non-stationary normal – mostly caused by climate change. In addition, epistemic uncertainty in the form of incompleteness in station-wide precipitation records results in heterogeneity and inconsistency in SPI results. The effects of such epistemic uncertainty on the accuracy of estimations of long-term changes in drought frequency are mostly unknown. Given such deficiency, SPI’s procedure and subsequent results remain deterministic and inadequately informative. Here, we introduce modifications to the traditional SPI using Dempster-Shafer theory (DST) to enable modeling and propagation of variability and epistemic uncertainty with the regular SPI procedure. By generalizing the SPI model from a deterministic setting to an “uncertainty-driven setting” provided by DST, this work makes possible: (a) efficiently propagating data uncertainty in interpolation of station-wide precipitation and SPI, and (b) modeling the effects of shift in precipitation normals (due to e.g., climate change) on drought frequency. In addition, the significance of this shift may then be evaluated with respect to the epistemic uncertainty by measuring how much of the surrounding epistemic uncertainty this shift encloses (i.e., “probability of enclosing”). The latter is especially important due to large unknowns already associated with climate change modeling. We implement the model on summer extreme drought for the Okanagan Basin, BC, Canada. For a single general circulation model and scenario (CGCM3 A2) a maximum 7 % increase in summer extreme drought (for 2080s, as per current definition) is estimated with a maximum probability of enclosing of 36 %. Copyright Springer Science+Business Media Dordrecht 2014

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  • Amin Zargar & Rehan Sadiq & Faisal Khan, 2014. "Uncertainty-Driven Characterization of Climate Change Effects on Drought Frequency Using Enhanced SPI," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(1), pages 15-40, January.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:1:p:15-40
    DOI: 10.1007/s11269-013-0467-0
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    References listed on IDEAS

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    1. Kai Duan & Yadong Mei, 2014. "Comparison of Meteorological, Hydrological and Agricultural Drought Responses to Climate Change and Uncertainty Assessment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(14), pages 5039-5054, November.
    2. Ana Paulo & Diogo Martins & Luís Santos Pereira, 2016. "Influence of Precipitation Changes on the SPI and Related Drought Severity. An Analysis Using Long-Term Data Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(15), pages 5737-5757, December.
    3. Md Haque & Ataur Rahman & Dharma Hagare & Golam Kibria, 2014. "Probabilistic Water Demand Forecasting Using Projected Climatic Data for Blue Mountains Water Supply System in Australia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(7), pages 1959-1971, May.
    4. I. García-Garizábal & J. Causapé & R. Abrahao & D. Merchan, 2014. "Impact of Climate Change on Mediterranean Irrigation Demand: Historical Dynamics of Climate and Future Projections," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(5), pages 1449-1462, March.
    5. Ayşegül Kuzucu & Gülay Onuşluel Gül, 2023. "Analysis of Drought Dynamics over Annual Maximum Drought Severity Series Based on Daily Index Definitions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1421-1436, February.
    6. Basem Shomar & Mohamed Darwish & Candace Rowell, 2014. "What does Integrated Water Resources Management from Local to Global Perspective Mean? Qatar as a Case Study, the Very Rich Country with No Water," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 2781-2791, August.
    7. B. Fiseha & S. Setegn & A. Melesse & E. Volpi & A. Fiori, 2014. "Impact of Climate Change on the Hydrology of Upper Tiber River Basin Using Bias Corrected Regional Climate Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(5), pages 1327-1343, March.
    8. Antonino Cancelliere, 2017. "Non Stationary Analysis of Extreme Events," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3097-3110, August.

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