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Estimation of Drought Severity on Independent and Dependent Hydrologic Series

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  • T. Sharma

Abstract

The drought severity is the most important parameter for the design of water storage systems in order to alleviate the water shortages during drought periods. The largest drought severity, i.e. severity of a worst drought at a desired truncation level and for the desired return period can be estimated using the truncated normal distribution of the deficits in individual drought years, Poisson distribution of the number of drought spells over a period of T years and geometric distribution of drought duration. The analysis can be done for random or Markovian structure of drought variable (annual rainfall or runoff sequences) distributed normally or lognormally. The study indicated that the severity at a high truncation level is larger than that at a low truncation level over any desired return period T. Severity is also larger in the case of autocorrelated drought variable. A frequency formula for the largest drought severity can be formulated analogous to the flood frequency formula commonly found in the hydrologic texts. Copyright Kluwer Academic Publishers 1997

Suggested Citation

  • T. Sharma, 1997. "Estimation of Drought Severity on Independent and Dependent Hydrologic Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 11(1), pages 35-49, February.
    • Handle: RePEc:spr:waterr:v:11:y:1997:i:1:p:35-49
    DOI: 10.1023/A:1007904718057
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    Cited by:

    1. T. Sharma & U. Panu, 2014. "A Simplified Model for Predicting Drought Magnitudes: a Case of Streamflow Droughts in Canadian Prairies," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(6), pages 1597-1611, April.
    2. T. Sharma & U. Panu, 2013. "Predicting Drought Magnitudes: A Parsimonious Model for Canadian Hydrological Droughts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(3), pages 649-664, February.
    3. 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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