On the Extreme Streamflow Drought Analysis

Emir Zelenhasic

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2002, vol. 16, issue 2, 105-132

Abstract: A procedure, based on the distribution of the largest streamflowdrought deficit and on the composite hydrograph recession curve, is proposed for the derivation of the n-year streamflow drought,for the cases for which the assumption of identical deficit and duration frequencies is not valid, for a given river at a given location.The present article is a continuation of the previous work of Zelenhasic on the extremes of low flows. The previous streamflowdrought stochastic model dealt with the situation where theirexists the equality of probability of occurrence of extreme droughtdeficit and extreme drought duration, i.e. the assumption ofidentical deficit and duration frequencies. In practice, thecondition of identical frequencies is often mitigated by the lessstringent condition of approximate frequencies. The present articleanalyzes the situation in which there is no equality of probabilityof occurrence of extreme drought deficit and extreme droughtduration. Or, to be more specific, this method has no constraintssuch as the assumption of identical deficit and duration frequencies. The earlier theoretical explanations of the individualstreamflow drought components of the method of streamflow droughtstochastic process are completely valid in this paper, as well. Themethod has been applied in this paper to data from gaging stationson the Sava River at Srem. Mitrovica, the Drava River at D.Miholjac and the Danube River at Bezdan. The application of theprocedure has shown that the method is simple, reliable and efficient. Copyright Kluwer Academic Publishers 2002

Keywords: engineering hydrology; extreme streamflow drought; random number of random variables; stochastic process; upper and lower statistical extremes (search for similar items in EconPapers)
Date: 2002
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Citations: View citations in EconPapers (3)

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DOI: 10.1023/A:1016108532059

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