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dc.contributor.authorYi Li
dc.contributor.authorTianwei Long
dc.contributor.authorXueao Sun
dc.date.accessioned2022-01-30T19:42:24Z
dc.date.available2022-01-30T19:42:24Z
dc.date.issued2020
dc.identifier.other%28ASCE%29HE.1943-5584.0001869.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4265828
dc.description.abstractCurrent probabilistic methods for maximum and minimum run lengths in a hydrologic time series need further development. Using the first-order Markov chain model and an extreme-value theory for randomly occurring events, this study investigates probabilistic properties of both extreme run lengths in a stationary hydrologic time series. The interaction between negative run length, positive run length, total run length, life span, and number of total runs was analyzed. As a result, a joint probabilistic space was defined for negative (or positive) and total run lengths, and a corrector was established for an existing cumulative distribution function (CDF) of negative run length. Lengths of incomplete runs were considered appropriately, especially when no total run occurred during the life span. A generalized CDF was formulated for each extreme value, and simplified versions of the generalized CDF were proposed as practical approximate methods, including expectation approximations and limiting approximations. Results of computational examples indicated that expectation approximations generally provided better results than limiting approximations for maximum negative run lengths, and the non-negligible probability of no total run occurring during the life span may have a significant influence on CDFs.
dc.publisherASCE
dc.titleProbabilistic Structure of Extreme Run Lengths in a Stationary Hydrologic Time Series
dc.typeJournal Paper
dc.journal.volume25
dc.journal.issue2
dc.journal.titleJournal of Hydrologic Engineering
dc.identifier.doi10.1061/(ASCE)HE.1943-5584.0001869
dc.page04019062
dc.treeJournal of Hydrologic Engineering:;2020:;Volume ( 025 ):;issue: 002
dc.contenttypeFulltext


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