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Markov mixture models for drought lengths
Author(s) -
Jackson Barbara Bund
Publication year - 1975
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr011i001p00064
Subject(s) - streamflow , markov chain , markov model , set (abstract data type) , mixture model , markov process , environmental science , computer science , mathematics , statistics , artificial intelligence , machine learning , geography , cartography , drainage basin , programming language
Markov mixture models combine a Markov model for transitions between low and normal streamflow states with a mixture model blending two normal subpopulations. The models are particularly effective for generating synthetic streamflow records with long and severe droughts. Their use in a hypothetical planning problem illustrates the application of a set of modeling precepts.