Application of the weighted Markov chain model in the inflow prediction of the Miyun Reservoir
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Abstract:
Acco rding t o the act ual inflow data of the Miyun Reservo ir fr om 1960 to 2011, riv er runoff was select ed as the r andom variable, and t he r elated concept of the w eig hted Markov chain model and the st eps for the inflow pr ediction in the incoming one year w ere intro duced. The classificat ion metho d of averag e2standard was used to div ide the inflow sequence into four conditio ns, including dr ought, lean dr ought, lean wet, and w et. The autocor relation w as r egar ded as weig ht coefficient to pr edict inflow be2 tw een 2010 and 2011, which w ere compared w ith the measured data. T he results showed that the weig hted Mar ko v cha in model can predict inflow o f the Miyun Reserv oir w it h high pr ecision. Therefo re, the model w as used to predict inf low betw een 2012 and 2013. Finally, the erg odicit y and statio nary distr ibut ion of Markov cha in wer e analyzed, and the return per iods of o bser ved sequence under the w et and dry condit ions w ere calculat ed, which sugg ested that the occurr ence pro bability o f lean dro ught is the larg est. The inflow of the Miy un Reserv oir was predicted to be lean dr ought in the futur e.
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