Hydrologic data assimilation using particle Markov chain Monte Carlo simulation: Theory, concepts and applications

Advances in Water Resources

Volumn 51, Issue , 2013, Pages 457-478

  Vrugt, Jasper A ^a,b   ter Braak, Cajo J F ^c   Diks, Cees G H ^d   Schoups, Gerrit ^e  

^a University of California at Irvine   (United States)

^b UNIVERSITY OF AMSTERDAM   (Netherlands)

^c WAGENINGEN UNIVERSITY   (Netherlands)

^d UNIVERSITY OF AMSTERDAM   (Netherlands)

^e DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

Bayes; DREAM; Markov chain Monte Carlo; Parameter and state estimation; Particle filtering; Sequential Monte Carlo

Indexed keywords

BAYES; DREAM; MARKOV CHAIN MONTE CARLO; PARAMETER AND STATE ESTIMATION; PARTICLE FILTERING; SEQUENTIAL MONTE CARLO;

CALIBRATION; COMPUTER SIMULATION; MATHEMATICAL MODELS; MONTE CARLO METHODS; UNCERTAINTY ANALYSIS;

DATA PROCESSING;

COMPUTER SIMULATION; DATA ASSIMILATION; ERROR ANALYSIS; ESTIMATION METHOD; HYDROLOGICAL MODELING; MARKOV CHAIN; MONTE CARLO ANALYSIS;

EID: 84872965655     PISSN: 03091708     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.advwatres.2012.04.002     Document Type: Article

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