Bayesian modelling of algal mass occurrences-using adaptive MCMC methods with a lake water quality model

Environmental Modelling and Software

Volumn 22, Issue 7, 2007, Pages 966-977

  Malve, Olli ^a   Laine, Marko ^b   Haario, Heikki ^c   Kirkkala, Teija ^d   Sarvala, Jouko ^e  

^a FINNISH ENVIRONMENT INSTITUTE   (Finland)

^b UNIVERSITY OF HELSINKI   (Finland)

^c LAPPEENRANTA UNIVERSITY OF TECHNOLOGY   (Finland)

^d Water Protection Association of SW Finland ^*  (Finland)

^e UNIVERSITY OF TURKU   (Finland)

Author keywords

Adaptive Markov chain Monte Carlo; Bayesian modelling; Lake eutrophication modelling; Parameter identifiability

Indexed keywords

ALGAE; LAKES; MATHEMATICAL MODELS; MONTE CARLO METHODS; PHOSPHORUS; PLANTS (BOTANY); STATISTICAL METHODS;

ADAPTIVE MARKOV CHAIN MONTE CARLO; BAYESIAN MODELING; LAKE EUTROPHICATION MODELING; PARAMETER IDENTIFIABILITY;

WATER QUALITY;

ALGAL BLOOM; BAYESIAN ANALYSIS; BIOMASS; CYANOBACTERIUM; EUTROPHICATION; GRAZING; LACUSTRINE ENVIRONMENT; MARKOV CHAIN; MONTE CARLO ANALYSIS; NUMERICAL MODEL; PHOSPHORUS; PREDATOR-PREY INTERACTION; SUCCESSION; TEMPERATURE EFFECT; WATER QUALITY; ZOOPLANKTON;

EURASIA; EUROPE; FINLAND; LAKE PYHAJARVI; NORTHERN EUROPE; SCANDINAVIA;

ALGAE; BACILLARIOPHYTA; CHRYSOPHYCEAE; CRUSTACEA; CYANOBACTERIA;

EID: 33846882597     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2006.06.016     Document Type: Article

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