Bayesian analysis for uncertainty estimation of a canopy transpiration model

@inproceedings{Samanta2007BayesianAF,
  title={Bayesian analysis for uncertainty estimation of a canopy transpiration model},
  author={Sandipan Samanta and D. S. Mackay and Murray K. Clayton and Eric L. Kruger and Brent E Ewers},
  year={2007}
}
[1] A Bayesian approach was used to fit a conceptual transpiration model to half-hourly transpiration rates for a sugar maple (Acer saccharum) stand collected over a 5-month period and probabilistically estimate its parameter and prediction uncertainties. The model used the Penman-Monteith equation with the Jarvis model for canopy conductance. This deterministic model was extended by adding a normally distributed error term. This extension enabled using Markov chain Monte Carlo simulations to… CONTINUE READING