Parameter Identification by MCMC Method for Water Quality Model of Distribution System

Parameter identification plays an important role in environmental model application. An integrated method of Markov Chain Monte Carlo simulation (MCMC) and EPANET Multi-Species Extension toolkit was constructed for the parameter identification of water quality model of distribution system, taking bacterial regrowth model with chlorine inhibition as an example. Combined with the prior distribution of the model parameters and water quality observation data, an upgraded algorithm called DRAM was introduced to the MCMC sampling to obtain the posterior parameter distribution. Results indicated that this MCMC method has its special advantages in producing posterior distribution and provides robust means of parameter identification of water distribution system modeling.