Modeling Nitrogen Dynamics in a Waste Stabilization Pond System Using Flexible Modeling Environment with MCMC

Int J Environ Res Public Health. 2017 Jul 12;14(7):765. doi: 10.3390/ijerph14070765.

Abstract

This study presents an approach for obtaining realization sets of parameters for nitrogen removal in a pilot-scale waste stabilization pond (WSP) system. The proposed approach was designed for optimal parameterization, local sensitivity analysis, and global uncertainty analysis of a dynamic simulation model for the WSP by using the R software package Flexible Modeling Environment (R-FME) with the Markov chain Monte Carlo (MCMC) method. Additionally, generalized likelihood uncertainty estimation (GLUE) was integrated into the FME to evaluate the major parameters that affect the simulation outputs in the study WSP. Comprehensive modeling analysis was used to simulate and assess nine parameters and concentrations of ON-N, NH₃-N and NO₃-N. Results indicate that the integrated FME-GLUE-based model, with good Nash-Sutcliffe coefficients (0.53-0.69) and correlation coefficients (0.76-0.83), successfully simulates the concentrations of ON-N, NH₃-N and NO₃-N. Moreover, the Arrhenius constant was the only parameter sensitive to model performances of ON-N and NH₃-N simulations. However, Nitrosomonas growth rate, the denitrification constant, and the maximum growth rate at 20 °C were sensitive to ON-N and NO₃-N simulation, which was measured using global sensitivity.

Keywords: GLUE; MCMC; flexible modeling environment; global uncertainty; nitrogen dynamic; parameterization; sensitivity; waste stabilization pond.

MeSH terms

  • Markov Chains
  • Models, Theoretical*
  • Monte Carlo Method
  • Nitrogen / analysis*
  • Nitrosomonas / growth & development
  • Ponds
  • Software
  • Uncertainty
  • Waste Disposal, Fluid*
  • Water Pollutants, Chemical / analysis*

Substances

  • Water Pollutants, Chemical
  • Nitrogen