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

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.

Modelling Nitrogen Removal in the Kibendera Wastewater Stabilization Ponds in Ruiru, Kenya

“…The high r values indicate that modelled concentrations were close to their corresponding observed concentrations for both calibration and validation periods. The values were consistent with those observed in previous studies [17,18]. Considering that experimental data was collected under uncontrolled environmental, chemical and physical conditions, the agreement between the model output and the observed effluent concentrations is reasonably good.…”

“…Modeling achieves complete evaluation of WSP perfor-mance in terms of nitrogen removal prediction under varying operating and shock loading conditions. Mathematical modeling methods have been found suitable for the analysis of nitrogen removal (Mayo 2013;Mukhtar et. al., 2017).…”

Temporal Variability in the Rhizosphere Bacterial and Fungal Community Structure in the Melon Crop Grown in a Closed Hydroponic System

“…By contrast, the strong competition between plants and microbes for nutrients can reduce plant productivity and yield. For instance, the contamination of a CHS with ammonia oxidizers and denitrifiers can potentially reduce the amounts of ammonia and nitrate that are available for plant growth [22][23][24].…”