Stormwater biofilter treatment model for faecal microorganisms.

Sci Total Environ

Environmental and Public Health Microbiology Laboratory (EPHM Lab), Department of Civil Engineering, Monash University, Clayton, VIC 3800, Melbourne, Australia; Department of Civil Engineering, Monash University, Clayton, VIC 3800, Melbourne, Australia. Electronic address:

Published: July 2018

AI Article Synopsis

  • A new model for simulating long-term microbial removal in stormwater biofilters was developed, utilizing a 'three-bucket' approach for water flow and a one-dimensional advection-dispersion equation for microbial transport.
  • The model incorporates key processes like adsorption, desorption, die-off, and includes temperature as a significant factor affecting die-off rates, validated through 44 weeks of data from five different biofilter configurations.
  • Calibration and validation results indicated strong performance, with limitations highlighted in model sensitivity due to potential data shortages, emphasizing the need for more comprehensive data for further refinement.

Article Abstract

This paper presents a new model to simulate long-term microbial removal in stormwater biofilters. The water flow module uses a 'three-bucket' approach to describe the flow processes in biofilters, while the microbial quality module employs the one-dimensional advection-dispersion equation to represent microbial transport and fate under different design and operational conditions. Three governing processes for microbial removal, adsorption, desorption and die-off, are included; temperature is also incorporated as a key factor for die-off. The model was tested using long term monitoring data collected from laboratory columns in which five different biofilter configurations were studied over a period of 44weeks. A multi-objective calibration with the balance of instantaneous ponding levels and event outflow volumes was implemented on the water flow module, and the Nash-Sutcliffe Efficiency (E) values ranged from 0.82 to 0.95. The microbial quality module was tested using the effluent Escherichia coli concentration data, and the E values obtained for different configurations were between 0.46 and 0.68. The optimized parameter values agreed with those presented in literature. However, sensitivity analyses suggested that the model's prediction was not sensitive to all parameters, the explanation for which was hypothesized to be data paucity rather than model structural uncertainties. Model validation was also conducted by splitting the data into calibration and validation datasets. The results further reinforced the needed for more data for model calibration.

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http://dx.doi.org/10.1016/j.scitotenv.2018.02.193DOI Listing

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