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Updated: Jul 20, 2025

Vegetated Treatment Systems for Removing Contaminants Associated with Surface Water Toxicity in Agriculture and Urban Runoff
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Developing nitrogen removal models for stormwater bioretention systems.

Jiayi Li1, Teresa B Culver1, Padmini P Persaud2

  • 1Department of Civil and Environmental Engineering, University of Virginia, 351 McCormick Road, Charlottesville, VA, 22904, United States.

Water Research
|July 30, 2023
PubMed
Summary
This summary is machine-generated.

New models improve bioretention system performance by accurately simulating nitrogen removal. These advanced nitrogen removal models (NRMs) better predict effluent concentrations, enhancing stormwater management.

Keywords:
ModelingNitrogenSWMMStormwater bioretention

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Area of Science:

  • Environmental Engineering
  • Water Quality Management
  • Stormwater Management

Background:

  • Bioretention systems reduce runoff volume and remove nitrogen.
  • Internal water storage (IWS) and real-time control (RTC) can enhance bioretention performance.
  • Existing models struggle to simulate nitrogen transformations influenced by IWS and environmental factors.

Purpose of the Study:

  • Develop and evaluate nitrogen removal models (NRMs) for bioretention systems.
  • Compare model performance with varying nitrogen cycling complexity (Single Nitrogen Pool vs. 3 Nitrogen Pool) and kinetics (0-order, 1st-order, Michaelis-Menten).
  • Assess model adaptability to systems with IWS and RTC, using soil moisture data.

Main Methods:

  • Developed six NRMs by combining SP and 3P models with 0-order, 1st-order, and Michaelis-Menten kinetics.
  • Calibrated and validated NRMs using laboratory bioretention system data.
  • Integrated NRMs with the Storm Water Management Model (SWMM) for simulation and comparison.

Main Results:

  • 0-order kinetics were unsuitable for simulating nitrogen removal in bioretention systems.
  • 1st-order kinetics and Michaelis-Menten models showed similar performance.
  • The best model (3P-m) improved prediction accuracy for nitrogen event mean concentrations by 20% compared to SWMM.
  • 3P-m accurately predicted cumulative nitrogen mass removal rates (±7% error) for systems with IWS/RTC, outperforming SWMM (-23% error).

Conclusions:

  • 3P models offer higher accuracy and better biochemical reaction rate predictions than SP models.
  • SP models provide improved accuracy with simpler initial condition requirements.
  • The developed 3P-m model enhances the simulation of nitrogen removal in bioretention systems, particularly those with IWS and RTC.