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Vegetated Treatment Systems for Removing Contaminants Associated with Surface Water Toxicity in Agriculture and Urban Runoff
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A software-based sensor for combined sewer overflows.

G Leonhardt1, S Fach, C Engelhard

  • 1Unit of Environmental Engineering, Institute for Infrastructure, University of Innsbruck, Technikerstrasse 13, A 6020 Innsbruck, Austria. guenther.leonhardt@uibk.ac.at

Water Science and Technology : a Journal of the International Association on Water Pollution Research
|August 7, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to estimate excess flow from combined sewer overflows (CSOs) using sewer data, eliminating the need for rainfall data. This approach enables online monitoring and can be extended to water quality modeling.

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Area of Science:

  • Environmental Engineering
  • Hydrology
  • Wastewater Management

Background:

  • Combined sewer overflows (CSOs) release untreated sewage and stormwater into water bodies.
  • Accurate estimation of excess flow from CSOs is crucial for environmental protection and infrastructure management.
  • Traditional methods often rely on rainfall data, which can be unavailable or inaccurate.

Purpose of the Study:

  • To develop a novel methodology for online estimation of excess flow from CSO structures.
  • To demonstrate the feasibility of using sewer flow and water level data to replace rainfall data in CSO modeling.
  • To enable real-time monitoring and management of CSO events.

Main Methods:

  • Development of an inverse rainfall-runoff model to simulate net rainfall using sewer flow and water level data.
  • Application of a standard rainfall-runoff model to simulate excess flow at CSO structures.
  • Integration of the model with SCADA systems for online operation and data acquisition.
  • Case study application to validate the methodology.

Main Results:

  • The inverse rainfall-runoff model successfully simulated net rainfall, compensating for the absence of direct rainfall measurements.
  • The methodology allowed for online estimation of excess flow from CSO structures.
  • The developed approach proved effective in a practical case study, showing its utility in data-scarce scenarios.
  • The system can be integrated with water quality models for pollutant concentration estimation.

Conclusions:

  • The proposed methodology provides a robust alternative for online excess flow estimation from CSOs, particularly when rainfall data is limited.
  • The use of sewer system data and inverse modeling offers a cost-effective and reliable solution for CSO monitoring.
  • The framework supports enhanced environmental management by enabling timely and accurate assessment of CSO impacts.