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Updated: May 19, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

Identifiability analysis in conceptual sewer modelling.

M Kleidorfer1, G Leonhardt, W Rauch

  • 1University of Innsbruck, Unit of Environmental Engineering, Technikerstrasse 13, 6020 Innsbruck, Austria. manfred.kleidorfer@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.

Parameter identifiability analysis helps calibrate environmental models. For combined sewer systems, optimal measurement sites are crucial for identifying key parameters like effective impervious area, reducing computational costs.

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Area of Science:

  • Environmental modeling
  • Hydrology
  • Water resource management

Background:

  • Accurate environmental model calibration requires assessing parameter sensitivity and identifiability.
  • Parameter identifiability analysis determines if parameter uncertainties can be compensated by others.
  • Identifiability is dependent on calibration data and measurement strategies.

Purpose of the Study:

  • To apply identifiability analysis to a combined sewer system model.
  • To investigate the impact of measurement site number and location on parameter identifiability.
  • To predict combined sewer overflow emissions effectively.

Main Methods:

  • Utilized identifiability analysis on a conceptual combined sewer system model.
  • Tested various measurement layouts, including number and location of sites.
  • Focused on identifying the 'effective impervious area' parameter.

Main Results:

  • With specific overflow and treatment plant runoff data, only 13 sensitive catchment areas (effective impervious area) were identifiable.
  • Demonstrated that measurement layout significantly influences the number of identifiable parameters.
  • Identifiability analysis offers low computational costs, equaling the number of model parameters.

Conclusions:

  • Measurement site selection is critical for robust parameter identification in combined sewer models.
  • Identifiability analysis is an efficient tool for calibrating complex environmental models with long runtimes.
  • This method aids in understanding and predicting combined sewer overflow emissions more accurately.