Receiving water quality assessment: comparison between simplified and detailed integrated urban modelling approaches

Area of Science:

• Environmental Engineering
• Water Resource Management
• Computational Hydrology

Background:

• Urban water quality management relies on numerical models to link inputs (rainfall, pollutants) to water quality responses.
• Conventional separate component modeling hinders whole-system optimization.
• Integrated urban drainage modeling is crucial for meeting Water Framework Directive requirements.

Purpose of the Study:

• To compare the uncertainty of detailed and simplified integrated urban drainage modeling approaches.
• To evaluate model reliability based on uncertainty limitation capacity.

Main Methods:

• Employed two modeling approaches: a detailed model using Saint-Venant and advection-dispersion equations, and a simplified reservoir model.
• Utilized a parsimonious bespoke model developed in prior research.
• Applied the Generalised Likelihood Uncertainty Estimation (GLUE) procedure for uncertainty analysis.

Main Results:

• Both detailed and simplified models demonstrated good capability in fitting experimental data for both quantity and quality aspects.
• The detailed model approach proved more robust, exhibiting narrower uncertainty bands.
• The simplified river water quality model approach showed higher uncertainty, potentially limiting its suitability for receiving water body assessments.

Conclusions:

• While both modeling approaches can fit data, detailed integrated urban drainage models provide greater reliability and reduced uncertainty.
• Simplified models, though faster, may introduce significant uncertainty, impacting the accuracy of water quality assessments in receiving waters.
• Choosing the appropriate modeling approach is critical for effective urban water quality management and regulatory compliance.