RIONET: a water quality management tool for river basins

Area of Science:

• Environmental Science
• Water Resource Management
• Ecosystem Modeling

Background:

• The EU Water Framework Directive mandates comprehensive water quality management in river basins.
• Existing tools often lack the capability to simulate complex river networks.
• Understanding self-purification processes is crucial for effective water quality assessment.

Purpose of the Study:

• To develop RIONET, an advanced water quality management tool for river basins.
• To enable simulation of water quality across entire river networks, not just single rivers.
• To incorporate detailed self-purification mechanisms, including benthic biofilm contributions.

Main Methods:

• Utilized a submodel of the IWA River Water Quality Model No. 1.
• Modeled self-purification processes occurring in both benthic biofilm and bulk water.
• Integrated Geographic Information Systems (GIS) for inputting hydrological data.
• Conducted test runs using the Bode river subcatchment in Saxon Anhalt.

Main Results:

• RIONET successfully simulates water quality in river networks.
• Laboratory experiments confirmed the significant role of benthic biofilm in self-purification.
• The tool effectively integrates diverse data inputs, including wastewater treatment plant discharges and river flow dynamics.
• Test runs in the Bode river basin demonstrated the tool's practical applicability.

Conclusions:

• RIONET provides a robust framework for water quality management in river basins.
• The model's emphasis on benthic biofilm processes enhances simulation accuracy.
• Integration with GIS streamlines data input and application of the management tool.
• RIONET supports compliance with the EU Water Framework Directive through advanced simulation capabilities.