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Case Study:
Municipal Water Quality Management

GeoSolutions Consulting has supported municipal water quality management. Analysis of environmental data was conducted to support the development of Decision Support Systems (DSS) for watershed management activities. In the Regional Municipality of Ottawa, there is a need to monitor the water quality within the watershed. The Rideau River often experiences poor water quality particularly after significant rainfalls throughout the summer. Beaches are often closed for periods throughout the summer. In this analysis GIS tools were used to model biological data, terrestrial characteristics and related parameters affecting the water quality of the Rideau River in the Regional Municipality of Ottawa-Carleton (1996).


To explore the feasibility of using 3D Modeling, Intergraph's Voxel Analyst was used to study changes within the biological data over time in the Rideau River. The area of Mooney's Bay was chosen as the test location.

Data Used:

  • Bathymetric Survey of the Mooney's Bay - Over 100,000 points were collected using a sounder and GPS technology.
  • Water Samples - At regular intervals through out the summer, samples at various depths were taken at surveyed sites in the bay. This provided very detailed and structured 4 dimensional data to model.
  • Environmental Data - In conjunction with the Water Samples, detailed records of rainfall, temperature and water flow were also recorded.

Mooney's Bay Bathemetric Model: Viewed in Voxel

Data Conversion:

Bathymetric survey points were converted into a TIN Model, which was then converted to an Intergraph 3D GRD or Grid Model. Using Intergraph's VOXEL product, a 3D solid model representing the body of water in Mooney's Bay was created.

Water Sample data was also converted from ASCII X, Y, Z data into VOXEL as 3D points with attributes.


The Analysis was conducted in VOXEL, an Intergraph 3D analysis tool.

The term Voxel is related to how the software stores the 3D volume data. Voxels are like Cubes that fill a volume. The amount of detail that can be represented is related directly to the size of the cubes that are used; the smaller the Voxels the larger the data set. Therefore a trade off between accuracy and processing speed was one of the analysis issues.

The water sample points were modeled using Voxel's Sparse to Volume utility that provides the capability to interpolate the distribution of the biological readings through out the Bay. The Solid model of the water in the bay was used to constrain the model. This provided a number of views, including cross sections of the water quality parameters of the bay throughout the summer.

Two Cross Sections of Biological Data Model

A flat cross Section with high values represented as 3D volumes.

A close up view of the above Picture. Notice how the 3D Volumes can be seen through the partially transparent cross section.