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Washington DOT to Implement CAiCE Visual Drainage Software 02.05.2003

CAiCE visual drainage will help automate design process and ease integration of existing highway data.

The Transportation Group for the GIS Division of Autodesk, Inc. announced the Washington Department of Transportation (WSDOT) has selected CAiCE Visual DrainageTM as its highway drainage design software. After a successful 6 month pilot project, WSDOT chose Visual Drainage for its ability to automate the drainage design process, integrate with other design applications, and reduce inefficiencies and costs typically associated with drainage design. The Visual Drainage deployment at the WSDOT will integrate with and complement CAiCE’s Visual PE software, which the WSDOT deployed in 1996 for survey and construction design automation.

The WSDOT manages over 7,000 miles of highway and employs approximately 2,500 engineering and support staff across six regions.

“The integration of roadway design and drainage data using Visual Drainage allows one of our key departments to become part of a more productive workflow process”, said Matt Witecki, P.E., H.E. State Hydraulics Engineer for the WSDOT. “With the addition of Visual Drainage, our engineers can efficiently handle an entire roadway design project – from survey through construction.”

The Visual Drainage software will be used by design and drainage engineers to perform network layout, spread analysis, storm tabulations, and culvert analysis. Using Visual Drainage, WSDOT designers will be able to use existing roadway data, such as superelevation, longitudinal slopes, edge-of-pavement markers, and seamlessly input them into the drainage design process. In addition, the WSDOT expects a reduction of costs, data entry errors, and staff time by eliminating manual input of data by drainage design engineers and easily integrate existing highway data into the design process. Visual Drainage’s automated hydrology tools will permit WSDOT engineers to delineate sub-basins and calculate time of concentration data in a fraction of the time, with increased accuracy over paper map methods.

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