Denver Suburb Adopts New Geospatial Technology
Arvada, Colo., switches to InfoWater for water infrastructure modeling and management
MWH Soft announced that Arvada, Colo., has adopted the company's InfoWater Suite software as its standard water modeling, design and management solution. The software will serve as the foundation for continued development of a comprehensive GIS-centric solution for the city’s complex drinking water distribution system.
Located 7 miles from the state capital, between Denver and the eastern edge of the Rocky Mountains, Arvada covers 23,000 acres and serves a population in excess of 100,000. The city’s drinking water system has the capacity to produce 52 million gal per day from its two water treatment plants. Its two primary sources of water are the Denver Water Department’s Moffat System and Clear Creek.
The Moffat water system, a year-round source, is diverted from Denver’s Ralston Reservoir. This mountain snowmelt water is collected from the Fraser River and South Boulder Creek basins and transported to Gross Reservoir and then to Ralston Reservoir. Approximately 25% of the city’s water supply is diverted from Clear Creek, where it is stored in a local reservoir until needed during months when water demand is high.
“MWH Soft has provided us with powerful software and top-notch service,” said Kevin Tohill, water quality technician for the city of Arvada. “We chose InfoWater because the products are very easy to learn and use, integrate seamlessly with our ArcGIS platform and have the power to model and analyze our complex water network quickly and reliably. These tools make master planning fast, easy, accurate and cost-effective. That gives us more power to improve the operation, performance and integrity of our existing systems and plan the new facilities we need to accommodate growth.”
Arvada also opted to extend the power of InfoWater by purchasing the suite’s add-on modules. These extras enable the city to perform valve criticality modeling, pump scheduling optimization, automated demand allocation, on-demand contaminant and main break customer notifications, automated hydraulic design and genetic algorithm-based model calibration.
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