Analyzing big data to improve water management

A data integration platform for watershed management has been implemented by the Sourthern Ontario Water Consortium (SOWC). The platform, which was built in collaboration with IBM, assimilates 600 data points per hour, streaming from more than 120 sensors installed within 80 square kilometers of watershed.

According to IBM, the new platform analyzes data collected every 15 minutes from meteorological, surface, subsurface and groundwater sensors, which monitor such factors as rain and snowfall, flow rates and water quality. The watershed nourishes urban, agriculture and forested land along the Grand River, the largest inland river system in southern Ontario.

Brenda Lucas, executive director of SOWC, says, “The opportunities enabled by highly instrumented, data-centric smart watersheds will not only improve understanding of watershed management challenges, but will allow the development of new tools for monitoring and incorporating real-time data into decision-making.”

An important feature of the platform, according to IBM, is the fact that information communicated by the sensors can be interpreted in real time, allowing rapid responses to environmental events, or “triggers.” That improves on traditional passive monitoring, which can miss important watershed behavior triggered by intense, short-lived environmental events.

The system will automatically alert users to the onset of an event such as a heavy downpour in one area of the watershed. That allows sensors elsewhere in the network to be triggered to increase the rate at which they collect data, facilitating a new paradigm in intelligent watershed monitoring, IBM says.

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