June 6, 2017
2 p.m. EST
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Flooding, fresh-water stewardship along Ontario’s Grand River to be studied
A new data integration platform for watershed management built by the Southern Ontario Water Consortium (SOWC) in collaboration with IBM is helping researchers, urban planners and others develop more sophisticated tools to predict floods, safeguard the drinking water supply and forecast the impact of growth and urbanization on vital ecosystems.
This first-in-Canada platform assimilates 600 data points per hour, streaming from more than 120 sensors installed within 80 sq kilometers of watershed that nourishes urban, agriculture and forested land along the Grand River, the largest inland river system in southern Ontario.
The Grand River, a mix of pristine, urbanizing and urban areas, offers an ideal environment for research and development. It comprises 25% of the Canadian land area draining into Lake Erie, and its basin is home to more than 750,000 people providing the water supply for the Region of Waterloo, Brantford and Six Nations.
The new platform analyzes data collected every 15 minutes from meteorological, surface, subsurface and groundwater sensors, which monitor everything from rain- and snowfall, soil moisture, water turbidity, flow rates, temperature, to groundwater and well water quality.
Traditionally, watershed research has been limited by the inability to collect, transmit and store massive amounts of data collected from monitoring sites, merge information to evaluate trends and capture sporadic events that could be crucial in understanding a watershed. Because of advances in both hardware and software, users of the data integration platform are able to gather the information needed to analyze and interpret a watershed unlike ever before.
An important feature of the platform is the fact that information communicated by the sensors can be interpreted in real time, allowing rapid responses to environmental events, or ‘triggers’. This 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. This 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.
The platform is now available to a variety of stakeholders including academics, provincial and municipal administrators and individuals or companies looking to develop, test or demonstrate new systems or technologies. It provides access to real-time data streams, and the ability to both create custom applications and expand on existing functionality through add-on features. The platform also provides public Web-access to anyone interested in simply viewing the data being captured.