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dwellings or commercial buildings within an inundation or flood zone. The AI algorithms are used to assess and identify data clusters that look like a house, using machine learning to understand local building materials for example. The learning is based on the buildings in the surrounding area and the algorithm also rules out things like bodies of water and other extraneous data. Analysis of visual satellite data from two different time periods allows new buildings to be detected. The flood zone or inundation area is overlaid onto the map and having identified a potential structure at risk the tool flags that location for further investigation. Presented with a timely update on structures that potentially affect a dam’s hazard rating without having to wade through all the data, dam safety officers are able to proactively prioritize dams with potentially risky new urban developments in the flood plain. Using freely available data keeps the costs down and does offer far more frequent observations than every five or six years. It therefore narrows the window of potentially dangerous uncertainty. “The data gives a very comprehensive set of high-resolution optical data to get that detail of a house. It means that for a dam considered low hazard we’re getting several additional views of that dam that wouldn’t have occurred under a normal regime of physical observations,” says Camilla Braithwaite, Rezatec’s Product Manager. With dam owners and regulators able to identify changes in urban development much more easily than with infrequent, manual inspections that can take weeks or months to complete, the Urban Change tool is able to provide a central view of changes within the inundation zone of every dam across a whole state. Highlighting potential changes to risks and hazard classifications is a targeted resource approach that allows regulators to deploy their staff resources with maximum efficiency. “These kinds of satellite observations really help with ensuring dams are appropriately classified in a timely way and that their emergency action plans are in place and up to date,” says Braithwaite. With dam safety officers able to prioritize dams
where change has occurred, it may be possible to reduce resources expended on other dams that aren’t such a high priority because nothing has changed over the course of several years. Remote observations can also potentially improve workplace safety. For example, when sending people out to walk the flood area and perhaps explore steep-sided ravines to check for new houses or commercial buildings there is the possibility of trips and falls or encountering wildlife, such as venomous snakes. “Having some tools to go beyond our normal
drive arounds would be certainly helpful, something automated. It is an interesting idea to use more satellite and AI technology to know if there a new house below this dam since the last time we looked,” says McCormick. Percell-Taureau also sees potential benefits, though she sounds a note of caution: “There’s value, but integrating it into the systems that we have requires money, people, and time. All of those things are stretched pretty thin. The money that we use to develop new tools for dam safety has been getting tighter and tighter every year so we really have to work hard to figure out which of these things are the highest priority and will give us the biggest impacts to improve our programs.”
Nonetheless, Braithwaite argues that technology companies are able to develop new products and spread the costs across the industry: “With most regulators struggling for resources, we want to drive efficiency with our technology. Rather than each regulator developing their own solution we can provide a lower-cost alternative,” she says.
Keeping people safe in a changing world
With a mandate to protect public safety and prevent economic loss from potential dam failure, and faced with a rise in urban development, dam safety officers are evidently challenged by a lack of resources even as their role has never been more important. Traditional methods of ground survey and inspection are often too resource-intensive to keep up with the rise in urban development in the inundation zones of the dams they are responsible for and potentially risky urban changes can therefore occur between inspections. New buildings and hazards can go unrecorded and unactioned which can impact hazard classifications for longer than is ideal. Dam owners and regulators now have alternative options when it comes to monitoring structures and surrounding areas. Using data from space rather than relying solely on ground-based inspections, clever machine-led analysis can enhance their processes and make sure new communities are identified before any potential failure puts them at risk. “In terms of the regulatory workload it’s not necessarily going to mean they’ve got less to do but it can help better prioritise their time more effectively, so they are able to keep ahead of their regulatory obligations and keep people safe,” says Braithwaite, adding: “These kinds of satellite observations help ensure dams are appropriately classified in a timely way and that their emergency action plans are in place and up to date.” As McCormick concludes: “It would be a good if we could use those tools because certainly the problem is that we have a limited number of staff to address these issues of changing hazard classifications. I think these kinds of tools would at least let you know if there are any blind spots out there and risks that need to be managed to some acceptable level.” Regulators can’t prevent change, but with smarter
tools it is possible to keep people safe in the most productive way. ●
www.waterpowermagazine.com | June 2022 | 13
Above: Machine led analysis can enhance the process of monitoring dam structures and the surrounding areas
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