North America |
j dams due to this hazard creep issue. This impacts our workload for dam safety programs because instead of looking at a dam and doing work every six years for a low hazard dam we have to do those same kinds of activities every year,” says McCormick.
Old job, new tools Given the growing demand for inspections, the
Below: New tools can help dam owners and regulators identify changes in urban development much more easily than with infrequent, manual inspections
increasing pace of urbanisation and the challenge of budgetary constraints, regulators and dam safety officials are now exploring new digital tools that can support their operational needs. They are adopting these measures in a bid to ensure all dams are classified correctly and that they have the appropriate safety measures in place. Some are already using open access satellite observations such as Google Earth or Digital Globe to support their physical observations. “We use tools like GIS where we can import the national infrastructure inventory and look at how that may intersect with the inundation boundaries of our facilities and also census data so that we can understand how populations are growing within our inundation reach. Satellite data is one of the layers that we can turn on in our GIS system,” says Percell-Taureau. Open access mapping tools are thus being scrutinised by regulatory staff to try to identify potential changes remotely. As McCormick explains: “That’s just using the tools that we have available to us. Back in the day you had to drive around more, but now you can maybe spot something from a distance and then
go back to the office and pull it up on Google Earth and see what’s going on. Once you see something on Google Earth then you can do the field work to see if it really is a problem or not and then do some modelling to double check it.” There are limitations to this approach though. Google Earth provides the date of the imagery being viewed at any given time and in addition has historic imagery, so you can look back and see when development might have occurred. However, in some areas the most recent imagery might be two to three years old, which is a constraint for real-time work. It is also possible to view observations in which tiles on the same page are not contemporaneous and therefore miss substantial urban developments in an inundation zone that could have a significant bearing on the hazard rating of a dam or other hydraulic structure. Indeed, in some images of the area around a dam, zooming in to the map presents older images and so houses can disappear as observers attempt to get a better view. To minimise dam risk in the age of hazard creep it is clearly important to have a reliable quality data set to review urban change and new tools are now becoming available that can fill this gap. One such development comes from geospatial AI firm Rezatec.
Mapping change with machine
learning Rezatec’s Urban Change tool gathers high-resolution optical data from satellites and a subsequent analysis using their machine-learning algorithm to identify new
12 | June 2022 |
www.waterpowermagazine.com
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