“Sunny day flooding” got you feeling gloomy?
It turns out that sunny days can bring doom and gloom, too. The National Oceanic and Atmospheric Administration (NOAA) has documented, with increasing frequency, the high tide flooding that threatens many coastal cities in the U.S. Also known as “sunny day” flooding, this phenomenon is a result of rising sea levels and is projected to worsen dramatically as the climate changes. (For perspective, the Fourth National Climate Assessment projects that the city of Charleston, SC, will face high tide flooding 180 days/year by 2045, compared to 11 days/year in 2014 — an order of magnitude increase.) You can imagine the strain that this puts on coastal cities’ water management infrastructure, such as combined sewer systems which are vulnerable to overflows and backup during high water volume periods.
While adaptation should not be a distraction from climate change mitigation, cities can leverage technology to become more resilient and prepared for flooding. The NOAA recently released its Coastal Inundation Dashboard which calculates flood risk by location based on water level monitors, 48 hour weather forecasts, and storm surge and historic flooding information. In the private sector, Google has applied machine learning algorithms to flood forecasting as part of its AI for Social Good initiative. They have developed inundation models, high-resolution elevation maps (drawing on satellite imagery from Google Maps), and hydraulic modeling that incorporates both traditional physics and machine learning.
As flood forecast models become more and more accurate, policy makers will have new — and difficult — decisions to make. Should cities invest in marginal water infrastructure improvements (e.g. smart sewers) for the short term, or long-term structural changes like redesign, relocation and mitigation?
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