Rise to meet the tide

As the threat of coastal flooding increases, scientists are responding with a flood of data. Faster, more accurate forecasts can save lives and property.

Christina Laughlin is usually doing everything she can to avoid flooding in her Norfolk, Va., Chesapeake Bay neighborhood. But on a blustery Sunday morning in October 2019, she donned a windbreaker and rain boots, grabbed her battered smartphone and deliberately headed straight for the high water mark.

Like her, hundreds of other locals were on the move that day, busy taking pictures of the water and linking them to GPS markers during the highest astronomical tide of the year, known as the of “royal tide”. Norfolk is one of many coastal cities in the eastern United States with record rates of sea level rise, and scientists hope the data collected by these citizen scientists can help refine the ability to predict. exactly when and where destructive floods will occur.

Mid-latitude low-rise towns like Norfolk are particularly vulnerable, says geographer James Voogt of the University of Western Ontario, one of the authors of a 2020 paper in the Annual Environment and Resource Review on climatic events in urban areas. “You have three things that work in the direction that increase a city’s vulnerability to flooding,” he says: rising sea levels, increased chances of severe precipitation events, and an abundance of impermeable surfaces that prevent water absorption and encourage runoff. .

As early as 2050, climatologists predict that the average high tide in the Norfolk region will equal today’s high tides. But it’s not just the Mid-Atlantic region: many other parts of the world will be increasingly prone to flooding that endangers lives and property. Understanding and accurately predicting flood risk from extreme weather and rising tides is therefore a major challenge for vulnerable cities around the world.

If we don’t get the forecasts right, we’ll be preparing for flooding in the wrong places, says forecaster David Lavers of the European Center for Medium-Range Weather Forecasts, an independent weather research and forecasting organization that provides data and forecasts meteorological data for 34 European countries.

That’s where Laughlin comes in — and hydrologist Derek Loftis of the Virginia Institute of Marine Science, whom Laughlin and others assist. In 2017, Loftis and his colleagues started a project called Catch the King that uses a smartphone app to collect data from citizen scientists during high tides. He will use this data to validate and improve his mathematical flood model, called TideWatch, for Norfolk and surrounding areas.

Loftis’ mission is simple: “I want to know where the water is going before it gets there,” he says. But as he and other scientists around the world know, collecting the necessary data and then processing it fast enough to make usable predictions is anything but easy.

Survey the floods

The first step towards building a forecast is a detailed understanding of the current weather situation. “You base your model on how the atmosphere works and you start with the conditions as they are now,” says hydrologist Hannah Cloke from the University of Reading in the UK. If that data isn’t precise and detailed, she says, the model probably won’t be very good.

Accurate flood forecasting also requires an understanding of the situation on the ground: physical factors such as river water flow, elevation, soil saturation and land cover. By the early 2000s, supercomputing had advanced enough that hydrologists and geologists could incorporate weather forecasting models into such measurements. But when Loftis began working on flood forecasting a decade ago, scientists still lacked the precise measurements of water levels needed for accurate forecasting, and the crucial ability to forecast floods. fast in real time.

To address this shortcoming, Loftis developed a forecasting model that relied in part on detailed city government maps and high-resolution land measurements with LiDAR, which uses pulsed laser beams to create a 3D map of the Earth’s surface. Earth. By testing his predictions against past floods, he showed that his calculations were broadly accurate.

But he needed real flood information to refine his models. So in 2017, he and his colleagues set up a network of 28 internet-connected water level sensors in communities around Norfolk, similar to systems used in Taiwan and the UK. The new sensors, combined with devices previously installed by the National Oceanic and Atmospheric Administration and the US Geological Survey, transmitted approximate measurements of water height and movement to a suite of supercomputers at the Virginia institute. . Some towns in the region are already using sensor data to alert residents to flooding.

Around the world, hydrologists like Loftis are trying to predict floods, with each region facing its own challenges. Countries with fewer resources are still struggling with the kinds of data scarcity issues that the United States once had. And without good input, scientists can’t build accurate models, says artificial intelligence expert Sella Nevo, principal engineer at the Google Flood Forecasting Initiative, which uses artificial intelligence to estimate when and where floods will occur. .

“Knowing that there was a flood in the Ganges, it’s easy,” says Nevo. “But knowing exactly down to 10 meters which areas were wet and which weren’t – that’s a challenge.” And without that level of detail, he says, forecasts won’t help people on the ground.

Like Loftis, the Nevo team uses data from flow gauges to track current water levels and how they change over time. Their fledgling initiative began by building a flood forecast for India, using more than 1,000 smart flow gauges deployed across the country by India’s Central Water Commission. Next, the team had to create fine-grained 3D digital elevation maps of the country. Existing elevation models didn’t have enough detail, so the group created their own by performing some mathematical feats on available satellite imagery.

With these two streams of information, Nevo and his colleagues built a flood model of what will happen if, for example, a river overflows its banks. This flood model combines physics-based calculations and machine learning to produce flood forecasts that can predict water levels within 15 centimeters 90% of the time.

But models like this are all theoretical until they are tested with real data. And that’s where projects like Catch the King come in.

Hold back the tide

Loftis designed its flood forecast to save lives during hurricanes and other severe weather events that are expected to increase as the climate continues to warm. But he needed a way to test his calculations in times when lives weren’t at stake.

He had his chance when Dave Mayfield, a retired journalist from the Virginien-Pilot Norfolk newspaper, approached the Virginia Institute of Marine Science to create a project to raise awareness of climate change and the consequences of sea level rise in the region. Together they launched Catch the King in 2017. They assembled a team to design an app called Sea Level Rise that allows users to map high water with their smartphones.

And then they spread the word in the local media. In their inaugural year, more than 700 volunteers traveled to map the royal tide – landing the effort in the Guinness Book of World Records as the environmental survey with the most contributions ever – and Loftis used the data to validate its street-level flood prediction model.

Hundreds of volunteers have shown up for Catch the King every year since — including about 200 this year despite the pandemic — to help Loftis continue to refine its predictions. “The more data we have, the better able we will be to meet the challenge of sea level rise and climate change,” he said. But this is only part of the solved problem. Another big challenge for him and other forecasters is making sure their detailed, high-resolution forecasts are available with enough notice for residents and governments to take action before the floods start.

Currently, TideWatch provides detailed forecasts up to 36 hours in advance. Ideally, by constantly refining its models, Loftis hopes to make reliable forecasts up to 72 hours in advance. Another flood forecasting system developed by researchers at George Mason University provides similar forecasts up to 84 hours in advance for residents in the Washington, DC area.

Other vulnerable parts of the United States want in on the action. “Knowing where it might flood two or three days in advance would be extremely valuable,” says Peter Singhofen, CEO of Streamline Technologies, Inc. and Florida flood pattern expert. “We can evacuate people, maybe we can change how we operate infrastructure like water pumping stations to potentially prevent flooding in certain areas or protect property and lives.”

The Google Flood Forecasting Initiative has also made progress. The project has global ambitions, but so far Nevo’s work has focused on the monsoon-prone Patna region of northeast India. Last year, the model provided accurate advance flood warnings for incoming monsoons and cyclones – a big step forward for the region. In June, Google expanded its forecast to encompass all of India and is starting work on forecasts for Bangladesh.

According to climatologist Megan Kirchmeier-Young of Environment and Climate Change Canada, a government agency promoting sustainability, it is essential to better understand how climate change could affect flooding regimes. “As we continue to warm, we’ll see continued increases in the frequency and severity of heavy rain across North America,” she says – and that means more flash flooding.

Loftis anticipates that these changes are imminent for the Norfolk region. As water levels rise, more streets will be flooded, or even impassable, for longer periods of time. All of this means that creating an accurate flood forecast is a never-ending job, as rising Atlantic waters slowly but surely claim growing swathes of coastal cities.

This article originally appeared in Knowable magazine, an independent journalism venture of Annual Reviews. Register to receive the newsletter.

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