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Rainwater Ebbs, Sinkholes Get Deeper: Broken Roads Sets NMC Hotline Abuzz

Rainwater Ebbs, Sinkholes Get Deeper: Broken Roads Sets NMC Hotline Abuzz

Time of India4 days ago
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Nagpur: The Nagpur Municipal Corporation (NMC) is flooded with complaints as roads across the city have broken apart following three days of incessant rainfall. The civic body's hotmix department is overwhelmed, receiving hundreds of distress calls and online grievances about pothole-ridden stretches across the city.
"In the last 10 days, the NMC's online portal received 106 complaints related to bad roads with a majority of these received in the last couple of days," said an official from NMC's grievance redressal cell.
With the NMC's hotmix plant shut during monsoon, emergency repairs are being carried out using Jetpatcher and Insta Patcher machines, but these temporary measures are proving inadequate. In areas with no stormwater drainage or clogged outflows, waterlogging has worsened the road, leading to formation of dangerous crater-sized potholes.
Key trouble spots like the Gaddigodam gurudwara underpass and the road near Loha Pul, approach roads to Automotive Square, have become nearly unmotorable. "Even a short ride has turned into a back-breaking journey," said Vishal Chauhan, a resident of Shanti Nagar. Several arterial and internal roads are no different, with complaints piling up every hour.
TOI has consistently reported on the poor state of city roads, with the current monsoon spell exposing infrastructure failure and neglect.
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A senior official from the hotmix department said repairs are underway at several points. "We patched the Mangalwari bazar stretch, started work at Ganeshpeth bus stand, and are attending to the Zero Mile and Ashoka Chowk area — though some stretches have ongoing cable-laying work that complicates restoration," the official said.
Even roads which were dug up for pipeline or stormwater networks were not restored properly.
Now, complaints of uneven stretches too have increased, said the official, citing the example of online road restoration work near Police Line Lake.
Due to heavy traffic during the day, the NMC is now planning night shifts for patchwork in high-density areas. "We began early-morning repairs, but to avoid congestion and safety issues, night patching is being prioritised," he added.
Still, residents say the damage reflects deeper systemic flaws.
"The monsoon hits every year — why aren't roads built to last? Where's the drainage plan? These are not new problems," asked Ajeet Singh, a resident of Palloti Nagar.
Given the poor state of most of the city's tar roads, the crisis is far from over. Unless NMC moves beyond patchwork and addresses the root causes — poor drainage, bad road design, and lack of coordination between departments — citizens will continue to pay the price in broken vehicles, injuries, and lost time.
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Businesses of all stripes make or lose money based on the forecast: retailers with far-flung supply chains, energy companies moving fuels around the country, even baseball teams watching for a rainout. The good news is that we may be poised to enter a new golden age of AI-enabled weather prediction. That heat wave that scorched the East Coast last month? WindBorne says its software first flagged that 15 days out, two to four days before competing forecasts. NYT News Service John Dean, chief executive of WindBorne, who started the company with four other members of a Stanford University space club, at its headquarters in Palo Alto, Calif., April 29, 2025. There's a catch, though. These new deep learning forecasts are built on data provided for free by public science agencies. In the United States, that relationship is threatened by the Trump administration's heavy cuts to the National Oceanic and Atmospheric Administration, or NOAA, which houses the National Weather Service. The Public-Private Symbiosis Every day, at more than 100 weather stations across the United States, a weather service worker fills a latex balloon with helium and launches it to collect atmospheric measurements -- until it flies too high and pops. These flights, which began in the 1930s, have been reduced because of staff cuts during the chaotic first months of the second Trump administration. Across the government, from the National Aeronautics and Space Administration to the Pentagon, the Trump administration's appointees have aimed to push the government's technical capacity into the private sector. Some in the weather industry -- and free-market Republicans -- see NOAA's forecasting work as a prime candidate for outsourcing and have called for the agency to be "dismantled." NOAA is also a target of the fossil fuel industry because its scientists contribute important climate change research. The White House has proposed $2 billion in cuts to the agency, or 28% of its budget. Some entrepreneurs and meteorologists say this binary view of public and private threatens to upset the mutually beneficial symbiosis between them and the government. "I would love to see a version of NOAA where there are more public-private partnerships," Dean said. "And then those benefits, some of them become public good and some of them are commercialized." As meteorology evolved, governments were often best positioned to assemble local data into a national and then global picture, with an emphasis on coordination and public safety. Now the weather service's key job is maintaining and operating physics-based models of the atmosphere -- software that describes the weather in precise mathematical detail -- to generate forecasts. The private sector, meanwhile, tailors forecast services for specific customers. 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The student club broke records for the longest flight time of a latex balloon, keeping one aloft for 70 to 80 hours. (The company has since smashed that record, recently keeping a balloon in the air for 57 days.) Venture investors hanging around campus encouraged their club's efforts, and five members -- Dean, Paige Brocidiacono, Joan Creus-Costa, Kai Marshland and Andrey Sushko -- founded WindBorne in 2019. They set out to capture a comprehensive set of global data, a real-time picture of the atmosphere, including places not currently measured. The company builds and launches 300 balloons a month at those 10 sites around the world, flying them on average for 12 days, with about 100 aloft at any given time. (Its ultimate goal is 10,000 balloons flying at once.) But the founders knew when they started the company that it would be more lucrative to produce forecasts rather than sell their data to someone else who could. "The big hole in the plan," Dean said, "was 'How do you actually go do global weather forecasting ?'" The cost seemed prohibitive. "You need $100 million to do this," he said. (WindBorne has raised $25 million in venture funding.) That was about to change. New data sets released by public weather agencies were ideal for training deep learning software, and researchers using it upended the weather ecosystem. In 2022, teams at chipmaker Nvidia and Chinese tech giant Huawei demonstrated that machine learning could forecast accurately. Ryan Keisler, a physicist working alone during a sabbatical, drew attention not just for the influential weather prediction model he published but for the cost of training it: $370. Dean and Creus-Costa, the company's head of AI, bought a bunch of powerful gaming computers -- picking them up at a McDonald's from a Craigslist vendor -- and got to work feeding their balloon data into this new approach to forecasting. Even as these AI forecasts begin to outperform traditional methods, their developers don't fully understand how they work. The software could be learning physics, simply matching patterns or using some effective combination of the two. "When you do a physics-based model, you're being smart," Creus-Costa said. "When you do a deep learning model, you don't have to be smart. We're not writing down the physics. We're just having it learn." Using artificial intelligence modelling, WindBorne says, its day-ahead temperature forecasts are 37% better than those performed by the European Center for Medium-Range Weather Forecasts, an organization that supports the European equivalents of the National Weather Service. (WindBorne releases the data so others can validate it.) In addition to NOAA, the startup sells its weather insights to investment funds and is working with arms of the U.S. military, which has a vital interest in the weather. NYT News Service A weather balloon fills with helium before launch at Windborne headquarters in Palo Alto, Calif., April 29, 2025. The Limits of Deep Learning For all the excitement about these new techniques -- Microsoft and Google also have AI weather models, as does the Air Force -- they have their limits. Matthew Chantry, a mathematician who leads the operational AI weather forecasting project at the European Center for Medium-Range Weather Forecasts, said the field of meteorology was still figuring out what the relationship between physics-based and AI models would be. The weather service, whose forecasts have fallen behind those at the European center, does not operate its own AI forecasting model, but teams up with private companies to support their work. Deep learning models have proved uniquely useful for complex events that are tricky for physics-based models, like the paths of hurricanes or cold fronts over the Midwest, a notably tricky place to forecast because of the Rocky Mountains. Physics models tend to be better at analyzing fine details. AI forecasts typically cover areas of 25 to 50 square miles. Most people need to know the weather in a much smaller area; government-run physics models analyze areas of around 6 square miles or less. WindBorne spotted heavy rains before the Texas floods, but not with the kind of granularity to deliver evacuation warnings. The company's goal is to reach a much smaller resolution in the years ahead, said Todd Hutchinson, WindBorne's chief meteorologist. Keisler, the influential weather-model creator, said WindBorne "is one of a few companies trying to do both data acquisition and also do the modelling." He added, "They also seem to be quite good at both." The Trump administration's cuts have imposed another limit, too. For now, weather forecasting models based on deep learning remain dependent on data releases from the physics-based models at the public weather agencies. Those paint a wide-ranging universe of observations onto a 3D grid as often as four times a day, from which the AI models can learn. Keisler cofounded Brightband, a company that is developing software that can ingest observation data directly into AI models, but its work is in its early days. Since President Donald Trump's inauguration, NOAA employees have been pushed to resign, resulting in nearly 2,000 departures. While the White House budget doesn't reduce forecasting spending directly, it cuts spending on satellite and radar systems, and Trump's recently enacted domestic policy bill cut millions of dollars in leftover Biden administration funding for improved forecasts. Some changes seem ideological -- the removal of a data set about extreme weather events -- while others baffle meteorologists: NOAA will no longer distribute data from a U.S. military weather satellite program that is seen as vital to hurricane tracking. Trump's nominee to lead NOAA, Neil Jacobs, who was cited for violating the agency's code of scientific ethics during the president's first term, endorsed the White House's cuts at his confirmation hearing last week, but also promised to restore the extreme weather data set and invest in computing. He told lawmakers that "even if artificial intelligence can't do something better, if it can do it faster and more efficiently, I think it's worth using." Congress could still reverse some or all of these cuts through the budget process in the months ahead, but current and former members of the weather service's staff say the loss of data and human expertise will degrade the accuracy of forecasts and potentially endanger lives. "We will continue to fulill our core mission of providing lifesaving forecasts, warnings and decision support services," a NOAA spokesperson said in a statement. But the fast changes happening in U.S. weather research put WindBorne in a complicated spot. The company needs NOAA's data, wants its business and hopes to do a better job of forecasting weather than the government currently can -- but the team of balloon-flying, AI-training techies are regular people, too. "I have my personal philosophies that are not aligned with, like, what's best for our private weather company," Dean told me. "You don't want to live in this capitalist nightmare of like, 'Pay 10 bucks for today's weather.' That's too far."

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