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Climate Gambit: Chinese team develops ‘super brain’ to guide flood precautions using weather, hydraulic and terrain data_我的网站

一 |     The Pentagon and the U.S. intelligence community believe that as better data becomes available, the "unidentified and purported anomalous nature" of most of the hundreds of UFO reports they have been investigating will likely be explained by "ordinary phenomena," according to a government review of the incidents that was released on Wednesday.The number of accounts of unidentified anomalous phenomena, or UAPs -- which is the official name now used for what were known as UFOs -- has grown to 801, with an increase of 291 additional reports from Aug. 31,2022, to April 30 of this year, according to the new government review.The total number of UAP sightings that is being examined by the Pentagon and intelligence officials stretches back decades and includes those made by both military and civilian personnel.The report released Wednesday is the first to be compiled jointly by Pentagon and the director of national intelligence's office in light of new legislation passed by Congress.The first-ever unclassified U.S. intelligence report on UAPs was released in June 2021, also due to congressional legislation, and detailed 144 incidents -- only one of which could be explained.The new report states that the Pentagon office reviewing UAP incidents, known as the All-Domain Anomaly Resolution Office, or AARO, is making progress in analyzing and integrating the hundreds of sightings it continues to receive.The report cites "gaps in domain awareness," such as a lack of information from sensor systems or other technological and mechanical issues, as the main reason for the continuing increase in the incidents being reviewed by AARO."These gaps are the direct result of insufficient data secured by radar, electro-optical (EO)/infrared (IR) sensors, the presence of sensor artifacts, such as IR flare; and optical effects such as parallax, that can cause observational misperceptions," the report states.Because the government's original UAP focus was on reports filed by military personnel, the total number of reports being investigated still tilts heavily toward those near military facilities and airspace, though that number is decreasing as more than 100 incidents from the Federal Aviation Administration are now being reviewed, according to the government report."Based on the ability to resolve cases to date, with an increase in the quality of the data secured, the unidentified and purported anomalous nature of most UAP will likely resolve to ordinary phenomena and significantly reduce the amount of UAP case submissions," the report states.

The report also plays down the potential aerial dangers that could be posed by UAPs by noting that the AARO had received no reports during the collection period that suggested that "UAP maneuvered to an unsafe proximity to civil or military aircraft, positioned themselves in flight paths, or otherwise posed a direct threat to flight safety of the observing aircraft."In an ABC News interview this past summer, Dr. Sean Kirkpatrick, the head of AARO, said that being caught off guard by "intelligent or extraterrestrial technical surprise" remained a top concern."Data and science has to guide where you go, and we will follow the data," Kirkpatrick said then.In late August, the Pentagon launched a new website to serve as a one-stop clearinghouse for unclassified information about UAPs.The platform includes unclassified videos and photos of resolved cases as well as links to reports and other resources. It will soon have a feature enabling AARO to accept reports "from current or former U.S. Government employees, service members, or contractors with direct knowledge of U.S. Government programs or activities related to UAP dating back to 1945."In June, the Pentagon issued a statement that "to date, AARO has not discovered any verifiable information to substantiate claims that any programs regarding the possession or reverse-engineering of extraterrestrial materials have existed in the past or exist currently."The was issued in response to unconfirmed claims by David Grusch, a former intelligence official who said he was stepping forward as a whistleblower to say that the U.S. had been collecting non-human craft for "decades."In late July, a House Government Oversight subcommittee held a hearing where Grusch went public with his allegations and urged Congress to investigate.。         Students from Xi'an University of Technology test a virtual reality-enabled emergency evacuation simulation system tailored for flood disasters on January 12, 2024. Photos: Courtesy of Xi'an University of TechnologyEditor's Note:
Extreme weather is increasingly a global challenge, and the key to addressing climate risks lies in earlier prediction, more precise action and smarter preparedness, with emerging technologies playing a vital role. The Global Times launches the "Climate Gambit" series, exploring how research teams are leveraging cutting-edge technologies, including artificial intelligence, high-performance computing and smart observation systems, to anticipate weather changes, enhance disaster early-warning and strengthen resilience against climate risks.
Inside a state key laboratory at Xi'an University of Technology, Northwest China's Shaanxi Province, there is a miniature but complete "water world" which simulated water channels, inland lakes and main rivers to recreate real flood scenarios and test their newly developed GPU Accelerated Surface Water Flow and Transport Model (GAST).
Known as a "super brain" for flood control, GAST can complete flood simulations involving more than 3 million computational units within 30 seconds, helping transform flood management from a reaction to emergency into active precautions since "flooding impacts can be predicted even before rainfall arrives."
At a time when extreme rainfall and summer flooding have become increasingly frequent, questions such as when the flooding will arrive, which roads may be submerged and when residents should evacuate have become increasingly important.
In an exclusive interview with the Global Times, Hou Jingming, a professor at Xi'an University of Technology and the leader of the research team, explained how the GAST model seeks to answer these questions by accurately predicting flood development and identifying vulnerable areas before disasters occur, and how the model helps authorities take preventive measures to reduce casualties and economic losses.
AI empowering 'flood drill'  
The water tank system in the lab was designed to create a controllable, repeatable and observable environment to simulate complex hydrological processes, including river flooding, urban water level changes, lake regulation, drainage pump operations and coordinated flood-control measures.
By adjusting variations such as upstream water inflow, rainfall intensity, downstream water levels and drainage conditions, scientists can recreate different flood scenarios. Meanwhile, water levels, flow speeds and other data are collected in real time and displayed on a digital twin platform.
"If a rainstorm and corresponding floods are an exam, GAST is like a 'drill,'" Hou said. "It can simulate how floods develop, where water will flow, which areas may be inundated and when river levels may rise, ensuring authorities are well but not overly prepared."
To answer the public's concern about "whether my neighborhood will be flooded when heavy rain arrives," the team developed new algorithms for urban surface water flow, including improvements in terrain slope and friction calculations.
These breakthroughs have improved simulation accuracy in complex urban environments. Compared with extensive monitoring data, GAST can keep simulation errors of key hydrodynamic factors within 15 percent. This means the model can provide not only general flood trends, but also quantitative information such as water depth, flow speed and inundation areas.
Combined with AI technologies, it can identify complex relationships between rainfall, water conditions, flood depth, flow velocity and affected areas, cutting simulations from hours in traditional methods to minutes or even seconds.
The faster calculation capability means that once meteorological authorities update forecasts, the model can quickly estimate flood risks in different parts of a city. 
"The earlier rainfall warnings are issued, the earlier we can identify potential flooding hotspots and high-risk areas," Hou said. "This saves valuable time for evacuation, traffic management and emergency deployment."
For smarter disaster response

Building an accurate flood prediction model also requires integrating large amounts of urban data other than weather forecasts, including urban terrain, drainage networks and infrastructure information.
For example, a model developed for Xi'an incorporates geographic data and drainage system information collected from relevant authorities and field surveys. After receiving rainfall forecasts, the system can quickly calculate possible flooding scenarios, showing when and where waterlogging may occur and highlighting vulnerable roads and areas through visual maps.
To demonstrate how the super brain works in case of possible flooding, the laboratory has set a virtual reality area where visitors can experience a simulated urban flooding evacuation in the Xiaozhai area of Xi'an. Wearing VR headsets, participants can see water levels gradually rising and follow emergency instructions to move toward higher ground.
The entire technological package has already been applied in real-world flood prevention.
    A 3D live-scene display lab in Xi'an that oversees stormwater drainage performance in Hengshui, North China's Hebei Province Photos: Courtesy of Xi'an University of Technology
During Typhoon Muifa in 2022, Haishu district in Ningbo, East China's Zhejiang Province, recorded a regional rainfall of 367 millimeters. Using GAST as its core technology, the local flood forecasting platform integrated weather forecasts, AI algorithms and real-time monitoring data to provide rolling three-hour flood risk predictions.
Post-event assessments showed that predicted risks at most locations matched actual flooding conditions. The average relative error between predicted and observed maximum water depths was 13 percent.
The GAST model was also integrated into a smart rain and flood management platform in Qinhan new city area in Xianyang of Shaanxi, and during a rainstorm warning in July 2022, the platform provided continuous monitoring and forecasts. Based on the results, local authorities shifted from routine inspections to targeted monitoring of flood-prone areas and optimized emergency drainage operations.
The model is also being applied to mountain torrent prevention, as it can simulate rapidly changing flows in complex terrain and, combined with machine learning, complete forecasts within seconds. For reservoirs and rivers, it supports sudden and gradual dam-break simulations.
In June 2026, the model was presented at a national symposium on flood risk mapping achievements. The technology has since been applied by water resources, emergency management and urban development authorities, expanding from Shaanxi to multiple provinces and regions across China.
Looking ahead, the research team is developing a framework that further keeps up with the pace focusing on AI technologies. "Currently, the system operates based on weather forecast, therefore, AI will increase efficiency by using historical cases and real-time monitoring data to correct errors and update forecasts dynamically," Hou said.
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