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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

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A | 9月27日，抚顺军分区党委第一书记任职宣布大会在抚顺军分区召开。

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

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.
。省委常委、省军区党委书记、省军区政治委员梁平宣布辽宁省军区党委任职通知：高键同志任抚顺军分区党委委员、常委、第一书记。市委书记、抚顺军分区党委第一书记高键作表态发言。

B | 市委副书记、市长王庆海出席。

C | 　　梁平代表省军区党委向高键任职表示祝贺，并就进一步做好党管武装工作提出要求。他要求，要坚决贯彻新时代政治建军方略，始终把思想政治建设摆在首位抓紧抓好，不断强化坚定捍卫“两个确立”、坚决做到“两个维护”的政治自觉，坚持不懈用党的创新理论凝心铸魂，深入学习贯彻军委政治工作会议精神，下大力气提升党管武装工作质效，进一步强固政治优势，牢牢把正军分区建设的正确政治方向。聚力推进打仗型国防动员建设，强化党委领战，突出实战实训，建强新质力量，努力实现新质生产力、新质战斗力的高效融合、双向拉动。全面夯实军分区高质量发展基础，锚定“雷锋式军分区”建设目标，建强党委班子，深化基层治理，打造过硬人才队伍，守牢安全底线。

D | 巩固发展新时代军政军民团结的良好局面，着力打造“雷锋城”名片，合力推动跨军地改革任务落实，聚力推进军民融合深度发展，助力打好攻坚之年攻坚之战。军分区要积极参与和支持地方经济社会建设，当好代表队、突击队、先锋队。

E | 地方各级党委、政府要一如既往关心支持部队建设，解决好部队官兵的后顾之忧。　　高键代表抚顺市委、市政府和抚顺军分区，对省军区党委长期以来给予的大力支持和关心帮助表示感谢。

F | 他表示，完全拥护、坚决服从省军区党委的决定，将坚决贯彻党中央决策部署及省委、省军区党委工作要求，扛牢政治责任、主动担当作为，尽心竭力履行好第一书记职责，不断开创我市党管武装工作和国防后备力量建设新局面。牢牢把握党管武装正确方向，深入学习贯彻习近平强军思想，毫不动摇坚持党对军队的绝对领导，坚决贯彻军委主席负责制，以实际行动坚定拥护“两个确立”、坚决做到“两个维护”。

G | 全面履行练兵备战使命任务，抓牢抓实备战打仗各项工作任务，推进国防动员高质量发展。持续深化军民融合，统筹推进党管武装与经济社会发展各项工作，推动国防建设和经济建设协同发展、互促共赢。坚决当好部队建设坚强后盾，不断巩固深化军政军民团结良好局面。　　会后，高键又立即组织相关城区部门，研究解决当前武装工作重点难点问题，持续推动全市党管武装工作全面落实。　　市委常委、副市长杨洪波，市委常委、秘书长金峰出席会议。市委常委、抚顺军分区政委沈瑞智主持会议。