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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 |     三代国门下的坚守    ■李国栋 杨智博 解放军报记者 郑茂琦        北部战区陆军某旅“国门卫士模范连”官兵，在绥芬河国门前执行巡逻任务。    

    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.
。彭旭日 摄    从黑龙江省哈尔滨市乘坐高铁一路向东，列车驶过牡丹江站后，海拔陡升。记者望向窗外，一座依山而建的边城轮廓渐渐清晰。    绥芬河，这座嵌在祖国东北边陲一角的小城，有着“百年口岸”的美誉。一条绵延的铁路线，串起这座“火车拉来的城市”的今昔岁月。走进绥芬河市站前路38号，一栋外墙黄白相间的建筑在街巷间格外醒目。

二 | 这里是原中东铁路最东端的绥芬河火车站旧址。当年的候车室已被改造为中东铁路记忆馆，馆内展陈的500余张历史照片，静静诉说着绥芬河与铁路相生相伴的深厚渊源。    从中东铁路记忆馆向着国门方向前行，绥芬河口岸的铁轨传来微微震颤，隐约夹杂着列车隆隆的声响，那是中欧班列即将通关的信号。如今的绥芬河口岸，铁路线纵横交织，货运场站内装卸作业昼夜不停。作为“一带一路”的重要陆路门户，这座边陲小城依托公路、铁路两个国家级一类口岸，已经成为名副其实的“国境商都”。    这天，记者跟随北部战区陆军某旅“国门卫士模范连”官兵执行边境巡逻任务。这条巡逻路，指导员杨学文已经走了12年。    巡逻车沿边境公路缓缓行驶，雨幕中，三代国门依次出现在眼前。    首先看到的，是一道不足10米宽的铸铁手动挡杆，那是1987年设立的第一代国门。“当年，连队官兵就在这儿手动抬杆，冬季铁挡杆冰得刺骨，必须戴上棉手套。

三 | ”杨学文指着窗外，对新兵朱述富讲起当年连队官兵的戍边往事。那时边境公路路面没有硬化，雨天全是泥坑，官兵们徒步巡逻深一脚浅一脚，裤腿上裹着厚厚一层黄泥，回到连队鞋子能倒出半鞋泥水。记者望着雨雾里静默的第一代国门，仿佛看见几十年前，年轻的士兵顶风冒雨动手抬杆的身影。    向南不远处，第二代国门的灰砖墙渐渐清晰，它见证了绥芬河从边陲小镇到“国境商都”的跨越。杨学文还记得，自己刚入伍来到绥芬河时，一位老班长就在这座国门前给他讲述往事：碰到大雨天气，查验岗的雨棚挡不住狂风骤雨，外面下大雨，棚里下小雨，几分钟就会浑身湿透，靴子里灌满雨水。“那时候条件差，但大家心里明白：雨下得再大，国门岗哨决不能松半分。”杨学文说。    行至第三代国门前，巡逻车稳稳停下。

四 | 这座2014年启用的新国门高51.8米，双向八车道开阔通畅，“中华人民共和国”7个红色大字在雨幕里仍旧醒目。杨学文下达指令，官兵开始徒步巡逻。    从简易挡杆到巍峨国门，三代国门的更迭是边境口岸发展的缩影，也是一代代“国门卫士”坚守的见证。

五 |     汽笛长鸣，一趟货运列车缓缓停下。

六 | 官兵们迅速就位，迎着风雨，仔细检查车体周边。班长刘述业大声叮嘱：“雨天视线差，边角缝隙都盯紧了，一处都不能漏！”检查完毕，列车启动。雨水顺着脸颊往下流，官兵们却纹丝不动，目光如炬扫过每一节车厢。    结束全线巡逻任务后，记者漫步在绥芬河街头，商家招牌错落有致，老式建筑的尖顶上挂着水珠，在渐亮的天光里显得格外鲜活。街面上，往来行人络绎不绝，既有操着各地口音的国内游客，也有不少外籍旅客，整座边城洋溢着安宁祥和的气氛。    密雨渐歇，云层渐渐散开。阳光越过连绵群山，洒在国门的红色大字上。记者望着远处的第三代国门，想起边境线上那些年轻的面孔，也想起杨学文的话：“国门会变新、变高，但我们守国门的心，就像界碑一样，牢牢扎在这里。”    资料链接    作为“一带一路”中蒙俄经济走廊重要陆路门户，绥芬河市依托公路、铁路两个国家级一类口岸，聚力推进对俄互联互通体系提质升级，不断放大通道经济辐射带动作用，在跨境物流、经贸往来、产业落地等领域取得显著成效，生动书写了边疆口岸深度融入和服务国家对外开放大局的实践答卷。    2025年，绥芬河市进出口总值296.96亿元。

七 | 其中，出口端增长动能尤为强劲，2023年起连续三年出口保持两位数同比增长。2026年上半年进出口同比增长30.1%，出口同比增长52.5%。外贸发展韧性持续显现，2025年口岸过货量1043.6万吨，铁路口岸始终为运能主力，公路口岸货运潜力加速释放，过货量从2015年58.3万吨增长至2025年的157万吨，10年增长近1.7倍。    返回，查看更多。

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Published on:16:08:51