小清新
Climate Gambit: Chinese team develops ‘super brain’ to guide flood precautions using weather, hydraulic and terrain data_我的网站
A | 不知道大家是否注意到，去年以来，围绕着“旅游搭子”这个新风口的旅游新业务日益增多。前有“登山陪爬”爆火一时，后有年轻人旅行“拼车、拼吃、拼住”流行，再有爱彼迎社交功能落地，本质上都是围绕着如何为年轻人旅途提供更多精准情绪价值而进行的新业务探索。 “旅游搭子”经济兴起，是年轻人的一次旅行情感消费的主动降级，他们不想再忍受与熟人共同旅行时的种种迎合与退让，与其委屈自己，不如消费降级，干脆找个志同道合的旅游搭子临时组队，在短暂旅途中寻求完全满足极的欢愉与快乐。
B |
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.
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.
。 而这也将成为旅游业未来的大势所趋。 图片：AI生成 01、为什么年轻人愈发讨厌与熟人一起旅行了呢？ 还不是因为这些所谓的熟人给年轻人提供的情绪价值越来越少了呗。
C | 父母易扫兴、朋友要迁就、同事存戒心。 在很多年轻人眼里，自己一年到头好不容易攒起一趟宝贵的旅行，无论是关系多么亲近或者要好的熟人，在旅途中总归要在某些方面让自己不得不去妥协和忍让，这样才能最终营造出一幅你好我好大家好的美好和谐局面。 然而旅途结束后这些年轻人却发现，自己的旅途中总会因为照顾熟人情绪留下一些小遗憾： 即便只是一次错过的日出、一顿小脏摊的宵夜、一张来不及拍的照片…… 或许这些细节再小不过，但是却能让很多年轻人感觉这趟旅行所能提供的情绪价值远低于预期。 有年轻人曾在社交媒体感叹，不知道是不是因为这几年大家活得太压抑，导致旅行的时候情绪敏感且脆弱，即便是亲爹亲妈，发小闺蜜，旅行中一旦出现意见相左的时候，自己愈发不想妥协了，为什么一定要牺牲我的体验来照顾所有人？！ 这不公平。 我想要一次100%让自己开心的旅行，不用迁就任何人，哪怕是自己最亲近的人。 有人将年轻人的这一心态解读为“旅行情感消费的主动降级”，他们向通过这种情感消费降级的方式，选择更加志同道合的旅游搭子，来短暂满足自己的旅行消费体验。 这一心态在年轻人中愈发普遍。 02 也有人质疑： 家人朋友同事这些熟人都提供不了的情绪价值，作为陌生人的旅游搭子就能满足了？！ 当然。 在不少年轻人眼里，自己的旅行更愿意找旅游搭子原因有三： 其一，不需要打破个人边界。因为自己和旅游搭子只是因为一个短期目标暂时组队旅行，因此不存在谁迎合谁，谁迁就谁的问题。你不用知道我的过往，我也不打听你的故事。大家的交际范围牢牢限制在共同感兴趣的旅途这一个点上。
D | 旅游搭子是一种恰到好处的陪伴。 按照流行的说法，旅游搭子是对个人的一种“相对占有，绝对自由”。 即便双方存在无法达成一致的问题，也能快速“解约”，双方付出的情感、时间、金钱成本无线趋近于零，不会过度影响情绪价值。 其二，探索更多未知的旅行。现在的年轻人旅行兴趣愈发广泛，你的好朋友或许在这次旅行上与你高度同频，但在下一次旅行中有可能南辕北辙。在这个时候，旅游搭子可以帮助你实现对于未知旅行的深度探索。 在这个维度来说，年轻人是在通过旅游搭子来延伸旅行边界。
E | A陪你冬天滑雪、B陪你春天踏青、C陪你夏天潜水、D陪你秋天徒步…… 透过不同的旅游搭子，年轻人的旅行走得更远，获得的情绪价值更足。 其三，分摊旅行费用。这也是旅游搭子出现的经济基础，很多长途旅行，尤其是涉及到出境目的地、极限旅行玩法的旅行规划，对于年轻人而言一个人承担所有费用过于昂贵，如果能够找到几个志同道合的旅游搭子，不仅可以大幅降低个人旅行花费，而且还能组团保障旅行安全。 在社交媒体上，纵观寻找旅游搭子的帖子，大部分都明确的带着分摊旅行费用的目的。 不过最近也有一种趋势，那就是很多年轻人对情感陪伴的需求开始高于分摊旅行费用的需求，简而言之就是，我旅行并不差钱，只是找不到一个合适的同行者，如果你是那个合适的人，我甚至不介意多分摊点费用。
F | 这或许是中国走向孤独社会的过程中，年轻人旅行情感需求的一种必然变化。 03、旅游搭子需求如此旺盛，未来是否会成为一门赚钱的好生意呢？ 实际上，旅游业内不少人持悲观态度。
G | 一方面，“搭子经济”在国内火了好多年了，隔几年就会爆出一轮舆论热潮，但始终未在商业领域有大的突破。 另一方面，这些年马蜂窝穷游等旅游攻略社区、携程等OTA，甚至包括不少大平台都曾推出过主打“旅游搭子”的功能或者业务，但是陆陆续续都没有了下文。 从“旅游搭子”商业变现逻辑来看，有两个致命的难题始终无法破局： 安全保障与期望落差。 “旅游搭子”经济的A面是诱人且美好的，但B面亦是黑暗与龌龊的，经常与情色交易和杀猪盘陷阱紧密相连。年轻人在各个平台上如何分辨哪些人是志同道合的旅游搭子，哪些人是带着面具的骗子，这几乎是个人与平台都无法有效解决的难题。 由于现在互联网天然存在“滤镜效应”，你在网络上看到的这个人与现实中的那个人重合度到底有多高，这是年轻人前期很难把控的，也根本无从查验。 例如，今年暑期“登山陪爬”爆火后，曾有几个女孩花高价雇佣一堆腹肌帅哥陪爬，后者不但全程陪伴加油鼓励，还在女孩爬山劳累时公主抱爬山，可谓情绪价值拉满。
H | 然而等其他女孩也跟风报名后却发现，从陪爬小哥质量到情绪价值提供，不能说一模一样，简直是毫无关系，由此再度引发一轮热议。
I | 旅游企业如果眼馋这块肥肉，少些抱怨，多思考如何破局才是王道。
J | 勇于尝试总好过犹豫不前。 不仅是行业巨头，一批小创业者也已经瞄上旅游搭子赛道，各类新APP、新社群、新玩法开始在社交平台披露。
K | 劲旅君鼓励旅游创业者们大胆假设，小心求证，期待旅游社交这个领域能跑出更多惊喜。
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