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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
A | 受台风灾害影响，国内茉莉花主产区广西横县鲜花收购价格7月曾一度冲高至历史高位，济南市场情况如何?近日，记者走访济南茶叶市场发现，依托前期充足成品库存，本地茉莉花茶终端售价保持平稳，新一季茉莉花茶预计9月批量入市。 制茶成本“水涨船高” 有商家缩减茶品种类 8月20日下午，位于市中区的天宇茶叶平价超市店内客流不断，不少市民专程到店选购茉莉花茶。
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.
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B | “济南人喝茉莉花茶是刚需，回头客特别多，一年四季需求量都很稳。”天宇茗茶副总经理李祚秀告诉记者，随着夏季消费旺季到来，茉莉花茶迎来销售高峰，“目前花茶销量已占到店铺总营收的一半以上，消费者以35岁以上的顾客为主，这两年喝茉莉花茶的年轻人也越来越多，可以说茉莉花茶是本地茶叶市场当之无愧的‘流量担当’。” 有着“中国茉莉之乡”美誉的广西横县，是国内茉莉花主产区，也是济南茶市茉莉花茶原料的主要来源，本地绝大多数花茶产品均依托此地原料加工制作。
C | 今年7月，受台风“美莎克”强势侵袭，横县大片正值盛花期的茉莉花田被淹，花朵受损、采收量断崖式下滑，使得鲜花收购价格短期大幅冲高。 根据茉莉花市场交易数据，7月2日至4日，横县茉莉鲜花市场均价分别为18.71元/斤、18.26元/斤和15.89元/斤。7月9日，其价格突破31元/斤，7月12日冲高至50元/斤，创下历史新高，均价同比上涨60%—70%。 李祚秀坦言，此前茉莉花价格也曾有过波动，但这一轮涨幅可以说是近几年最明显的一次。
D | 原料价格飙升直接推高了制茶成本。“店里原本有四十多款茉莉花茶，九月一般能达到六十多种。
E | 本轮涨价后，为控制成本，我们暂时停止了部分品种的炒制。”李祚秀介绍，部分产品成本能上涨20%左右，“目前店里在售产品缩减至十五款左右。
F | ”
价格“终端”没受影响
多数品牌并未调价
在老一辈人的记忆里，茉莉花茶有个雅致的旧称 ——“香片”。这缕茉莉芬芳，早已不只是茶饮的风味，更是一代人的生活印记，深深镌刻进老济南的市井烟火之中。
G | “茉莉花茶茶香浓郁，受到不少消费者追捧。” 天宇茗茶副总经理李祚秀告诉记者，在过去很长一段时间，茉莉花茶都是济南百姓饮茶的首选，是家家户户常备的口粮茶，一年最多能卖出去15万斤，销售额过千万元。
H | “很多济南人，都是从小伴着爷爷奶奶冲泡的茉莉茶香长大。” 玖百春茶叶负责人薛军对此同样深有感触。“茉莉花茶核心消费市场集中在北方，济南作为南茶北销的重要枢纽，更是花茶开拓北方市场的桥头堡。” 薛军说，为牢牢把控茶叶品质，济南不少规模茶商远赴福建、广西原料产地自建加工茶厂，将品质管控前置到源头窨制环节。“仅茉莉花茶这一个品类，我们企业年销售额就可达 300 多万元。
I | ” 记者走访了解到，茉莉花价上涨并未传导至茶价方面，济南茉莉花茶售价一直保持平稳。“茉莉花原料价格确实涨了，但我们的售价没有变化。”据玖百春茶叶负责人薛军介绍，去年采收的优质茉莉原料、加工完成的成品茶库存充足，可以覆盖现阶段的市场销售需求，无需高价采购受灾后的新季原料，依靠库存优势稳稳对冲了本轮行情波动。
J | 此外，天福茗茶等多家茶叶专卖店工作人员也表示，店内的茉莉花茶并未调价，销售情况也没有受到太大影响。 据悉，目前产区茉莉行情已迎来明显回暖。8月初开始，广西横县茉莉花收购价持续回落，现已稳定在23元/斤左右。
K | “新一批的茉莉花在品质上与之前不会有太大的变化，按照制茶、运输的产销周期推算，新一季的茉莉花茶预计在9月左右批量登陆济南市场，届时本地花茶品类将再度丰富。”
年轻人也爱上“老味道”
茉莉花茶正跨越年龄圈层
一边承载老济南代代相传的饮茶记忆，一边拥抱年轻消费浪潮。眼下，茉莉花茶既留住了老茶客长久的偏爱，也成功撬开了年轻消费市场，实现新老消费群体双向兼顾。 记者走访济南多家茶叶市场与品牌专卖店看到，便携的茉莉花茶袋泡茶、调味花茶被摆放在门店货架的显眼位置，产品供给形态愈发多元丰富。“近两年到店选购茉莉花茶的年轻人持续增多，消费群体正在快速拓宽。” 济南市历下区一家茶叶店负责人李先生说道。
这款陪伴几代人的传统口粮茶，正在悄然完成身份蜕变，一跃成为新茶饮时代的“顶流” 品类。中国茶叶流通协会《2025 年度全国茉莉花茶产销形势调研报告》显示，茉莉花茶在十大新中式茶饮品牌茶底用量占比达 32.32%，面向年轻群体的消费增量空间十分广阔。 市场的蓬勃活力，也有全球行业数据作为支撑。PW Consulting(PW 咨询机构)统计显示，2025 年全球茉莉花茶市场规模已突破21亿美元。在消费升级与茶饮年轻化浪潮驱动下，行业保持稳健上行，预计2032年全球市场规模将达到30.7亿美元，年复合增长率约 5.45%。
L | “茉莉风味清爽，大众容易接受，又契合当下消费者对饮品清爽低负担的需求。
M | ” 一家新茶饮品牌相关人士表示，从产业角度来看，茉莉花原料供给体量可观，生产供应具备基础保障;同时茉莉花茶适配性极强，能够和牛乳、鲜果等各类原料碰撞出丰富风味，既适配传统奶茶，也可以支撑注重茶感表达的新式产品创新。 无论作为日常饮用的传统茶饮，还是新式茶饮的核心茶底，茉莉花茶正跨越年龄圈层，展现出旺盛且持久的产业生命力。
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