幻夜

“因为没买司机的商品，我们全车人被丢弃在新加坡路边4小时！”_我的网站

A |     我们时常会在中国的社交媒体上看到导游强迫游客消费的新闻，万万没想到的是，在中国游客最喜爱的出国游目的地之一、法律严明的旅游城市新加坡，也发生了这样的事……前段时间，一组由20多名中国游客组成的旅游团表示，由于他们拒绝购买旅游巴士司机出售的纪念品，被抛弃在新加坡路边。

B |     

    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.
。在一段时长1分49秒的视频中，可以看到一群中国游客正在与一名巴士司机争吵。他们还站在路边，身边放着自己的行李。在视频里，疑似旅行团成员的抖音网友“Wei Da Piao Liang”讲述了事情的经过。

C | 该网友表示，他们还遭到了巴士司机的侮辱和咒骂，司机卸下他们的行李后开车离开，留下他们一车人在路边。

D | 据本地媒体报道，事件于2024年8月16日中午12点左右发生在跑马埔路（Race Course Road）一带。当时这群游客正在参观寺庙，这是他们为期10天的东南亚国家之旅的一部分，行程中包括新加坡、马来西亚和泰国。这次旅行是由一家中国旅行社安排的。

E | 该网友还在视频中表示，他们这个旅行团刚开始只有15个人。

F | 抵达新加坡后，他们的旅行团与另一个旅行团合并了，人数达到了20多人。

司机在车上卖纪念品

    网友表示，午餐前，旅游大巴司机在车上售卖纪念品，但旅行团的反响并不如他预期。之后，旅行团下车去吃午餐。当一名女游客想要回到车上取高血压药物时，司机拒绝让她上车，还说中国人不愿意花钱。视频截图 司机最后还是打开了车门，但却撞到了一名游客。

G | 旅行团成员对此感到非常愤怒，但司机拒绝道歉。他卸下了所有游客的行李，然后开车离开了。

旅游团滞留四小时

    整车人被困在路边。“我们想报警，但导游威胁我们。”一名游客说道。另一位网友在视频下评论说，她知道旅行团会出售纪念品，但不会强迫他们购买，对于这个旅行团的遭遇她表示不满。事发现场旁一名37岁的餐厅老板表示，旅行团是在他的餐厅用餐的。

H | 他的餐厅的部分生意就来自这样的旅游团，那天，他的员工听到了餐馆外面的一阵骚动。尽管不知道发生争执的原因，餐厅的工作人员还是向游客提供了饮料和茶点，以安抚他们，防止他们打扰其他就餐者。他说，在滞留了4小时后，旅游团乘坐另一辆来接他们的巴士离开了。示意图 一名70岁的司机在8月20日驾驶旅游巴士前往事发的同一地区，他在接受本地媒体采访时认出视频中的司机是自己的同事。这位司机表示，旅游巴士司机确实会尝试出售每件价值几新元的纪念品，但绝不会强迫游客购买。

I | 他补充说，旅游巴士司机谋生很困难，他们没有小费，而且还必须搬运沉重的行李。

J |

新加坡旅游局正在调查此事

    新加坡旅游局发言人表示，目前正在与所有相关方联系，对这起事件进行彻底调查。发言人说：“作为新加坡旅行社的监管机构，我们强调所有持牌人都必须履行职责。”图源：STB 发言人补充说，新加坡旅游局不会容忍任何不尊重游客或将游客置于危险之中的行为，并会毫不犹豫地对不良行为采取行动。“新加坡游客的安全和健康至关重要，我们致力于维护新加坡作为所有游客的安全与热门目的地的声誉。”

游客已返回中国

    中国驻新加坡大使馆证实，大使馆于8月16日中午12点49分接到一名中国赴新加坡旅游团成员的举报。了解情况后，大使馆敦促游客寻求紧急医疗救助，并提醒他们依法享有的权利。

K | 大使馆还向他们提供了本地警方的联系电话和旅游热线。示意图在联系该团的导游和当地旅游联络人员后，另一辆车被派去接回中国游客。事发第二天，该旅行团就按原计划前往马来西亚，并于8月19日返回中国。在新加坡发生这样的事情，也是活久见了。后续将会如何处理？让我们拭目以待吧。

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Published on:20:17:37