LI Zhenhong, WANG Jianwei, HU Yufeng, ZHU Wu, FU Xin, ZHANG Shuangcheng, YU Chen, WANG Le, ZHANG Chi, DU Jiantao, HUANG Wubiao, LÜ Xiahe, ZHANG Chenglong, CHEN Bo, LIU Xuxu, YUE Yuqing. Rapid Assessment of Traffic Inefficiency Under Flood Scenarios over Wide Regions[J]. Geomatics and Information Science of Wuhan University, 2023, 48(7): 1039-1049. DOI: 10.13203/j.whugis20220512
Citation: LI Zhenhong, WANG Jianwei, HU Yufeng, ZHU Wu, FU Xin, ZHANG Shuangcheng, YU Chen, WANG Le, ZHANG Chi, DU Jiantao, HUANG Wubiao, LÜ Xiahe, ZHANG Chenglong, CHEN Bo, LIU Xuxu, YUE Yuqing. Rapid Assessment of Traffic Inefficiency Under Flood Scenarios over Wide Regions[J]. Geomatics and Information Science of Wuhan University, 2023, 48(7): 1039-1049. DOI: 10.13203/j.whugis20220512

Rapid Assessment of Traffic Inefficiency Under Flood Scenarios over Wide Regions

  •   Objectives  In July 2021, Henan Province of China suffered continuous extreme rainfalls, causing widespread flood and serious paralysis of the highway network. The flood caused by the heavy rainfalls brought enormous loss to people?s lives and properties in Henan Province.
      Methods  We collectively used a range of earth observations, namely remote sensing images from Sentinel-1 and Gaofen-3 satellites, rainfall and water vapor data from the European Centre for Medium-Range Weather Forecasts, and geohazard survey data to investigate and analyze the evolving process of the flood caused by the heavy rainfalls in Henan Province, and proposed a new technical framework for rapid assessment of traffic inefficiency under flood scenarios over wide regions.
      Results  The application of the new framework to the case in Henan Province suggests that: (1) The cumulative rainfall was highly concentrated, reaching a historic high level and affecting a wide region. (2) The total affected area in Zhengzhou City, Henan Province and its surrounding areas reached 3 800 km2. (3) The potential of secondary landslides in mountainous areas such as Sanmenxia City and Dengfeng City was highly increased.(4) About 1 300.46 km of major roads were affected by this flood, and the overall connectivity of major highway networks in Zhengzhou and its surrounding five cities decreased about 21.27%, with 34.22% for expressways, 13.78% for national highways, and 14.86% for provincial highways.
      Conclusions  This study shows how to integrate remote sensing, secondary landslide analysis, road network analysis, and other multi‑field technologies to construct a framework for traffic inefficiency assessment under natural hazards. It is believed that this framework could be applied to other hazardous events and provide valuable information for emergency rescue.
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