Research on the Urban Flood Disaster Refined Early Warning and the New Modular Resettlement Systems
With global climate change, extreme torrential weather leading to frequent urban flood disasters has been hindering the economic development of cities and posing threats to citizens' health, life, and property safety. Against this backdrop, timely early warning and emergency resettlement research for urban flood disasters are important. This paper first investigates and analyzes the current issues in early warning and resettlement during urban flood disasters. Combining the factors contributing to urban flood disasters, it proposes a refined and scientific early warning platform study. Based on the smart city platform, it integrates geographic information data, urban drainage capacity information, flood rainfall data, and actual rainfall measurements to achieve precise early warnings for flood disasters. Utilizing modular construction and BIM technology, in conjunction with the early warning platform, the site selection, transportation, and assembly of modular resettlement buildings are carried out. The modular resettlement houses provide an efficient and comfortable environment for the affected populace, achieving a humanized and healing space function. The system proposed in the paper can warn the degree and timing of urban flood disaster occurrence areas promptly, form emergency measures, and implement rapid construction of temporary resettlement sites. It offers solutions for emergency resettlement in disaster-stricken areas from the perspective of smart cities, providing fast, efficient, and intelligent resettlement measures for the affected masses.
Authors
- Lingjun Meng
- Hao Yu
- Wei Li
- Zhongge Guo
- Jiale Ren
- Shuai Zhang (ORCID: https://orcid.org/0000-0003-1075-9355)
Institutions
- Beijing Jiaotong University (CN)
Publication Details
- Published
- 2024-08-16
- DOI
- https://doi.org/10.1145/3696500.3696584
- Primary Topic
- Safety and Risk Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00