Proceedings of the 2017 7th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2017)

Risk Analysis of Urban Waterlogging Disaster based on Large Data Simulation

Authors
Bingde Deng, Wen Li
Corresponding Author
Bingde Deng
Available Online December 2017.
DOI
https://doi.org/10.2991/mcei-17.2017.210How to use a DOI?
Keywords
Large Data, Simulation, Urban Flooding, Risk
Abstract
This paper uses the principle and method of simplifying the urban waterlogging model to set up a model of waterlogging problem in a horizontal bridge of Changchun. This model is combined with the precipitation data from 1950 to 2010 in Changchun City, and the probability of waterlogging risk at the bottom of the bridge is calculated by simulation method. The results show that the drainage network is not suitable for the heavy rainfall, and the greening rate on both sides of the road can reduce the risk of waterlogging caused by moderate intensity rainfall. The innovation of this paper is to combine simulation with large rainfall data, which is of practical significance to predict the risk of urban waterlogging.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2017 7th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2017)
Part of series
Advances in Computer Science Research
Publication Date
December 2017
ISBN
978-94-6252-430-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/mcei-17.2017.210How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Bingde Deng
AU  - Wen Li
PY  - 2017/12
DA  - 2017/12
TI  - Risk Analysis of Urban Waterlogging Disaster based on Large Data Simulation
BT  - 2017 7th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2017)
PB  - Atlantis Press
SP  - 976
EP  - 980
SN  - 2352-538X
UR  - https://doi.org/10.2991/mcei-17.2017.210
DO  - https://doi.org/10.2991/mcei-17.2017.210
ID  - Deng2017/12
ER  -