Evaluation of Resident Evacuations in Urban Rainstorm Waterlogging Disasters Based on Scenario Simulation: Daoli District (Harbin, China) as an Example
Abstract
:1. Foreword
2. Overview for the Research Area
2.1. Natural Conditions
2.2. Overview of Waterlogging Disasters in the Research Area
3. Data Collection and Processing
4. Scenario Simulation of Urban Rainstorm Waterlogging
5. Analysis of the Factors Influencing Resident Evacuation in Urban Rainstorm Waterlogging Disasters
5.1. Analysis of Internal Factors
5.1.1. Influencing Factors and Correlation Analysis of Evacuation
Residents’ Own Characteristics | Correlation | Evacuation Shelter | Selection Tendency of Evacuation Shelter | Evacuation Method | Evacuation Route |
---|---|---|---|---|---|
Gender | Correlation sig. (both sides) | 0.119 0.237 | 0.195 ** 0.036 | −0.43 0.666 | 0.147 ** 0.032 |
Age | Correlation sig. (both sides) | −0.216 *** 0.010 | 0.152 *** 0.049 | −0.063 0.448 | −0.410 *** 0.002 |
Occupation | Correlation sig. (both sides) | −0.36 0.700 | 0.122 0.159 | 0.046 0.621 | 0.358 *** 0.000 |
Education background | Correlation sig. (both sides) | 0.065 0.307 | 0.182 0.059 | 0.057 0.766 | 0.323 *** 0.001 |
Waterlogging disaster experience | Correlation sig. (both sides) | −0.154 0.126 | −0.031 0.739 | 0.118 0.240 | −0.285 *** 0.007 |
5.1.2. Correlation Analysis between Residents’ Own Characteristics and Evacuation Behaviors
- (1)
- Concomitant probability values sig (at both sides) between gender factor and selection tendency of evacuation shelter and evacuation route selection are all below the significance level of 0.05, which indicates that there is a significant correlation between gender factor and selection tendency of evacuation shelter, and evacuation road selection.
- (2)
- Concomitant probability values sig (at both sides) between age and evacuation behavior (evacuation shelter selection, and evacuation route selection) are all below the significance level of 0.01, which indicates that there is a significant linear relation between the two.
- (3)
- Concomitant probability values sig (at both sides) between occupation and evacuation behavior (evacuation route) are all below the significance level of 0.01, which indicates that there is a significant linear relation between the two.
- (4)
- Concomitant probability values sig (at both sides) between education background and evacuation route are below the significance level of 0.01, which indicates that there is a significant linear relation between the two.
- (5)
- Concomitant probability values sig (at both sides) between waterlogging disaster experience and evacuation route are below the significance level of 0.05, which indicates that there is a significant linear relation between the two.
5.2. External Factor Analysis
6. Difficulty Evaluation Index System and Model Building for Residents’ Evacuation at Urban Rainstorm Waterlogging Disasters
6.1. Indicator System Selection
6.2. Index Quantification and Weight Calculation
6.2.1. Index Quantification
6.2.2. Weight Calculation
Factors Typ | Impact Factor Expert Score | ||
---|---|---|---|
Level of education assignment | Junior middle school and below 1 | High school and junior college 2 | Bachelor degree or above 3 |
Types of profession assignment | Farmer | Worker | Student |
1 | 2 | 3 | |
Evacuation channel type | Township roads 1 | Provincial and municipal roads 2 | Urban main roads 3 |
Optimal path choice assignment | Shortest path 1 | Shortest time 2 | Highest security 3 |
Shelter type assignment | Temporary shelter | District shelter | Municipal shelter |
1 | 2 | 3 |
Factor | Deputy Factor | Index | Weight | |
---|---|---|---|---|
Waterlogging disaster Residents evacuation difficulty evaluation index | Dangerousness (H) | Rainfall factors | Precipitation greater than 50mm (XH1) | 0.1692 |
Waterlogging factor | Waterlogging depth (XH2) | 0.2185 | ||
Waterlogging flow velocity (XH3) | 0.0329 | |||
Road factors (E) | Road conditions | Road grade (XE1) | 0.1365 | |
Road network density(X E2) | 0.0683 | |||
Residents’ own vulnerability (V) | Fragility of life is affected by water depth, flow velocity | 0–14 years old, population of more than 60 years old (XV1) | 0.1388 | |
Residents’ walking speed in water | 0.1340 | |||
Residents’ evacuation behavior (R) | Evacuation behavior characteristics | Types of profession(XR1) | 0.0622 | |
Level of education(XR2) | 0.1097 | |||
Evacuation action selection | Quantity of shelter(XR3) | 0.0374 | ||
Evacuation method (XR4) | 0.0206 | |||
Evacuation channel type (XR5) | 0.0440 | |||
Shelter type (XR6) | 0.0257 |
6.3. Evaluation Model Building
6.4. Results Analysis
Item No. | Street Name | Road Waterlogging Length (m) | Evacuation Difficulty |
---|---|---|---|
1 | Xinyang Road | 80 | Relatively difficult for evacuation |
2 | North Jianguo Liudao Street | 60 | Relatively difficult for evacuation |
3 | Central Avenue | 30 | Relatively difficult for evacuation |
4 | Diduan Street | 50 | Relatively difficult for evacuation |
5 | Intersection of Xinyang Road and Minqing Street | 100 | Difficult for evacuation |
6 | Zhaolin Street | 120 | Difficult for evacuation |
7 | Anfeng Street | 100 | Difficult for evacuation |
Item No. | Street Name | Road Waterlogging Length (m) | Evacuation Difficulty |
---|---|---|---|
1 | Xinting Street | 50 | Relatively difficult for evacuation |
2 | Gongnong Avenue | 60 | Relatively difficult for evacuation |
3 | Ansheng Street | 130 | Relatively difficult for evacuation |
4 | Hesong Street | 200 | Relatively difficult for evacuation |
5 | Min’an Street | 120 | Relatively difficult for evacuation |
6 | Hexing Road | 38 | Relatively difficult for evacuation |
7 | Daoli South&North Road | 55 | Relatively difficult for evacuation |
8 | Weiwu Road | 45 | Relatively difficult for evacuation |
9 | Min’an Street | 100 | Relatively difficult for evacuation |
10 | Down Shitoudao Bridge | 500 | Difficult for evacuation |
11 | Intersection of Toulong Street and Maimai Street | 300 | Difficult for evacuation |
12 | Intersection of Toulong Street and Zhaolin Street | 300 | Difficult for evacuation |
13 | Intersection of Anfa Street and Jingwei 2nd Street | 1500 | Difficult for evacuation |
14 | Anguo Street | 900 | Difficult for evacuation |
7. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Chen, P.; Zhang, J.; Jiang, X.; Liu, X.; Bao, Y.; Sun, Y. Scenario simulation-based assessment of trip difficulty for urban residents under rainstorm waterlogging. Int. J. Environ. Res. Public Health 2012, 9, 2057–2074. [Google Scholar] [PubMed]
- Ding, G.; Gao, L.; Li, X.; Zhou, M.; Liu, Q.; Ren, H.; Jiang, B. A mixed method to evaluate burden of malaria due to flooding and waterlogging in Mengcheng county, China: A case study. PLoS One 2014, 9, 1371–1375. [Google Scholar]
- Yin, J.; Xu, S.; Wen, J. Community-based scenario modelling and disaster risk assessment of urban rainstorm waterlogging. J. Geogr. Sci 2011, 21, 274–284. [Google Scholar] [CrossRef]
- Shi, Y.; Shi, C.; Xu, S.Y.; Sun, A.; Wang, J. Exposure assessment of rainstorm waterlogging on old-style residences in Shanghai based on scenario simulation. Natural Hazards 2010, 53, 259–272. [Google Scholar]
- Shi, P.; Du, J.; Ji, M.; Liu, J.; Wang, J. Urban risk assessment research of major natural disasters in China. Advan. Earth Sci. 2006, 21, 170–177. [Google Scholar]
- Shi, P.; Du, J.; Ji, M.; Liu, J.; Wang, J. Urban risk assessment research of major natural disasters in China. Advan. Earth Sci. 2006, 21, 170–177. [Google Scholar]
- Zhou, N.; Yuan, W. The study on storm born surface water accumulation in downtown area of Shanghai. Acta Geogr. Sinica 1993, 48, 262–271. [Google Scholar]
- Drabek, E. Human System Responses to Disaster: An Inventory of Sociological Findings; Springer-Verlag: NewYork, NY, USA, 1986. [Google Scholar]
- Whyte, A. Survey of Households Evacuated during the Mississauga Chlorine Gas Emergency November 10–16, 1979; Toronto: Emergency Planning Project, Institute for Environmental Studies; University of Toronto: Toronto, Canada, 1980. [Google Scholar]
- Shinji, I.; Kenichiro, T.; Kazuhide, T.K. Development of evacuation analysis system for flood events and verification of applicability to emergency management. River Tech. Pap. 2002, 8, 15–20. (In Japanese) [Google Scholar]
- Toshitaka, K.; Makoto, K.; Kazunori, O. Risk image of flood disaster and its effect on evacuation behavior. J. Hydrosci. Hydraul. Eng. 2000, 6, 261–266. (In Japanese) [Google Scholar]
- Yasuda, K. Influential factors of city water logging and the meteorological service. J. Catastrophol. 2008, 2, 47–49. (In Japanese) [Google Scholar]
- Shinji, I.; Kenichiro, T.; Kazuhide, T.; Kazuki, K.; Makoto, K.; Ryouji, H.; Yasushi, T. Development of evacuation analysis system for flood events and verification of applicability to emergency management. J. Hydrosci. Hydraul. Eng. 2002, 8, 25–29. (In Japanese) [Google Scholar]
- Kohei, M.; Miho, O.; Kimiro, M.; Testutaro, S. Study on risks and human evacuation plan in Koto Delta, Tokyo during large flood. Seisan-Kenkyu 2010, 62, 149–152. [Google Scholar]
- Taisuke, I.; Keiichi, T.; Yasuyuki, B.A. Experimental study on evacuation from underground space by using real size models. Ann. Disaster Prevent. Res. Inst. 2006, 48, 583–588. [Google Scholar]
- Yasuyuki, B.A.; TaisukeIshigaki, B.A. Difficulty of evacuation behavior from a submerged vehicle. Bull. Disaster Prevent. Res. Inst. 2010, 53, 553–558. (In Japanese) [Google Scholar]
- Inoue, K. Development of urban flood model due to heavy rainfall and its application to flood control planning. J. Hydrosci. Hydraul. Eng. 2001, 5, 20–25. [Google Scholar]
- Zhang, H. Hazard assessment on rainstorm water-logging disasters based on scenario simulation: A case study on agricultural land of Pudong new area. Mod. Agr. Sci. Technol. 2011, 19, 19–21. [Google Scholar]
- Jing, Y.; Yin, Z.; Yin, J. GIS-based analysis on rainstorm waterlogging hazards in Pudong new area in Shanghai. J. Catastrophol. 2010, 25, 58–63. [Google Scholar]
- Zhou, C.; Ou Yang, M. Progresses of geographical grid systems researches. Prog. Geogr. 2009, 28, 657–662. [Google Scholar]
- Cheng, X.; Yang, L.; Chen, X.-J. Flood diversion and storage flood routing model. J. Nat. Disasters 1996, 5, 34–40. [Google Scholar]
- Li, N.; Qiu, J.-W.; Cheng, X.-T. Study on simulation system of rainstorm waterlogging in Tianjin City. J. Nat. Disasters 2002, 11, 113–118. [Google Scholar]
- Xie, Y.-Y.; Li, D-M.; Shen, S.-Q. Mathematical simulation of rainstorm water logging on “030704” in Nanjing city. J. Yangtze River Sci. Res. Inst. 2004, 21, 73–76. (In Chinese) [Google Scholar]
- Yin, Z.-E.; Xu, S.-Y.; Yin, J.; Wang, J. Small-scale based scenario modeling and disaster risk assessment of urban rainstorm water-logging. Acta Geogr. Sinica 2010, 65, 554–557. [Google Scholar]
- Zhang, L. Urban flooding analysis and modeling using GIS. Acta Geogr. Sinica 1995, 50, 76–84. [Google Scholar]
- Liu, R.-Y.; Liu, N. A GIS based model for calculating of flood area. Acta Geogr. Sinica 2001, 56, 1–6. [Google Scholar]
- Chen, P. Scenario Simulation-Based Residents Shelter and Safety Transfer Research in Harbin Rainstorm Waterlogging Disaster. Doctor Thesis, Northeast Normal University, Chang Chun, Jilin, China, 3 July 2013. [Google Scholar]
- Sun, Y.-M. Using SPSS software to analyze the correlation between variables. J. Xinjiang Educ. Inst. 2007, 23, 120–123. (In Chinese) [Google Scholar]
- Peng, X.-B.; Liu, L.; Li, X.-J. Study on correlation between building damage and strong motion parameters in Wenchuan earthquake. J. Basic Sci. Eng. 2011, 4, 579–580. (In Chinese) [Google Scholar]
- Lu, Q.-Y. Study of the correlation analysis between landslides with its influence factors based on the statistical methods. Geol. Fujian 2010, S1, 52–55. (In Chinese) [Google Scholar]
- Wang, Y.; Wan, Y.-Q.; Qian, X. Construction and empirical analysis of evaluating index system of risk avoiding ability of residents in downstream reservoirs. China Rural Water Hydropower 2009, 1, 26–32. (In Chinese) [Google Scholar]
- Sun, H.-C.; Tian, P.; Wang, L.-F. Analytic Network Process and Decision Sciences; National Defence Industry Press: Beijing, China, 2011. [Google Scholar]
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Chen, P.; Zhang, J.; Zhang, L.; Sun, Y. Evaluation of Resident Evacuations in Urban Rainstorm Waterlogging Disasters Based on Scenario Simulation: Daoli District (Harbin, China) as an Example. Int. J. Environ. Res. Public Health 2014, 11, 9964-9980. https://doi.org/10.3390/ijerph111009964
Chen P, Zhang J, Zhang L, Sun Y. Evaluation of Resident Evacuations in Urban Rainstorm Waterlogging Disasters Based on Scenario Simulation: Daoli District (Harbin, China) as an Example. International Journal of Environmental Research and Public Health. 2014; 11(10):9964-9980. https://doi.org/10.3390/ijerph111009964
Chicago/Turabian StyleChen, Peng, Jiquan Zhang, Lifeng Zhang, and Yingyue Sun. 2014. "Evaluation of Resident Evacuations in Urban Rainstorm Waterlogging Disasters Based on Scenario Simulation: Daoli District (Harbin, China) as an Example" International Journal of Environmental Research and Public Health 11, no. 10: 9964-9980. https://doi.org/10.3390/ijerph111009964