Urban flood risk assessment under rapid urbanization in Zhengzhou City, China
Received date: 2023-01-28
Revised date: 2023-05-21
Accepted date: 2023-08-23
Online published: 2023-10-20
With accelerated urbanization and climate change, urban flooding is becoming more and more serious. Flood risk assessment is an important task for flood management, so it is crucial to map the spatial and temporal distribution of flood risk. This paper proposed an urban flood risk assessment method that takes into account the influences of hazard, vulnerability, and exposure, by constructing a multi-index urban flood risk assessment framework based on Geographic Information System (GIS). To determine the weight values of urban flood risk index factors, we used the analytic hierarchy process (AHP). Also, we plotted the temporal and spatial distribution maps of flood risk in Zhengzhou City in 2000, 2005, 2010, 2015, and 2020. The analysis results showed that, the proportion of very high and high flood risk zone in Zhengzhou City was 1.362%, 5.270%, 4.936%, 12.151%, and 24.236% in 2000, 2005, 2010, 2015, and 2020, respectively. It is observed that the area of high flood risk zones in Zhengzhou City showed a trend of increasing and expanding, of which Dengfeng City, Xinzheng City, Xinmi City, and Zhongmu County had the fastest growth rate and the most obvious increase. The flood risk of Zhengzhou City has been expanding with the development of urbanization. The method is adapted to Zhengzhou City and will have good adaptability in other research areas, and its risk assessment results can provide a scientific reference for urban flood management personnel. In the future, the accuracy of flood risk assessment can be further improved by promoting the accuracy of basic data and reasonably determining the weight values of index factors. The risk zoning map can better reflect the risk distribution and provide a scientific basis for early warning of flood prevention and drainage.
LI Guoyi , LIU Jiahong , SHAO Weiwei . Urban flood risk assessment under rapid urbanization in Zhengzhou City, China[J]. Regional Sustainability, 2023 , 4(3) : 332 -348 . DOI: 10.1016/j.regsus.2023.08.004
| [1] | Aghapour A.H., Yazdani M., Jolai F., et al., 2019. Capacity planning and reconfiguration for disaster-resilient health infrastructure. J. Build. Eng. 26, 100853, doi: 10.1016/j.jobe.2019.100853. |
| [2] | Bera A., Taloor A.K., Meraj G., et al., 2021. Climate vulnerability and economic determinants: Linkages and risk reduction in Sagar Island, India; A geospatial approach. Quaternary Science Advances. 4, 100038, doi: 10.1016/j.qsa.2021.100038. |
| [3] | Calvet L., Wang D.D., Juan A., et al., 2019. Solving the multidepot vehicle routing problem with limited depot capacity and stochastic demands. Int. Trans. Oper. Res. 26(2), 458-484. |
| [4] | Camorani G., Castellarin A., Brath A., 2005. Effects of land-use changes on the hydrologic response of reclamation systems. Phys. Chem. Earth. 30(8-10), 561-574. |
| [5] | Fariza A., Basofi A., Prasetyaningrum I., et al., 2020. Urban flood risk assessment in Sidoarjo, Indonesia, using fuzzy multi-criteria decision making. Journal of Physics: Conference Series. 1444, 012027, doi: 10.1088/1742-6596/1444/1/012027. |
| [6] | Feng L.T., 2020. Research on risk assessment of flood disaster in Zhengzhou City based on RS and GIS. Master Thesis. Zhengzhou: Zhengzhou University (in Chinese). |
| [7] | Ghosh A., Kar S.K., 2018. Application of analytical hierarchy process (AHP) for flood risk assessment: a case study in Malda district of West Bengal, India. Nat. Hazards. 94, 349-368. |
| [8] | Haasnoot M., Middelkoop H., Offermans A., et al., 2012. Exploring pathways for sustainable water management in river deltas in a changing environment. Clim. Change. 115, 795-819. |
| [9] | Halgamuge M.N., Nirmalathas A., 2017. Analysis of large flood events: Based on flood data during 1985-2016 in Australia and India. Int. J. Disaster Risk Reduct. 24, 1-11. |
| [10] | Huang G.R., 2018. Discrimination of relationship between urban storm waterlogging prevention and sponge city construction. China Flood & Drought Management. 28(2), 8-14 (in Chinese). |
| [11] | Huang G.R., Luo H.W., Chen W.J., et al., 2019. Scenario simulation and risk assessment of urban flood in Donghaochong basin, Guangzhou. Advances in Water Science. 30(5), 643-652 (in Chinese). |
| [12] | Kazakis N., Kougias I., Patsialis T., 2015. Assessment of flood hazard areas at a regional scale using an index-based approach and Analytical Hierarchy Process: Application in Rhodope-Evros region, Greece. Sci. Total Environ. 538, 555-563. |
| [13] | Kia M.B., Pirasteh S., Pradhan B., et al., 2012. An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia. Environ. Earth Sci. 67, 251-264. |
| [14] | Kumar M.D., Tandon S., Bassi N., et al., 2021. A framework for risk-based assessment of urban floods in coastal cities. Nat. Hazards. 110, 2035-2057. |
| [15] | Kundzewicz Z.W., Kanae S., Seneviratne S.I., et al., 2014. Flood risk and climate change: global and regional perspectives. Hydrol. Sci. J.-J. Sci. Hydrol. 59(1), 1-28. |
| [16] | Lei X.X., Chen W., Panahi M., et al., 2021. Urban flood modeling using deep-learning approaches in Seoul, South Korea. J. Hydrol. 61, 126684, doi: 10.1016/j.jhydrol.2021.126684. |
| [17] | Li Z.H., Song K.Y., Peng L., 2021. Flood risk assessment under land use and climate change in Wuhan City of the Yangtze River Basin, China. Land. 10(8), 878, doi: 10.3390/land10080878. |
| [18] | Liu J.H., Li Z.J., Mei C., et al., 2019. Urban flood analysis for different design storm hyetographs in Xiamen Island based on TELEMAC-2D. Chin. Sci. Bull. 64(19), 2055-2066 (in Chinese). |
| [19] | Liu J.H., Luo Z.R., Zhang Y.X., et al., 2022. Influence of urbanization on spatial distribution of extreme precipitation in Henan Province. Water Resources Protection. 38(1), 100-105 (in Chinese). |
| [20] | Liu J.H., Pei Y.J., Mei C., et al., 2023. Waterlogging cause and disaster prevention and control of “7·20” torrential rain in Zhengzhou. Journal of Zhengzhou City University (Engineering Science). 44(2), 38-45 (in Chinese). |
| [21] | Nandi A., Mandal A., Wilson M., et al., 2016. Flood hazard mapping in Jamaica using principal component analysis and logistic regression. Environ. Earth Sci. 75, 465, doi: 10.1007/s12665-016-5323-0. |
| [22] | Paprotny D., Kreibich H., Morales-Nápoles O., et al., 2020. Exposure and vulnerability estimation for modelling flood losses to commercial assets in Europe. Sci. Total Environ. 737, 140011, doi: 10.1016/j.scitotenv.2020.140011. |
| [23] | Park K., Won J.H., 2019. Analysis on distribution characteristics of building use with risk zone classification based on urban flood risk assessment. Int. J. Disaster Risk Reduct. 38(3), 101192, doi: 10.1016/j.ijdrr.2019.101192. |
| [24] | Pham B.T., Luu C., Dao D.V., et al., 2021. Flood risk assessment using deep learning integrated with multi-criteria decision analysis. Knowledge-Based Syst. 219, 106899, doi: 10.1016/j.knosys.2021.106899. |
| [25] | Radwan F., Alazba A.A., Mossad A., 2019. Flood risk assessment and mapping using AHP in arid and semiarid regions. Acta Geophys. 67, 215-229. |
| [26] | Saaty T.L., 1977. A scaling method for priorities in hierarchical structures. J. Math. Psychol. 15(3), 234-281. |
| [27] | Shao R., Shao W.W., Su X., et al., 2022. Impact of various flood scenarios on urban emergency responses times based on the TELEMAC-2D model. Journal of Tsinghua University (Science and Technology). 62(1), 60-69 (in Chinese). |
| [28] | Tehrany M.S., Pradhan B., Jebur M.N., 2015. Flood susceptibility analysis and its verification using a novel ensemble support vector machine and frequency ratio method. Stoch. Environ. Res. Risk Assess. 29(4), 1149-1165. |
| [29] | Tomar P., Singh S.K., Kanga S., et al., 2021. GIS-based urban flood risk assessment and management—a case study of Delhi National Capital Territory (NCT), India. Sustainability. 13(22), 12850, doi: 10.3390/su132212850. |
| [30] | Wang Z.L., Lai C.G., Chen X.H., et al., 2015. Flood hazard risk assessment model based on random forest. J. Hydrol. 527, 1130-1141. |
| [31] | Xu Z.X., Chen H., Ren M.F., et al., 2020. Progress on disaster mechanism and risk assessment of urban flood/waterlogging disasters in China. Advances in Water Science. 31(5), 713-724 (in Chinese). |
| [32] | Yazdani M., Mojtahedi M., Loosemore M., 2020. Enhancing evacuation response to extreme weather disasters using public transportation systems: a novel simheuristic approach. J. Comput. Des. Eng. 7(2), 195-210. |
| [33] | Yazdani M., Mojtahedi M., Loosemore M., et al., 2021. Hospital evacuation modelling: A critical literature review on current knowledge and research gaps. Int. J. Disaster Risk Reduct. 66, 102627, doi: 10.1016/j.ijdrr.2021.102627. |
| [34] | Yu Q., Wang Y.Y., Li N., 2022. Extreme flood disasters: comprehensive impact and assessment. Water. 14(8), 1211, doi: 10.3390/w14081211. |
| [35] | Zhang D.F., Shi X.G., Xu H., et al., 2020. A GIS-based spatial multi-index model for flood risk assessment in the Yangtze River Basin, China. Environ. Impact Assess. Rev. 83, 106397, doi: 10.1016/j.eiar.2020.106397. |
| [36] | Zhang J.P., Zhang H., Fang H.Y., et al., 2021. Study on the characteristics of rainstorm in Zhengzhou. Journal of China Hydrology. 41(5), 78-83 (in Chinese). |
| [37] | Zhang J.Y., Wang Y.T., He R.M., et al., 2016. Discussion on the urban flood and waterlogging and causes analysis in China. Advances in Water Science. 27(4), 485-491 (in Chinese). |
| [38] | Zhao J.H., Xu H.S., Wang T.Y., et al., 2022. Improved entropy weight-TOPSIS-grey correlation method-based urban flood-waterlogging risk assessment. Water Resources and Hydropower Engineering. 53(10), 58-73 (in Chinese). |
| [39] | Zhou Y.H., Peng T., Shi R.Q., 2019. Research progress on risk assessment of heavy rainfall and flood disasters in China. Torrential Rain and Disasters. 38(5), 494-501 (in Chinese). |
/
| 〈 |
|
〉 |