Rainstorm waterlogging risk assessment in central urban area of Shanghai based on multiple scenario simulation

With the acceleration of the urbanization process, waterlogging problems in coastal cities are becoming more and more serious due to climate change. However, up until now, the common procedures and programs for rainstorm waterlogging risk assessment in coastal cities still have not formed. Considering a series of impact factors of rainstorm waterlogging in coastal city, the present study established a paradigm for rainstorm waterlogging risk assessment through the combination of hydrological modeling and GIS spatial analysis, and took the residence in central urban area of Shanghai as an example. First, the simplified urban waterlogging model was applied to simulate the depth and extent of rainstorm waterlogging under six hypothetic scenarios. Second, the residence exposed to rainstorm waterlogging was extracted and analyzed supported by spatial analysis module of ArcGIS. Then, stage-damage curves were applied to analyze the loss rate of structure and contents of residential building. Finally, the waterlogging loss maps of residence in different scenarios, the annual average loss, and the risk curve were taken as the expression of waterlogging risk. The results show that the inundated water depth, vulnerability, and losses of residence all increase as the intensity of rainstorm increases. The old-style residence is most vulnerable to rainstorm waterlogging, followed by the new-style residence, and villa is less vulnerable to rainstorm waterlogging. The annual average loss of residence in Shanghai central urban area was about CNY 22.25 million. The results also indicate high risk in Yangpu and Putuo districts, Xuhui, Hongkou, Changning and Zhabei districts come under medium-risk zone, and Jing’an, Luwan and Huangpu districts come under low-risk zone. These results provide important information for the local government, and the methodology can be applied in other cities to provide guidance on waterlogging risk governance.

[1]  D. Dutta,et al.  A mathematical model for flood loss estimation , 2003 .

[2]  J. Nott Extreme Events: A Physical Reconstruction and Risk Assessment , 2006 .

[3]  Jie Yin,et al.  Modelling the combined impacts of sea-level rise and land subsidence on storm tides induced flooding of the Huangpu River in Shanghai, China , 2013, Climatic Change.

[4]  D. Wilhite Drought as a natural hazard : Concepts and definitions , 2000 .

[5]  Jie Yin,et al.  Multiple scenario analyses of Huangpu River flooding using a 1D/2D coupled flood inundation model , 2013, Natural Hazards.

[6]  Shiyuan Xu,et al.  Community-based scenario modelling and disaster risk assessment of urban rainstorm waterlogging , 2011 .

[7]  Gong Shi Effect of Land Subsidence on Urban Flood Prevention Engineering in Shanghai , 2008 .

[8]  C. Tanavud,et al.  Assessment of flood risk in Hat Yai Municipality, Southern Thailand, using GIS , 2004 .

[9]  J. Wang,et al.  Exposure assessment of rainstorm waterlogging on old-style residences in Shanghai based on scenario simulation , 2010 .

[10]  Donald A. Wilhite,et al.  Drought : a global assessment , 2000 .

[11]  Annegret H. Thieken,et al.  Estimation of the regional stock of residential buildings as a basis for a comparative risk assessment in Germany , 2006 .

[12]  M. Islam,et al.  Flood hazard assessment in Bangladesh using NOAA AVHRR data with geographical information system , 2000 .

[13]  XU Shi-yuan,et al.  Exposure Assessment of Rainstorm Waterlogging on Buildings in Central Urban Area of Shanghai Based on Scenario Simulation , 2011 .

[14]  Michael Oppenheimer,et al.  The potential impacts of sea level rise on the coastal region of New Jersey, USA , 2008 .

[15]  L. Cui,et al.  Characteristics of high impact weather and meteorological disaster in Shanghai, China , 2012, Natural Hazards.

[16]  Yong Shi,et al.  Risk analysis of rainstorm waterlogging on residences in Shanghai based on scenario simulation , 2012, Natural Hazards.

[17]  J. Palutikof,et al.  Climate change 2007 : impacts, adaptation and vulnerability , 2001 .

[18]  B. Wisner,et al.  At Risk: Natural Hazards, People's Vulnerability and Disasters , 1996 .

[19]  Jie Yin,et al.  Composite risk assessment of typhoon-induced disaster for China’s coastal area , 2013, Natural Hazards.

[20]  Min Liu,et al.  Waterlogging risk assessment based on land use/cover change: a case study in Pudong New Area, Shanghai , 2010 .

[21]  Yong Shi Population vulnerability assessment based on scenario simulation of rainstorm-induced waterlogging: a case study of Xuhui District, Shanghai City , 2013, Natural Hazards.

[22]  Jie Yin,et al.  National assessment of coastal vulnerability to sea-level rise for the Chinese coast , 2012, Journal of Coastal Conservation.

[23]  J. Beddington,et al.  Climate change: Migration as adaptation , 2011, Nature.

[24]  T. Chang,et al.  Inundation simulation for urban drainage basin with storm sewer system , 2000 .

[25]  Shiyuan Xu,et al.  Evaluation of the combined risk of sea level rise, land subsidence, and storm surges on the coastal areas of Shanghai, China , 2012, Climatic Change.

[26]  Min Liu,et al.  Risk assessment of rainstorm waterlogging on subway in central urban area of Shanghai, China based on scenario simulation , 2011, 2011 19th International Conference on Geoinformatics.

[27]  Theo G. Schmitt,et al.  Analysis and modeling of flooding in urban drainage systems , 2004 .

[28]  P. Shi,et al.  Integrated Risk Governance: Science Plan and Case Studies of Large-scale Disasters , 2013 .

[29]  R. Nicholls,et al.  A global analysis of human settlement in coastal zones , 2003 .

[30]  V. Singh,et al.  SCS-CN-based modeling of sediment yield , 2006 .

[31]  Dapeng Yu,et al.  An evaluation of the impacts of land surface modification, storm sewer development, and rainfall variation on waterlogging risk in Shanghai , 2012, Natural Hazards.

[32]  Mahendra Singh Nathawat,et al.  Waterlogging and flood hazards vulnerability and risk assessment in Indo Gangetic plain , 2010 .

[33]  L. Da,et al.  Dynamics of ruderal species diversity under the rapid urbanization over the past half century in Harbin, Northeast China , 2013, Urban Ecosystems.

[34]  M. Diakakis,et al.  Floods in Greece, a statistical and spatial approach , 2012, Natural Hazards.

[35]  S. Carpenter,et al.  Social-Ecological Resilience to Coastal Disasters , 2005, Science.

[36]  T. Ouarda,et al.  Use of Systematic, Palaeoflood and Historical Data for the Improvement of Flood Risk Estimation. Review of Scientific Methods , 2004 .

[37]  S. Stefanidis,et al.  Assessment of flood hazard based on natural and anthropogenic factors using analytic hierarchy process (AHP) , 2013, Natural Hazards.