Large-Scale Natural Disaster Risk Scenario Analysis: a Case Study of Wenzhou City, China
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Nat Hazards (2012) 60:1287–1298 DOI 10.1007/s11069-011-9909-2 ORIGINAL PAPER Large-scale natural disaster risk scenario analysis: a case study of Wenzhou City, China Yaolong Liu • Zhenlou Chen • Jun Wang • Beibei Hu • Mingwu Ye • Shiyuan Xu Received: 17 September 2010 / Accepted: 16 July 2011 / Published online: 14 August 2011 Ó Springer Science+Business Media B.V. 2011 Abstract Based on the analysis and calculation of the hazard intensity of typhoon rainstorms and floods as well as the vulnerability of flood receptors and the possibility of great losses, risk scenarios are proposed and presented in Wenzhou City, Zhejiang Prov- ince, China, using the Pearson-III model and ArcGIS spatial analyst tools. Results indicate that the elements of risk scenarios include time–space scenarios, disaster scenarios, and man-made scenarios. Ten-year and 100-year typhoon rainstorms and flood hazard areas are mainly concentrated in the coastal areas of Wenzhou City. The average rainfall across a 100-year frequency is 450 mm. The extreme water depth of a 100-year flood is 600 mm. High-vulnerability areas are located in Yueqing, Pingyang, Cangnan, and Wencheng counties. The average loss rate of a 100-year flood is more than 50%. The greatest possible loss of floods shows an obvious concentration-diffusion situation. There is an area of about 20–25% flood loss of 6–24 million Yuan RMB/km2 in the Lucheng, Longwan and Ouhai districts. The average loss of a 100-year flood is 12 million Yuan RMB/km2, and extreme loss reaches 49.33 million Yuan RMB/km2. The classification of risk scenario may be used for the choice of risk response priorities. For the next 50 years, the 10-year typhoon rainstorm-flood disaster is the biggest risk scenario faced by most regions of Wenzhou City. For the Yueqing, Ruian, and Ouhai districts, it is best to cope with a 100-year disaster risk scenario and the accompanying losses. Y. Liu Science and Technology Department, Taiyuan University of Technology, Taiyuan 030024, China Y. Liu Á Z. Chen Á J. Wang (&) Á M. Ye Á S. Xu Key Laboratory of Geographic Information Science of Ministry of Education, East China Normal University, Shanghai 200062, China e-mail: [email protected] J. Wang Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80521, USA B. Hu College of Urban and Environment Science, Tianjin Normal University, Tianjin 300387, China 123 1288 Nat Hazards (2012) 60:1287–1298 Keywords Risk Á Scenario analysis Á Typhoon rainstorm-flood Á Large scale Á Wenzhou City 1 Introduction With global warming, sea levels rising, and the accelerated urbanization process, the intensity and frequency of natural disasters and the vulnerability of society and the economy are growing quickly (Ruisong et al. 2010). More and more scholars are concerned about the risks of natural disasters in coastal cities (Yafeng et al. 2000; PeiJun et al. 2001; Shiyuan et al. 2006; Dapeng et al. 2008; Beibei et al. 2009; Yong et al. 2010). Currently, the basic method of disaster risk analysis is to build risk models (Chongfu 1999). Sophisticated risk assessment models and methods in China and abroad include the Disaster Risk Index (UNDP 2004), the Hotspots Projects (UNDP 2004), the System of Indicators for Disaster Risk Management (IDEA, IDB 2005), Multi-risk Assessment (Stefan 2006), HAZUS (FEMA 2004), and CBDRM (Bollin 2006). The spatial scales of disaster assessment are involved in global, continental, national, and local communities. As one of the crucial competitive intelligence methods in enterprises (Gilbert 2000), scenario analysis has been widely used in economics (Yiming et al. 2006; Shrestha et al. 2007), environmental impact (Jawjit et al. 2008; Zhixi et al. 2010), ecology and ecosystem (Carpenter et al. 2006;Ma¨rker et al. 2008, Ferng 2009), and global change areas (Abildtrup et al. 2006; Tao and Watson 2010). Applied in hazard risk study, it is mainly used in earthquake (Klu¨gel et al. 2006), flood disaster (Yanyan et al. 2009), environmental and man-made disaster (Tsai and Su 2004; de Bruin and Swuste 2008) risk assessment. Natural disaster risk scenario analysis is a scenario-based expression and characterization of natural disaster risk, which is often combined with GIS (Shaping et al. 2004; Pessina and Meroni 2009). Specifically, based on the conditions of disaster risk scenarios, spatial distribution of risk is carried out. As for the risk scenario, it includes the time and space scenarios, disaster scenarios, and man-made scenarios. Taking Wenzhou City as a large spatial scale empirical area, this paper launched a typhoon rainstorm-flood disaster risk analysis study under the conditions of different time frames and disaster scenarios. 2 Materials and methods 2.1 Background about the study area Wenzhou City is located in the Zhejiang Province in southeastern China (Fig. 1) with geographical coordinates between latitude 27°030 and 28°360 N and longitude 119°370 and 121°180 E. The city has a total population of about 0.75 million, covering an area of 11,784 km2. Wenzhou has a subtropical marine monsoon climate with an average annual temperature of 18°C. Due to plenty of rain, its annual precipitation ranges from 1,100 to 2,200 mm. The average annual precipitation is 1,800 mm, and its spatial distribution and seasonal variation are uneven. Located in the sea–land interface area, the effect between human and geography in Wenzhou is quite strong. There are frequent typhoons, torrents, floods, droughts, tides, cold snaps, and hailstones, and the floods caused by typhoons and storms occur quite often. 123 Nat Hazards (2012) 60:1287–1298 1289 Fig. 1 The sketch map of the study area According to the historical records, 73 floods and 64 large droughts took place from 684 to 1948 A.D. (1,264 years). Since the foundation of the People’s Republic of China in 1949, there have been 198 typhoons affected Wenzhou in which large waves and heavy rain floods occurred 44 times. Due to global climate changes, the frequency and intensity of typhoon rainstorms and floods have gradually increased in Wenzhou. 2.2 Definition of risk scenarios Risk scenario is defined as an outcome that is determined by combining a set of conditions, such as time span, spatial scale, the type of disaster, and man-made factors of hazards. Among them, spatial and temporal scenarios include time span (the next X years), spatial scales (large, medium, and small scale), and return period (X-year hazards). Disaster scenarios refer to the type of disaster, such as typhoon, rainstorm, flood, water-logging, etc. Man-made scenarios involve demographic, economic levels, land-use change, etc. (Figure 2). Scenario-based analysis of disaster risk involves exploring the demographic, economic, and social potential risks of different kinds of disasters and disaster groups, which are in the specific time and space situational conditions. Wenzhou City’s disaster risk scenario is defined as follows: (a) In large spatial scale, (b) In the next 50 years, (c) 10-year and 100-year hazards, 123 1290 Nat Hazards (2012) 60:1287–1298 Establishment of risk scenarios Space-time scenes disaster scenes man-made scenes Land-use change Land-use Economic lev Economic Return period Return Waterlogging Demographic Spatial scales Rainstorm Time span Time Typhoon Floods el The expression and distribution of scenario-based risk Fig. 2 The definition and types of risk scenarios (d) Occurring in the form of typhoon rainstorm-floods, and (e) The size and distribution of the disaster risk. For the coastal cities, the large spatial scale refers to provinces, cities, and prefecture- level cities; the middle spatial scale refers to counties; and the small spatial scale refers to the community and the streets. Choosing two typical return periods, the paper explores the risk differences of Wenzhou City in the next 50 years. 2.3 Data collection and processing In this study, the historical typhoon rainstorm monitoring data of Wenzhou city during the period of 1952–2006 were obtained from the Northwest Pacific tropical cyclone tracks retrieve information system, Wenzhou Historical Flood and Drought Information, Wenzhou City Annals, Wenzhou City Water Annals, and Zhejiang Meteorological Disasters Annals (2003–2007) (http://www.zjmb.gov.cn). The hazard-bearing objects type and spatial distribution data were derived from land- use maps of the Zhejiang Province (1997) and the Zhejiang Province land-use plan (1997–2010) (http://gtt.zj.gov.cn/). The per unit area GDP data for Wenzhou City and the surrounding districts and counties were obtained from the Wenzhou Statistical Yearbook 2008 (http://www.wzstats.gov.cn/), the Zhejiang Statistical Yearbook 2008 (http://tjj. zj.gov.cn/), and the Fujian Statistical Yearbook 2008 (http://www.stats-fj.gov.cn/). All the original data are publicly available at the websites listed here or in the publications. 2.3.1 Pearson-III model frequency analysis The Pearson-III probabilistic model was used to estimate the intensity of typhoons rain- storms in different frequencies. Its probability density function is as follows: ba f ðxÞ¼ ðx À a ÞaÀ1eÀbðxÀa0Þ ð1Þ CðaÞ 0 where C(a)isa’s gamma function and a, b, a0 are three parameters. 123 Nat Hazards (2012) 60:1287–1298 1291 4 2 2Cv a ¼ 2 ; b ¼ ; a0 ¼ x 1 À ð2Þ Cs xC vCs Cs where x is the average value; Cv is the deviation coefficient; and Cs is the deviation coefficient. The relationship between the return period Tn (years) and the annual frequency p (%) is as follows: 1 T ¼ ð3Þ n p By the formula (1) and (2), the intensity frequency distribution of typhoon rainstorm disasters in Wenzhou City was calculated at different frequencies p (%). By the formula (3), the return period of Tn (a) at different frequencies p (%) was calculated.