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The Value of China's Coastal Wetlands and Seawalls for Storm Protection

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The Value of China's Coastal Wetlands and Seawalls for Storm Protection Ecosystem Services 36 (2019) 100905 Contents lists available at ScienceDirect Ecosystem Services journal homepage: www.elsevier.com/locate/ecoser The value of China’s coastal wetlands and seawalls for storm protection T ⁎ Xin Liua,d, , Yebao Wanga,b,c, Robert Costanzad, Ida Kubiszewskid, Ning Xue, Meihua Yuand,f, Ruiying Genga,b a Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, Shandong 264003, PR China b University of Chinese Academy of Sciences, Beijing 100049, PR China c Ocean College, Yantai University, Yantai 264005, PR China d Australian National University, Canberra, ACT 2601, Australia e Shangqiu Normal University, Shangqiu 476000, PR China f National Taiwan University, Taipei 10617, Taiwan, ROC ARTICLE INFO ABSTRACT Keywords: China has relied on seawalls for storm protection along its coasts for decades. In contrast, the storm protection Coastal wetlands functions of coastal wetlands are often ignored by decision makers in China. We examined 127 historical storms Storm protection function with consequent economic loss to China from 1989 to 2016 and estimated the value of coastal wetlands with Service valuation controlling for seawalls for storm protection. A regression model with the natural log of damage per unit gross Regression model domestic product in the storm swath as the dependent variable and explanatory variables including the length of Storm trajectory existing seawalls in the storm swath and the natural logs of wind speed, storm duration and wetland area in the Protective seawalls storm swath was highly significant and explained 59.2% of the variation in relative damages. Results show that a gain of 1 km2 of wetlands corresponds to an average CNY 83.90 million (median = CNY 11.87 million) decrease in storm damage from specific storms. Coastal wetlands are gifts of nature and self-maintaining so they have zero construction and maintenance costs. They also provide many other valuable ecosystem services that hard sea- walls do not. 1. Introduction Coastal wetlands are a good example of natural buffers against storms. A wetland between uplands terrain and the storm surge is likely to Storms, including typhoons, cyclones, tropical storms, hurricanes, diminish storm intensity (Costanza et al., 2008; Simpson and Riehl, tornadoes, winter storms, and tropical depressions, can result in human 1981). Examining the role of wetlands in mitigating storms generally fatalities, economic losses, and ecological damages (IPCC, 2013). China falls into two classes: numerical simulations and empirical observa- has been hit by the most storms out of any country since 1970, the time tions. when modern global satellite surveillance became available (NOAA's A burgeoning pool of research has quantified the effect of wetlands Hurricane Research Division, 2010). For example, when the 2016 ty- on storm surge and flooding using numerical simulations. Multiple of phoon Mujigae made landfall in the China coastal provinces, it killed factors such as size of wetlands, vegetation species, marsh elevation and approximately 5 people due to flooding and had a total economic cost bottom friction have been shown to have a definite and wide ranging to China of CNY 2.67 billion (Marine Disaster Bulletin, 2016). Low- effect on storm peak surge levels (Loder et al., 2009; Barbier et al., lying sedimentary coasts are generally much less resilient to flooding 2013; Wamsley et al., 2010; Narayan et al., 2017). Barbier et al. (2013) (Woodruff et al., 2013). Storm impacts are likely to increase in the simulated four storms to show that storm surge levels decline with future partly due to an increase in storm frequency driven by climate wetland continuity and vegetation roughness. Loder et al. (2009) con- change (IPCC, 2013; Rahmstorf, 2017; Garner et al., 2017) and partly as firmed that storm surge is parameterized in terms of marsh elevation population and cities expand along the coast (Dinan, 2017). and bottom friction. In addition, storm related parameters including Storm damages are mainly attributed to flooding from storm-tidal intensity, duration, forward speed and maximum wind radius can be surge and rainfall, but are also caused by high winds (Farber, 1987). affected by wetlands to attenuate storm surges (Deng et al., 2010; Hu ⁎ Corresponding author at: Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, Shandong 264003, PR China. E-mail address: [email protected] (X. Liu). https://doi.org/10.1016/j.ecoser.2019.100905 Received 5 November 2018; Received in revised form 31 January 2019; Accepted 1 March 2019 2212-0416/ © 2019 Elsevier B.V. All rights reserved. X. Liu, et al. Ecosystem Services 36 (2019) 100905 Table 1 An overview of data obtained in this study. Data Descriptions Sources Websites Historical typhoons in All major typhoons caused economic damages in China Marine Disaster Bulletin http://www.soa.gov.cn/zwgk/hygb/zghyzhgb/index.html china from 1991 to 2016 were detailed. (MDB) Hurricane tracking data Hurricane/tropical data with wind speeds and Unisys Weather http://weather.unisys.com/hurricane trajectories Global disasters International disaster database recording individual EM-DAT http://www.emdat.be cases for countries Herbaceous coastal Data were extracted from Landsat satellite images Geospatial Data Cloud http://www.gscloud.cn wetlands Hard engineered defence Data were retrieved from Landsat satellite images U.S. Geological Survey http://www.usgs.gov Census data Raster data showing the distribution of Chinese SEDAC RESDC http://sedac.ciesin.columbia.edu/data/colection/gpw-v3 population http://www.resdc.cn GDP Temporal statistical GDP data for Chinese coastal National Bureau of http://data.stats.gov.cn/easyquery.htm?cn=E0103 provinces Statistics of China et al., 2015; Marsooli, et al., 2016; Zhang et al., 2012). “red line” to conserve at least 53.33 million ha of wetlands in the Several empirical studies have found evidence of the effectiveness of country (Bai et al., 2016). On the other hand, no work has been done to wetlands in reducing death tolls and in protecting property (Das et al., estimate the storm protection value by coastal wetlands in China, al- 2009; Koch et al., 2009; Seriño et al., 2017). Some studies have at- though coastal wetlands have been identified widely in literature to tempted to value the protection service of coastal wetlands against the provide storm protection. storms. For example, a regional study by Narayan et al. (2017) showed fl that wetlands avoided USD 0.6 billion in direct ood damages to 2. Data and methods properties during Hurricane Sandy. Seriño et al. (2017) found that the estimated average cost of saving life by retaining a hectare mangrove This paper provides an estimate of the value of coastal wetlands for area was USD 301,811 in Visayas, Philippines during the super typhoon storm protection with controlling for seawalls. To estimate the storm HAIYAN. However, some of these studies have been criticized for fo- protection value of coastal wetlands, we used a regression model in cusing on a regional scale, using small samples, or inadequately con- which the dependent variable was the natural log of storm damage (TD) trolling for confounding factors such as protective structures. Literature per unit gross domestic product (GDP) in the swath of the storm (ln(TD/ reviewed by Seriño et al. (2017) indicated that long-term empirical GDP)) and the explanatory variables included the length of seawalls in fi evidence that coastal wetlands provide signi cant protection against the storm swath and the natural logs of the wind speed at landfall, storms is scarce (Das et al., 2009). Recently, wetlands as ecosystem- storm duration and the wetlands area in the storm swath. based hazard protection measures have challenged traditional hard To determine the storm protection value provided by coastal wet- ff engineering in terms of sustainability and cost-e ectiveness lands, available data were collected from a variety of sources. Details (Temmerman et al., 2013; Smith et al., 2017). To support such an ar- can be seen in Table 1 as follows: gument, evidence of the value of storm protection services by wetlands Since 1989, the State of Ocean Administration (SOA), China has based on large samples collected at the national scale, controlling for issued an annual Marine Disaster Bulletin to the public to provide of- confounding factors is necessary. Our analysis is one of the few (another ficial statistics about maritime disasters and their impacts. The is Costanza et al., 2008) that synthesizes historical cases at a national International Disaster Database, from EM-DAT, provided individual scale, in this case for China. records of typhoons worldwide including Chinese cases since 1900. We China has responded to storm strikes by establishing hard en- mainly collected the total economic damage (TD) data for typhoons gineered defences since 1970. The positive role of hard engineered from Marine Disaster Bulletin (MDB) and the international EM-DAT defences in mitigating economic loss caused by storms has been ad- complemented several cases. In summary, 127 typhoons with economic dressed by the Chinese State of Ocean Administration (Liu et al., 2019). loss over 28 years from 1989 to 2016 were sampled and coded in the China is an ideal case to analyse because its coastline is approximately regression model. The total economic damage (TD) from MDB is com- 34,000 km with 13,830 km of hard engineering structures (Luo et al., prehensive including properties, roads, bridges, fishing ships, human ’ 2015). China s coastal population was approximately 595 million by lives, agriculture and mari-aquaculture that were damaged by the 2015, it has been hit by the most storms since 1970, and nearly 58% of storms. coastal wetlands have been lost since 1950 due to land reclamation and Hurricane tracking data from Unisys Weather was used to estimate infrastructure development (Yang et al., 2017; Bi et al., 2012).
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