2022 Vol. 13, No. 2

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ARTICLE
A Building Classification System for Multi-hazard Risk Assessment
Vitor Silva, Svetlana Brzev, Charles Scawthorn, Catalina Yepes, Jamal Dabbeek, Helen Crowley
2022, 13(2): 161-177. doi: 10.1007/s13753-022-00400-x
Abstract:
A uniform and comprehensive classification system, often referred to as taxonomy, is fundamental for the characterization of building portfolios for natural hazard risk assessment. A building taxonomy characterizes assets according to attributes that can influence the likelihood of damage due to the effects of natural hazards. Within the scope of the Global Earthquake Model (GEM) initiative, a building taxonomy (GEM Building Taxonomy V2.0) was developed with the goal of classifying buildings according to their seismic vulnerability. This taxonomy contained 13 building attributes, including the main material of construction, lateral load-resisting system, date of construction and number of stories. Since its release in 2012, the taxonomy has been used by hundreds of experts working on exposure and risk modeling efforts. These applications allowed the identification of several limitations, which led to the improvement and expansion of this taxonomy into a new classification system compatible with multi-hazard risk assessment. This expanded taxonomy (named GED4ALL) includes more attributes and several details relevant for buildings exposed to natural hazards beyond earthquakes. GED4ALL has been applied in several international initiatives, enabling the identification of the most common building classes in the world, and facilitating compatibility between exposure models and databases of vulnerability and damage databases.
Experimental Evidence for Coverage Preferences in Flood Insurance
J. Connor Darlington, Niko Yiannakoulias
2022, 13(2): 178-189. doi: 10.1007/s13753-022-00397-3
Abstract:
We used a hypothetical choice experiment to estimate the effect of dwelling value and coverage limits on the probability of purchasing flood insurance while holding the probability of flooding and insurance price constant. The results indicate that demand for flood insurance is negatively associated with the amount of insurance coverage. For people assigned higher-valued dwellings, however, the opposite effect is observed. Since more coverage is generally preferred to less, all else being equal, differences in purchase probability dependent on dwelling value indicate an inconsistent approach to home protection. The higher probability of purchasing flood insurance from people in higher-valued dwellings may indicate an investment into the home as a financial asset, a strategy that is not observed to the same extent among people in lower-valued dwellings. This suggests that use of coverage limits may be differentially preferred based on dwelling value, such that low coverage insurance may have lower uptake for those in high-valued dwellings. As Canada evaluates a national flood insurance program, this research suggests that variable coverage maximums could be a way to increase accessibility and uptake of insurance. This research shows an inconsistent demand for flood insurance, dependent on dwelling value and independent of income.
A Regional Economy’s Resistance to the COVID-19 Shock: Sales Revenues of Micro-, Small-, and Medium-Sized Enterprises in South Korea
Seong-Jin Lee, Joong-Hoo Park, Seung-Min Cha, Donghyun Kim
2022, 13(2): 190-198. doi: 10.1007/s13753-022-00402-9
Abstract:
The coronavirus disease 2019 (COVID-19) is a global pandemic that has heavily impacted not only the health sector, but also the economic sector in general. Many countries have projected a negative economic impact, and the effect on micro-, small-, and medium-sized enterprises (MSMEs) is predicted to be significantly large. This study estimated the regional resistance of MSME sales revenues and identified the regional economic factors that affect resistance by analyzing South Korea, a country with one of the lowest economic impact projections from COVID-19. Resistance was estimated by comparing sales revenues and changes in resistance observed during the early COVID-19 period to those recorded in the same weeks (weeks 6 to 9) of 2019. The factors that affect regional resistance were determined by conducting robust regression and spatial regression analyses. The results show that the number of confirmed COVID-19 cases, a direct risk factor, is negatively related to regional resilience, while diversity is positively related to regional resistance. To improve the regional resistance against uncertain events, this study recommends increased diversity among regional industrial structures to reduce the duration of the early shock of an unexpected adverse event.
Dealing with Multisource Information for Estuarine Flood Risk Appraisal in Two Western European Coastal Areas
Ana Rodrigues Rilo, Alexandre Manuel de Oliveira Soares Tavares, Paula Maria dos Santos Freire, José Luis Zêzere
2022, 13(2): 199-213. doi: 10.1007/s13753-022-00403-8
Abstract:
Estuaries are usually affected by compound flooding triggers that cause diverse territorial damages. While fluvial flood risk assessment frameworks are well established in the literature, integrated management instruments that deal with estuarine flood risk remain incomplete and often lacking. This research presents a methodology to extract relevant information from multiple sources post-event and a database building process that is applied to two contrasting estuaries (the Tagus River estuary in Portugal, and the Shannon River estuary in Ireland) in the Western European coastal area. Overall, a total of 274 documents were analyzed and the information was stored in two databases. Multiple correspondence analysis was applied to extract the most informative and relevant estuarine flood indicators. An integrated estuarine flood risk assessment framework is presented and discussed based on the extracted indicators. The framework is driven by two distinct dimensions (oceanic and hydrographic) and revealed the transversal position of triggers of estuarine floods, reflecting the compounding effects usually present in these areas. The results also highlight two levels of flood risk mostly based on damage typology.
Resilience in Agriculture: Communication and Energy Infrastructure Dependencies of German Farmers
Franz Kuntke, Sebastian Linsner, Enno Steinbrink, Jonas Franken, Christian Reuter
2022, 13(2): 214-229. doi: 10.1007/s13753-022-00404-7
Abstract:
Agriculture is subject to high demands regarding resilience as it is an essential component of the food production chain. In the agricultural sector, there is an increasing usage of digital tools that rely on communication and energy infrastructures. Should disruption occur, such strengthened dependencies on other infrastructures increase the probability of ripple effects. Thus, there is a need to analyze the resilience of the agricultural sector with a specific focus on the effects of digitalization. This study works out resilience capacities of the interconnected technologies used in farm systems based on the experiences and opinions of farmers. Information was gathered through focus group interviews with farmers (N = 52) and a survey with participants from the agricultural sector (N = 118). In particular, the focus is put on the digital tools and other information and communication technologies they use. Based on a definition of resilience capacities, we evaluate resilience regarding energy and communication demands in various types of farm systems. Especially important are the resilience aspects of modern systems’ digital communication as well as the poorly developed and nonresilient network infrastructure in rural areas that contrast with the claim for a resilient agriculture. The result is a low robustness capacity, as our analysis concludes with the risk of food production losses.
How Participatory is Participatory Flood Risk Mapping? Voices from the Flood Prone Dharavi Slum in Mumbai
Subhajyoti Samaddar, Ha Si, Xinyu Jiang, Junho Choi, Hirokazu Tatano
2022, 13(2): 230-248. doi: 10.1007/s13753-022-00406-5
Abstract:
Participatory flood risk mapping (PFRM) is a well-recognized and widely implemented tool for meaningful community involvement in disaster risk reduction (DRR). The effectiveness of PFRM remains anecdotal. The PFRM exercise has rarely been applied identically in two different places by two different organizations, which produces varied and uncertain outcomes. In the absence of any agreed and comprehensive framework for participatory DRR, existing studies struggle to provide a scientific account of how the structure, design, and process of PFRM ensure the effective participation of local communities. This study, examines what factors and methods make PFRM an effective participatory DRR tool. In this study, we first identified the process-based criteria of participation. Then we briefly introduced a participatory flood risk mapping exercise conducted in a flood-prone informal settlement in Dharavi, Mumbai. The exercise was carefully designed to meet the process criteria of effective participation. Finally, using qualitative research methods, we evaluated the effectiveness of our PFRM from the local community perspective. The findings show that ensuring community livelihood security and true involvement of marginalized groups, preparing an action plan, and incorporating fun and cultural connotations into the facilitation process are critical components that enhance community participation through PFRM in DRR.
Carbon Emission Risk and Governance
Lu Jiang, Xiaokang Hu, Gangfeng Zhang, Yanqiang Chen, Honglin Zhong, Peijun Shi
2022, 13(2): 249-260. doi: 10.1007/s13753-022-00411-8
Abstract:
Within the hazard and disaster risk research field, explicitly treating carbon emissions as a hazard remains rather nascent. Applying hazard and disaster risk research perspectives to seek new insights on integrated mitigation and adaptation approaches and policy measures is equally elusive. Since China’s pledge to achieve carbon neutrality by 2060, the “dual carbon” goals of carbon emission peaking and neutrality have stimulated nationwide attention, research, and policies and action plans. How to ensure that the transition pathways are on track and well-contextualized is one of the crucial challenges for policymakers and practitioners. This article examines the “risks” of missing the carbon neutrality goal at a regional scale in China, denoted as Carbon Emission Risk (CER). Carbon emissions (CE) as hazard, combined with the human socioeconomic system as exposure and human living environment, constitute the regional carbon emission environmental risk system. The “risks” of missing (or achieving) the carbon neutrality target for any region at any time, the article argues, is essentially determined by the ratio of CE to carbon absorption (CA, for uptake and removal). These variables are modified by a broadly defined “vulnerability coefficient” (Cv) that embodies both the potential for changes (decreasing CE and increasing CA), and the uncertainties of measuring CE and CA. Thus, the ratio of CE to CA is a measure of reality at any moment of time, whereas Cv indicates the overall propensity or capacity for moving the CE/CA ratio towards 1, that is, realizing carbon neutrality. Based on our calculation, CER at the provincial level in eastern China is higher than in western China. The article also calls for strengthening CER research and summarizes key measures for carbon emission risk governance.
Typhoon Risk Perception: A Case Study of Typhoon Lekima in China
Jiting Tang, Saini Yang, Yimeng Liu, Kezhen Yao, Guofu Wang
2022, 13(2): 261-274. doi: 10.1007/s13753-022-00405-6
Abstract:
The typhoon is one major threat to human societies and natural ecosystems, and its risk perception is crucial for contextualizing and managing disaster risks in different social settings. Social media data are a new data source for studying risk perception, because such data are timely, widely distributed, and sensitive to emergencies. However, few studies have focused on crowd sensitivity variation in social media data-based typhoon risk perception. Based on the regional disaster system theory, a framework of analysis for crowd risk perception was established to explore the feasibility of using social media data for typhoon risk perception analysis and crowd sensitivity variation. The goal was to quantitatively analyze the impact of hazard intensity and social and geographical environments on risk perception and its variation among population groups. Taking the Sina Weibo data during Typhoon Lekima of 2019 as an example, we found that: (1) Typhoon Lekima-related Weibo public attention changed in accordance with the evolution of the typhoon track and the number of Weibo posts shows a significantly positive correlation with disaster losses, while socioeconomic factors, including population, gross domestic product, and land area, are not explanatory factors of the spatial distribution of disaster-related Weibo posts; (2) Females, nonlocals with travel plans, and people living in areas with high hazard intensity, low elevation, or near waterbodies affected by Lekima paid more attention to the typhoon disaster; and (3) Descriptions of rainfall intensity by females are closer to the meteorological observation data.
Risk Assessment of Tsunamis Along the Chinese Coast Due to Earthquakes
Chun Hui, Lixin Ning, Changxiu Cheng
2022, 13(2): 275-290. doi: 10.1007/s13753-022-00407-4
Abstract:
China’s coastal areas are densely populated, economically developed, and located in close proximity to several potential tsunami sources; therefore, tsunami risk cannot be ignored. This study assessed tsunami risk in coastal areas of China by developing a framework for tsunami risk assessment from the perspectives of hazards, vulnerability, and exposure. First, a probabilistic tsunami hazard assessment (PTHA) model was applied to estimate the potential tsunami sources in both local crustal faults and circum-Pacific subduction zones based on numerical simulations. The output of the PTHA includes tsunami wave height distributions along the coast. Then, an indicator system reflecting exposure and vulnerability to tsunamis in the coastal areas of China was established by using the entropy method and analytic hierarchy process. The PTHA findings show that the tsunami wave height is close to 3 m on the southern coast of the Bohai Sea, the Pearl River Estuary, and the Yangtze River Delta and exceeds 2 m near the Taiwan Strait for the 2000-year return period. The results of the tsunami risk assessment show that the cities at the highest risk level (level I) include Tangshan, Yantai, and Hong Kong, while cities at the high risk level (level II) include Fuzhou, Xiamen, and Quanzhou near the Taiwan Strait and many cities on the Yangtze River Delta, the Pearl River Estuary, and the southern coast of the Bohai Sea. Our findings can provide an understanding of differences in tsunami risk between Chinese coastal cities that may be affected by tsunamis in the future.
Flash Flood Risk Assessment and Driving Factors: A Case Study of the Yantanxi River Basin, Southeastern China
Liutong Chen, Zhengtao Yan, Qian Li, Yingjun Xu
2022, 13(2): 291-304. doi: 10.1007/s13753-022-00408-3
Abstract:
In the context of climate change, the impact of extreme precipitation and its chain effects has intensified in the southeastern coastal region of China, posing a serious threat to the socioeconomic development in the region. This study took tropical cyclones–extreme precipitation–flash floods as an example to carry out a risk assessment of flash floods under climate change in the Yantanxi River Basin, southeastern China. To obtain the flash flood inundation characteristics through hydrologic–hydrodynamic modeling, the study combined representative concentration pathway (RCP) and shared socioeconomic pathway (SSP) scenarios to examine the change of flash flood risk and used the geographical detector to explore the driving factors behind the change. The results show that flash flood risk in the Yantanxi River Basin will significantly increase, and that socioeconomic factors and precipitation are the main driving forces. Under the RCP4.5-SSP2 and RCP8.5-SSP5 scenarios, the risk of flash floods is expected to increase by 88.79% and 95.57%, respectively. The main drivers in the case study area are GDP density (q = 0.85), process rainfall (q = 0.74), asset density (q = 0.68), and population density (q = 0.67). The study highlights the influence of socioeconomic factors on the change of flash flood disaster risk in small river basins. Our findings also provide a reference for regional planning and construction of flood control facilities in flash flood-prone areas, which may help to reduce the risk of flash floods.
Machine Learning-Based Evaluation of Susceptibility to Geological Hazards in the Hengduan Mountains Region, China
Jiaqi Zhao, Qiang Zhang, Danzhou Wang, Wenhuan Wu, Ruyue Yuan
2022, 13(2): 305-316. doi: 10.1007/s13753-022-00401-w
Abstract:
The Hengduan Mountains Region (HMR) is one of the areas that experience the most frequent geological hazards in China. However, few reports are available that address the geological hazard susceptibility of the region. This study developed six machine learning models to assess the geological hazard susceptibility. The results show that areas with medium and high susceptibility to geological hazards as a whole account for almost 21% of the total area, while both are 18% when it comes to the single hazard of landslide and rockfall respectively. Medium and high geological hazard susceptibility is found in three parts of the HMR with different characteristics: (1) the central and southern parts, where the population of the region concentrates; (2) the northern part, where higher geological hazard susceptibility is found along the mountain ranges; and (3) the junction of Tibet, Yunnan, and Sichuan in the eastern part, which is prone to larger-scale geological hazards. Of all the potential influencing factors, topographic features and climatic variables act as the major driving factors behind geological hazards and elevation, slope, and precipitation are crucial indicators for geological hazard susceptibility assessment. This study developed the geological hazard susceptibility maps of the HMR and provided information for the multi-hazard risk assessment and management of the region.