International Journal of Disaster Risk Science

2020 Vol. 11, No. 4

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EDITORIAL

Editorial Note on the 10-Year Anniversary of the International Journal of Disaster Risk Science: A Thank You Letter

Peijun Shi, Carlo Jaeger

2020, 11(4): 411-413. doi: 10.1007/s13753-020-00297-4

Abstract(26) PDF

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ARTICLES

Thirty Years of Science, Technology, and Academia in Disaster Risk Reduction and Emerging Responsibilities

Rajib Shaw

2020, 11(4): 414-425. doi: 10.1007/s13753-020-00264-z

Abstract(109) PDF

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The 1990 initiation of the International Decade for Natural Disaster Reduction marked its 30th year in 2019. The three decades since then have seen significant developments in science and technology and their incorporation into the decision making in the field of disaster risk reduction. The disasters that have occurred during that time have enhanced the importance of the field, and new research and innovations have evolved. This article summarizes this evolution through the review of specific milestones. While the Sendai Framework for Disaster Risk Reduction 2015–2030 provides opportunities for synergies with the sustainable development agenda, the science and technology communities have also changed their roles from advisory to co-designing and co-delivering solutions. Higher education plays an important role in developing new generations of professionals, and the role of thematic incubation in higher education institutions is highlighted along with the development of the professional society in disaster risk reduction. The evolution from Society 4.0 (information age) to Society 5.0 will see an enhanced role of the technology-driven approach in disaster risk reduction, while traditional knowledge and indigenous technologies still remain valid for society. Scientists and science communities need to be more sensitive to changing the “last mile” concept to “first mile” thinking with respect to the users' needs and perspectives.

Disaster Risk Science: A Geographical Perspective and a Research Framework

Peijun Shi, Tao Ye, Ying Wang, Tao Zhou, Wei Xu, Juan Du, Jing'ai Wang, Ning Li, Chongfu Huang, Lianyou Liu, Bo Chen, Yun Su, Weihua Fang, Ming Wang, Xiaobin Hu, Jidong Wu, Chunyang He, Qiang Zhang, Qian Ye, Carlo Jaeger, Norio Okada

2020, 11(4): 426-440. doi: 10.1007/s13753-020-00296-5

Abstract(173) PDF

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In this article, we recall the United Nations' 30-year journey in disaster risk reduction strategy and framework, review the latest progress and key scientific and technological questions related to the United Nations disaster risk reduction initiatives, and summarize the framework and contents of disaster risk science research. The object of disaster risk science research is the “disaster system” consisting of hazard, the geographical environment, and exposed units, with features of regionality, interconnectedness, coupling, and complexity. Environmental stability, hazard threat, and socioeconomic vulnerability together determine the way that disasters are formed, establish the spatial extent of disaster impact, and generate the scale of losses. In the formation of a disaster, a conducive environment is the prerequisite, a hazard is the necessary condition, and socioeconomic exposure is the sufficient condition. The geographical environment affects local hazard intensity and therefore can change the pattern of loss distribution. Regional multi-hazard, disaster chain, and disaster compound could induce complex impacts, amplifying or attenuating hazard intensity and changing the scope of affected areas. In the light of research progress, particularly in the context of China, we propose a three-layer disaster risk science disciplinary structure, which contains three pillars (disaster science, disaster technology, and disaster governance), nine core areas, and 27 research fields. Based on these elements, we discuss the frontiers in disaster risk science research.

Intensive Versus Extensive Events? Insights from Cumulative Flood-Induced Mortality Over the Globe, 1976–2016

Bo Chen, Fanya Shi, Tingting Lin, Peijun Shi, Jing Zheng

2020, 11(4): 441-451. doi: 10.1007/s13753-020-00288-5

Abstract(67) PDF

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More attention has been paid to the cost of intensive but sporadic floods than the cost of extensive but frequent events. To examine the impacts of intensive versus extensive events, we investigated the loss structure of global flood-induced mortality by using the cumulative loss ratio, marginal benefit chart, and cumulative loss plot. Drawing on the flood-induced mortality data for four decades (1976–2016) from the international disaster database EM-DAT, we defined the levels of flood loss according to the frequency of flood-induced deaths, and calculated the cumulative mortality and the marginal benefits of flood loss prevention practices at different levels. Our analysis showed that for the world's leading 30 countries with large flood-induced mortality and different levels of development: (1) 70% of them have the cumulative deaths from extensive floods exceeding half of those caused by intensive floods in the study's four data decades; and (2) 80% of them tend to gain less marginal benefit with increasing levels of flood prevention, with their marginal benefits peaking at loss prevention levels of 2-year or 5-year flood-induced mortality. These results indicate that, in the long run, the cumulative deaths of extensive floods are comparable to that of intensive events, and prevention of loss from extensive events can be an efficient way to reduce the total loss. For flood risk management under conditions of climate change, extensive loss events deserve more consideration.

Seismic Risk Assessment of the Railway Network of China's Mainland

Weihua Zhu, Kai Liu, Ming Wang, Elco E. Koks

2020, 11(4): 452-465. doi: 10.1007/s13753-020-00292-9

Abstract(105) PDF

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Earthquakes pose a great risk to railway systems and services around the world. In China alone, earthquakes caused 88 rail service disruptions between 2012 and 2019. Here, we present a first-of-its-kind methodology to analyze the seismic risk of a railway system using an empirically derived train service fragility curve. We demonstrate our methodology using the Chinese railway system. In doing so, we generate a set of stochastic earthquake scenarios for China based on a national-scale seismicity model. Using disruption records, we construct an empirically grounded fragility curve that relates the failure probability of train services to peak ground acceleration. By combining the simulated earthquakes, the fragility curve, and empirical train flow data from 2016, we quantitatively assess the seismic impact and the risk faced by the Chinese railway system. The maximum train trip loss could reach 2400 trips in response to a single seismic event, accounting for 34% of the national daily train trips. Due to the spatially uneven daily train flow and seismicity distribution, the seismic impact on the railway system in different seismic zones is highly heterogeneous and does not always increase when the hazard intensity increases. More specifically, the results show that the railway lines located in the Qinghai-Tibet and Xinjiang seismic zones exhibit the highest risk. The generated impact curves and the risk map provide a basis for railway planning and risk management decisions.

Jing Zhang, Zhao Zhang, Fulu Tao

2020, 11(4): 466-483. doi: 10.1007/s13753-020-00283-w

Abstract(76) PDF

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Rainfall-related hazards—deficit rain and excessive rain—inevitably stress crop production, and weather index insurance is one possible financial tool to mitigate such agro-metrological losses. In this study, we investigated where two rainfall-related weather indices—anomaly-based index (AI) and humidity-based index (HI)—could be best used for three main crops (rice, wheat, and maize) in China's main agricultural zones. A county is defined as an “insurable county” if the correlation between a weather index and yield loss was significant. Among maize-cropping counties, both weather indices identified more insurable counties for deficit rain than for excessive rain (AI: 172 vs 63; HI: 182 vs 68); moreover, AI identified lower basis risk for deficit rain in most agricultural zones while HI for excessive rain. For rice, the number of AI-insurable counties was higher than the number of HI-insurable counties for deficit rain (274 vs 164), but lower for excessive rain (199 vs 272); basis risks calculated by two weather indices showed obvious difference only in Zone I. Finally, more wheat-insurable counties (AI: 196 vs 71; HI: 73 vs 59) and smaller basis risk indicate that both weather indices performed better for excessive rain in wheat-planting counties. In addition, most insurable counties showed independent yield loss, but did not necessarily result in effective risk pooling. This study is a primary evaluation of rainfall-related weather indices for the three main crops in China, which will be significantly helpful to the agricultural insurance market and governments' policy making.

Wind Erosion Climate Change in Northern China During 1981–2016

Feng Zhang, Jing'ai Wang, Xueyong Zou, Rui Mao, Daoyi Gong, Xingya Feng

2020, 11(4): 484-496. doi: 10.1007/s13753-020-00291-w

Abstract(96) PDF

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Wind erosion is largely controlled by climate conditions. In this study, we examined the influences of changes in wind speed, soil wetness, snow cover, and vegetation cover related to climate change on wind erosion in northern China during 1981–2016. We used the wind erosion force, defined as wind factor in the Revised Wind Erosion Equation Model, to describe the effect of wind speed on wind erosion. The results show that wind erosion force presented a long-term decreasing trend in the southern Northwest, northern Northwest, and eastern northern China during 1981–2016. In the Gobi Desert, the wind erosion force presented for 1981–1992 a decreasing trend, for 1992–2012 an increasing trend, and thereafter a weakly decreasing trend. In comparison to wind speed, soil wetness and snow cover had weaker influences on wind erosion in northern China, while vegetation cover played a significant role in the decrease of wind erosion in the eastern northern China during 1982–2015.

Lessons from the Mainland of China's Epidemic Experience in the First Phase about the Growth Rules of Infected and Recovered Cases of COVID-19 Worldwide

Chuanliang Han, Yimeng Liu, Jiting Tang, Yuyao Zhu, Carlo Jaeger, Saini Yang

2020, 11(4): 497-507. doi: 10.1007/s13753-020-00294-7

Abstract(65) PDF

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The first phase of the novel coronavirus disease (COVID-19) that emerged at the end of 2019 has been brought under control in the mainland of China in March, while it is still spreading globally. When the pandemic will end is a question of great concern. A logistic model that depicts the growth rules of infected and recovered cases in China's mainland may shed some light on this question. This model well explained the data by 13 April from 31 countries that have been experiencing serious COVID-2019 outbreaks (R²≥0.95). Based on this model, the semi-saturation period (SSP) of infected cases in those countries ranges from 3 March to 18 June. According to the linear relationship between the growth rules for infected and for recovered cases identified from the Chinese data, we predicted that the SSP of the recovered cases outside China ranges from 22 March to 8 July. More importantly, we found a strong positive correlation between the SSP of infected cases and the timing of a government's response. Finally, this model was also applied to four regions that went through other coronavirus or Ebola virus epidemics (R²≥0.95). There is a negative correlation between the death rate and the logistic growth rate. These findings provide strong evidence for the effectiveness of rapid epidemic control measures in various countries.

Linking a Storm Water Management Model to a Novel Two-Dimensional Model for Urban Pluvial Flood Modeling

Yuhan Yang, Leifeng Sun, Ruonan Li, Jie Yin, Dapeng Yu

2020, 11(4): 508-518. doi: 10.1007/s13753-020-00278-7

Abstract(72) PDF

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This article describes a new method of urban pluvial flood modeling by coupling the 1D storm water management model (SWMM) and the 2D flood inundation model (ECNU Flood-Urban). The SWMM modeling results (the overflow of the manholes) are used as the input boundary condition of the ECNU Flood-Urban model to simulate the rainfall–runoff processes in an urban environment. The analysis is applied to the central business district of East Nanjing Road in downtown Shanghai, considering 5-, 10-, 20-, 50-, and 100-year return period rainfall scenarios. The results show that node overflow, water depth, and inundation area increase proportionately with the growing return periods. Water depths are mostly predicted to be shallow and surface flows generally occur in the urban road network due to its low-lying nature. The simulation result of the coupled model proves to be reliable and suggests that urban surface water flooding could be accurately simulated by using this methodology. Adaptation measures (upgrading of the urban drainage system) can then be targeted at specific locations with significant overflow and flooding.

Supply–Demand Analysis of Urban Emergency Shelters Based on Spatiotemporal Population Estimation

Xiaodong Zhang, Jia Yu, Yun Chen, Jiahong Wen, Jiayan Chen, Zhan'e Yin

2020, 11(4): 519-537. doi: 10.1007/s13753-020-00284-9

Abstract(83) PDF

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Supply–demand analysis is an important part of the planning of urban emergency shelters. Using Pudong New Area, Shanghai, China as an example, this study estimated daytime and nighttime population of the study area based on fine-scale land use data, census data, statistical yearbook information, and Tencent user-density big data. An exponential function-based, probability density estimation method was used to analyze the spatial supply of and demand for shelters under an earthquake scenario. The results show that even if all potential available shelters are considered, they still cannot satisfy the demand of the existing population for evacuation and sheltering, especially in the northern region of Pudong, under both the daytime and the nighttime scenarios. The proposed method can reveal the spatiotemporal imbalance between shelter supply and demand. We also conducted a preliminary location selection analysis of shelters based on the supply–demand analysis results. The location selection results demonstrate the advantage of the proposed method. It can be applied to identify the areas where the supply of shelters is seriously inadequate, and provide effective decision support for the planning of urban emergency shelters.

Linkages Between Tropical Cyclones and Extreme Precipitation over China and the Role of ENSO

Licheng Wang, Zhengnan Yang, Xihui Gu, Jianfeng Li

2020, 11(4): 538-553. doi: 10.1007/s13753-020-00285-8

Abstract(66) PDF

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This research investigated the linkages between tropical cyclones (TCs) and extreme precipitation, and their associations with El Niño-Southern Oscillation (ENSO) over China. The contribution of TC-induced to total extreme precipitation events along the southeast coast of China was higher than 50%, and the values gradually decreased as TCs moved inland. However, the precipitation extremes (magnitude and frequency) related to TCs did not show statistically significant changes over the most recent 57 years. The impacts of TCs on precipitation extremes are evidently modulated by the ENSO phases. We found less extreme precipitation linked with TCs in southeastern China during El Niño phase, because of the fewer TC tracks over this region and less TC genesis in the western North Pacific (WNP). The small TC track density over southeastern China is due to the prevalent westerly steering flow and abnormal integrated vapor transport from northern to southern China during El Niño years. Additionally, warmer sea surface temperature, more vigorous westerlies, larger vorticity in 250 hPa, and higher divergence in 850 hPa in an El Niño phase jointly displaced the mean genesis of the WNP TCs eastward and this led to fewer TCs passing through southeastern China.