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Advances in Climate Change Research 2020年第3期11卷 239-251页

作者： ZHU Yu-Yao yang saini State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing100875China Key Laboratory of Environmental Change and Natural Disaster Ministry of EducationBeijing100875China Faculty of Geographical Science Academy of Disaster Reduction and Emergency ManagementBeijing Normal UniversityBeijing100875China

A model-by-model analysis for historical simulations was necessary for identifying reasonably performing models in the updated Coupled Model Intercomparison Project(CMIP6)over the Tibetan *** determine whether the capacity of the CMIP6 models in simulating temperature and precipitation over the Plateau has been enhanced,we compared the outputs of 23 CMIP6 models with an observational dataset(CN05.1)for the period 1961–*** results suggest the systematic model biases(cold bias and wet bias)in the Tibetan Plateau still exist in *** models in CMIP6 realistically simulated the surface temperature and spatial distribution of precipitation,with a pattern correlation exceeding *** bias in the mean surface temperature of the multi-model ensemble(MME)simulation was 1.08℃ lower than the observational data,which had been decreased compared with the cold bias of CMIP5(1.52℃).At the seasonal scale,most models exhibited a warm temperature bias in summer and a cold bias in *** CMIP6 MME displayed a higher reproducibility of the precipitation amplitude over dry regions compared with CMIP5 and a lower ability over wet regions.

关键词： CMIP6 GCMs Temperature Precipitation Tibetan Plateau Climate change

Resilience-Driven Road Network Retrofit Optimization Subject to Tropical Cyclones Induced Roadside Tree Blowdown

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International Journal of Disaster Risk Science 2021年第1期12卷 72-89页

作者： Fuyu Hu saini yang Russell G.Thompson Theoretical Division Los Alamos National LaboratoryLos AlamosNM 87545USA Key Laboratory of Environmental Change and Natural Disaster Ministry of EducationBeijing Normal UniversityBeijing 100875China State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100875China Academy of Disaster Reduction and Emergency Management Ministry of Civil Affairs&Ministry of EducationBeijing Normal UniversityBeijing 100875China Faculty of Geographical Science Beijing Normal UniversityBeijing 100875China School of Engineering The University of MelbourneMelbourne 3052Australia

This article focuses on decision making for retrofit investment of road networks in order to alleviate severe consequences of roadside tree blowdown during tropical *** consequences include both the physical damage associated with roadside trees and the functional degradation associated with road networks.A trilevel,two-stage,and multiobjective stochastic mathematical model was developed to dispatch limited resources to retrofit the roadside trees of a road *** the model,a new metric was designed to evaluate the performance of a road network;resilience was considered from robustness and recovery efficiency of a road *** proposed model is at least a nondeterministic polynomialtime hardness(NP-hard)problem,which is unlikely to be solved by a polynomial time ***-optimal solutions for this problem can be obtained by a proposed trilevel *** random forest method was employed to transform the trilevel algorithm into a singlelevel algorithm in order to decrease the computation *** tree retrofit of a provincial highway network on Hainan Island,China was selected as a case area because it suffers severely from tropical cyclones every year,where there is an urgency to upgrade roadside trees against tropical *** found that roadside tree retrofit investment significantly alleviates the expected economic losses of roadside tree blowdown,at the same time that it promotes robustness and expected recovery efficiency of the road network.

关键词： Hainan Island Nondominated sorting genetic algorithm II(NSGA II) Random forest method Road network resilience Roadside tree retrofit Tropical cyclones

Incorporating Triggering and Environmental Factors in the Analysis of Earthquake-Induced Landslide Hazards

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International Journal of Disaster Risk Science 2014年第2期5卷 125-135页

作者： Ming Wang Min Liu saini yang Peijun Shi State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100875China Academy of Disaster Reduction and Emergency Management Beijing Normal UniversityBeijing 100875China

Pingwu County of Sichuan Province was severely hit by the 12 May 2008 Wenchuan Earthquake and experienced widely distributed earthquake-induced *** proposed an integrated method that incorporates landslide triggering factors embedded in the Newmark displacement computation and other environmental factors,expressed as lithology,land-use type,vegetation cover(Normalized Difference Vegetation Index,NDVI),elevation,and profile and plan curvature,in the analysis of earthquake-induced landslide hazards in the study *** earthquake-induced landslide inventory of this area was obtained by visual interpretation of two highresolution SPOT-5 images before and after the *** used GIS tools to generate an equal number of landslide and non-landslide cell samples in a 30-m grid map,and assigned triggering and environmental variables to each cell.A logistic regression model was built to investigate the occurrence of earthquake-induced *** results show that Newmark displacement(in which triggering factors are embedded)and lithology(as an environmental factor)were the two dominant variables controlling landslide *** environmental factors,including NDVI,land-use type,and elevation,also significantly affected landslide ***81.2%correctness was achieved in the regression *** results confirm the predictive power of our method,which integrates both triggering and environmental factors in modeling earthquake-induced landslides.

关键词： earthquake Earthquake curvature

Systemic Risks: A Homomorphic Approach on the Basis of Complexity Science

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International Journal of Disaster Risk Science 2018年第3期9卷 292-305页

作者： Klaus Lucas Ortwin Renn Carlo Jaeger saini yang Institute of Technical Thermodynamics Aachen University Institute for Advanced Sustainability Studies (IASS) Economic and Social Science Department University of Stuttgart Academy of Disaster Reduction and Emergency Management School of Geography Beijing Normal University Global Climate Forum Key Laboratory of Environmental Change and Natural Disasters Ministry of Education Beijing Normal University

Although the notion of systemic risk gained prominence with respect to financial systems, it is a generic term that refers to risks of increasing importance in many domains—risks that cannot be tackled by conventional techniques of risk management and governance. We build on a domain-overarching definition of systemic risks by highlighting crucial properties that distinguish them from conventional risks and plain disasters. References to typical examples from various domains are included. Common features of systemic risks in different domains—such as the role of agents and emergence phenomena, tipping and cascading, parameters indicating instability, and historicity—turn out to be more than noncommittal empirical observations. Rather these features can be related to fundamental theory for relatively simple and well-understood systems in physics and chemistry. A crucial mechanism is the breakdown of macroscopic patterns of whole systems due to feedback reinforcing actions of agents on the microlevel, where the reinforcement is triggered by boundary conditions moving beyond critical tipping *** the whole article, emphasis is placed on the role of complexity science as a basis for unifying the phenomena of systemic risks in widely different domains.

关键词： Complexity science Integrated risk governance Multiagent modeling Systemic risks

Typhoon Risk Perception: A Case Study of Typhoon Lekima in China

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International Journal of Disaster Risk Science 2022年第2期13卷 261-274页

作者： Jiting Tang saini yang Yimeng Liu Kezhen Yao Guofu Wang Key Laboratory of Environmental Change and Natural Disaster Ministry of EducationBeijing Normal UniversityBeijing 100875China State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100875China School of National Safety and Emergency Management Beijing Normal UniversityBeijing 100875China Academy of Disaster Reduction and Emergency Management Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China National Climate Center Beijing 100081China

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 ***, 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.

关键词： China Crowd sensitivity Regional disaster system theory Risk perception Social media Typhoon Lekima

Variability in Regional Ecological Vulnerability: A Case Study of Sichuan Province, China

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International Journal of Disaster Risk Science 2020年第6期11卷 696-708页

作者： Yimeng Liu saini yang Chuanliang Han Wei Ni Yuyao Zhu Key Laboratory of Environmental Change and Natural Disaster Ministry of EducationBeijing Normal UniversityBeijing 100875China State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100875China Academy of Disaster Reduction and Emergency Management Ministry of Emergency Management and Ministry of EducationFaculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research Beijing Normal UniversityBeijing 100875China

Rapid urbanization and natural hazards are posing threats to local ecological processes and ecosystem services *** land use,socioeconomic,and natural hazards data,we conducted an assessment of the ecological vulnerability of prefectures in Sichuan Province for the years 2005,2010,and 2015 to capture variations in its capacity to modulate in response to disturbances and to explore potential factors driving these *** selected five landscape metrics and two topological indicators for the proposed ecological vulnerability index(EVI),and constructed the EVI using a principal component analysis-based entropy method.A series of correlation analyses were subsequently performed to identify the factors driving variations in ecological *** results show that:(1)for each of the study years,prefectures with high ecological vulnerability were located mainly in southern and eastern Sichuan,whereas prefectures in central and western Sichuan were of relatively low ecological vulnerability;(2)Sichuan’s ecological vulnerability increased significantly(p=0.011)during2005–2010;(3)anthropogenic activities were the main factors driving variations in ecological *** findings provide a scientific basis for implementing ecological protection and restoration in Sichuan as well as guidelines for achieving integrated disaster risk reduction.

关键词： Anthropogenic activities Ecological vulnerability Natural hazards PCA-based entropy method Rank correlation

Modeling the Adverse Impact of Rainstorms on a Regional Transport Network

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International Journal of Disaster Risk Science 2016年第1期7卷 77-87页

作者： saini yang Guofan Yin Xianwu Shi Hao Liu Ying Zou State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Academy of Disaster Reduction and Emergency Management Beijing Normal University National Marine Hazard Mitigation Service Beijing Transportation Information Center Beijing Municipal Commission of Transport

Cities are centers of socioeconomic activities,and transport networks carry cargoes and passengers from one city to another. However, transport networks are influenced by meteorological hazards, such as rainstorms,hurricanes, and fog. Adverse weather impacts can easily spread over a network. Existing models evaluating such impacts usually neglect the transdisciplinary nature of approaches for dealing with this problem. In this article, a mesoscopic mathematical model is proposed to quantitatively assess the adverse impact of rainstorms on a regional transport network in northern China by measuring the reduction in traffic volume. The model considers four factors: direct and secondary impacts of rainstorms, interdependency between network components, and recovery abilities of cities. We selected the Beijing-Tianjin-Hebei region as the case study area to verify our ***, precipitation, and traffic volume data in this area were used for model calibration and *** case study highlights the potential of the proposed model for rapid disaster loss assessment and risk reduction planning.

关键词： China Disaster loss assessment Mathematical modeling Rainstorm hazards Recovery Transport networks

Green Development and Integrated Risk Governance

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International Journal of Disaster Risk Science 2017年第2期8卷 231-233页

作者： Peijun Shi saini yang Qian Ye Ying Li Guoyi Han State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Academy of Disaster Reduction and Emergency Management Faculty of Geographical ScienceBeijing Normal University Stockholm Environment Institute

The‘‘International Symposium on Integrated Governance of Large-scale Disaster and Economic Risks’’was held in Qianhai,Shenzhen,China on 13–14 May *** Academy of Disaster Reduction and Emergency Management of Mini... 详细信息

关键词： over Green Development and Integrated Risk Governance

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

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International Journal of Disaster Risk Science 2020年第4期11卷 497-507页

作者： Chuanliang Han Yimeng Liu Jiting Tang Yuyao Zhu Carlo Jaeger saini yang State Key Laboratory of Cognitive Neuroscience and Learning and IDG/Mc Govern Institute for Brain Research Beijing Normal UniversityBeijing 100875China Key Laboratory of Environmental Change and Natural Disaster Ministry of EducationBeijing Normal UniversityBeijing 100875China State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100875China Academy of Disaster Reduction and Emergency Management Ministry of Emergency Management and Ministry of EducationFaculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Global Climate Forum 10178 BerlinGermany

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 *** 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 *** 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 *** 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 *** importantly,we found a strong positive correlation between the SSP of infected cases and the timing of a government’s ***,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 *** findings provide strong evidence for the effectiveness of rapid epidemic control measures in various countries.

关键词： China COVID-2019 Epidemiological properties Logistic model Pandemic

Fourteen Actions and Six Proposals for Science and Technology-Based Disaster Risk Reduction in Asia Second Asian Science and Technology Conference for Disaster Risk Reduction:SciencePolicy Dialogue for Implementation of the Sendai Framework,April 2018

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International Journal of Disaster Risk Science 2018年第2期9卷 275-279页

作者： Peijun Shi Rajib Shaw Ali Ardalan Emily Ying yang Chan Jamilur Reza Choudhury Peng Cui Bojie Fu Guoyi Han Qunli Han Takako Izumi Fumiko Kasuga Antonia Yulo Loyzaga Joy Jacqueline PereiraShirish Kumar Ravan David Sanderson Vinod Kumar Sharma Frank Thomalla Sugeng Triutomo Siquan yang Qian Ye Ming Wang Yaqiao Wu Renhe Zhang Wenjian Zhang Ying Li saini yang State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Academy of Disaster Reduction and Emergency Management Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Graduate School of Media and Governance Keio UniversityShonan Fujisawa Campus(SFC)FujisawaKanagawa 252-0882Japan Department of Disaster and Emergency Health Tehran University of Medical SciencesTehranIran Faculty of Medicine The Chinese University of Hong KongHong KongChina University of Asia Pacific DhakaBangladesh The Institute of Mountain Hazards and Environment(IMHE) Chinese Academy of SciencesChengduChina Faculty of Geographical Science Beijing Normal UniversityBeijingChina Stockholm Environment Institute StockholmSweden Integrated Research on Disaster Risk BeijingChina International Research Institute of Disaster Science(IRIDeS) Tohoku UniversitySendaiJapan Future Earth TokyoJapan Manila Observatory Quezon CityPhilippines Southeast Asia Disaster Prevention Research Initiative(SEADPRI-UKM) Universiti Kebangsaan MalaysiaBangiMalaysia United Nations Office for Outer Space Affairs(UNOOSA) ViennaAustria The University of New South Wales Sydney SydneyAustralia Disaster Management/Consultant at Indian Institute of Public Administration New DelhiIndia Stockholm Environment Institute BangkokThailand Disaster Risk Reduction Foundation Daerah Khusus IbukotaIndonesia National Disaster Reduction Center of China Ministry of Emergency ManagementBeijingChina Integrated Risk Governance Program Academy of Disaster Reduction and Emergency ManagementFaculty of Geographical ScienceBeijing Normal UniversityBeijingChina Fudan University ShanghaiChina World Meteorological Organization GenevaSwitzerland

1 Introduction The Sendai Framework for Disaster Risk Reduction 2015–2030 shifts the focus from managing disasters to reducing *** a shift requires a better understanding of risk in all its dimensions of environment,... 详细信息

关键词： disaster Actions Reduction governance dimensions managing vulnerability technological innovative urgent