Disaster assessment for the “Belt and Road” region based on SDG landmarks

ABSTRACT In this study, based on the EM-DAT (The Emergency Events Database) database, disaster assessment for the “Belt and Road” region was carried out in relation to the indicator of the Sustainable Development Goals (SDGs) agenda launched in 2015. A new method for diagnosing trends in the indicators based on the Theil-Sen median method is proposed. In addition, using the data available in the EM-DAT, an overview of disaster records is used to quantify disasters for a total of 73 countries. The disaster trends for the period 2015‒2019 were found to demonstrate the following. (1) As a result of geological and climate conditions, Asia and Africa are high-risk disaster areas and disasters have caused considerable economic losses and affected the populations in developing and underdeveloped countries in these regions. (2) The clear positive value of found for China reflects the country’s encouraging achievements in disaster prevention and mitigation. (3) The value of was observed to be increasing in South Asia, northwest Africa and South Africa, with the increase in India and Mauritania being the most serious. The new method proposed in this paper allows the real trend in the indicator in various countries to be derived and provides critical intelligence support for international disaster risk reduction plans and sustainable development goals.

[1]  M. Kervyn,et al.  Questioning knowledge foundation: What is the best way to integrate knowledge to achieve substantial disaster risk reduction? , 2020 .

[2]  G. Zuccaro,et al.  Future research and innovation priorities in the field of natural hazards, disaster risk reduction, disaster risk management and climate change adaptation: a shared vision from the ESPREssO project , 2020 .

[3]  Roger C. Shouse,et al.  Disaster resilience through big data: Way to environmental sustainability , 2020 .

[4]  Ming Wang,et al.  Driving factors of natural disasters in belt and road countries , 2020 .

[5]  A. Almeida,et al.  Multidimensional flood risk management under climate changes: Bibliometric analysis, trends and strategic guidelines for decision-making in urban dynamics , 2020 .

[6]  I. Rana.  Disaster and climate change resilience: A bibliometric analysis , 2020 .

[7]  Sachin Kumar Gupta,et al.  Multi-hazard disaster studies: Monitoring, detection, recovery, and management, based on emerging technologies and optimal techniques , 2020 .

[8]  Anwar Khan,et al.  The dilemma of natural disasters: Impact on economy, fiscal position, and foreign direct investment alongside Belt and Road Initiative countries. , 2020, The Science of the total environment.

[9]  Qiang Zhang,et al.  Drought risk assessment in China: Evaluation framework and influencing factors , 2020 .

[10]  Qingchen Chao,et al.  An overview of assessment methods and analysis for climate change risk in China , 2020, Physics and Chemistry of the Earth, Parts A/B/C.

[11]  Jiang-bo Gao,et al.  Hazards of extreme events in China under different global warming targets , 2020 .

[12]  G. Jia.  The role of big Earth data in understanding climate change , 2020 .

[13]  Akiko Iizuka.  Developing capacity for disaster risk reduction: Lessons learned from a case of Sri Lanka , 2020 .

[14]  S. Vicente‐Serrano,et al.  A review of environmental droughts: Increased risk under global warming? , 2020 .

[15]  Jingyong Zhang,et al.  Dataset of high temperature extremes over the major land areas of the Belt and Road for 1979-2018 , 2020, Big Earth Data.

[16]  Linhao Zhong,et al.  Datasets of meteorological drought events and risks for the developing countries in Eurasia , 2020 .

[17]  Kai-heng Hu,et al.  Outburst floods in China: A review , 2019, Earth-Science Reviews.

[18]  Adam Vaughan.  Global warming will drive extreme wet weather in summer , 2019, New Scientist.

[19]  E. Alam.  Importance of long-term earthquake, tsunami and tropical cyclone data for disaster risk reduction in Bangladesh , 2019, Progress in Disaster Science.

[20]  Q. Tang,et al.  Droughts in East Africa: Causes, impacts and resilience , 2019, Earth-Science Reviews.

[21]  R. Djalante.  Key assessments from the IPCC special report on global warming of 1.5 °C and the implications for the Sendai framework for disaster risk reduction , 2019, Progress in Disaster Science.

[22]  F. Imamura,et al.  Recent occurrences of serious tsunami damage and the future challenges of tsunami disaster risk reduction , 2019, Progress in Disaster Science.

[23]  O. P. Mishra,et al.  Disaster Risk Reduction Including Climate Change Adaptation Over South Asia: Challenges and Ways Forward , 2018, International Journal of Disaster Risk Science.

[24]  F. Witlox,et al.  Agricultural land conversion: Reviewing drought impacts and coping strategies , 2018, International Journal of Disaster Risk Reduction.

[25]  A. Pasuto,et al.  An international program on Silk Road Disaster Risk Reduction–a Belt and Road initiative (2016–2020) , 2018, Journal of Mountain Science.

[26]  Yong Chen,et al.  Seismological challenges in earthquake hazard reductions: reflections on the 2008 Wenchuan earthquake. , 2018, Science bulletin.

[27]  Nicolas Faivre,et al.  Translating the Sendai Framework into action: The EU approach to ecosystem-based disaster risk reduction , 2017, International Journal of Disaster Risk Reduction.

[28]  Garth le Pere,et al.  China’s Belt and Road Initiative , 2017 .

[29]  S. Egawa,et al.  Integrated health education in disaster risk reduction: Lesson learned from disease outbreak following natural disasters in Indonesia , 2017, International Journal of Disaster Risk Reduction.

[30]  T. Robinson,et al.  Sustainable Development Goals , 2016 .

[31]  Zhongliang Wu,et al.  Multi-scale seismic hazard and risk in the China mainland with implication for the preparedness, mitigation, and management of earthquake disasters: An overview , 2013 .

[32]  David Birkes,et al.  Alternative Methods of Regression: Birkes/Alternative , 1993 .

[33]  H. B. Mann.  Nonparametric Tests Against Trend , 1945 .