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All issues Volume 165 (2020) E3S Web Conf., 165 (2020) 03049 References
Open Access
Issue
E3S Web Conf.
Volume 165, 2020
2020 2nd International Conference on Civil Architecture and Energy Science (CAES 2020)
Article Number 03049
Number of page(s) 6
Section Geology, Mapping, and Remote Sensing
DOI https://doi.org/10.1051/e3sconf/202016503049
Published online 01 May 2020
  1. G. Sun, C. Pan, J. Li, Yang, Y. Spatial distribution of the extreme hydrological events in Xinjiang, north-west of China. Natural Hazards, 67,483-495 (2013) [Google Scholar]
  2. X. Li, J. Du, Long, H. A Comparative Study of Chinese and Foreign Green Development from the Perspective of Mapping Knowledge Domains. Sustainability, 10,4357 (2018) [Google Scholar]
  3. X. Li, J. Du, H. Long, Sun, G. Characteristics and risk analysis of hydrological disaster events from 1949 to 2015 in Urumqi, China. Theoretical and Applied Climatology, 137, 745-754 (2019) [Google Scholar]
  4. National Bureau of Statistics of China. National Data. http://data.stats.gov.cn/easyquery.htm?cn=C01 (accessed on January 12, 2019) [Google Scholar]
  5. X. Li, G. Sun, H. Long, X. Zheng, L. Wang, Wang H. Research Progress of Urban Hydrological Disaster Risk Assessment From 1988 to 2017. Journal of Sichuan University of Science and Engineering (Natural Science Edition), 31,74-82 (2018). (in Chinese) [Google Scholar]
  6. X. Li, J. Du, Long, H. Theoretical framework and formation mechanism of the green development system model in China. Environmental Development, 32, 100465 (2019) [Google Scholar]
  7. L.D. Jenkins, S.J. Dreyer, H.J. Polis, E. Beaver, A.A. Kowalski, H.L. Linder, Wiesebron, L.E. Human dimensions of tidal energy: A review of theories and frameworks. Renewable and Sustainable Energy Reviews, 97,323-337 (2018) [CrossRef] [Google Scholar]
  8. E. Tempero, Ralph, P. A framework for defining coupling metrics. Science of Computer Programming, 166, 214-230 (2018) [Google Scholar]
  9. H. Baojuan, W. Yetang, S. Weijun, Xiaoyan, W. The unique “Regional East Gale with Blowing Snow” natural disaster in Jeminay County, Xinjiang Uygur Autonomous Region, China. Natural Hazards, 93,1105-1108 (2018) [Google Scholar]
  10. S. Wu, T. Pan, Yang Q. Risk pattern and Prevention of Major Meteorological and Hydrological disasters in China. Science publishing house, Beijing (2014) (in Chinese) [Google Scholar]
  11. J. Parker, A. Donnellan, M. Glasscoe, G. Fox, J. Wang, M. Pierce, Ma, Y. Advantages to Geoscience and Disaster Response from QuakeSim Implementation of Interferometric Radar Maps in a GIS Database System. Pure and Applied Geophysics, 172, 2295-2304 (2014) [Google Scholar]
  12. X. Li, Z. Sun, G. Sun, W. Zhao, Wang, T. Influence of Hail Disaster on Fruit Trees in Aksu Prefecture. Journal of Agricultural Catastrophology, 6,32-35 (2016) (in Chinese) [Google Scholar]
  13. Z. Sun, X. Li, G. Sun, T. Wang, Zhao, W. Risk assessment of main hydrological disaster of fruit trees in Aksu Prefecture of Xinjiang. Agricultural Science Journal of Yanbian University, 38,242-247(2016) (in Chinese) [Google Scholar]
  14. M. Wulamu, Moming A. The city disaster characteristics and disaster reduction countermeasure in Urumqi. Journal of Geological Hazards and Environment Preservation, 12,12-16 (2001) (in Chinese) [Google Scholar]
  15. J. Bing, Dou, X. Study on the Critical Rainfall Distribution and Prevention and Control Regionalization of Mountain Flood Disasters in Urumqi. Research of Soil and Water Conservation, 12,252-255 (2005) (in Chinese) [Google Scholar]
  16. X. Xi, Zhao, J. Study on Climate Change in Urumqi and Relationship with EI Nino/La Nina Events in Recent 49 Years. Arid Zone Research, 29,826-831 (2012) (in Chinese) [Google Scholar]
  17. Y. Zheng, Gong H. Climatic Characteristics of Cold Wave in Urumqi. Desert and Oasis Meteorology, 9,56-61(61) (in Chinese) [Google Scholar]
  18. Y. Zhang, G. Fan, Y. He, Cao, L. Risk assessment of typhoon disaster for the Yangtze River Delta of China. Geomatics, Natural Hazards and Risk, 8, 1580-1591 (2017) [Google Scholar]
  19. J. Gao, Sang, Y. Identification and estimation of landslide-debris flow disaster risk in primary and middle school campuses in a mountainous area of Southwest China. International Journal of Disaster Risk Reduction, 25, 60-71 (2017) [Google Scholar]
  20. G.C. Ohlmacher, Davis, J.C. Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Engineering Geology, 69, 331-343 (2003) [Google Scholar]
  21. B. Bajracharya, A.B. Shrestha, Rajbhandari, L. Glacial Lake Outburst Floods in the Sagarmatha Region. Mountain Research and Development, 27,336-344 (2007) [Google Scholar]
  22. C. Samela, R. Albano, A. Sole, Manfreda, S. A GIS tool for cost-effective delineation of flood-prone areas. Computers, Environment and Urban Systems, 70,43-52 (2018) [Google Scholar]

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