Construction of evaluation model of rainstorm and flood disaster in Xinjiang and its temporal and spatial distribution characteristics

Yun Wang, Xi Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Rainstorm and flood disasters caused by short-term heavy precipitation often lead to huge losses in the agriculture and animal husbandry in Xinjiang. In this study, the five disaster elements of rainstorms and floods in Xinjiang are used to construct the disaster loss index using the ratio method and the dimensionless linear combination method. The probability distribution function is used to classify the disaster loss index of counties and cities into four grades, mild (grade 1), moderate (grade 2), severe (grade 3), and extremely severe (grade 4). Further, the spatial and temporal distribution of disasters and their causes are analyzed. Results show that the five disaster elements exhibit significant geographical variability, with grade 4 disasters concentrated in the Yili River Valley and Kashgar Prefecture. There were frequent rainstorm disasters between April and August, with those in July being the most serious. The interannual variation of fatalities, collapsed houses, collapsed livestock shelters, livestock deaths, and the ratio between affected area and sown area all showed a significant linear decreasing trend between 1986 and 2019. When there was not much change in the hazard of short duration heavy rainfall, the enrichment projects and emergency relief systems implemented by the Xinjiang government have played an important role in disaster prevention and mitigation, ensuring a year-by-year disaster loss reduction.

Original languageEnglish
Title of host publicationInternational Conference on Applied Statistics, Computational Mathematics, and Software Engineering, ASCMSE 2022
EditorsSteven Guan, Haibin Zhu
PublisherSPIE
ISBN (Electronic)9781510657625
DOIs
Publication statusPublished - 2022
Event2022 International Conference on Applied Statistics, Computational Mathematics, and Software Engineering, ASCMSE 2022 - Qingdao, China
Duration: 20 May 202222 May 2022

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12345
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference2022 International Conference on Applied Statistics, Computational Mathematics, and Software Engineering, ASCMSE 2022
Country/TerritoryChina
CityQingdao
Period20/05/2222/05/22

Keywords

  • climatic cause
  • disaster exponent
  • grade division
  • rainstorm and flood
  • temporal and spatial distribution

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