TY - GEN
T1 - Construction of evaluation model of rainstorm and flood disaster in Xinjiang and its temporal and spatial distribution characteristics
AU - Wang, Yun
AU - Wang, Xi
N1 - Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - climatic cause
KW - disaster exponent
KW - grade division
KW - rainstorm and flood
KW - temporal and spatial distribution
UR - http://www.scopus.com/inward/record.url?scp=85140057941&partnerID=8YFLogxK
U2 - 10.1117/12.2648829
DO - 10.1117/12.2648829
M3 - Conference contribution
AN - SCOPUS:85140057941
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - International Conference on Applied Statistics, Computational Mathematics, and Software Engineering, ASCMSE 2022
A2 - Guan, Steven
A2 - Zhu, Haibin
PB - SPIE
T2 - 2022 International Conference on Applied Statistics, Computational Mathematics, and Software Engineering, ASCMSE 2022
Y2 - 20 May 2022 through 22 May 2022
ER -