HUANG Huijie1, PENG Chao2, XU Gang1, LI Guimei1, QIU Yuchao1
（1.School of Geographical Sciences,Southwest China University,Chongqing 400715,China;
2. Beibei Meteorological Bureau, Chongqing 400700, China）
Abstract: The regional rainstorm is of the worst natural disasters in Chongqing, and a systematical study on it is much needed for disaster prevention and mitigation. The risks and spatial-temporal distributions of regional rainstorm in Chongqing were systematically studied by using probability statistics, Matlab wavelet analysis and ArcGIS spatial analysis methods on daily precipitation data documented from 1962 to 2016 at 34 national basic weather stations in Chongqing. The assessing results based on the 4 indexes of average rainfall volume, 24h-rainfall extreme value, coverage and duration of the regional rainstorm indicated that, among the recorded 176 regional rainstorms, mild risk rainstorms accounted for 47.16% (83 times), moderate risk rainstorms accounted for 27.84% (49 times), severe risk rainstorms accounted for 19.89% (35 times) and extremely severe risk rainstorms accounted for 5.11% (9 times). In terms of the temporal distribution, the regional heavy rainstorms occur frequently in June and July and relatively less in other months, the highest average regional rainstorm risk index occurs in July; two variation periods of 7-years and 28-years could be identified, and the number and severity of regional rainstorm in different periods were quite similar but the grade composition of regional rainstorm were different significantly. In terms of the spatial distribution, the occurrence of regional rainstorms in center Chongqing were different from around areas, Kaizhou (northeastern Chongqing) and Rongchang (western Chongqing) were centers of regional rainstorm; furthermore, the regional rainstorm center changed in different seasons, it often occurred in the western Chongqing in spring, in the northeastern and western Chongqing in summer, and in the northeastern Chongqing in autumn.
Key words: regional rainstorm; degree of risk; quantitative analysis; temporal and spatial distribution; Chongqing
EARTH AND ENVIRONMENT Vol.46, No.3, Tot No.323, 2018, Page 237-244