文章摘要
龙训建, 翁薛柔, 叶 琰, 张逸轩, 徐廷兵, 叶 勇.基于聚类分析的重庆市侵蚀性降雨特征研究Journal of Water Resources and Water Engineering[J].,2021,32(6):19-26
基于聚类分析的重庆市侵蚀性降雨特征研究
Characteristics of erosive rainfalls in Chongqing City based on cluster analysis
  
DOI:10.11705/j.issn.1672-643X.2021.06.03
中文关键词: 侵蚀性降雨  降雨侵蚀力  时空特征  聚类分析  重庆市
英文关键词: erosive rainfall  rainfall erosivity  spatiotemporal characteristics  cluster analysis  Chongqing City
基金项目:中央高校基本科研业务费专项资金项目(XDJK2020C070); 重庆市教育委员会科学技术研究项目(KJZD-K202100201)
Author NameAffiliation
LONG Xunjian1, WENG Xuerou1, YE Yan1, ZHANG Yixuan2, XU Tingbing3, YE Yong1 (1.西南大学 资源环境学院 重庆 400715 2.重庆市人工影响天气办公室重庆 400074 3.西南大学 后勤保障部 重庆 400715) 
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中文摘要:
      基于重庆市32个国家气象站点的2009-2018年逐分钟降雨观测数据,开展侵蚀性降雨的雨量、历时、雨强及降雨侵蚀力特征值分析,探讨研究区侵蚀性降雨时空分布特征及雨情特点。结果表明:研究区多年平均侵蚀性降雨量、历时、雨强及发生次数分别占多年平均降雨量、历时、雨强及发生次数的75%、44%、55%和18%;侵蚀性降雨年内主要集中于5-9月,雨量、历时的年内分布呈双峰变化,雨强、发生次数和降雨侵蚀力年内变化则呈单峰特征;降雨侵蚀力年际变化幅度为-22%~27%。侵蚀性降雨各特征值在空间上表现出明显的区域差异性,主成分聚类分析方法将研究区划分为轻度、中度和重度3类降雨侵蚀区;研究区雨情基于K均值聚类分为3类,类Ⅰ为区域主要雨型,类Ⅲ为降雨侵蚀力最剧烈的雨型,类Ⅱ的雨量、雨强、历时以及降雨侵蚀力则介于类Ⅰ、类Ⅲ之间。
英文摘要:
      Based on the minute-per-minute rainfall observation data of 32 national meteorological stations in Chongqing City from 2009 to 2018, the characteristics of amount, duration, intensity and erosivity of erosive rainfalls were analyzed to explore the spatiotemporal distribution characteristics and different patterns of erosive rainfalls in the study area. The results show that the amount, duration, intensity and occurrence frequency of the average annual erosive rainfall accounted for 75%, 44%, 55% and 18% of those of the average annual rainfall, respectively. Erosive rainfalls were mainly concentrated in May to September, of which the amount and duration showed a bimodal annual variation; whereas the intensity, occurrence frequency and rainfall erosivity presented a unimodal annual variation. The annual rainfall erosivity ranged from -22% to 27%, with a unimodal distribution. The various characteristic indices of erosive rainfalls showed obvious regional differences at different time scales. Then, principal component cluster analysis (PCA) was used to divide the study area into three types: light, moderate and severe rainfall erosion areas, and the rainfall patterns in the study area were divided into three categories based on K-means clustering, in which Category I was the dominant rainfall type in the region, Category Ⅲ was the rainfall type with the most severe erosivity, and the rainfall amount, intensity, duration and erosivity of Category II were between those of Category I and Category III.
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