地球信息科学学报 ›› 2019, Vol. 21 ›› Issue (10): 1550-1564.doi: 10.12082/dqxxkx.2019.180442

• 地理空间分析综合应用 • 上一篇    下一篇

重庆市山洪灾害时空格局及影响因素研究

熊俊楠1,2,李进1,朱吉龙1,程维明2,*(),郭良3,4,王楠2,张晓蕾3,4   

  1. 1. 西南石油大学土木工程与建筑学院,成都 610500
    2. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100101
    3. 中国水利水电科学研究院,北京 100038
    4. 水利部防洪抗旱减灾工程技术研究中心,北京 100038
  • 收稿日期:2018-09-06 修回日期:2019-05-20 出版日期:2019-10-25 发布日期:2019-10-29
  • 通讯作者: 程维明 E-mail:chengwm@lreis.ac.cn
  • 作者简介:熊俊楠(1981-),男,四川南充人,副教授,主要从事遥感地理信息系统理论与灾害风险分析方面的研究。E-mail: neu_xjn@163.com
  • 基金资助:
    中国科学院战略性先导科技专项(XDA20030302);水科院全国山洪灾害调查评价项目(SHZH-IWHR-57);中国地质调查项目(DD20190637);数字福建自然灾害监测大数据研究所开放课题(NDMBD2018003);西南石油大学科技创新团队项目“测绘遥感”(2017CXTD09)

Spatial-temporal Distribution and the Influencing Factors of Mountain Torrent Disasters in Chongqing

XIONG Junnan1,2,LI Jin1,ZHU Jilong1,CHENG Weiming2,*(),GUO Liang3,4,WANG Nan2,ZHANG Xiaolei3,4   

  1. 1. School of Civil Engineering and Architecture, SWPU, Chengdu 610500, China
    2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic and Natural Resources Research, Chinese Academy Sciences, Beijing 100101, China
    3. China Institute of Water Resources and Hydropower Research, Beijing 100038, China
    4. Research Center on Flood & Drought Disaster Reduction of the Ministry of Water Resources, Beijing 100038, China;
  • Received:2018-09-06 Revised:2019-05-20 Online:2019-10-25 Published:2019-10-29
  • Contact: CHENG Weiming E-mail:chengwm@lreis.ac.cn
  • Supported by:
    Supported by the Strategic Priority Research Program of Chinese Academy of Sciences(XDA20030302);National Mountain Flood Disaster Survey and Evaluation Project of Chinese Academy of Water Sciences(SHZH-IWHR-57);China Geological Survey Project(DD20190637);Open Topic of Digital Fujian Institute of Large Data for Natural Disaster Monitoring(NDMBD2018003);Scie.pngic and Technological Innovation Team Project of Southwest Petroleum University(2017CXTD09)

摘要:

山洪灾害时空分布规律及其影响因素研究,是山洪灾害研究领域中重点关注的问题。本文利用重庆市1950-2015年历史山洪灾害数据,采用平均中心、标准差椭圆、核密度分析和M-K突变检测等方法分析了重庆市历史山洪灾害时空分布规律,并在此基础上分析了山洪与各影响因素的相关性。结果表明:① 1950-2015年重庆市历史山洪灾害发生频次总体呈先稳定后上升的趋势,山洪灾害主要集中在5-9月发生,山洪灾害发生频次按年代际整体上呈指数增长趋势;② 重庆市山洪灾害发生具有明显的集聚性,相邻县域山洪发生频次较为相近,其中九龙坡区、南岸区、北碚区、璧山区山洪灾害密度均超过50次/1000 km 2,属于山洪灾害高发区域;③ 山洪灾害整体呈“西南-东北”分散,“西北-东南”聚集的空间分布格局。2010年前,山洪重心主要集中在涪陵区一带;2010年后山洪灾害分布方向向西北倾斜,重心移至忠县,聚集程度降低,山洪发生随机性变强;④ 2002年是重庆市山洪灾害突变的年份,突变以增多为主,主要集中在铜梁区、璧山区、九龙坡区、巴南区、彭水苗族土家族自治县和开县;⑤ 山洪影响因素探究表明高程和河网密度与山洪灾害密度呈正相关关系,而植被覆盖度与山洪灾害密度呈负相关关系,短历时的强降雨对山洪的发生有激发作用。研究结果对重庆市山洪防灾减灾具有重要意义。

关键词: 重庆市, 山洪灾害, 时空分布, 标准差椭圆, 影响因素, 防洪减灾

Abstract:

The spatiotemporal distribution of mountain torrents and its influencing factors are the key issues for disaster research. Based on the historical torrent disaster data of Chongqing from 1950 to 2015, the spatiotemporal distribution of torrential disasters in Chongqing was analyzed by mean center, standard deviation ellipse, kernel density estimation, and M-K mutation detection. Subsequently, the correlation between mountain torrents and various influencing factors were qua.pngied. Results show that: (1) From 1950 to 2015, the occurrence frequency of the historic mountain torrents in Chongqing presented a trend of stabilization at first and then increase. Mountain torrents mainly occurred from May to September. The occurrence frequency of mountain torrents presented an exponential growth trend on the whole according to the interdecadal trend. (2) The occurrence of mountain torrents in Chongqing had an obvious agglomeration, and the frequency of mountain torrents in adjacent counties was similar. The density of mountain torrents in Jiulongpo, Nanan, Beibei, and Bishan was more than 50 times per 1000 km 2, which belonged to high risk regions. (3) The spatial distribution pattern of mountain torrent disasters was "scattered in southwest-northeast and concentrated in northwest-southeast." Before 2010, the gravity center of mountain torrents mainly concentrated in the vicinity of Fuling; After 2010, the distribution of mountain torrent disasters inclined to northwest, the heart moved to Zhongxian county, the degree of accumulation decreases, and the occurrence of mountain torrents increased randomly; (4) 2002 was the year of a sudden change of mountain torrents in Chongqing, which mainly increased in Tongliang, Bishan, Jiulongpo, Banan, Pengshui Miao Autonomous County, and Kai County. (5) Both the elevation and the density of river networks were positively correlated with the density of mountain torrents, while vegetation coverage was negatively correlated. Short-duration heavy rainfall can stimulate the occurrence of mountain torrents. Our findings are of great significance for flood prevention and disaster mitigation in Chongqing.

Key words: Chongqing, mountain torrents disaster, spatial-temporal distribution, Standard Deviational Ellipse (SDE), influencing factors, flood control and disaster reduction