| 广东省山洪灾害分布特征及关键影响因素分析 |
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| 作者姓名： | 王钧 宇岩 宫清华 袁少雄 陈军 |
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| 作者单位： | 1. 南方海洋科学与工程广东省实验室(广州), 广州 511458;2. 广东省科学院广州地理研究所 广东省地理空间信息技术与应用公共实验室, 广州 510070;3. 广东省科技图书馆/广东省科学院信息研究所, 广州 510070 |
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| 基金项目： | Supported by the Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), China (GML2019ZD0301), National Natural Science Foundation of China (41771024, 41977413), GDAS' Project of Science and Technology Development (2020GDASYL-20200301003, 2020GDASYL-040101, 2020GDASYL-20200102002), and Guangdong Provincial Science and Technology Program (2018B030324002, 2018B030324001). |
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| 摘 要： | 基于已发山洪灾害数据，首先探讨山洪灾害的空间分异规律；其次基于山洪灾害形成的地形、物源、水动力条件，选择相对高差、坡度、水系密度、地层岩性、多年平均24h降雨和距水系距离6大主因子，定量分析山洪灾害与各因子之间的数量和概率相关关系。基于ArcGIS将广东省划分为179 801个网格，按网格分别统计每个因子中山洪灾害的数量和发生概率。结果表明：广东省山洪灾害数量和灾害密度最大的流域为韩江流域；行政区划上，梅州市山洪灾害数量最多，而潮州市山洪灾害密度最高；相对高差、坡度、水系密度与山洪灾害发生概率之间的相关关系可以用y=a1eb1x+a2eb2x模拟；地层岩性、多年平均24h降雨和距水系距离与山洪灾害发生概率之间的相关关系可以用y=aebx模拟。研究成果可以为广东省山洪灾害防治提供依据。
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| 关 键 词： | 山洪灾害 分布特征 影响因素 概率模型 广东省 |
| 收稿时间： | 2019-11-01 |
| 修稿时间： | 2020-02-02 |
Geospatial distribution characteristics and key influencing factors of mountain torrents in Guangdong Province,China |
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| Authors: | WANG Jun YU Yan GONG Qinghua YUAN Shaoxiong CHEN Jun |
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| Institution: | 1. Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou), Guangzhou 511458, China;2. Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China;3. Science and Technology Library of Guangdong Province/Institute of Information Research, Guangdong Academey of Sciences, Guangzhou 510070, China |
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| Abstract: | According to the data from mountain torrent sites, the geospatial distribution regularity of mountain torrents was first explored. Second, six influencing factors such as relative relief, slope gradient, drainage density, stratigraphy, average annual 24-hour rainfall, and distance to rivers, were chosen to explore the relationship between torrents and these factors. The study area was classified into 179 801 grid cells, and each cell data of six factors was collected using ArcGIS software. Then, the statistical analysis of the quantity distribution and occurrence probability of torrents was carried out. The results showed that both the quantity and density of torrents in the Hanjiang River basin were the largest in Guangdong Province. In terms of administrative division, Meizhou has the largest quantity of torrents while Chaozhou has the highest density. Results also showed that relationships between the occurrence probability of torrents and the relative relief/slope/drainage density were described by y=a1eb1x+a2eb2x with different fitting constants while relationships between the occurrence probability and the stratigraphy/average annual 24-hour rainfall/distance to rivers could be described by y=aebx with different fitting parameters. The study results can provide basis for prevention and control of mountain torrents in Guangdong Province. |
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| Keywords: | mountain torrents distribution characteristics influencing factor probability method Guangdong Province |
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