| 四川省山洪灾害时空分布规律及其影响因素研究 |
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| 引用本文： | 熊俊楠,赵云亮,程维明,郭良,王楠,李伟.四川省山洪灾害时空分布规律及其影响因素研究[J].地球信息科学,2018,20(10):1443-1456. |
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| 作者姓名： | 熊俊楠 赵云亮 程维明 郭良 王楠 李伟 |
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| 作者单位： | 1. 西南石油大学土木工程与建筑学院,成都 6105002. 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 1001013.中国水利水电科学研究院,北京 1000384. 水利部防洪抗旱减灾工程技术研究中心,北京 100038 |
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| 基金项目： | 中国水利水电科学研究院全国山洪灾害调查评价项目（SHZH-IWHR-57）;国家自然科学基金项目(51774250);西藏自治区科技支撑计划项目(省809);西南石油大学科技创新团队项目(2017CXTD09) |
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| 摘 要： | 山洪灾害时空分布规律及其影响因素,是灾害时空数据挖掘领域所关注的重点问题。本研究采用1950-2015年四川省历史山洪灾害事件数据,结合地统计、地理探测器、空间分析等方法,系统地分析了四川省1950-2015年历史山洪灾害的时空分布规律及其影响因素。结果表明：① 1950-2015年四川省山洪灾害数量整体呈先稳定后增长的趋势;山洪灾害主要集中在5-9月,7月覆盖率100%。② 县域灾害频次在南-北方向呈递减分布趋势;平均降雨量（历史山洪灾害过程降雨的平均值）在东-西方向呈指数型增长趋势,南-北方向由中部向南北递减。③ 1950s-2010s和5-9月历史累计山洪灾害重心及各标准差椭圆中心集中在四川中部地区,向东北方向移动,累计灾害点空间分布呈西南—东北格局。④ 县域山洪灾害数量及平均降雨量呈空间正自相关。⑤ 地理探测器分析表明自然因素、降雨、人类活动等因素对山洪灾害时空分布影响较大,其中不同降雨指标、高程标准差、坡度是山洪灾害时空分布规律的主要驱动因素。研究结果对查清四川省山洪灾害时空分布特征及小流域山洪监测预警、风险评价、防治区划等提供坚实的理论基础和科技支撑。
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| 关 键 词： | 山洪灾害 时空分布规律 标准差椭圆 空间自相关 地理探测器 |
| 收稿时间： | 2018-04-16 |
Temporal-spatial Distribution and the Influencing Factors of Mountain-Flood Disasters in Sichuan Province |
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| XIONG Junnan,ZHAO Yunliang,CHENG Weiming,GUO Liang,WANG Nan,LI Wei.Temporal-spatial Distribution and the Influencing Factors of Mountain-Flood Disasters in Sichuan Province[J].Geo-information Science,2018,20(10):1443-1456. |
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| Authors: | XIONG Junnan ZHAO Yunliang CHENG Weiming GUO Liang WANG Nan LI Wei |
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| Institution: | 1. School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China3. Chinese Institute of Water Resources and Hydropower Research, Beijing 100038, China4. Research Center on Flood & Drought Disaster Reduction of the Ministry of Water Resources, Beijing 100038, China; |
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| Abstract: | The temporal-spatial distribution and influencing factors of mountain-flood disaster are a key issue in the disaster data mining. Using the historical mountain-flood catastrophe data that is learned from the National Mountain Flood Disaster Investigation Project from 1950 to 2015 in the Sichuan Province, and employing the methods in geo-statistics, geographic detector and geo-spatial analysis, this paper systematically analyzed the temporal-spatial distribution of historical mountain-flood disaster and the influencing factors in Sichuan Province. The main findings are the following : (1) The total amount of mountain-flood disasters in the Sichuan Province, from 1950 to 2015, remained stable and then increased rapidly. In addition, the catastrophe mainly occurred from May to September, especially in July every year. (2) The frequency of county disasters over Sichuan showed a decreasing trend from south to north. The average rainfall during historical mountain-flood disaster (ARD) increased exponentially from east to west, and decreased from middle to north. (3) From May to September each year and from1950s to 2010s, the center of gravity and the elliptical center of each standard deviation of the accumulated mountain-flood disaster are concentrated in the central part of Sichuan, moving to the northeast. The accumulated disaster points emerged in a pattern of southwest-northeast. (4) The spatial autocorrelation analysis indicates a positive spatial correlation between the amount of mountain-flood disaster and ARD in county area. (5) The geographic detector analysis indicates that natural factors, rainfall, human activity and other factors have a great influence on the temporal-spatial distribution of mountain-flood disaster. In particular, the main driving factors are the rainfall index, standard deviation of elevation and slope. The results provide a theoretical basis, scientific and technological support for the investigation of the temporal-spatial distribution characteristics of mountain-flood disaster in the Sichuan Province, which can also benefit the monitoring and early warning, the risk assessment, the prevention and control of mountain-flood disaster in small watersheds. |
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| Keywords: | mountain flood disaster spatial and temporal distribution spatial autocorrelation geographic detector |
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