Journal of Geo-information Science >
Temporal-spatial Distribution and the Influencing Factors of Mountain-Flood Disasters in Sichuan Province
Received date: 2018-04-16
Request revised date: 2018-06-22
Online published: 2018-10-17
Supported by
IWHR (China Institute of Water Resources and Hydropower Research) National Mountain Flood Disaster Investigation Project, No.SHZH-IWHR-57
National Natural Science Foundation of China, No.51774250
The Tibet Autonomous Region Science and Technology Support Project, No.809
Southwest Petroleum University of Science And Technology Innovation Team Projects, No.2017CXTD09.
Copyright
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.
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]. Journal of Geo-information Science, 2018 , 20(10) : 1443 -1456 . DOI: 10.12082/dqxxkx.2018.180193
Fig. 1 Distribution of historical mountain torrents in Sichuan Province图1 四川省历史山洪灾害点分布 |
Fig. 2 The number and average rainfall of historical mountain-flood disaster events in Sichuan Province图2 四川省历史山洪事件数量及平均降雨量 |
Fig. 3 The number of historical mountain-flood disaster in each month图3 各月份历史山洪灾害数量 |
Fig. 4 The number and average rainfall of mountain-flood disaster in different periods图4 各年代历史山洪灾害数量及平均降雨量 |
Fig. 5 Spatial trend analysis of disaster quantity, average rainfall, economic loss and casualty in county area图5 县域灾害数量、平均降雨、经济损失、人员伤亡空间趋势分析 |
Fig. 6 Moving track of the center of gravity and standard deviation ellipse of historical mountain-flood disaster from 1950s to 2010s图6 1950s-2010s历史山洪灾害重心移动轨迹及标准差椭圆 |
Tab.1 Variation of gravity center and standard deviation of elliptical parameters in historical mountain-flood disaster表1 历史山洪灾害点重心及标准差椭圆参数变化 |
年代(s) | (x,y) | S/(km) | R/(°) | X(std/km) | Y(std/km) |
---|---|---|---|---|---|
1950 | (104°06'E 29°52'N) | 0 | 31.286 | 165.428 | 131.502 |
1960 | (104°16'E 30°15'N) | 44.957 | 27.733 | 214.612 | 120.166 |
1970 | (103°55'E 29°51'N) | 54.981 | 30.037 | 326.437 | 151.235 |
1980 | (104°26'E 30°10'N) | 59.511 | 45.449 | 258.547 | 161.959 |
1990 | (104°07'E 29°41'N) | 61.440 | 39.051 | 281.271 | 181.354 |
2000 | (104°37'E 29°51'N) | 50.985 | 45.945 | 358.121 | 205.776 |
2010 | 104°42′E 30°30´N | 73.633 | 51.348 | 281.190 | 157.570 |
注:(x,y):重心点坐标; S/(km): 重心点的移动距离;R/(°):标准差椭圆中,椭圆的方向角度;X:沿x轴的长半轴长度;Y: 沿Y轴的短半轴长度 |
Fig. 7 Movement track of the center of gravity and standard deviation ellipse of historical mountain-flood disaster from May to September图7 5-9月历史山洪灾害重心移动轨迹及标准差椭圆 |
Tab.2 Variation of gravity center and standard deviation of elliptical parameters in historical mountain-flood disaster表2 历史山洪灾害点重心及标准差椭圆参数变化 |
5月 | 6月 | 7月 | 8月 | 9月 | |
---|---|---|---|---|---|
(x,y) | (104°28'E 29°40'N) | (103°59'E 30°00'N) | (103°56'E 29°53'N) | (103°37'E 29°46'N) | (105°00'E 30°49'N) |
S/km | 0 | 58.187 | 14.495 | 32.020 | 174.55 |
R/° | 48.450 | 31.187 | 46.040 | 34.488 | 53.282 |
X(std/km) | 239.183 | 225.783 | 335.372 | 284.142 | 251.181 |
Y(std/km) | 204.515 | 183.707 | 181.039 | 183.186 | 127.615 |
注:(x,y):重心点坐标; S/(km): 重心点的移动距离;R/(°):标准差椭圆中,椭圆的方向角度;X:沿x轴的长半轴长度;Y: 沿Y轴的短半轴长度 |
Tab. 3 Moran's I index and P value of Global spatial autocorrelation表3 全局空间自相关性Moran's I指数与P值 |
各项指标 | 各县山洪 总数/起 | 死亡人员 总数/人 | 过程平均降雨/mm | 直接经济 损失/万元 |
---|---|---|---|---|
Moran's I指数 | 0.1169 | -0.0151 | 0.2765 | -0.00527 |
P值 | 0.007 | 0.054 | 0.001 | 0.305 |
Fig. 8 Regional spatial autocorrelation of the number of historical mountain-flood disasters and average rainfall图8 县域历史山洪灾害数量以及平均降雨量局部空间自相关分析 |
Fig. 9 Hazard distribution of historical mountain-flood in Sichuan Province图9 四川省历史山洪灾害危险度分布 |
Tab. 4 Geographical detection and analysis table of influence factors表4 影响因素地理探测分析表 |
探测指标 | Q | P | 排序(从大到小) |
---|---|---|---|
高程标准差(X1) | 0.1780 | 0.0000 | 6 |
坡度因子(X2) | 0.1781 | 0.0000 | 5 |
坡向因子(X3) | 0.0020 | 0.0000 | 12 |
植被覆盖度(X4) | 0.0176 | 0.0000 | 7 |
10年一遇10 min降雨(X5) | 0.5773 | 0.0000 | 1 |
20年一遇6 h降雨(X6) | 0.5341 | 0.0000 | 2 |
100年一遇6 h降雨(X7) | 0.5288 | 0.0000 | 3 |
100年一遇24 h降雨(X8) | 0.5103 | 0.0000 | 4 |
土壤类型(X9) | 0.1055 | 0.0000 | 8 |
土地利用类型(X10) | 0.0790 | 0.0000 | 10 |
GDP增速(X11) | 0.0687 | 0.0000 | 11 |
人口增速(X12) | 0.0938 | 0.0000 | 9 |
Fig.10 Spatial distribution of different rainfall and rainfall index图10 不同降雨指标空间分布图 |
Tab. 5 Interaction between rainfall indices表5 各降雨指标之间的交互作用 |
降雨因素交互指标 | q | 影响模式 |
---|---|---|
100_24 ∩ 100_6 | 0.5387 | 双线性增强 |
100_24 ∩ 20_6 | 0.5528 | 双线性增强 |
100_24 ∩ 10_10 | 0.6585 | 双线性增强 |
100_6 ∩ 20_6 | 0.5410 | 双线性增强 |
100_6 ∩ 10_10 | 0.640 | 双线性增强 |
20_6 ∩ 10_10 | 0.6337 | 双线性增强 |
The authors have declared that no competing interests exist.
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