独库高速阿尔先沟段雪崩空间分布及因子探测

doi:10.13866/j.azr.2024.02.05

摘要/Abstract

摘要：

拟建独库高速公路阿尔先沟段地貌以高山峡谷为主，由于降雪和气候变化，雪崩频发。利用无人机遥感解译与现场调研协同调查的方法识别92个雪崩点，选取高程、坡度、地表切割度、地面粗糙度，积雪期最大积雪深度、最大风速、平均温度和平均降雪量为驱动因子，运用地理探测器分析不同分辨率地形因子与雪崩稳定性的关系。结果表明：本研究区雪崩发育较为活跃，稳定性较差，但较多雪崩释放区、运动区位于山体坡面，堆积区位于远离拟建线路的谷底，对拟建线路影响较小。通过地理探测器分析，坡度、地面粗糙度对雪崩稳定性解释力与分辨率呈正相关，高程、地表切割度呈负相关，交互探测结果均是双因子增强或者非线性增强，且非线性增强比双因子增强更加显著，坡度与其他因子结合对雪崩稳定性影响至关重要。本研究可为雪崩易发性、危险性评价工作提供可靠的数据支撑，为独库高速公路的建设运营提供科学依据。

关键词: 阿尔先沟, 雪崩, 地理探测器, 驱动因子, 空间分布

Abstract:

The proposed Aerxiangou section of the Duku expressway, characterized by high mountainous terrain and canyons, faces frequent avalanches due to heavy snowfall and climate change. In this study, a collaborative investigation using UAV remote sensing interpretation and field research identified 92 avalanche points. In addition, elevation, slope, surface cutting degree, ground roughness, maximum snow depth, maximum wind speed, average temperature, and average snowfall were selected as driving factors. A geographical detector was used to examine the relationship between terrain factors, different resolutions, and avalanche stability. The results of this study revealed strong avalanche activity with generally poor stability in the study area. However, it was reassuring to note that most avalanche release and activity areas are located on mountain slopes. The accumulation area lies on the valley floor, a considerable distance away from the planned road route, thus minimizing its impact. Results from the geographical detector analysis suggest positive correlations between interpretations of slope and ground roughness with snow avalanche stability across varying resolutions. The interactive detection results are both double-factor enhancement and nonlinear enhancement, with the latter being more significant than the former. The combination of slope and other factors is crucial for determining the impact of avalanche stability. This study offers reliable data support for assessing avalanche vulnerability and risks, thereby establishing a solid scientific basis for constructing and operating the Duku expressway.

Key words: Aerxiangou, avalanche, geographical detector, driving factors, spatial distribution

程秋连, 刘杰, 杨治纬, 张天意, 王斌. 独库高速阿尔先沟段雪崩空间分布及因子探测[J]. 干旱区研究, 2024, 41(2): 220-229.

CHENG Qiulian, LIU Jie, YANG Zhiwei, ZHANG Tianyi, WANG Bin. Spatial distribution and factor analysis of avalanche in the Aerxiangou section of the Duku expressway[J]. Arid Zone Research, 2024, 41(2): 220-229.

图/表 11

图1

表1

交互作用探测依据"

判断依据	交互图示	交互性
$q X 1 ⋂ X 2 < m i n q X 1, q X 2$		非线性减弱
$m i n q X 1, q X 2 < q X 1 ⋂ X 2 < m a x q X 1, q X 2$		单因子非线性减弱
$q X 1 ⋂ X 2 > m a x q X 1, q X 2$		双因子增强
$q X 1 ⋂ X 2 = q X 1 + q X 2$		相互独立
$q X 1 ⋂ X 2 > q X 1 + q X 2$		非线性增强

表1

图2

表2

图3

表3

表4

图4

图5

图6

图7

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稳定性分级	雪崩数量/个	所占比例/%
稳定	6	6.5
相对稳定	18	19.6
稳定性较差	45	48.9
不稳定	18	19.6
极其不稳定	5	5.4

对拟建线路的影响	雪崩数量/个	所占比例/%
无影响	59	64.2
影响一般	12	13
影响较重	12	13
影响严重	9	9.8

地形因子			气象积雪因子
影响因子	分级区间	级别	影响因子	分级区间	级别
高程/m	<2400	Ⅰ	平均温度/℃	<-8.3	Ⅰ
	2400~2700	Ⅱ		-8.3~-7.8	Ⅱ
	2700~3000	Ⅲ		-7.8~-7.4	Ⅲ
	3000~3300	Ⅳ		-7.4~-6.9	Ⅳ
	>3300	Ⅴ		-6.9~-6.6	Ⅴ
坡度/m	0~15	Ⅰ	平均降雪量/cm	<18	Ⅰ
	15~30	Ⅱ		18~19	Ⅱ
	30~45	Ⅲ		19~20	Ⅲ
	45~60	Ⅳ		20~21	Ⅳ
	>60	Ⅴ		>21	Ⅴ
地表切割度/m	0~30	Ⅰ	最大积雪深度/cm	<55	Ⅰ
	30~60	Ⅱ		55~57.5	Ⅱ
	60~90	Ⅲ		57.5~60	Ⅲ
	90~120	Ⅳ		60~62.5	Ⅳ
	>120	Ⅴ		62.5~65	Ⅴ
地面粗糙度	0~0.2	Ⅰ	最大风速/(m·s^-1)	<15.6	Ⅰ
	0.2~0.4	Ⅱ		15.6~15.7	Ⅱ
	0.4~0.6	Ⅲ		15.7~15.9	Ⅲ
	0.6~0.8	Ⅳ		15.9~16.1	Ⅳ
	>0.8	Ⅴ		>16.1	Ⅴ