基于地貌特征的青藏高原边缘泥石流沟分类

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梁馨月^,¹^,²^,⁵, 徐梦珍², 吕立群²^,³, 崔一飞², 张风宝¹^,⁴

1. 中国科学院水利部水土保持研究所黄土高原土壤侵蚀与旱地农业国家重点实验室,杨凌 712100

2. 清华大学水沙科学与水利水电工程国家重点实验室,北京 100084

3. 北京林业大学水土保持学院,北京100083

4. 西北农林科技大学水土保持研究所,杨凌 712100

5. 中国科学院大学,北京 100049

Geomorphological characteristics of debris flow gullies on the edge of the Qinghai-Tibet Plateau

LIANG Xinyue^,¹^,²^,⁵, XU Mengzhen², LYU Liqun²^,³, CUI Yifei², ZHANG Fengbao¹^,⁴

1. State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation , CAS and Ministry of Water Resources, Yangling 712100, Shaanxi, China

2. State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China

3. Beijing Engineering Research Center of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China

4. Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, Shaanxi, China

5. University of Chinese Academy of Sciences, Beijing 100049, China

通讯作者: 张风宝(1980-), 男, 宁夏彭阳人, 研究员, 博士生导师, 主要从事坡面土壤侵蚀过程及机制研究。

收稿日期:2019-11-2修回日期:2020-05-27网络出版日期:2020-07-25

基金资助:

中国科学院战略性先导科技专项.XDA23090401
国家自然科学基金项目.41790434

Received:2019-11-2Revised:2020-05-27Online:2020-07-25

Fund supported:

Strategic Priority Research Program of the Chinese Academy of Sciences.XDA23090401
National Natural Science Foundation of China.41790434

作者简介 About authors
梁馨月(1995-), 女, 四川南充人, 硕士生, 主要从事土壤侵蚀与山地灾害研究。E-mail: liangxinyue17@mails.ucas.edu.cn

摘要
青藏高原地形急变带受构造运动、极端降水等因素的影响,呈现泥石流高发、群发的特点。对泥石流沟地貌特征的科学分类有利于探索泥石流发生机制、确定防治对策,对山区防灾减灾和生态修复具有重要意义。本文以青藏高原边缘7个泥石流高发流域为研究对象,开展地貌测量和统计分析。通过非度量多维尺度分析,将泥石流沟分为3种类型：I型是基岩下切区暴雨型泥石流;II型是基岩下切区冰川融水型泥石流;III型是沉积盆地下切区暴雨型泥石流。通过Kruskal-Wallis检验进一步分析3类泥石流沟地貌差异性,从地质、地貌与气候等方面探讨了3类泥石流沟的松散物来源与水沙输移特性。在气候变暖的影响下,II型泥石流的活跃性将增大;随着极端降雨频率的增加,I型和III型泥石流活跃性也将增加。
关键词： 青藏高原;泥石流沟分类;非度量多维尺度分析;Kruskal-Wallis检验

Abstract

The edge of the Qinghai-Tibet Plateau is characterized by high topographic relief, significant tectonic motion, extreme precipitation, and densely populated active debris flow gullies. It is essential to scientifically categorize the debris flow gullies to understand their mechanisms, prevent and mitigate debris flow disasters, and find out strategies to restore the ecology. The present study carried out topographical measurements and statistical analyses of seven regions on the edge of the Qinghai-Tibet Plateau, in which active debris flow gullies are concentrated. The debris flow gullies are classified into three types by means of nonmetric multidimensional scaling. Type I is formed by rainstorms in exposed bedrock areas, Type II is formed by glaciers in exposed bedrock areas, and Type III is formed by rainstorms in depositional basins. The variation in landforms of the three types is analyzed using Kruskal-Wallis tests. The sources of loose material and the characteristics of water flow and sediment transport in all the three types of debris flow gullies are discussed from the aspects of geology, topography, and climate. It is shown that the activity of Type II increases along with the warming of the Qinghai-Tibet Plateau, and the activities of types I and III increase along with the frequency of extreme rainfalls.

Keywords：Qinghai-Tibet Plateau;categorization of debris flow gullies;nonmetric multidimensional scaling;Kruskal-Wallis test

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本文引用格式
梁馨月, 徐梦珍, 吕立群, 崔一飞, 张风宝. 基于地貌特征的青藏高原边缘泥石流沟分类. 地理学报[J], 2020, 75(7): 1373-1385 doi:10.11821/dlxb202007004
LIANG Xinyue, XU Mengzhen, LYU Liqun, CUI Yifei, ZHANG Fengbao. Geomorphological characteristics of debris flow gullies on the edge of the Qinghai-Tibet Plateau. Acta Geographica Sinice[J], 2020, 75(7): 1373-1385 doi:10.11821/dlxb202007004

1 引言

泥石流是山区最主要的自然灾害之一,大规模破坏山区城镇基础设施,甚至威胁人民生命财产安全。泥石流的防灾减灾是美丽山区建设的重要内容。为有效服务泥石流的防治工作,****从泥石流的灾害风险评价及灾害防治原理和技术方面开展了大量调查与研究工作。已有研究利用概率神经网络（PNN）^[1]、人工神经网络（ANN）^[2]、层次分析^[3]以及人工智能^[4]等方法对泥石流进行风险评估和预测,以减少泥石流灾害带来的损失。同时也深入分析致灾因子与受灾体之间的关系^[5],识别受泥石流威胁的建筑物以及暴露人群,解决人群疏散问题,研究高效管理措施^[6,7]。结合对公众和资源分配的调查,培训公众提高泥石流的灾害意识和风险感知,以降低灾害风险^[8,9],缓解危害度^[10]。针对泥石流的工程防控体系,谷坊坝系被广泛应用,其防控效果受谷坊坝的结构和配置模式,以及泥石流的侵蚀与沉积路径、地形地貌条件等的影响^[11,12]。

地貌条件决定泥石流的能量及其转化条件,同时影响着地表径流的汇流过程以及物源的补给方式^[13,14]。青藏高原受印度洋板块向欧亚板块不断碰撞的影响,边缘剧烈隆起^[15],断裂带与造山带为泥石流的发生提供了有利的地貌条件^[16]。为探索青藏高原边缘泥石流灾害类型与地貌特征的关系,本文对其东南、东北和西部的7个典型泥石流高发流域：怒江峡谷区（NR）、雅鲁藏布江大峡谷及帕隆藏布（YR）、小江（XR）、白龙江（BL）、大河坝河（DH）、盖孜河（GZ）以及印度河上游（IR）等进行了系统考察,并针对7个流域内382条典型沟道进行了资料收集^[17]、野外观测和遥感影像解译。旨在阐明青藏高原边缘不同流域内泥石流沟的典型特征,从地质、地貌以及气候方面对不同类型沟道的泥石流灾害成因进行分析,为青藏高原地形急变带泥石流防灾减灾提供参考。

2 研究区概况与研究方法

2.1 研究区域

雅鲁藏布江大峡谷区发育了最典型的海洋性冰川,冰川融水对源区年径流量的贡献率为11%^[18];盖孜河地处西昆仑北缘深断裂带,区域内冰碛广布,冰川融水补给量对年径流量的贡献率为77.8%^[19,20];印度河流域上游也覆盖有大量的冰川,其冰川融水补给量对源区年径流量的贡献率为50%^[21]。冰川消融、冰湖溃决为泥石流的发生提供了充足的水源和物源条件。怒江地处横断山区强烈碰撞挤压带,在云南境内中上游形成了深切V形河谷。白龙江位于青藏高原向黄土高原过渡的地形急变带,断裂带交错,地形切割剧烈。小江发育在深大断裂带上,老构造错综复杂,新构造运动强烈^[22]。大河坝河位于青藏高原东北部的同德盆地,区内黄河以4 mm/a速率进行下切侵蚀,侵蚀基准面降低使黄河支流下切侵蚀及溯源侵蚀不断发展。大河坝河在此背景下快速下切,使兴海盆地由沉积区变为侵蚀区。兴海盆地内新生代地层发育,河相沉积物普遍分布,中下游主要以卵石夹砂为主、覆盖较厚层黄土^[23,24]。其他流域岩性主要由坚硬岩（花岗岩）及较硬岩（石灰岩、板岩、白云岩等）组成。

青藏高原边缘强震及大震频繁（图1）。印度河上游,雅鲁藏布江中游和盖孜河的地震动峰值加速度在0.2~0.3 g之间,小江、白龙江在0.2 g左右,怒江流域高山峡谷段在0.15 g左右,大河坝河在0.1 g左右。地震动峰值加速度越大,表明地震基本烈度越大。

图1

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图1青藏高原泥石流灾害及地震的空间分布

Fig. 1Spatial distribution of debris flow disasters and earthquakes on the Qinghai-Tibet Plateau

2.2 研究方法

2.2.1 泥石流沟地貌参数地貌参数的定性和定量统计分析与GIS结合可有效支撑地貌特征分析^[25,26,27]。本文采用空间分辨率为30 m的ASTER GDEMV2数据集作为基本地形数据,提取影响泥石流发生的主要地貌参数。研究表明^{[28,29,30,31]},面积（A）、坡度（S）、主沟长度（L）、比降（G）、高差（RA）、沟谷形状指数（R_f）、面积—高程积分值（HI）、纵剖面形态指数（N）、沟壑密度（GD）和植被覆盖度（FVC）是影响泥石流规模和频率的主要参数（表1）。

Tab. 1
表1
表1影响泥石流发生的主要地貌参数
Tab. 1Main factors affecting the occurrence of debris flows

地貌参数	公式	公式释意
面积(A)	通过ArcGIS水文分析模块提取	面积是泥石流物源条件的反映,面积较大的沟谷有更多滑坡、崩塌为泥石流发生提供松散物质。
坡度(S)	$S = ta n^{- 1} (\frac{H_{h}}{L_{h}})$	H_h为岩体垂直高度;L_h为水平长度。坡度反映松散物补给方式和汇流速度,坡度越陡,松散物越容易启动。
主沟长度(L)	通过ArcGIS水文分析模块提取	主沟越长,越利于增加水量,接纳和搬运的松散碎屑物越多。
比降(G)	$G = \frac{? H}{? L}$	$? H$ 为海拔变化; $? L$ 为长度变化。比降反映沟道演化状况,表征泥石流沟水动力条件和物质输送能力,在一定范围内,比降越大越易爆发泥石流。
高差(RA)	$RA = h_{\max} - h_{\min}$	h_max和h_min分别是流域内的最高和最低海拔;RA表示切口深度和地表剥蚀程度,反映流域构造活动强度和能量条件。高差越大,越易发生泥石流。
沟谷形状指数(R_f)	$R_{f} = \frac{A}{L^{2}}$	R_f反映沟谷的汇水和水动力条件。R_f大,沟道中洪峰流量越大,越有利松散物质的起动。
面积—高程积分值(HI)	$HI = \frac{h_{mean} - h_{\min}}{h_{\max} - h_{\min}}$	h_mean表示是流域内的平均海拔。HI反映流域受侵蚀程度,HI越大,表明流域演化阶段越年轻,可蚀性越大。
纵剖面形态指数(N)	$h = H {(\frac{l}{L})}^{N}$	h及l：纵剖面上某点与河口的高差及距离;H及L：河源与河口之间的高差及水平距离;N反映泥石流发育地貌条件,可将泥石流分为幼年期、壮年期和老年期。
沟壑密度(GD)	$GD = L_{总} / A$	L_总为沟谷河流的总长;GD反映流域发育的完善程度。沟壑密度越大的地区,不稳定面越多,边坡稳定性越弱,发生泥石流的可能性也越大
植被覆盖度(FVC)	$FVC = \frac{(NDVI - NDV I_{soil})}{(NDV I_{veg} - NDV I_{soil})}$	NDVI_soil是裸土或者无植被覆盖区域的NDVI;NDVI_veg是完全被植被覆盖的NDVI。通常植被覆盖度越高,坡面越稳定。

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2.2.2 泥石流差异性分析方法

（1）非度量多维尺度分析

非度量多维尺度分析（Nonmetric Multidimensional Scaling, NMDS）是一种非约束排序的分类方法。将多维空间的研究对象简化到低维进行定位和归类,同时保留对象间原始关系,利用欧式距离计算泥石流沟间的相异性

δ_{ij}

,并将

δ_{ij}

从大到小排列^[32],其具体算法如下：

（1）

d_{ij} = \sqrt[]{\overset{t}{\sum_{k = 1}} (X_{ik} - X_{jk})^{2}}, (i, j = 1,2, \dots, n, i \neq j)

式中：X_ik、X_jk表示泥石流沟i、j在欧式空间的位置;t为地貌参数数量。除去泥石流本身的相异性,一共有

m = \frac{n (n - 1)}{2}

个相异性。假定

δ_{ij} \approx f (d_{ij})

。

在二维空间里使用欧式距离计算泥石流沟的距离：

（2）

{\overset{?}{d}}_{ij} = \sqrt[]{(x_{i} - x_{j})^{2} + (y_{i} - y_{j})^{2}}

式中：x_i、x_j表示二维空间中泥石流沟i、j的x轴坐标值;y_i、y_j表示二维空间中泥石流沟i、j的y轴坐标值。

使用胁强系数Stress来衡量二维排序点拟合原始实体的优度,使二维空间内泥石流点间距离排序与相异性指标排序尽可能保持一致。

（3）

Stress = {[\frac{\overset{n}{\sum_{i = 1}} \overset{n}{\sum_{j = 1}} (d_{ij} - {\overset{?}{d}}_{ij})^{2}}{\overset{n}{\sum_{i = 1}} \overset{n}{\sum_{j = 1}} d_{ij}^{2}}]}^{1 / 2}

Stress ≤ 0.05为拟合极好;0.05 < Stress

\leq

0.1为拟合较好;0.10 < Stress

\leq

0.2为拟合一般;Stress > 0.2为拟合较差。上述过程在R 3.6.1中完成。

（2）Kruskal-Wallis检验

Kruskal-Wallis检验通过推断样本来自多个总体的中位数或者分布形态是否存在差异性显著,既不要求数据来自正态分布的总体,也不要求方差齐性,适用多个水平的检验。Kruskal-Wallis检验在SPSS 19.0软件完成。

3 结果分析

3.1 泥石流沟分布特征

泥石流沟集中在青藏高原边缘的地形急变地带上。怒江流域泥石流沟分布在贡山—泸水段,白龙江流域泥石流沟分布在舟曲—武都段,雅鲁藏布江流域泥石流沟分布在帕隆藏布,大河坝河流域泥石流沟主要集中在河段下游。7个流域泥石流沟位于主流比降较大区域（图2）。白龙江流域泥石流沟段位于主流纵比降5.5‰,大河坝河为11‰左右,盖孜河为32‰,小江为12‰,怒江为4.1‰,印度河为3.5‰,雅鲁藏布江为5.1‰。雅鲁藏布江、印度河、怒江比降相对小,但流量大（雅鲁藏布江年平均流量为4425 m3/s^[33],怒江雨季出境流量为2775 m3/s^[34],印度河融雪洪峰流量可达11300 m3/s^[35]）,径流功率大,侵蚀力强,泥石流频发。

图2

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图2泥石流沟空间分布及其在主河纵剖面分布

Fig. 2Spatial distribution of debris flow gullies in the catchments and along the longitudinal profiles of the main streams

3.2 泥石流沟分类

将泥石流沟地貌参数进行相关分析后剔除比降,进行非度量多维尺度分析。Stress = 0.13（< 0.2）,认为NMDS二维空间的拟合结果能够较准确的反映实际泥石流沟的特征信息。泥石流地貌参数聚集为3组（图3）：I型主要为白龙江、怒江和小江流域内分布的泥石流沟,其共同特征为基岩底质侵蚀下切严重,主要由暴雨引发,为基岩下切区暴雨型泥石流。II型主要为雅鲁藏布江、盖孜河、印度河流域内分布的泥石流沟,其共同特征为冰川融水为主要水源补给,为基岩下切区冰川融水型泥石流。III型主要为大河坝河流域内分布的泥石流沟,其共同特征为沉积地貌,松散物质丰富,由暴雨引发,为沉积盆地下切区暴雨型泥石流。

图3

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图3泥石流沟在二维非度量尺度空间分布

Fig. 3Clusters of debris flow gullies in the two-dimensional space obtained by NMDS

3.3 不同类型泥石流沟地貌因素差异

基于NMDS结果,对3类泥石流沟地貌参数进行了Kruskal-Wallis检验（图4a）,I型泥石流沟植被覆盖度高（0.6）,面积（23 km2）、地形起伏（1830 m）、坡度（31°）都较大,而沟壑密度小（1.6 km/km2）;II型泥石流沟面积（33 km2）、地形起伏（2300 m）,坡度（33°）都最大,发育阶段处于壮年期居多（HI = 0.49）;III型泥石流沟面积（1.3 km2）、地形起伏（450 m）、坡度（14°）都最小,而沟壑密度大（2.9 km/km2）、发育阶段处于幼年期（HI=0.63）。3类泥石流沟的高差、沟壑密度与植被覆盖度差异性显著（p < 0.05）;面积、主沟长度、面积—高程积分值、坡度和纵剖面形态指数等地貌参数,III型与I、II型差异性显著（p < 0.05）,但后两者差异性不显著（p > 0.05）。II型与III型沟谷形状差异性显著（p < 0.05）,但都与I型差异不显著（p > 0.05）。II型长期遭受冰川侵蚀,沟壑密度大,沟头逐渐呈现出圆形,以漏斗状为主。III型物质松散,易发生下切或溯源侵蚀,以狭长状为主。I型松散物粒径较大,漏斗状沟谷在相同降雨条件下能形成更大的洪峰流量,因此,I型沟谷形态由III型向II型过渡（图4b）。

图4

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图43类泥石流沟地貌特征

注：a图中用不同字母表示类别间存在显著性差异。
Fig. 4Variation in morphologies among the three types of debris flow gullies

III型泥石流沟内沉积物易遭受水力侵蚀,在地貌特征上与I、II型有很大差异。I型与II型泥石流沟受暴雨和冰川的侵蚀,在植被覆盖度、沟谷纵比降、沟壑密度、地形起伏等地貌因子上表现明显差异：① II型泥石流沟海拔更高,气温更低,不适宜植被生长,故其植被覆盖度比I型更低;② 冰川携带泥沙能力远大于水流,当携带相同泥沙量,II型泥石流沟所需沟谷比降更小;③ 冰川侵蚀沟谷形成U型谷,两侧沟坡更陡,更易产生沟壑;④ II型泥石流沟地形起伏大,利于冰川形成和融化。

实地考察3类泥石流沟堆积扇的粒径级配（图5a）：I型堆积扇中值粒径D₅₀主要在100 cm左右;II型堆积扇粒径变化范围大,D₅₀在5~50 cm;III型堆积扇颗粒小,D₅₀小于1 cm。泥石流堆积扇除粒径级配有差异之外,堆积形态、规模也不尽相同（图5c）。受主流宽度的影响,I型堆积扇面积差异较大,如怒江河谷狭窄,泥石流堆积扇发育受到制约,面积较小（约0.05 km2）,白龙江、小江泥石流堆积扇面积较大（0.5~1 km2）、比降差异大（50‰~300‰）。II型堆积扇比降小（80‰~180‰）、面积大（约1 km2）;III型堆积扇比降较大（160‰~280‰）、面积较小（约0.1 km2）。堆积扇面积能反映泥石流规模大小。II型泥石流规模最大,如1953年古乡沟（II型）发生特大泥石流,泥沙输移量高达2000万m3,堆积扇面积高达4 km2。

图5

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图53种泥石流堆积扇的特征

Fig. 5Characteristics of the three types of debris flow fans

4 讨论

地震不仅能引发滑坡、崩塌等灾害,还扰动边坡,使震后泥石流的临界降雨量或者累计降雨量降低^{[36,37,38,39]}。泥石流活动在震后5年内进入极度活跃期,10年内将处于高度活跃期^[40,41]。高强度、高频率地震为印度河上游,雅鲁藏布江中游以及盖孜河流域带来了大量的崩塌、滑坡物源,是该地区泥石流活跃的重要原因。

构造抬升形成的地貌是泥石流发生的重要基础^[42]。Hack剖面反映了河流纵剖面的整体变化,当其为直线时,河流全河段达到动态平衡的状态^[43]。Seeber^[44]用标准化河长坡降指标（SL/K）值表示岩石抗侵蚀能力和构造活动,当SL/K

\leq

2,河流发育接近于均衡状态,2 < SL/K

\leq

10为陡河段,SL/K >10为极陡河段。青藏高原边缘处于地壳抬升阶段,短期内河流纵剖面形态难以达到均衡（图6）。泥石流沟主要分布在各流域构造抬升最为活跃地段,基岩破碎,为泥石流提供了丰富的物源。跨越地形急变带的雅鲁藏布江、怒江和印度河的SL/K >2,强烈的构造抬升使得河流比降局部变化大;受到青藏高原边缘挤压的大河坝河、小江、盖孜河、白龙江,其SL/K在1~2之间,受构造抬升影响较小;相比之下,远离青藏高原,未受挤压影响的辽河（LR）和淮河（HR）,SL/K最大值在1左右,河流处于均衡状态,流域发生泥石流概率小。

图6

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图6Hack剖面及SL/K指数

注：K为均衡坡降指数,利用K对SL指数进行标准化,形成标准河流坡降指数SL/K。
Fig. 6Hack profiles and SL/K indices of nine rivers

除构造运动,河流下切也影响着泥石流的发生。径流强度指数（SPI）是控制坡面侵蚀的主要因素之一,反映坡脚侵蚀和河流下切作用^[45]。地形湿度指数（TWI）被广泛用于描述地形在产流区的影响和评价滑坡风险^[46]。在无资料地区,SPI和TWI能帮助判断滑坡和泥石流风险,SPI和TWI越高则发生泥石流风险越大^[47]。III型泥石流沟TWI高,降雨易使土壤饱和而引发浅层滑坡,即使其坡度低于泥石流沟典型坡度（27°~38°）（图7a）。同时区域内沉积物松散胶结,休止角小,细小颗粒易起动和搬运,冲击力较弱,一般不易形成堵江危害。I型和II型SPI高（图7b）,粗大颗粒受重力侵蚀和水力侵蚀并被搬运至沟口,冲击性强,甚至运动到主流堵江,造成堰塞风险。如2007年和2018年天摩沟（II型）发生特大泥石流形成堰塞体冲断川藏公路,形成堰塞湖,而怒江云南段（I型）也形成大量泥石流堵江堰塞湖^[48]。

图7

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图73类泥石流沟的水力特征

Fig. 7Hydrodynamic characteristics of the three types of debris flow gullies (a. Relation between TWI and slope; b. Relation between SPI and slope)

在中低纬度区,青藏高原拥有最大面积的冰川。冰川侵蚀会破坏岩石结构,增加冰缝间的不稳定性,影响着土壤的侵蚀率和泥沙输移率^[49]。青藏高原是气候敏感区,其气温上升速率是全球平均气温的两倍。从1961—2007年青藏高原有明显的增暖增湿过程,同时极端降雨事件有明显增加^[50]。近50年来青藏高原冰川储量减少约20%,藏东南冰川退缩平均40 m/a^[51]。II型受气候变暖影响,冰川退缩留下大量冰碛物,导致泥石流的活跃性增强。近年的研究表明,横断山区也呈现变暖趋势^[52], 年均降水量以9 mm/10 a的速度增加,而青藏高原东北部年降水日数微弱减少,但降水强度呈增加趋势^[53]。随着区域性降水量以及极端暴雨次数增加,I型和III型泥石流沟发生可能性也将增加。

5 结论

本文对青藏高原边缘地形急变带典型流域的泥石流沟分布和类型进行分析,运用非度量多维尺度方法将泥石流沟分为3类：小江,怒江,白龙江为代表的基岩下切区暴雨型泥石流（I型）;雅鲁藏布江中游,印度河上游、盖孜河为代表的基岩下切区冰川融水型泥石流（II型）;以大河坝河为代表的沉积盆地下切区暴雨型泥石流（III型）。I型在河流下切和良好水沙输移特性下,由暴雨激发易形成较大规模泥石流,有堵江风险;II型在构造抬升、地震、冰川侵蚀和良好水沙输移特性下,易形成高频率、大规模泥石流,堵江风险高;III型松散物来源于沉积盆地,由降雨激发易形成高频率、小规模泥石流,群发特点显著。I型和III型泥石流随局部区域极端降雨频率的增加,活跃性也将增加。持续强烈的构造抬升和气候变暖,冰川消融,II型泥石流的活跃性将增大。随着藏东南冰川剧烈退缩和川藏铁路建设,雅鲁藏布江流域沿线泥石流易发区将成为关注重点,泥石流的风险判识和风险评估将深入研究。随着黄河流域生态保护的推进,大河坝河泥石流易发区将受到更多的关注。

参考文献原文顺序
文献年度倒序
文中引用次数倒序
被引期刊影响因子

[1]

Liu

C N

, Dong

J J

, Peng

Y F

, et al. Effects of strong ground motion on the susceptibility of gully type debris flows
Engineering Geology, 2009,104(3):241-253.

[本文引用: 1]

[2]

Chang

T C

, Chao

R J

. Application of back-propagation networks in debris flow prediction
Engineering Geology, 2006,85(3):270-280.

DOI:10.1016/j.enggeo.2006.02.007 URL [本文引用: 1]

[3]

Gao

, Sang

. Identification and estimation of landslide-debris flow disaster risk in primary and middle school campuses in a mountainous area of Southwest China
International Journal of Disaster Risk Reduction, 2017,25:60-71.

[本文引用: 1]

[4]

Zhao

, Meng

, Qi

, et al. AI-based identification of low-frequency debris flow catchments in the Bailong River basin, China
Geomorphology, 2020: 107125. Doi: 10.1016/j.geomorph.2020.107125.

[本文引用: 1]

[5]

Zou

, Cui

, He

, et al. Regional risk assessment of debris flows in China: An HRU-based approach
Geomorphology, 2019,340:84-102.

[本文引用: 1]

[6]

Melo

, Zêzere

J L

, Oliveira

S C

, et al. Defining evacuation travel times and safety areas in a debris flow hazard scenario
Science of the Total Environment, 2020,712:136452. Doi: 10.1016/j.scitotenv.2019.136452.

DOI:10.1016/j.scitotenv.2019.136452 URLPMID:31931203 [本文引用: 1]

Debris flows are one of the most hazardous types of landslides in mountain regions. In the upper part of the Zezere valley (Serra da Estrela, Portugal) several debris flows events occurred in the last 200 years, some of them causing loss of lives and material damages. In this work, a methodology for pedestrian evacuation modelling, in a debris flow hazard scenario, was implemented. A dynamic run-out model, developed in previous studies, was used to evaluate the debris flows velocities, thickness of the deposits and extent of the mobilized material. The buildings potentially affected by the impact of debris flows were identified and the potentially exposed population was estimated by applying a dasymetric distribution. The results lead to the conclusion that, in the study area, the elderly are those who are most exposed to debris flows. Furthermore, the time lapse between the debris flows initiation and the arrival at the buildings at risk was estimated, allowing to account for the overall number of buildings where the evacuation time takes longer than the debris flows arrival. Additionally, the safe areas within the study area were identified, and several safe public buildings with the capacity to gather a large number of persons were selected. Considering that the study area is located in a mountain region, characterized by steep slopes, the evacuation modelling was performed based on an anisotropic approach, in order to consider the influence of slope direction on travel costs. At the end, three pedestrian evacuation travel time scenarios, based on different walking speeds to accommodate residents with different ages in safer places, were compared and the results mapped. The implemented methodology is not local dependent, which allows its reproduction elsewhere.

[7]

Rodríguez

Morata C

, Villacorta

, Stoffel

, et al. Assessing strategies to mitigate debris-flow risk in Abancay province, south-central Peruvian Andes
Geomorphology, 2019,342:127-139.

[本文引用: 1]

[8]

Miao

, Liu

. Characterization of acceptable risk for debris flows in China: Comparison in debris-flow prone areas and nonprone areas
International Journal of Disaster Risk Reduction, 2020,42:101405. Doi: 10.1016/j.ijdrr. 2019.101405.

[本文引用: 1]

[9]

Liu

, Miao

, Guo

. Acceptability of debris-flow disasters: Comparison of two case studies in China
International Journal of Disaster Risk Reduction, 2019,34:45-54.

[本文引用: 1]

[10]

Winter

M G

. A strategic approach to debris flow risk reduction on the road network
Procedia Engineering, 2016,143:759-768.

[本文引用: 1]

[11]

Chen

H X

, Li

, Feng

S J

, et al. Simulation of interactions between debris flow and check dams on three-dimensional terrain
Engineering Geology, 2019,251:48-62.

[本文引用: 1]

[12]

Cucchiaro

, Cazorzi

, Marchi

, et al. Multi-temporal analysis of the role of check dams in a debris-flow channel: Linking structural and functional connectivity
Geomorphology, 2019,345:106844. Doi: 10.1016/j.geomorph. 2019.106844.

[本文引用: 1]

[13]

Zhao

Yan

, Meng

Xingmin

, Zheng

Jiaoyu

. Application of geomorphological theory in study of debris flow and exploration of its applied theory
Journal of Catastrophology, 2017,32(1):43-49.

[本文引用: 1]

[ 赵岩, 孟兴民, 郑娇玉, 等. 地貌学在泥石流研究中的应用与理论初探
灾害学, 2017,32(1):43-49.]

[本文引用: 1]

[14]

Singh

, Gupta

, Singh

. Hydrological inferences from watershed analysis for water resource management using remote sensing and GIS techniques
The Egyptian Journal of Remote Sensing and Space Science, 2014,17(2):111-121.

[本文引用: 1]

[15]

Zhang

P Z

, Shen

Z K

, Wang

, et al. Continuous deformation of the Tibetan Plateau from Global Positioning System Data
Geology, 2004,32(9):809-812.

[本文引用: 1]

[16]

Wang

. Geological environment and sisasters along railway line in the Qinghai-Tibet Plateau
Earth Science Frontiers, 2007,14(6):31-37.

[本文引用: 1]

[17]

Huang

Jiangcheng

, Ou

Guoqiang

, Pan

Huali

. Geomorphic evolution of comparison on debris flow gullies in Bailongjiang and Xiaojiang basins
The Chinese Journal of Geological Hazard and Control, 2014,25(1):6-11.

[本文引用: 1]

[ 黄江成, 欧国强, 潘华利. 白龙江与小江泥石流流域地貌演化比较分析
中国地质灾害与防治学报, 2014,25(1):6-11.]

[本文引用: 1]

[18]

Yao

Tandong

, Yu

Wusheng

, Wu

Guangjian

, et al. Glacier anomalies and relevant disaster risks on the Tibetan Plateau and surroundings
Chinese Science Bulletin, 2019,64(27):2770-2782.

[本文引用: 1]

[ 姚檀栋, 余武生, 邬光剑, 等. 青藏高原及周边地区近期冰川状态失常与灾变风险
科学通报, 2019,64(27):2770-2782.]

[本文引用: 1]

[19]

Seong

Y B

, Owen

L A

, Yi

, et al. Geomorphology of anomalously high glaciated mountains at the northwestern end of Tibet: Muztag Ata and Kongur Shan
Geomorphology, 2009,103(2):227-250.

[本文引用: 1]

[20]

Wang

Jie

, Zhou

Shangzhe

, Zhao

Jingdong

, et al. Quaternary glacial geomorphology and glaciations of Kongur Mountain, eastern Pamir, China
Scientia Sinica (Terrae), 2011,41(3):350-361.

[本文引用: 1]

[ 王杰, 周尚哲, 赵井东, 等. 东帕米尔公格尔山地区第四纪冰川地貌与冰期
中国科学: 地球科学, 2011,41(3):350-361.]

[本文引用: 1]

[21]

Winiger

, Gumpert

, Yamout

. Karakorum-Hindukush-western Himalaya: Assessing high-altitude water resources
Hydrological Processes, 2005,19(12):2329-2338.

[本文引用: 1]

[22]

Zhao

Xin

, Cheng

Zunlan

, Liu

Jiankang

, et al. Hazard degree assessment on site-specific debris flows in Dongchuan of Yunnan Province
Journal of Catastrophology, 2013,28(1):102-106.

[本文引用: 1]

[ 赵鑫, 程尊兰, 刘建康, 等. 云南东川地区单沟泥石流危险度评价研究
灾害学, 2013,28(1):102-106.]

[本文引用: 1]

[23]

Jun

, Wang

Zhaoyin

, Li

Zhiwei

, et al. A preliminary study on spinulose stream networks in the Tongde Basin of the Yellow River source
Journal of Arid Land Resources and Environment, 2014,28(2):129-135.

[本文引用: 1]

[ 杜俊, 王兆印, 李志威, 等. 黄河源同德盆地刺状水系初步研究
干旱区资源与环境, 2014,28(2):129-135.]

[本文引用: 1]

[24]

Yang

Dayuan

, Wu

Shengguang

, Wang

Yunfei

. On river terraces of the upper reaches of the Huanghe River and change of the river system
Scientia Geographica Sinica, 1996,16(2):137-143.

[本文引用: 1]

[ 杨达源, 吴胜光, 王云飞. 黄河上游的阶地与水系变迁
地理科学, 1996,16(2):137-143.]

[本文引用: 1]

[25]

Singh

, Thakur

J K

, Singh

. Morphometric analysis of Morar River Basin, Madhya Pradesh, India, using remote sensing and GIS techniques
Environmental Earth Sciences, 2013,68(7):1967-1977.

[本文引用: 1]

[26]

Dai

F C

, Lee

C F

. Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong
Geomorphology, 2002,42(3):213-228.

[本文引用: 1]

[27]

Abdallah

, Chorowicz

, Bou

Kheir R

, et al. Detecting major terrain parameters relating to mass movements' occurrence using GIS, remote sensing and statistical correlations, case study Lebanon
Remote Sensing of Environment, 2005,99(4):448-461.

[本文引用: 1]

[28]

Wan

, Lei

T C

, Huang

P C

, et al. The knowledge rules of debris flow event: A case study for investigation Chen Yu Lan River, Taiwan
Engineering Geology, 2008,98(3):102-114.

[本文引用: 1]

[29]

Pike

, Wilson

. Elevation-relief ratio, hypsometric integral, and geomorphic area-altitude analysis
Geological Society of America Bulletin, 1971,82(4):1079-1084.

[本文引用: 1]

[30]

Jiang

Zhongxin

. A statistical analysis on longitudinal profile shape of debris flow valley along Palongzangbu River in Tibet
The Chinese Journal of Geological Hazard and Control, 2001,12(4):41-47.

[本文引用: 1]

[ 蒋忠信. 西藏帕隆藏布泥石流沟谷纵剖面形态统计分析
中国地质灾害与防治学报, 2001,12(4):41-47.]

[本文引用: 1]

[31]

Basu

, Pal

. RS-GIS based morphometrical and geological multi-criteria approach to the landslide susceptibility mapping in Gish River Basin, West Bengal, India
Advances in Space Research, 2019,63(3):1253-1269.

[本文引用: 1]

[32]

Zhiqiang

, Li

Weiquan

, Chen

Zishen

, et al. Influencing factors and classifications of arc-shaped coasts in South China
Acta Geographica Sinica, 2014,69(5):595-606.

[本文引用: 1]

[ 李志强, 李维泉, 陈子燊, 等. 华南岬间弧形海岸平面形态影响因素及类型
地理学报, 2014,69(5):595-606.]

[本文引用: 1]

[33]

Yang

Zhigang

, Zhuoma, Lu

Hongya

, et al. Characteristics of precipitation variation and its effects on runoff in the Yanglung Zangbo River basin during 1961-2010
Journal of Glaciology and Geocryology, 2014,36(1):166-172.

[本文引用: 1]

[ 杨志刚, 卓玛, 路红亚, 等. 1961—2010年西藏雅鲁藏布江流域降水量变化特征及其对径流的影响分析
冰川冻土, 2014,36(1):166-172.]

[本文引用: 1]

[34]

Zhang

Wancheng

, Xiao

Ziniu

, Zheng

Jianmeng

, et al. Characteristics of the Nujiang River runoff for a long term and its response to climate change
Chinese Science Bulletin, 2007,52(Suppl.II):135-141.

[本文引用: 1]

[ 张万诚, 肖子牛, 郑建萌, 等. 怒江流量长期变化特征及对气候变化的响应
科学通报, 2007,52(增刊II):135-141.]

[本文引用: 1]

[35]

Tate

E L

, Farquharson

F A K

. Simulating reservoir management under the threat of sedimentation: The case of Tarbela Dam on the River Indus
Water Resources Management, 2000,14(3):191-208.

DOI:10.1023/A:1026579230560 URL [本文引用: 1]

The useful life of Tarbela reservoir, on the River Indus, is threatened by a sediment delta which is approaching the dam'sintake tunnels; these lead to a hydroelectric power station and are used for irrigation releases. This article describes thesimulated system, involving Tarbela Dam, with Ghazi Barotha hydropower scheme downstream, and the planned construction of Basha Dam upstream. This study formed an innovative approachwhich enabled the relationship between demands and supply in the basin to be studied, under a range of development and operating scenarios, and to different time horizons. A computer software package, 'Hydro', was used to perform systemsimulation modelling of Tarbela Dam and the Upper Indus Basin,Pakistan. The results enabled estimation of the economic benefits of several potential future operating strategies forTarbela to be tested and compared. Employing the results of associated sediment modelling, projected storage/elevation curves were used to predict the irrigation and power benefitsavailable to Pakistan over the coming sixty years. It wassubsequently demonstrated that the most beneficial remedial measures are an underwater dike or dam to protect the intakes,and low-level flushing facilities.]]>

[36]

Tang

, Jiang

, Li

. Seismic landslide evolution and debris flow development: A case study in the Hongchun Catchment, Wenchuan area of China
Engineering Geology for Society and Territory, 2015,2:445-449.

[本文引用: 1]

[37]

Tang

, Zhu

, Li

W L

, et al. Rainfall-triggered debris flows following the Wenchuan earthquake
Bulletin of Engineering Geology and the Environment, 2009,68(2):187-194.

[本文引用: 1]

[38]

, Wang

, Qi

, et al. Disaster chains initiated by the Wenchuan earthquake
Environmental Earth Sciences, 2012,65(4):975-985.

[本文引用: 1]

[39]

Wang

, Cui

, Wang

. Mass movements triggered by the Wenchuan earthquake and management strategies of quake lakes
International Journal of River Basin Management, 2009,7(4):391-402.

[本文引用: 1]

[40]

Cui

Peng

, Wei

Fangqiang

, Chen

Xiaoqing

, et al. Geo-hazards in Wenchuan earthquake area and countermeasures for disaster reduction
Bulletin of the Chinese Academy of Sciences, 2008,23(4):317-323.

[本文引用: 1]

[ 崔鹏, 韦方强, 陈晓清, 等. 汶川地震次生山地灾害及其减灾对策
中国科学院院刊, 2008,23(4):317-323.]

[本文引用: 1]

[41]

Tang

Chuan

. Activity tendency prediction of rainfall induced landslides and debris flows in the Wenchuan Earthquake areas
Mountain Research, 2010,28(3):341-349.

[本文引用: 1]

[ 唐川. 汶川地震区暴雨滑坡泥石流活动趋势预测
山地学报, 2010,28(3):341-349.]

[本文引用: 1]

[42]

Cheng

, Wang

, Zhao

, et al. Relative tectonics and debris flow hazards in the Beijing mountain area from DEM-derived geomorphic indices and drainage analysis
Geomorphology, 2016,257:134-142.

[本文引用: 1]

[43]

Hack

J T

. Stream-profile analysis and stream-gradient index
Journal Research of United States Geological Survey, 1973,1(4):421-429.

[本文引用: 1]

[44]

Seeber

, Gornitz

. River profiles along the Himalayan arc as indicators of active tectonics
Tectonophysics, 1983,92(4):335-367.

[本文引用: 1]

[45]

Nefeslioglu

H A

, Duman

T Y

, Durmaz

. Landslide susceptibility mapping for a part of tectonic Kelkit Valley (Eastern Black Sea region of Turkey)
Geomorphology, 2008,94(3):401-418.

[本文引用: 1]

[46]

Gokceoglu

, Sonmez

, Nefeslioglu

H A

, et al. The 17 March 2005 Kuzulu landslide (Sivas, Turkey) and landslide-susceptibility map of its near vicinity
Engineering Geology, 2005,81(1):65-83.

[本文引用: 1]

[47]

Kim

, Sharma

. The role of floodplain topography in deriving basin discharge using passive microwave remote sensing
Water Resources Research, 2019,55(2):1707-1716.

[本文引用: 1]

[48]

Lyu

Liqun

, Wang

Zhaoyin

, Xu

Mengzhen

, et al. Geomorphic characters of debris flow fans along Nu River and the river blocking mechanisms
Journal of Hydraulic Engineering, 2016,47(10):1245-1252.

[本文引用: 1]

[ 吕立群, 王兆印, 徐梦珍, 等. 怒江泥石流扇地貌特征与扇体堵江机理研究
水利学报, 2016,47(10):1245-1252.]

[本文引用: 1]

[49]

Comiti

, Mao

, Penna

, et al. Glacier melt runoff controls bedload transport in alpine catchments
Earth and Planetary Science Letters, 2019,520:77-86.

DOI:10.1016/j.epsl.2019.05.031 URL [本文引用: 1]

[50]

Wang

, Guo

. Precipitable water conversion rates over the Qinghai-Xizang (Tibet) Plateau: Changing characteristics with global warming
Hydrological Processes, 2012,26:1509-1516.

[本文引用: 1]

[51]

Yao

Tandong

, Wu

Guangjian

, Xu

Baiqing

, et al. Asian water tower change and its impacts
Bulletin of the Chinese Academy of Sciences, 2019,34(11):1203-1209.

[本文引用: 1]

[ 姚檀栋, 邬光剑, 徐柏青, 等. “亚洲水塔”变化与影响
中国科学院院刊, 2019,34(11):1203-1209.]

[本文引用: 1]

[52]

Fei

, Jia

Yangwen

, Niu

Cunwen

, et al. Variation character of annual, seasonal and monthly temperature and precipitation
Mountain Research, 2018,36(2):171-183.

[本文引用: 1]

[ 徐飞, 贾仰文, 牛存稳, 等. 横断山区气温和降水年季月变化特征
山地学报, 2018,36(2):171-183.]

[本文引用: 1]

[53]

Lin

, Li

Xiaodong

, Xiao

Ruixiang

, et al. The heterogeneity of climate change and its genesis in the northeastern Qinghai-Tibet Plateau
Journal of Natural Resources, 2019,34(7):1496-1505.

[本文引用: 1]

[ 李林, 李晓东, 校瑞香, 等. 青藏高原东北部气候变化的异质性及其成因
自然资源学报, 2019,34(7):1496-1505.]

[本文引用: 1]