Simulation prediction and risk evaluation of debris flow in gullyprone ditches of Lajing Village, Lanping County, Yunnan Province, China
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摘要:
兰坪县位于云南省西北部,地质环境不良,近年来该地区受降雨影响泥石流灾害频发,但是该地区缺乏较为精确的灾害风险评价。为对该地区泥石流灾害进行防范预警,文章应用FLO-2D软件对兰坪县啦井村1#典型泥石流河灾害进行动力过程反演分析,基于反演所得模拟参数对2#沟在20年、50年和100年三种降雨重现期工况进行预测分析和灾害风险评价。结果表明:啦井村2#沟道泥石流淤积深度和最大流速随降雨强度的增大呈增加趋势,极端降雨条件下沟道底部淤积深度将超过2.5 m,流通区最大流速将大于5 m/s,泥石流携带更多的松散物于堆积区堆积,易造成安全隐患;啦井村2#沟中高风险区主要分布在沟道中流速泥深较大、沟道周围民房较为集中位置以及泥石流堆积区域。研究结果可为该地区防灾减灾工程与泥石流早期预警等研究提供一定参考。
Abstract:Lanping County, located in the northwestern part of Yunnan Province, is characterized by unfavorable geological conditions. In recent years, debris flow disasters have frequently occurred in this area due to the influence of rainfall, yet there is a lack of accurate disaster risk evaluations. To enhance early warning preparedness for debris flow disasters in the region, the FLO-2D model was employed to perform an inverse analysis of a historical debris flow event in Lajing Village, Lanping County. Based on the parameters obtained from this analysis, predictions of the dynamic characteristics and risk assessments were conducted for another debris flow-prone gully under three rainfall recurrence period conditions: 20, 50 and 100 years. The results indicate that in Gully No. 2 of Lajing Village, the siltation depth and maximum flow velocity of debris flow increase with the intensification of rainfall. Under extreme rainfall conditions, the siltation depth at the trench bottom is expected to exceed 2.5 m, and the maximum flow velocity in the transportation zone may exceed 5 m/s, leading to the accumulation of more loose materials in the deposition area and creating significant safety hazards. The high-risk zones in gully No. 2 are primarily located in areas with high flow velocity and mud depth, around densely populated residential areas near the gully, and within the debris flow accumulation zone. The findings of this study provide valuable references for disaster prevention and mitigation engineering, as well as for early warning systems in the region.
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Keywords:
- debris flow /
- FLO-2D /
- numerical simulation /
- dynamic analysis /
- risk evaluation
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0. 引言
泥石流作为山区沟谷环境的典型灾害特征,是主要由降雨引起的边坡固态物质向流态化运动转变的过渡过程,常常伴随着洪水发生。据统计,1950—2016年中国共发生318起致死性泥石流灾害,占全国致死性崩滑流地质灾害总数的16.6%,每年因泥石流灾害而造成的经济损失超过30亿元,死亡人数在百人以上[1 − 2]。云南省降水诱发的地质灾害表现为点多面广、地质灾害类型复杂多样的特征[3],其中泥石流多发生在山区,展开泥石流预测和风险评价的工作十分必要。
泥石流动力冲击效应是造成灾害影响严重的主要原因,目前学者主要采用模型试验和数值模拟手段对泥石流运移过程中的冲击动力特性进行研究[4]。计算机技术的发展为应用数值模拟研究泥石流动力过程提供了有效工具,数值模拟逐渐成为精细化评价泥石流危险性的常用手段,相关的模拟软件有RAMMS、Massflow、FLO-2D等[5 − 10]。Shen等[11]通过利用Massflow模型对红椿沟泥石流进行模拟,提供了模拟软件作为有效工具来量化已有拦挡措施效率的新思路。刘军友[12]采用FLO-2D、CFX等三种软件,模拟分析岷县耳阳河流域泥石流活动强度,对比研究表明FLO-2D泥石流模拟最为准确。数值模拟可揭示泥石流灾害动力过程,为泥石流灾害定量风险评估、防灾减灾提供有效依据。
经过近30年的发展,泥石流风险评价研究已取得很大进展,评价方法逐步由定性、半定量向定量研究发展。层次分析法、信息熵法等先后应用于泥石流危险度研究,为防灾减灾工作提供参考并取得较好效果[13 − 14],此外还有GIS评价法[15]、机器深入学习法[16]、模糊综合评判法[17]等。胡凯衡等[18]、崔鹏等[19 − 21]等对四川、云南等地区泥石流进行考察,提出有效的泥石流风险分析方法和防治手段,部分学者基于数值模拟结果依据不同风险指标对灾害区进行危险性划分[21 − 26]。本次风险评价为单沟泥石流风险评价,一般考虑为危险性与易损性叠加[27]。
云南省兰坪县发育较多沟谷型泥石流,较为陡峻的地形地貌以及较为频繁的降雨使得泥石流灾害频发。为进一步加强对兰坪县泥石流灾害的风险评价,选取兰坪县啦井村发育的2条泥石流作为研究对象,FLO-2D软件模型因具有操作简单、对泥石流流变时空变化特征及运动过程模拟较为准确等优点,本文利用FLO-2D软件对云南省兰坪县啦井村泥石流灾害进行动力学反演和模拟预测,基于模拟结果应用层次分析风险评价对这一典型泥石流隐患点进行危险性分区,研究结果可为该地区泥石流灾害的风险防范和治理提供借鉴。
1. 研究区概况
兰坪县全称兰坪白族普米族自治县,位于云南省西北部、怒江傈僳族自治州东部,地处滇西横断山脉中段,怒山山脉与云岭山脉过渡地带,见图1(a)。总体地势北高南低,最高点为西北端的老窝山山顶,海拔
4435.4 m,最低点位于县境最南端澜沧江江面,海拔1365 m,相对高差3070.4 m。整个地区地形起伏较大,呈现高山与峡谷交错地貌,自北向南纵向延伸,自西向东大致平行分布。研究区地形起伏大,高山峡谷相间排列,由北向南延伸,由西向东大致平行展布。西部由怒山山脉与云岭山脉夹持澜沧江,形成强烈构造侵蚀高山峡谷地貌,东部为云岭山脉分支腹地夹澜沧江一级支流通甸河和沘江,形成构造侵蚀高中山及槽谷地貌。
研究区域上属澜沧江水系,啦井河为澜沧江左岸一级支流。长23.1 km,汇水面积233.0 km2。河流纵坡降5.65 %。据长期观测资料,雨季最大流量74.70 m3/s,旱季最枯流量0.48 m3/s,河宽13 m左右,在河谷中可见0.2~0.8 m高的跌水坎,河谷断面呈“V”型,谷坡坡度25°~50°。区域地处滇西北三江褶皱系的兰坪—思茅中坳陷北部,从地层发育情况看,境内主要以新生界和中生界地层最为发育,主要为砾岩、砂岩和泥质岩类等。兰坪地区晚近纪以来构造运动强烈,其中新近系和第四系地层分布和岩性特征表现显著,中新世时期新构造运动为上升运动,上新世时期新构造运动为下降运动,第四系以来,新构造运动主要表现为间歇性上升运动。
在近20年来,兰坪县共发生8次泥石流灾害,造成一定的人员伤亡和经济损失。本文关注2011和2014年发生在兰坪县啦井镇啦井村的泥石流灾害。怒江州于2011年6月15日开始降雨,日降雨量达28.7 mm/d,至6月16日,暴雨强度最大达45 mm/h。2011年6月16日上午6时,怒江州兰坪县啦井镇啦井村发生泥石流灾害,泥石流主要发生在1#沟,见图1(b)。泥沙堆积于沟道内及公路上,堆积面积约0.3×104 m2,淤积厚度约1 m,此次灾害冲出物体积达0.3×104 m3,容重达1.60~1.70 t/m3,为黏性泥石流。此次泥石流共造成14户农户受灾,预计直接经济损失15万元。2014年8月4日兰坪县再次出现暴雨,8月5日早上5时许,兰坪县啦井镇1#沟发生泥石流灾害,日降雨量达15 mm/d,大量洪水夹杂沙石块冲向沟口,见图1(c)。本次泥石流灾害持续1 h左右,泥沙及淤泥堆积于沟道内及公路上,堆积面积约0.5×104 m2,淤积厚度约1 m,冲出物达0.5×104 m3。该次泥石流造成311省道临时中断,260 m村内道路和6栋房屋受损,经济损失60多万元。
目前,2#沟尚未发生泥石流灾害,但于强降雨条件下发生过洪水及高含沙水流。根据现场调查结果显示,目前该沟道内存在丰富物源条件,见图1(d),一旦受到暴雨诱发,沟道内堆积区物源可能参与泥石流活动,威胁沟口136户约600名居民的生命财产安全,并可能造成630 m公路拥堵,潜在损失巨大。
2. 灾害动力过程分析
2.1 计算原理及模型建立
FLO-2D是一款模拟洪涝灾害的数值模型,是O’Brien于1988年开发的基于非牛顿流体模型及中央有限差分数值方法的泥石流模拟软件,能较完整的分析泥石流的运动状态特征。可用来模拟洪水灾害,适用于都市淹水、工程风险设计、桥梁涵洞水利演算等情况。该软件所模拟模型采用全动态波动动量方程和8种可能流向的中心在限差分路径选择方案,在正方形网格单元系统中预测洪水波过程。
通过动量方程和连续性方程,可以计算出每个网格单元中沿x、y方向的流体速度和堆积深度,从而获取流体运动范围。模型如下:
(1)运动方程:
$$ i=\frac{\partial h}{\partial t}+\frac{\partial \left(\lambda h\right)}{\partial x}+\frac{\partial \left(\theta h\right)}{\partial y} $$ (1) 式中:i——降雨强度/(m·h−1);
h——流体流深/m;
t——泥石流流域降雨历时/h;
λ、θ——x、y轴方向上的平均流速/(m·s−1)。
(2)连续方程:
$$ s_{ox}-s_{\mathrm{f}x}=\lambda\frac{\partial\lambda}{\partial x}+\theta\frac{\partial\theta}{\partial x}+g\frac{\partial h}{\partial t}+\frac{\partial\lambda}{\partial t} $$ (2) $$ s_{oy}-s_{\mathrm{f}y}=\lambda\frac{\partial\lambda}{\partial y}+\theta\frac{\partial\theta}{\partial y}+g\frac{\partial h}{\partial t}+\frac{\partial\theta}{\partial t} $$ (3) 式中:Sox、Soy——x、y方向的泥石流沟床坡降/‰;
Sfx、Sfy——泥石流沟x、y方向的摩擦坡降/‰;
g——重力加速度/(m·s−2)。
2.2 模拟参数确定
对于云南省兰坪县泥石流1#、2#沟道进行现场调查,获取沟道实际流域面积、沟长、平均坡降等实际调查数据,得到结果如表1所示。
表 1 沟道现场调查数据Table 1. The site investigation data of each ditch参数 流域面积/km2
(1#/2#)沟长/ km
(1#/2#)平均坡降/‰
(1#/2#)取值 0.96/0.99 2.11/2.08 301/432 数字地面模型是地表的数字表达,是泥石流数值模拟基础文件,其范围和精度直接影响着模拟的精度,啦井村1#、2#泥石流模拟使用工作区高精度地形底图,将其导入在ArcGIS软件中矢量化为最优化不规则三角网模型,再运用转换工具转换为数字高程模型,进一步转换为数值分析所需求的ASCII地形文件[28 − 30]。
曼宁系数代表坡面或沟道的粗糙程度。其大小与地面的粗糙度、沟道的起伏度和植物生长情况等相关,其计算公式:
$$ {n}_{\mathrm{c}}=0.033{R}_{\mathrm{n}\mathrm{s}}^{-0.51}\mathrm{e}^{(0.34{R}_{\mathrm{n}\mathrm{s}}^{0.17})\mathrm{ln}h} $$ (4) 式中:nc——曼宁系数;
Rns——泥石流的体积浓度/%;
h——泥石流泥深/m,均根据泥石流堆积扇的厚度 确定。
黏滞系数(n)与屈服应力(τy)这2个参数的变化主要与泥沙浓度的变化有关,屈服应力和黏度作为含沙量的函数,其经验关系式如下:
$$ n={\alpha }_{1}{\mathrm{e}}^{{\beta }_{1}{c}_{\mathrm{v}}} $$ (5) $$ {\tau }_{y}={\alpha }_{2}{\mathrm{e}}^{{\beta }_{2}{c}_{\mathrm{v}}} $$ (6) 式中:${\alpha }_{1} $、${\alpha }_{2} $、${\beta }_{1} $、${\beta }_{2} $——流变系数;
cv——泥沙体积浓度/%。
根据野外调查及经验取值,式中选用参数如表2所示。
表 2 流变系数Table 2. Rheological coefficient参数 α1 β1 α2 β2 取值 0.811 13.72 0.00462 11.24 泥石流在较高体积浓度和屈服应力的作用下会出现分层流动的现象,而层流间的摩擦系数用K表示,取值范围如表3所示,其中研究区地面为稀疏植被,故本次模拟中选择K为2 280。
表 3 FLO-2D手册建议的层流阻力系数值Table 3. Recommended laminar flow resistance coefficient values from the FLO-2D manual地面条件 K值范围 级配土 90~400 被侵蚀黏土 100~500 稀疏植被 1000 ~4000 矮草原 3000 ~10000 根据《泥石流灾害防治工程勘查规范》(DZ/T 0220—2006)[31]及现场调查推测,泥石流的重度为1.60~1.80 t/m3,本模拟选取泥石流重度参数为1.65 t/m3。
模拟计算所需的参数通过现场调查以及查阅FLO-2D手册确定,通过泥石流灾害动力模拟对参数进行调整和修正,最终参数取值见表4。
表 4 FLO-2D数值模型主要物理力学参数Table 4. Main physical and mechanical parameters of the FLO-2D numerical model参数 曼宁
系数摩擦
系数泥石流重度
/(t·m−3)黏滞系数
(1#/2#)屈服应力kPa
/(1#/2#)取值 0.07 2280 1.65 3644.13 /1860.49 4.53/2.62 2.3 数值模拟结果及分析
2014年啦井村1#沟泥石流实际情况冲出沟口120 m左右,堆积区平面上呈“喇叭状”,上窄下宽,上部宽15~20 m,下部宽150~170 m,最大流速达到6.11 m/s。应用2014年8月4日啦井村降雨工况对啦井村1#沟泥石流进行动力学过程模拟如图2所示,结果显示啦井村1#泥石流在沟口形成了大量松散堆积物堆积,最大的淤积深度为4.84 m,在上游沟道窄陡处流速达到8.14 m/s。泥石流威胁区范围内平均淤积深度为1.91 m,平均流速为1.67 m/s,泥石流冲出沟口约100 m,少量泥沙淤积至河道,可能会造成堵江风险,模拟结果与证明了模拟参数的适配性和数值模拟的可行性。故利用模拟反演所获得参数对啦井村2#泥石流沟进行不同降雨重现周期泥石流动力学模拟,并基于模拟结果对该沟道泥石流灾害进行风险性评价[32]。
啦井村2#沟泥石流模拟结果如图3—4所示。结果显示,在20年降雨重现期工况下,啦井村2#泥石流沟松散堆积物主要堆积于沟内,少量泥沙冲出沟口,沟内最大淤积深度为2.61 m,最大流速4.21 m/s。泥石流影响区范围内平均淤积深度为0.87 m,平均流速为0.74 m/s,将对沟口的道路以及少量房屋造成淤埋。在50年降雨重现期工况下,啦井村2#泥石流沟松散堆积物主要堆积于沟口,最大淤积深度为3.24 m,在上游沟道窄陡处流速高达6.14 m/s。泥石流影响区范围内平均淤积深度为1.42 m,平均流速为1.01 m/s。根据模拟结果可知,泥石流在50年一遇暴雨条件下冲出沟口约60 m,少量泥沙淤积至河道,可能会造成堵江风险。在100年降雨重现期工况下,松散堆积物在沟道内开始淤积,沟口最大淤积深度为5.24 m,平均淤积深度为1.41 m,泥石流堆积范围较大,冲出沟口约200 m,对沟口大量房屋造成淤埋,且在沟口形成大面积淤积,泥沙冲出体积约0.8×104 m³。泥沙淤积至河道,河道中泥沙的最大淤积深度为4.33 m,易造成河道堵塞。
沟道纵坡陡峭地段的泥石流模拟结果显示:泥石流流量越大,会导致携带更多松散物于堆积区漫流堆积,最终导致堆积范围和强度增大;因泥石流淤积深度和最大流速自堆积区中心向两侧逐渐减低,泥石流强度由内向外呈现降低趋势[33]。
3. 灾害风险评价
3.1 危险性评价及易损性评价
泥石流危险性指的是人类及其周围环境受到泥石流损害的可能性大小。泥石流危险性评价是制定泥石流灾害防治决策的前提。本文根据20年一遇、50年一遇和100年一遇降雨重现期工况模拟结果,将模拟的泥深、流速作为评价的基本依据,然后根据学者常鸣等[26]提出的强度划分标准(表5),得出不同降雨频率条件下的泥石流强度分布,然后结合泥石流强度与重现周期,进行危险性评价等级分区[34]。
表 5 泥石流强度影响划分表[26]Table 5. Classification table of debris flow intensity impacts泥石流强度 泥深/m 关系 泥深与最大流速乘积/(m2·s−1) 高 H≥2.5 OR VH≥2.5 中 0.5≤H<2.5 AND 0.5≤VH<2.5 低 0<H<0.5 AND VH<0.5 易损性是指受灾体遭受地质灾害破坏的机会多少以及发生损毁的难易程度,反映了社会经济系统对地质灾害的响应能力,包括受灾体对灾害活动的敏感程度和承受能力。由于威胁区承灾体的复杂性,根据《地质灾害风险调查评价技术要求》,评价地质灾害承灾体易损性,根据现场对工作区范围内承灾体详细调查结果,将易损性评价指标分为4大类进行选取:社会易损性、物质易损性、经济易损性、环境易损性。社会易损性的人口密度评价指标数据、人口年龄结构与人口受教育程度指标可通过实地调查获得;物质易损性评价指标数据的获取主要根据卫星影像精细遥感解译及现场实地调查;经济易损性值可由区域内承灾体年均收入得到;环境易损性指标主要根据室内遥感解译得到,并在野外调查时复核修正(表6)。
表 6 易损性计算公式Table 6. Vulnerability calculation formula易损性指标 社会易损性 建筑易损性 交通易损性 经济易损性 表达式 $F = \displaystyle\sum_{{{i}} = 1}^n {{F_{i,j}}} $
F为社会易损性;Fi,j为主级指标
权重标准化的值乘以次级
指标权重标准化的值$M = \displaystyle\sum_{{{i}} = 1}^n {{A_{i,j}}} $
M为物质易损性值(建筑/交通);
Ai,j为承灾体主级指标权重标准化
的值乘以次级指标权重标准化的值$J = G/N$
J为经济易损性,无量纲,G为区域内每个
承灾体家庭年收入(万元);
N为区域人均年收入(万元)权重按照层次分析法计算原理计算得到:社会易损性(
0.4626 )、建筑易损性(0.2378 )、交通易损性(0.1973 )、经济易损性(0.1023 ),得到综合易损性指数。3.2 风险评价结果及分析
近年来,泥石流形成机理与形成条件研究取得了突破性进展,已建立了典型地区的泥石流信息系统,从而把泥石流预测建立在泥石流形成机理与发生条件的基础上。泥石流灾害风险可用风险度来衡量,联合国将灾害的风险度定义为危险度与易损度的乘积:
$$ R=H\cdot V $$ (7) 式中:R——泥石流风险度;
H——泥石流危险度;
V——泥石流影响下受灾体的易损度。
根据泥石流强度影响及危险性分区标准,在ArcGIS中使用栅格计算工具,通过重分类工具将低危险、中危险、高危险的属性分别赋值,得到啦井村泥石流危险性评价图,见图5(a)。将不同类型承灾体易损性按照权重值叠加各易损性图层,按照自然断点原则将其划分为极高、高、中、低易损性,最后得到啦井村2#泥石流沟易损性分布图,见图5(b)。
20年重现周期下急坡街2#仅有少量泥沙冲出,对下游居民房屋的危害较小,主要以低中风险为主;50年重现周期下急坡街2#泥石流沟道内为低中风险区,民房集中区、重要道路位置为中风险,高风险区域为堆积区;100年重现周期下急坡街2#泥石流沟道内为低中风险区,高风险主要分布于堆积区。
将地质灾害的危险性和易损评价结果叠加,根据现场调查可知,泥石流上游沟道两侧斜坡坡体崩滑物源发育较多,新增物源较为丰富,利用GIS的功能将泥石流危险性分区与承灾体易损性分区叠加计算,得到泥石流风险分区图,见图5(c)。
由评价结果可知,由于泥石流物质在沟道上游沿原始沟道运动,主要对沟道两侧的岸坡造成影响,在沟道局部拐弯处会对岸坡产生强烈冲刷。此外,沟口处由于民房聚集,对居民生命安全将造成巨大威胁。啦井村泥石流堆积范围较宽,对周围房屋建筑、公路直接造成威胁,泥石流对下游居民房屋的危害较小,主要以低中风险为主,易损性较低;在沟道中流速、泥深较大位置存在少量高风险,易损性较高。
4. 结论
(1)模拟结果表明在啦井村2#沟道泥石流淤积深度和最大流速随降雨强度的增大呈不断增加的趋势,堆积物深度和范围逐步增大,灾害区域和程度逐步增大。
(2)通过开展啦井村泥石流灾害风险预测发现,随着流量增大,泥石流携带更多的松散物于堆积区漫流堆积,最终导致堆积范围和强度增大;因泥石流泥深和流速由堆积区中心向两侧逐渐减低,泥石流强度由内向外呈降低的趋势。
(3)将模拟的泥深、流速作为评价的基本依据,根据不同频率的降雨强度,将泥石流强度与重现周期相结合,进行风险评价。研究表明,啦井村2#沟较高风险区主要分布于沟道中流速大、淤积深度大的区域,而下游居民区受灾风险相对较低。评价区内人口密集,潜在人口风险较大,研究成果可有效服务泥石流影响区的国土空间规划和防灾减灾工作。
-
表 1 沟道现场调查数据
Table 1 The site investigation data of each ditch
参数 流域面积/km2
(1#/2#)沟长/ km
(1#/2#)平均坡降/‰
(1#/2#)取值 0.96/0.99 2.11/2.08 301/432 表 2 流变系数
Table 2 Rheological coefficient
参数 α1 β1 α2 β2 取值 0.811 13.72 0.00462 11.24 表 3 FLO-2D手册建议的层流阻力系数值
Table 3 Recommended laminar flow resistance coefficient values from the FLO-2D manual
地面条件 K值范围 级配土 90~400 被侵蚀黏土 100~500 稀疏植被 1000 ~4000 矮草原 3000 ~10000 表 4 FLO-2D数值模型主要物理力学参数
Table 4 Main physical and mechanical parameters of the FLO-2D numerical model
参数 曼宁
系数摩擦
系数泥石流重度
/(t·m−3)黏滞系数
(1#/2#)屈服应力kPa
/(1#/2#)取值 0.07 2280 1.65 3644.13 /1860.49 4.53/2.62 表 5 泥石流强度影响划分表[26]
Table 5 Classification table of debris flow intensity impacts
泥石流强度 泥深/m 关系 泥深与最大流速乘积/(m2·s−1) 高 H≥2.5 OR VH≥2.5 中 0.5≤H<2.5 AND 0.5≤VH<2.5 低 0<H<0.5 AND VH<0.5 表 6 易损性计算公式
Table 6 Vulnerability calculation formula
易损性指标 社会易损性 建筑易损性 交通易损性 经济易损性 表达式 $F = \displaystyle\sum_{{{i}} = 1}^n {{F_{i,j}}} $
F为社会易损性;Fi,j为主级指标
权重标准化的值乘以次级
指标权重标准化的值$M = \displaystyle\sum_{{{i}} = 1}^n {{A_{i,j}}} $
M为物质易损性值(建筑/交通);
Ai,j为承灾体主级指标权重标准化
的值乘以次级指标权重标准化的值$J = G/N$
J为经济易损性,无量纲,G为区域内每个
承灾体家庭年收入(万元);
N为区域人均年收入(万元) -
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