Correlation between soil-water characteristic curve and collapsibility in undisturbed loess
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摘要:
为了研究原状黄土土-水特征曲线与黄土湿陷性之间的联系,在陕西西安长安区取地表以下30 m范围内的原状黄土土样,进行基本物理指标试验和湿陷性试验。对不同典型地层的黄土-古土壤试样进行土水特征曲线试验,通过电镜扫描从微观角度分析。研究结果表明:大孔隙的数量与饱和体积含水率呈正相关;中孔隙的数目与过渡区斜率的大小呈正相关,孔隙数目越多土体失水速度越快;微小孔隙的数目和土的塑性指数影响残余含水率的大小。对于不同深度土层,饱和体积含水率和过渡区斜率与土层的湿陷系数呈正相关;塑性指数接近土层的湿陷系数对残余体积含水率的影响不明显;古土壤层的SWCC与湿陷系数之间存在与黄土层相同的正相关性。文章从非饱和土力学的方向去研究黄土的湿陷性,为湿陷性的研究提供一种新的研究角度。
Abstract:This study investigates the correlation between the soil-water characteristic curve (SWCC) of undisturbed loess and its collapsibility. Undisturbed loess soil samples, obtained from depths up to 30 meters below the surface in Chang’an District, Xi’an City, Shaanxi Province, were taken for basic physical index tests and collapsibility assessments. SWCC analyses of loess-paleosol samples from different typical strata were conducted and analyzed using scanning electron microscope. The findings reveal a positive correlation between the number of macropores and saturated volumetric water content. Additionaly, the number of pores is positively correlated with the slope of the transition zone, indicating that a higher pore count accelerates the soil's water loss rate. The number of tiny voids and the plasticity index of soil affect the residual moisture content. For different soil layers, saturated volumetric water content and slope of transition zone exhibit a positive correlation with collapsible coefficient. The influence of collapsible coefficient of plastic index close to soil layer on residual volumetric water content is not obvious. The study also indicates a positive correlation between SWCC and the collapsibility coefficient of the loess layer. By approaching loess collapsibility from the direction of unsaturated soil mechanics, this paper introduces a novel research angle for the study of collapsibility.
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0. 引言
地面形变作为一种缓变性地质灾害,主要具有缓变性、滞后性、区域性、差异性、长期性以及不可逆等特点,始终威胁着城市安全及经济社会的可持续发展[1]。
传统的形变监测方法成本高、效率低、受天气影响,且需建立监测网,无法快速开展大面积监测[2]。合成孔径雷达干涉测量技术( Interferometric synthetic aperture radar,InSAR)凭借其全天侯、强穿透性、高精度获取连续覆盖地面高程和信息的突出优势,已在地表形变监测、滑坡监测、矿区沉降监测、危岩体监测等相关领域得到广泛应用[3-9]。在此基础上发展起来的永久散射体合成孔径雷达干涉测量技术(Permanent scatterers interferometric synthetic aperture radar,PS-InSAR)[10-11],有效消除了时空失相干引起的相位噪声,解决了大气效应难以消除的问题,适用于持续性、区域性地表微小形变监测[12],已经广泛应用在城市地面形变监测。
本研究采用PS-InSAR技术对深圳市南山区后海的片区进行了大范围、长时间的地面和建(构)筑物沉降监测,获得巨厚风化深槽地区地面及采用桩基础施工工艺的建构筑物沉降特征和规律,为深圳后海巨厚深槽地质灾害的排查、防治工作提供基础。
1. 研究区域与数据
1.1 研究区域
深圳市位于华南褶皱系中的紫金—惠阳凹褶断束的西南部、五华—深圳大断裂带南西段,高要—惠来东西向构造带中段的南缘地带。北东向莲花山断裂带与北西向珠江口大断裂带两条断裂在深圳南山后海片区交汇,对深圳、香港的地层稳定性均有影响[13]。
南山区是全国百强区,后海片区是总部大厦基地。该片区原为滨海滩涂,被第四系覆盖,填海造陆区未进行过详细的地质调查。在工程建设中发现其下断层发育,基岩埋深70~130 m,形成了巨厚的风化深槽,上面建筑采用超长桩基础[14]。
图1为本次研究区范围,为南山区南部东侧沿海区域。北至白石路,南至望海路,西至后海大道,东边沿沙河西路—望海路,面积约为11.0 km2。
1.2 数据源
采用2018年2月—2020年12月52期COSMO-SkyMed重复轨道SAR影像,InSAR数据的基本参数见表1。
表 1 In-SAR数据基本参数Table 1. Basic Parameters of In-SAR Data参数 数值 监测日期 卫星类型 COSMO-SkyMed 2018-02-04 、2018-03-08 、2018-03-24 、2018-04-09 、2018-05-11 成像模式 StripMap (条带成像)模式 2018-06-12 、2018-07-11 、2018-09-13 、2018-10-02 、2018-10-18 数据波段 X波段(3.1cm) 2018-11-03 、2018-11-19 、2018-12-01 、2019-01-06 、2019-01-22 空间分辨率/m 3 2019-02-07 、2019-02-19 、2019-03-11 、2019-03-27 、2019-04-12 升/降轨模式 降轨 2019-04-28 、2019-05-10 、2019-06-10 、2019-06-26 、2019-07-12 极化方式 HH极化 2019-07-28 、2019-08-14 、2019-08-29 、2019-10-09 、2019-10-25 中心入射角/(°) 32.55 2019-11-01 、2019-12-03 、2020-01-13 、2020-02-05 、2020-02-21 影像数量 52景 2020-03-24 、2020-04-09 、2020-04-25 、2020-05-11 、2020-05-27 数据级别 SLC数据(单视复) 2020-06-12 、2020-06-28 、2020-07-14 、2020-07-30 、2020-08-15 监测日期 2018-02-04—2020-12-21 2020-09-16 、2020-10-11 、2020-10-18 、2020-11-03 、2020-11-19 处理方法 PS-InSAR 2020-12-05 、2020-12-21 2. 基于PS-InSAR的结果分析
2.1 整体形变分析
本研究利用PS-InSAR技术,对2018年2月—2020年12月的影像数据进行计算,获得148151个有效PS点。
区域累计形变量为−79.1~37.5 mm,累计形变量−8~8 mm的PS点占总数的86%,累计形变量统计见图2。区域平均形变速率为−26.9~11.6 mm/a,形变速率在−3~3 mm/a的PS点占总数的91%,超过9 mm/a的PS点共1106个,占0.8%。
2.2 重点监测点形变分析
在研究区域深槽上方选取21处(点1—点21)地面以及构(建)筑物作为重点形变监测特征点进行形变分析,监测特征点位置分布见图3,监测特征点形变特点及曲线见表2。
表 2 监测特征点形变特点及曲线Table 2. Deformation characteristics and curves of feature points监测特征点
分类监测特征点位置 沉降形变特点 典型形变—日期序列曲线 已有高层建筑 点2舜远金融大厦
点3大成基金总部大厦
点5海信南方大厦
点6深圳湾一号
点7卓越维港名苑形变曲线总体均呈略有
起伏的变化趋势,
整体形变稳定
见右侧点7卓越维港名苑形变—日期曲线图在建项目 点1红土创新广场
点4恒裕深圳湾监测期间受施工影响,形变曲线不规律,或呈略有起伏上升趋势,或呈略有起伏下降趋势
见右侧点1红土创新广场形变—日期曲线图桥梁 点8滨海海滨立交桥
点17桥梁
点21桥梁形变曲线总体呈略有起伏的变化趋势,整体形变稳定
见右侧点17桥梁形
变—日期曲线图道路 点9海德三道
点10创业路
点11望海路
点12望海路
点20东滨路形变曲线总体呈略有起伏的变化趋势,整体形变稳定
见右侧点12望海路形
变—日期曲线图公园草地 点14绿化草地
点13、点16、点18、点19深圳湾公园草地
点15大运会纪念碑广场除了点18深圳湾公园草地形变曲线为均匀缓慢沉降趋势(见右侧点18形变—日期曲线图)外,其余形变曲线均为总体呈略有起伏的下降趋势,整体形变稳定 注:PS为监测特征点的控制点,VEL为高程。 综上,研究区域处于比较稳定或整体缓慢形变,存在一处集中形变区域,位置在深圳湾公园周边。
3. InSAR技术精度验证
InSAR技术可快速、精确地获得区域垂向形变场,其在城区可获得毫米级地表形变[15]。InSAR形变监测结果能提供时间序列形变量,统计影像获取期内任意两期影像间的形变量,可以充分保障外业水准资料和 InSAR数据获取形变量比对的时空一致性。
将研究区域InSAR形变监测结果与同一地区的蛇口文体中心基坑支护工程变形监测结果对比,结果见表3。
表 3 相同位置不同技术手段成果对比Table 3. Comparison of results of different technical means in the same position项目 蛇口文体中心基坑
支护形变监测项目后海断裂带项目 技术手段 S05级水准仪(134次) InSAR(52期) 对应位置 点7附近
(深圳市育才舒曼艺术学校体育场)点7
(卓越维港名苑)监测时间 2019年2月—2020年4月 累计形变/mm −1.9 −1.6 根据《工程测量标准》(GB50026—2020)[16],对同一目标点采用两种不同的监测手段,相同的监测时段内二者的实际误差为±0.3 mm,小于观测中误差±0.71 mm和最大观测误差±1.41 mm,监测精度满足规范要求。
由此可见,InSAR技术可获取大面积、全天候、高精度和高分辨率的地表三维空间微小变化,在地表形变监测方面显示出传统监测不具备的优越性。
4. 形变原因分析
监测期间,深圳湾公园及周边区域累计形变量较大,因此在该区域选取了5个点(A1—A5)的勘察资料进行分析,位置分布见图4。
4.1 A2中建钢构大厦北侧
中建钢构大厦北侧草地累计形变量为-62.1 mm,平均形变速率为20.4 mm/a,形变—日期曲线见图5。
该大厦勘察资料表明,场地内人工填土(
${\rm{Q}}^{ml} $ )成分主要为翻填淤泥,多呈流—软塑状态,组分不均,堆填时间较短,属软弱土层;第四系全新统海相沉积层(${\rm{Qh}}^m$ )淤泥以及第四系上更新统沼泽相沉积层(${\rm{Qp}}^h$ )淤泥均呈流塑状态,含水量大,孔隙比大,具高压缩性、低强度等特征,属软弱土层,最厚达15 m。场地受断裂构造影响,场地内基岩大部分蚀变严重,局部碎裂岩化特征明显,绿泥石化现象显著。各风化基岩起伏变化较大,块状强风化蚀变粗粒花岗岩顶板标高−41.44~−18.49 m,变化幅度达22.95 m;中风化蚀变粗粒花岗岩顶板标高−48.14~−22.84 m,变化幅度达25.30 m。大厦桩基础采用了旋挖桩,平均桩长30.2m,最深50.6m,观测期间大厦整体形变稳定。而大厦北侧场地有均匀沉降趋势,沉降主要由填土及淤泥引起。
4.2 点A1、A3、A4、A5深圳湾公园内草地
该4点累计形变量为40.9~59.6 mm,平均形变速率为15.29~19.76 mm/a,总体呈均匀沉降趋势。以A5深圳湾人才公园为例,形变—日期曲线见图6。
根据A5深圳湾人才公园勘察资料,钻探深度范围内揭露的地层岩性特征自上而下见表4。
表 4 地层岩性特征Table 4. Formation lithologic characteristics地层岩性 地层岩性特征 第四系人工
填土层液性指数 压缩指数
/MPa−1压缩模量
/MPa0.45 0.5 4.0 主要为素填土,层厚1.2~26.9 m,呈松散~稍密状,物理力学性质不均匀,工程性质较差,承载力较低,在上部较大荷载长期作用下易产生沉降及不均匀沉降 第四系海积
冲积层液性指数 压缩指数
/MPa−1压缩模量
/MPa1.36 1.28 2.0 主要为淤泥软土层,层厚0.3~17.0 m,呈流塑状,含较多腐殖质、贝壳碎屑,承载力极低,灵敏度高 第四系残积层及燕山四期侵入花岗岩 残积的砾质黏性土和全风化花岗岩、强风化花岗岩,粉粒含量高,受水浸湿或浸泡后,易软化变形,强度、承载力骤减 该区域填土层及淤泥质软土层厚,工程性质差,承载力低,易产生不均匀沉降。该区域草地沉降主要由填土及软土沉降引起。
5. 结论
(1)本研究基于长时间序列雷达数据,采用PS-InSAR技术对深圳后海片区进行了高精度连续形变监测与分析。通过与传统监测技术对比,监测精度满足规范要求。PS-InSAR新技术能实现大范围、低成本、高精度、高效率的变形监测需求,体现出传统监测不具备的优越性。
(2)对监测结果进行统计分析,南山后海片区深槽上建(构)筑物的沉降相对稳定,沉降量较大的区域为深圳湾公园草地及其周边区域。研究表明,该区域沉降原因为软土沉降。目前在片区深厚深槽上已有的建筑物桩基础是安全的。
(3)深圳湾公园草地均处于缓慢持续沉降状态,后续需重点关注。
(4)该片区巨厚深槽上在建的红土广场、华润深圳湾住宅等建筑。工程桩超长,建筑物的后期沉降值得持续关注。
(5)深槽区域的浅埋地下燃气、排污管网等管线的变形,本次研究未作深入,此类隐患的影响较大,值得深入关注。
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表 1 试验土样基本物理参数
Table 1 Basic physical parameters of test soil samples
地层 深度/m 天然含水率/% 干密度/(g·cm−3) 孔隙比 饱和度/% 液限/% 塑限/% 塑性指数 液性指数 6 m黄土(Qp) 6 21.8 1.46 0.849 70.5 33.5 21.4 12.1 0.05 11 m古土壤(Qp) 11 19.6 1.61 0.677 78.8 35.2 22.0 13.2 <0 15 m黄土(Qp) 15 22.3 1.40 0.933 65.1 33.8 22.2 11.7 0.05 23 m古土壤(Qp) 23 20.8 1.55 0.745 75.9 35.4 22.2 13.3 <0 28 m黄土(Qp) 28 22.8 1.48 0.833 75.0 33.9 22.2 11.7 0.05 表 2 各地层黄土湿陷系数
Table 2 Loess collapsibility coefficient of various strata in loess regions
土层 起始湿陷压力/kPa 自重湿陷系数 湿陷系数 6 m黄土(Qp) 50 0.015 0.032 11 m古土壤(Qp) 200 0.008 0.008 15 m黄土(Qp) 50 0.038 0.042 23 m古土壤(Qp) 200 0.017 0.015 28 m黄土(Qp) 150 0.016 0.016 表 3 SWCC的VG拟合相关参数
Table 3 VG fitting parameters of SWCC
土层 残余体积
含水率
/%饱和体积
含水率
/%a n m R2 6 m黄土(Qp) 7.76 45.92 0.0563 1.9913 0.4978 0.9883 11 m古土壤(Qp) 8.63 40.37 0.0160 2.4253 0.5877 0.9997 15 m黄土(Qp) 7.93 48.27 0.2626 1.6456 0.3923 0.9985 23 m古土壤(Qp) 8.67 42.70 0.0315 2.527 0.6042 0.9740 28 m黄土(Qp) 8.63 45.44 0.0799 1.9027 0.4744 0.9936 表 4 各个土层孔隙含量
Table 4 Porosity content of each soil layer
孔隙
类型6 m黄土
孔隙比/%11 m古土壤
孔隙比/%15 m黄土
孔隙比/%23 m古土壤
孔隙比/%28 m黄土
孔隙比/%大孔隙 12 6 13 8 10 中孔隙 24 18 26 18 20 小孔隙 20 27 18 26 24 微孔隙 44 49 43 48 46 -
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