刘 艳, 张文静, 陈新伟, 晏凌宇, 蒙凯捷, 范倛瑞
(浙江大学 地球科学学院, 浙江 杭州 310027)
钱塘江杭州下沙段流向剖面沉积物粒度特征及水动力条件分析
刘艳, 张文静*, 陈新伟, 晏凌宇, 蒙凯捷, 范倛瑞
(浙江大学 地球科学学院, 浙江 杭州 310027)
摘要:对钱塘江中沉积物粒度的研究,前人多关注横剖面的粒度变化.为了解钱塘江沉积物粒度在流向上的变化特征,在下沙段(下沙大桥至江东大桥)进行粒度采样,对含泥砂悬浮物样品和砂泥样品的粒度进行分析.结果表明,粒度在1.45~3 500 μm,属粘土至砾组分,以粉砂组分占比最多;粒径均值为3.24~5.92 μm,位于粉砂至极细砂范围;粒度频率呈多峰分布,分选差至分选非常差,峰度为非常尖峰至宽峰.在该区间的直流河段粒度特征相似,而在下沙大桥河流弯曲的凸岸处粒度特征不同.反映该处水动力条件复杂,可能同时受到层流和紊流的影响.最大水流分量在下沙大桥凸岸处最小,在直流河段随流向逐渐减小.粒度和最大水流分量特征受钱塘江下沙段河流形态控制.
关键词:钱塘江;粒度特征;水动力条件;曲流河
0引言
钱塘江是浙江省最大的水系[1-2],同时也孕育着人类最早的水稻农耕文明[3-4].钱塘江水动力条件的变化不仅影响河床形态、河流的携沙冲淤能力、河流水质、河岸工程、航道稳定等[1,5-11],还影响古人类文明的迁徙[3-4].沉积物粒度是搬运水动力条件的重要表征,对确定河流水动力条件变化具有重要意义[12-18].前人对钱塘江水动力条件的研究主要集中于下切河谷作用及沉积特征[16-24]、河口地区冲淤作用及河床变形[6-9,12,25]、涌潮沉积作用[17,25-27]以及第四纪以来沉积层序特征[21,28-32];沉积物粒度研究或侧重于横切钱塘江剖面采样,或偏重于钻孔柱纵剖面采样粒度特征分析,对沿流向剖面的沉积物粒度特征研究鲜有报道.
沿钱塘江流向采样,开展了沉积物和含泥砂悬浮物样品的粒度分析.旨在通过对钱塘江沿流向剖面的粒度特征分析,揭示钱塘江沿流向的水动力条件的变化及其控制条件.
1研究区及样品概况
钱塘江发源于皖南境内,经皖、浙2省最终流入东海[31],全长600余km,流域面积4.88×104km2[32],年径流量3.909×1010m3以上[33].钱塘江在富阳以上的上游地区表现为山间直流河;富阳至杭州湾的下游地区表现为平原地区曲流河(见图1).
本文粒度分析的样品来自钱塘江下沙大桥至江东大桥的下沙段,段内河流由上游的九堡大桥至下沙大桥区间的北西-南东走向突转至北东-南西走向,河流弯曲处位于下沙大桥,钱塘漏斗形河口的上段,平均流速0.68~3.7 m·s-1,文献[17]认为该区域为钱塘河口粉砂质浅滩源头.在河流的凹岸一侧,表现为河流的侧向侵蚀作用,而在凸岸,则表现为侧向加积作用,可见沙坝沉积.在该河段北岸4个采样点采取岸堤砂泥沉积物和含泥砂水样(见图1),共获得8个分析样品,其中采样点D位于河流弯曲处的北岸沙坝沉积及分支河道所在位置.各采样点GPS数据为:A点30°18′16″N,120°23′42″E;B点30°18′17″N,120°23′22″E;C点30°16′57″N,120°22′40″E;D点30°15′57″N,120°21′12″E.
图1 钱塘江河流形态及本文采样位置图Fig.1 Morphology of the Qiantang River and sample locations采样点GPS数据见正文; GPS data shown in the text.
2分析方法
由于本次分析样品均未固结且颗粒分散,因此,未采取前处理程序而直接进行粒度分析.粒度分析在浙江大学地球科学学院粒度分析实验室完成,采用英国Malvern公司生产的Mastersizer 3000型激光粒度分析仪,测试粒径范围0.01~3 500 μm.每个样品重复测量5次,取5次结果的平均值.
粒度统计分析采用林秀斌等[34]所归纳的方法,将粒度分析数据做Φ值转换,即将以μm为单位的粒度数据转换成无量纲的Φ值,Φ=-log2(x/xo),其中,x是以mm为单位的粒径值,xo为参考粒径,等于1 mm[35].对粒径Φ值作概率累积曲线,并获得Φ05、Φ16、Φ25、Φ50、Φ75、Φ84和Φ95的值,其中Φn为当累积频率达到n%时的Φ值.粒径的分布特征主要以4个反映频率曲线特征的统计量来表征,分别为均值Mean、标准方差SDev、偏斜度Skewness和峰度Kurtosis[36],其中Mean=(Φ16+Φ50+Φ84)/3,SDev=(Φ84-Φ16)/4+(Φ95-Φ05)/6.6,Skewness=(Φ16+Φ84-2Φ50)/(2Φ84-Φ16)+(Φ05+Φ95-2Φ50)/(2Φ95-Φ05),Kurtosis=(Φ95-Φ05)/2.44(Φ75-Φ25).按照FOLK等[36]的方案对这些统计量进行划分(见文献[34]),其中,标准方差<0.35为分选非常好,0.35~0.50为分选好,0.50~0.71为分选较好,0.71~1.0为分选中等,1.0~2.0为分选差,2.0~4.0为分选非常差,>4.0为分选极差;偏斜度1~0.3为强烈偏向细粒,0.3~0.1为偏向细粒,0.1~-0.1为近对称,-0.1~-0.3为偏向粗粒,-0.3~-1.0为非常强烈偏向粗粒;峰度<0.67为非常宽峰,0.67~0.90为宽峰,0.90~1.11为中等峰度,1.11~1.50为尖峰,1.50~3.0为非常尖峰,>3.0为极尖峰.
本文采用UDDEN[37]和WENTWORTH[38]所提出的标准对粒级分类,粒径小于4 μm为粘土(对应Φ值大于8),4~64 μm为粉砂(对应Φ值在4~8),64~125 μm为极细砂(对应Φ值在3~4),125~250 μm为细砂(对应Φ值在2~3),250~500 μm为中砂(对应Φ值在1~2),500~1 000 μm为粗砂(对应Φ值在0~1),1 000~2 000 μm为极粗砂(对应Φ值在0~-1),大于2 000 μm为砾(对应Φ值小于-1)[39].
3粒度分析结果
样品粒度分析结果列于表1.由表1知,粒径分布于0.991~3 500 μm,即粘土至砾粒级均有分布.
表1粒度分析结果
Table 1 Grain-size analyses results
续表
粒径范围/μm体积分数/%A-悬浮物A-砂泥B-悬浮物B-砂泥C-悬浮物C-砂泥D-悬浮物D-砂泥86.43.243.934.504.855.232.861.332.4598.12.253.003.864.314.562.551.062.551111.442.173.203.753.842.260.852.681270.851.502.593.203.132.000.702.821440.461.012.052.702.481.790.582.991630.240.691.612.291.931.630.503.191860.140.511.271.961.491.540.433.422110.130.431.051.721.181.490.383.652400.170.430.921.540.971.490.323.872720.200.460.861.400.851.510.274.023100.220.500.851.300.781.550.224.083520.210.540.871.210.741.580.174.014000.190.570.911.140.721.610.123.784540.160.590.951.080.701.610.113.415160.120.620.991.040.681.580.102.915860.070.651.001.010.651.510.072.346660.060.701.001.010.611.400.051.757560.040.760.971.030.561.270.041.208590.040.830.921.080.511.130.010.749760.040.900.851.130.461.000.000.3911100.030.960.771.180.420.890.000.1712600.021.010.691.210.380.810.000.0414300.021.010.601.210.350.740.000.0216300.010.980.511.160.310.670.000.0018500.010.890.421.050.280.590.000.0021000.000.770.340.910.230.490.000.0023900.000.600.240.720.180.370.000.0027100.000.410.160.490.100.250.000.0030800.000.210.070.250.050.120.000.003500
A-含泥砂悬浮物样品粒径为2.42~2 100 μm(见表1),在粘土至极粗砂粒级范围(见表2),其中以粉砂组分为主,体积分数达77.81%;极细砂组分次之,体积分数达17.65%;其他组分的体积分数均不足2%(见表2、图2).粒度频率分布图反映该样品粒度呈多峰式分布,其中主峰粒径10~200 μm(见图3).粒度概率累积曲线上并未见明显的跳跃(见图4).由概率累积曲线计算得出的Mean值为4.76,SDev值为1.15,Skewness值为0.23,Kurtosis值为1.27,表明该样品Φ值粒径均值在粉砂粒径范围内,分选差,粒度分布偏向细粒,为尖峰分布(见表3).
表2粒级组分含量
Table 2 Percentages of grain-size components
图2 样品粒度组分体积分数图Fig.2 Percentages of grain-size components粒度组分划分方案见正文.The division of grain-size components shown in the text.
A-砂泥样品粒径为3.12~3 500 μm(见表1),在粘土至砾粒级范围(见表2),其中以粉砂组分为主,体积分数达60.83%;极细砂组分体积分数也较为可观,可达21.29%;其他组分的体积分数均不足5%(见表2和图2).粒度频率分布图反映该样品粒度分布呈多峰式,其中主峰粒径在10~200 μm(见图3).粒度概率累积曲线上并未见明显的跳跃(见图4).由概率累积曲线计算Mean值为4.05,SDev值为1.78,Skewness值为-0.24,Kurtosis值为1.96,表明该样品Φ值粒径均值在粉砂粒径范围内,分选差,粒度分布偏向粗粒,为非常尖峰分布(见表3).
图3 样品粒度频率分布图Fig.3 Grain-size frequency distributionΦ值计算方法见正文.The calculation of Phi (Φ) valueis shown in the text.
图4 样品粒度累积曲线Fig.4 Grain-size cumulative frequency diagramΦ值计算方法见正文.The calculation of Phi (Φ) valueis shown in the text.
表3样品粒度分布统计量及分类结果
Table 3 Statistic measures and their division of the grain-size analyse results
B-含泥砂悬浮物样品粒径为3.55~3 500 μm(见表1),在粘土至砾粒级范围(见表2),其中以粉砂组分为主,体积分数达53.85%;含有较多的极细砂组分,可达24.86%;其他组分的体积分数均不足7%(见表2和图2).粒度频率分布图反映该样品粒度呈多峰式分布,其中主峰粒径在10~300 μm(见图3).粒度概率累积曲线上并未见明显的跳跃(见图4).由概率累积曲线计算得Mean值为3.84,SDev值为1.70,Skewness值为-0.22,Kurtosis值为1.48,表明该样品Φ值粒径均值在极细砂粒径范围内,分选差,粒度分布偏向粗粒,为尖峰分布(见表3).
B-砂泥样品粒径为3.55~3 500 μm(见表1),在粘土至砾粒级范围(见表2),其中以粉砂组分为主,体积分数达41.91%;也含有较多的极细砂组分,可达27.01%;另外细砂组分也较可观,为10.21%;其他组分均不足7.5%(见表2和图2).粒度频率分布图反映该样品粒度呈多峰式分布,其中主峰粒径在10~700 μm(见图3).粒度概率累积曲线上并未见明显的跳跃(见图4).由概率累积曲线计算得Mean值为3.24,SDev值为1.91,Skewness值为-0.32,Kurtosis值为1.27,表明该样品Φ值粒径均值在极细砂粒径范围内,分选差,粒度分布强烈偏向粗粒,为尖峰分布(见表3).
C-含泥砂悬浮物样品粒径为3.55~3 500 μm(见表1),在粘土至砾粒级范围(见表2),其中以粉砂组分为主,体积分数达53.22%;也含有较多的极细砂组分,可达28.78%;另外细砂组分也较可观,为8.05%;其他组分均不足5%(见表2和图2).粒度频率分布图反映该样品粒度大体呈单峰式分布,主峰粒径10~300 μm(见图3).粒度概率累积曲线上并未见明显跳跃(见图4).由概率累积曲线计算得Mean值为3.95,SDev值为1.45,Skewness值为-0.13,Kurtosis值为1.42,表明该样品Φ值粒径均值在极细砂粒径范围内,分选差,粒度分布偏向粗粒,为尖峰分布(见表3).
C-砂泥样品粒径为2.42~3 500 μm(见表1),在粘土至砾粒级范围(见表2),其中以粉砂组分为主,体积分数达53.40%;极细砂组分为16.29%;中砂组分为9.44%;其他组分均不足8%(见表2和图2).粒度频率分布图反映该样品粒度呈多峰式分布,其中主峰粒径10~200 μm(见图3).粒度概率累积曲线上并未见明显跳跃(见图4).由概率累积曲线计算得Mean值为3.85,SDev值为2.31,Skewness值为-0.18,Kurtosis值为1.00,表明该样品Φ值粒径均值在极细砂粒径范围内,分选非常差,粒度分布偏向粗粒,为中等峰度分布(见表3).
D-含泥砂悬浮物样品粒径为1.45~976 μm(见表1),在粘土至粗砂粒级范围(见表2),其中以粉砂组分为主,体积分数达76.05%;粘土组分为12.90%;其他组分均不足8%(见表2和图2).粒度频率分布图反映该样品粒度大体呈双峰式分布,频率峰粒径分别为1~10和10~200 μm(见图3).粒度概率累积曲线上并未见明显跳跃(见图4).由概率累积曲线计算得Mean值为5.92,SDev值为1.62,Skewness值为-0.02,Kurtosis值为0.88,表明该样品Φ值粒径均值在粉砂粒径范围内,分选差,粒度分布近对称,为宽峰分布(见表3).
D-砂泥样品粒径为1.45~1 630 μm(见表1),在粘土至极粗砂粒级范围(见表2),其中粉砂组分相对占优,体积分数达35.01%;极细砂、细砂和中砂组分也较可观,分别占15.15%,17.12%和22.21%;其他组分均不足7%(见表2和图2).粒度频率分布图反映该样品粒度呈多峰式分布,其中主峰粒径在70~1 000 μm(见图3).粒度概率累积曲线上并未见明显跳跃(见图4).由概率累积曲线计算得Mean值为3.43,SDev值为2.21,Skewness值为0.27,Kurtosis值为0.83,表明该样品Φ值粒径均值在极细砂粒径范围,分选非常差,粒度分布偏向细粒,为宽峰分布(见表3).
结果表明,这些采样点的样品粒度显示某些一致性的规律,所有砂泥样品的粒度均值均大于该点含泥砂水样品的粒度均值,从流向上看,除D点外其余砂泥样品与含泥砂水样品的粒度均值趋势一致(见图5).所有砂泥样品的粒度分布标准方差均大于该点悬浮物样品的粒度分布标准方差(见图6).从统计量的数值来看,所有样品普遍呈分选差至分选非常差的特点(见表3),与样品粒度均显示多峰分布的特点相一致(见图3).
图5 采样点粒度均值(Mean)变化图Fig.5 The diagram showing variation of graphic meansof the samples横坐标为采样点,均值Mean的计算方法见正文.The calculation of mean values is shown in the text.
图6 采样点粒度标准差(SDev)变化图Fig.6 The diagram showing variation of graphic SDevsof the samples横坐标为采样点,标准差的计算方法见正文.The calculation of SDev values is shown in the text.
这些结果同时表明,相较于其他3个采样点,采样点D具有独特的粒度特征.从粒度组分来看,采样点A、B、C的粒度特征大体相似,均以粉砂组分占主导并含有较多的极细砂;采样点D的粒度特征相对独特,其中D-悬浮物样品含有较多更细的粘土组分,而D-砂泥样品含有较多更粗的极细砂、细砂甚至中砂组分(见表2和图2).从统计数值来看,采样点A、B、C的粒度大体偏向粗粒、尖峰的特征;采样点D则显示近对称或偏向细粒、宽峰的特征(见表3).
4水动力条件分析
所有采样点中砂泥样品的粒度均值和标准方差均大于该点的悬浮物样品(见图5和图6),反映水流条件减弱使粗粒成分沉积,更细粒组分仍然被水流携带.如前所述,相较于采样点A、B、C,采样点D具有一些独有的特征.D-砂泥样品分选非常差,宽峰且偏向细粒的粒度特征表明水流动力条件显著下降,这也与D-砂泥样品和D-悬浮物样品均值在所有样品中相差最大的结果相一致(见表3).
然而,所测试的样品普遍分选差(见表3),频率分布图中普遍呈多峰的特点(见图3),表明水流动力条件复杂,除了层流之外可能还有紊流的影响[44],各点砂泥样和悬浮物样的均值和标准方差值在流向方向的变化不显著(见图5和图6),也从侧面反映了水流动力条件较为复杂.为了揭示流向方向的变化规律,对各样品粒径频率分布曲线进行组分正态分布拟合,以分离不同的正态分布组分[45-46],拟合结果如图7所示.拟合结果显示,采样点A、B、C的悬浮物样品的粒度分布可用3个不同均值的正态分布曲线拟合,这几个采样点砂泥样品的粒度分布可用4个不同均值的正态分布曲线拟合.其中,A-悬浮物样品的3个正态分布组分均值分别为7.64,40.1和310 μm,B-悬浮物样品的分别为6.72,45.61和1 100 μm,C-悬浮物样品的分别为6.72,51.8和859 μm;A-砂泥样品的3个正态分布组分均值分别为6.72,45.6和1 260 μm,B-砂泥样品的4个正态分布组分均值分别为8.68,58.9,240和1 260 μm,C-砂泥样品的分别为7.64,45.6,454和1 340 μm(见图7).与此不同,D-悬浮物样品可仅用2个不同均值的正态分布曲线拟合,均值分别为
6.72和27.4 μm;D-砂泥样品亦可仅用2个正态分布曲线拟合,均值分别为3.11和310 μm(见图7).本文选取可能代表层流水动力条件的最大正态组分的均值,作流向方向对比图(见图8),以期揭示水动力条件在流向方向的变化规律.结果显示,包括悬浮物样品和砂泥样品在内的所有样品均显示最大正态组分均值的系统性变化,即随流向方向,均值在采样点D最小,至C点激增至最大,C至A点持续下降(见图8).
结果表明,钱塘江下沙段水动力条件复杂,除了层流之外可能还受紊流影响.样品粒度的最大正态组分均值结果显示,最大水流分量(可能代表层流)在下沙大桥河流弯曲的侧向加积处(D点)最小;随着水流经过弯曲处进入直流段,最大水流分量激增(C点),之后在直流河段最大水流分量向下游逐渐减小(C点至A点).赵澄林[40]指出,曲流河表层水流在河流弯曲的凸岸处显著减小,使得凸岸发生侧向加积作用而形成沙坝;在直流段,水流随流向逐渐减小.本文采样点D位于钱塘江下沙段的下沙大桥河流弯曲的凸岸处,因此,其最大水流分量动力小,从而形成下沙大桥处的凸岸沙坝,这也是该点样品粒度特征与其他采样点显著不同的原因.采样点C至A显示随流向往下游最大水流分量动力逐渐减小的趋势,这与直流河段水动力条件逐渐减弱的趋势相一致.这种水流趋势可能由钱塘江下沙段的河流形态所控制,其中D点水动力条件受控于河流弯曲的凸岸形态,而C至A点的水动力条件减弱的趋势则受控于直流河形态.
5结论
对钱塘江下沙段下沙大桥至江东大桥区间砂泥样品和含泥砂悬浮物样品粒度的分析表明:
5.1粒径组分从粘土至砾均有分布,以粉砂组分占比最多,粒径均值在粉砂至极细砂范围,粒度频率显示多峰分布特点,分选差至分选非常差,峰度为非常尖峰至宽峰.
5.2该区间的直流河段粒度特征相似,与下沙大桥河流弯曲凸岸处的粒度特征不同.
5.3粒度特征所反映的复杂水动力条件,可能同时受到层流和紊流的影响.最大水流分量在下沙大桥凸岸处最小,在直流河段随流向往下游减小.
5.4粒度和最大水流分量受钱塘江下沙段河流形态控制.
图7 粒度组分正态曲线拟合图Fig.7 Curve-fitting of the grain-size distribution with Gaussian-distribution grain-size components图中数值为各组分正态曲线的均值.The values in the diagrams are Gaussian distribution means of used components.
图8 采样点最大粒径组分正态曲线均值变化图Fig.8 Variation of the Gaussian distribution means of the maximum grain-size components
感谢浙江大学地球科学学院粒度分析实验室为本研究提供粒度测试!感谢林春明教授和匿名审稿专家提出的宝贵意见!
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LIU Yan, ZHANG Wenjing, CHEN Xinwei, YAN Lingyu, MENG Kaijie, FAN Qirui
(SchoolofEarthSciences,ZhejiangUniversity,Hangzhou310027,China)
Grain-size analyses of the sediments across stream-directed section in Xiasha segment of Qiantang River. Journal of Zhejiang University(Science Edition), 2016,43(3):325-336
Abstract:In light of the grain-size analyses in Qiantang River, previous studies mostly emphasized on the cross-stream section. To determine the sediment grain-size variation across stream-directed section, we have collected grain-size samples between Xiasha and Jiangdong Bridges in the Xiasha segment of the river. Both soluble and solid samples have been collected and analyzed. The analyzed results indicate that the sediment grains, ranging from 1.45-3 500 μm, consist of clay to gravel components with the silt component taking dominance. The mean grain sizes, spanning from 3.24-5.92 μm, are within the range between silt and very fine sand. Frequency-distribution diagrams suggest that the grain sizes are multimodal, very platykurtic to leptokurtic, and poorly to very poorly sorted. Grain-size features are similar in the samples collected from the straight-directed part of the river, which are dramatically different with those from salient point of the river. Generally, the grain-size features suggest complex hydrodynamic condition impacted by both laminar and turbulent flows. However, the results indicate that the force of maximum flow component is the least in the salient point and decreases downward the flow direction in the straight-directed part of the river, which is inferred to be controlled by the river morphology.
Key Words:Qiantang River; grain-size analyses; hydrodynamic condition;meandering river
中图分类号:P 714
文献标志码:A
文章编号:1008-9497(2016)03-325-12
作者简介:刘艳(1986-),ORCID:http://orcid.org/0000-0002-7005-4501,女,硕士,实验员,主要从事地质学相关实验工作.*通信作者,ORCID:http://orcid.org/0000-0003-2757-8171,E-mail:wenjing19910523@126.com.
基金项目:中央高校基本科研业务费专项资金科研发展专项项目(2016FAZ3007);浙江大学SRTP项目;浙江大学探究性实验项目.
收稿日期:2015-08-06.
DOI:10.3785/j.issn.1008-9497.2016.03.014