DIFFERENCE IN GRAIN-SIZE PARAMETERS OF TIDAL DEPOSITS DERIVED FORM THE GRAPHIC AND ITS POTENTIAL CAUSES
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摘要: 采用Folk-Ward图解法(GM)、Friedman-Johnson矩值法(MMFr)和McManus矩值法(MMMc)公式,分别计算了杭州湾顶-钱塘江河口中高潮滩短柱状样395个砂、泥质纹层的粒度参数。比较分析发现,除平均粒径可以完全相互替代外,随着矩值法阶矩数的增加,彼此关系变得越复杂而无法直接相互替代。MMMc矩值法未采用传统统计学法计算偏态和峰度值,目前二者的物理意义尚不清楚,其适用范围有待进一步探讨;由于两种矩值法计算的粒度参数差别较大,鉴于目前MMFr矩值法应用更广泛且物理意义明确,建议统一使用MMFr公式以便于对比研究。砂、泥质(纹)层的粒度参数特征差异明显,沉积物组分分析(反演)进一步表明,二者由各自特征的粗、细组分构成,与各自形成时的水动力条件相符合。由此认为,取样时选相同或单一动力沉积单元进行粒度分析是重要的。运用正态分布函数二组分叠置法(正演)较好地模拟出矩值法与图解法偏态与峰度的复杂关系,其中主次组分的百分含量和众数差值是主要影响因素。随着细组分(次组分)含量的减少,矩值法偏态和峰度值都相应增加,细微地反映了粒度分布的整体变化趋势。但图解法偏态和峰度值发生先增加,到达某一拐点后再减小,这与其只采取有限的若干特征值进行统计和忽略尾部(φ16~φ84)部分的描述,可能是偏态拐点出现的位置在细组分百分含量为35%的原因。图解法与矩值法各具优势,但图解法对于次组分和尾部特征的表述具有不一致性,而矩值法在此方面具有趋同性,更适合于建立统一标准,开展粒度参数的物理意义解释。
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关键词:
- 粒度参数 /
- 图解法 /
- 矩值法 /
- 正态分布函数组分分析(反演) /
- 粒度分布模拟(正演)
Abstract: Grain-size parameters of 395 samples from separately sandy or muddy layers of the intertidal-flat deposits in the Qiangtang Estuary were calculated using Fork-Ward graphic method (GM), and moment methods of Friedman-Johnson (MMFr) and McManus (MMMc), respectively. Comparative studies indicate that the parametric relationships are quite complex among the different methods especially for the higher order moments, only with an exception of mean size, in that GM mean size almost equates to that of MM. Physical meaning of MMMc skewness and kurtosis has never been well expressed due to its non-traditional statistical methodology, so unique application of MMFr formula is strongly recommended to calculate moment parameters for environmental interpretations and comparison. The parametric difference is notable between sandy and muddy layers, which are composed of separate coarser and finer dynamic populations in response to their different depositional processes on the basis of the numerical partitioning analyses (inverse modeling). It is therefore extrapolated that the sampling unit for grain size analyses should be strictly deposited under similar hydrodynamic conditions. A numerical modeling of the mixtures of two log-normal populations (forward modeling) was successfully applied to simulate the complex relationships of GM and MM parameters in terms of skewness and kurtosis, which are majorly controlled by the difference of percentiles and modes between the major and secondary populations. As the finer (secondary) population percentiles decrease, the value of MM skewness and kurtosis increases sensitively to the detail change in grain-size distribution pattern; while the value of graphic skewness and kurtosis increases before reaching their maxima and decreases after those critical points, mainly resulting from finite statistics of graphic method on a few eigenvalues and neglecting the tail (<5%) components.The critical value for graphic skewness to change from increasing into decreasing trend is 35% for the secondary population percentiles, hypothetically related with an additional expression in the grahic skewness formula to stress the percentiles (16 and 84) on the grain-size distribution, which are not included in the graphic kurtosis formula. The both methods have their own advantage and disadvantage, but the moment method has a priority in establishing a uniform standard in the future, typically for physical interpretation of grain-size parameters, considering that it can elaborately and consistently reflect changes in secondary population tail features in comparison with the failure of the graphic method. -
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