In this work, a method of identifying distinct suspended sediment populations in terms of concentration and particle size distribution (PSD) is proposed, based solely on the statistical analysis of ADCP acoustic backscatter. The initial hypothesis is stated as that statistically distinct ADCP acoustic responses correspond to statistically distinct associations of suspended sediment concentration and PSD. To prove this, k-means cluster analysis was applied to three different ADCP acoustic backscatter datasets and the resulting partitions characterized in terms of suspended sediment concentration and PSD using simultaneous LISST measurements. All three dataset partitions yielded three similar populations of suspended sediments, which are statistically significantly different between them, proving the initial hypothesis true for the analyzed datasets.

在这项工作中，仅基于ADCP声反向散射的统计分析，提出了一种根据浓度和粒径分布（PSD）识别不同的悬浮沉积物种群的方法。最初的假设是，统计上不同的ADCP声学响应对应于悬浮物浓度和PSD的统计上不同的关联。为了证明这一点，将k均值聚类分析应用于三个不同的ADCP声向后向散射数据集，并使用同时的LISST测量对所得的分区进行了以悬浮泥沙浓度和PSD表示的特征。所有这三个数据集分区都产生了三个相似的悬浮沉积物种群，它们之间在统计学上显着不同，证明了所分析数据集的初始假设是正确的。