Northeastern Section - 51st Annual Meeting - 2016

Paper No. 19-3
Presentation Time: 1:30 PM-5:30 PM

COMPARISON OF GRAIN-SIZE ANALYSIS METHODS FOR UNCONSOLIDATED SEDIMENTS


ARROYO, Andres and WIZEVICH, Michael C., Department of Geological Sciences, Central Connecticut State University, 1615 Stanley St, New Britain, CT 06050, aarroyo@my.ccsu.edu

Rapid particle size analysis of sediments saves significant time over the traditional methods of sieving (sand fraction) and settling from suspension (silt and clay fractions). However, due to the different methodologies and inherent assumptions, comparison of results from the methods is not straightforward. In this study sediment samples were analyzed by using a Malvern Mastersizer 3000, an instrument that utilizes laser diffraction to optically measure particles between 0.01 and 2000 microns in size, to obtain grain size data. The results were compared to samples sieved (for 10 minutes in 12 sieves over a 2000 to 44 micron range, or ½ phi intervals) for the sand fraction and hydrometer analysis for the finer grains.The samples consisted of represent a full range of sediments from clayey muds to moderately well-sorted medium sands; eight samples were collected along a 100 meter traverse across a bar in the Farmington River in Windsor, Ct., and two additional mud samples were obtained from a mud volcano near Page, Az.The results of the different methods were compared by analysis of grain size frequency curves and parameters used to describe the grain size distribution were mean grain size, sorting, skewness, and kurtosis. Comparison of results of the sand samples shows reasonably close agreement (<10% difference) for all parameters for nearly all samples. For all samples the mean value obtained from the Mastersizer was lower (finer) than that obtained by sieving. For one sample the difference in the mean was nearly 25%, which may be explained by the relatively high percentage of mica in that sample. Results for the mud samples also lend comparison of the different methods and will help in the understanding of what measurements and pitfalls each methodology provides.