Articles | Volume 7, issue 3
Research article
02 Sep 2019
Research article |  | 02 Sep 2019

Percentile-based grain size distribution analysis tools (GSDtools) – estimating confidence limits and hypothesis tests for comparing two samples

Brett C. Eaton, R. Dan Moore, and Lucy G. MacKenzie

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Cited articles

Beschta, R. L. and Jackson, W. L.: The intrusion of fine sediments into stable gravel bed, Journal of Fisheries Resource Board of Canada, 36, 204–210, 1979. a
Buffington, J. M. and Montgomery, D. R.: A procedure for classifying textural facies in gravel-bed rivers, Water Resour. Res., 35, 1903–1914, 1999. a
Bunte, K. and Abt, S. R.: Sampling frame for Improving pebble count accuracy in coarse gravel-bed streams, J. Am. Water Resour. As., 37, 1001–1014, 2001a. a, b, c, d, e, f, g, h, i, j, k
Bunte, K. and Abt, S. R.: Sampling surface and subsurface particle-size distributions in wadable gravel-and cobble-bed streams for analyses in sediment transport, hydraulics, and streambed monitoring, Gen. Tech. Rep. RMRS-GTR-74, US Department of Agriculture, Rocky Mountain Research Station, Fort Collins, CO, USA, 2001b. a, b, c, d
Bunte, K., Abt, S. R., Potyondy, J. P., and Swingle, K. W.: Comparison of three pebble count protocols (EMAP, PIBO and SFT) in two mountain gravel-bed streams, J. Am. Water Resour. As., 45, 1209–1227, 2009. a, b, c, d, e, f
Short summary
Researchers studying gravel bed rivers almost always require a sample of the bed surface grain size range. These samples are typically expressed as cumulative frequency distributions. We present statistical techniques for generating and plotting confidence intervals for the various size percentiles and for determining whether size percentiles from two samples are statistically different. The techniques are implemented in an R package; a simplified version is implemented in a spreadsheet.