Grain sorting in gravel‐bed streams and the choice of particle sizes for flow‐competence evaluations

Flow‐competence assessments of floods have been based on the largest particle sizes transported, and yield either the mean flow stress, mean velocity, or discharge per unit flow width. The use of extreme particle sizes has potential problems in that they may have been transported by debris flows rather than by the flood, it may be difficult to locate the largest particles within the flood deposits, and there are questions concerning how representative one or a few large particles might be of the transported sediments and therefore of the flood hydraulics. Such problems would be eliminated for the most part if competence evaluations are based on median grain sizes of transported sediments, or perhaps on some coarse percentile that is established by a reasonable number of grains. In order to examine such issues, the gravel‐transport data of Milhous from Oak Creek, Oregon, and of Carling from Great Eggleshope Beck, England, have been analysed in terms of changing grain‐size percentiles with varying flow stresses. A comparison between these two data sets is of added interest because the bed material in Oak Creek is segregated into well‐developed pavement and subpavement layers, while such a layering of bed materials is largely absent in Great Eggleshope Beck. The analyses show that the trend of increasing sizes of the largest particles in the bedload samples (diameter D m ) with increasing flow stresses is consistent with similar dependencies based on sieve percentiles ranging from the medians ( D 50 ) to the 95th percentiles ( D 95 ). This indicates that the largest particles are an integral part of the overall distributions of bedload grain sizes, and respond to changing flow hydraulics along with the rest of the size distribution. In Oak Creek, the median grain size shows the largest change with increasing flow stresses, followed by D 60 , and so on to D 95 which shows the smallest change. The variations in D m continue this trend, and are similar to those for D 95 . This systematic variation of grain‐size percentiles in Oak Creek is consistent with changes in the overall distributions which tend to be symmetrical and Gaussian for low discharges, but become skewed Rosin distributions for high discharges. In contrast, in Great Eggleshope Beck the several percentiles and D m show the same rate of shift to coarser sizes as flow stresses increase. This results in part from differences in sampling techniques wherein the bedload samples from Great Eggleshope Beck represent a complete flood event, while shorterterm samples at a specific flow stage were obtained in Oak Creek. As a result of the integrated sampling in Great Eggleshope Beck, the bedload grain‐size distributions are more complex, commonly with a bimodal pattern. However, after accounting for differences in sampling schemes in the two streams, contrasting patterns in changing grain‐size distributions remain, and these are concluded to reflect grain sorting differences as the bedload grain‐size distributions approach the distributions of the bed materials. It is surprising that if criteria commonly employed to demonstrate the equal mobility of different grain sizes are used in the comparison, then Great Eggleshope Beck is far closer to this condition in spite of its minimal development of a pavement. It is concluded that the respective shapes of the bed‐material grain‐size distributions, in particular their degrees of skewness, are more important to the observed sorting patterns than are the effects of a pavement layer regulating grain entrapment to produce an equal mobility of different grain sizes. Therefore, the comparison has established that flow‐competence relationships will differ from one stream to another, depending on the pattern of grain sorting which is a function of the bedmaterial grain‐size distribution.