On The Accuracy Of Bed-Material Sampling

Vries, Martijn de

doi:10.1080/00221687009500329

Cited by 28 publications

(14 citation statements)

References 1 publication

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“…Several studies have confirmed the validity of the Church et al (1987) criteria (Gale and Hoare, 1992;Ferguson and Paola, 1997;Milan, 1999) and the comprehensive review of Bunte and Abt (2001) indicates their similarity to other recommendations (e.g. De Vries, 1970). We adopt the criteria of Church et al (1987) here as a standard reference set that we refer to as the 'CMW' criteria.…”

Section: Introductionmentioning

confidence: 90%

A hybrid method for size characterization of coarse subsurface fluvial sediments

Rice

Haschenburger

2004

Earth Surf Processes Landf

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This paper introduces and evaluates a novel method for ascertaining the grain-size distribution of subsurface sediments that involves profoundly less sampling effort than standard methods. It is based on hybrid sampling principles previously applied to the construction of synthetic surface grain-size distributions. The method is developed from an empirical demonstration of the approximate similarity of surface and subsurface grain-size distributions when compared over a common range of sizes. Subsurface hybrid models are found to provide good facsimiles of grain-size distributions defined using standard criteria and to yield distribution percentiles with millimetre accuracy. The technique is presented as an expedient alternative to standard methods for large, perennial gravel-bed rivers. As this is a new technique, prudent application is advised in lieu of further investigation.

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Section: Introductionmentioning

confidence: 90%

A hybrid method for size characterization of coarse subsurface fluvial sediments

Rice

Haschenburger

2004

Earth Surf Processes Landf

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“…The few published guidelines on sample sizes to characterize gravel GSDs (de Vries, 1970;ISO, 1977;Church et al, 1987;Gale and Hoare, 1992) involve some multiple of the mass or volume of the D 84 or D max grain, irrespective of the purpose of sampling. Our results show that different criteria are required depending on which GSD percentile is of interest, and whether the only consideration is to avoid bias or also to achieve a specified precision better than that which holds at the minimum sample size for negligible bias.…”

Section: Implications For Sample Sizementioning

confidence: 99%

“…But in bulk sampling the number of grains is unknown and is itself a stochastic variable. De Vries (1970) used empirically calibrated relationships between number and total weight of particles in given sieve fractions to obtain an approximate expression for the coefficient of variation of the proportion of a bulk GSD falling within a particular fraction, and thus a criterion for sample size for given precision. However, he neglected the stochastic variation in n and it is not obvious how to extend his approach to an analytical treatment of sampling variability in percentiles.…”

Section: Introductionmentioning

confidence: 99%

“…Obtaining a sample that includes large numbers of the coarsest clasts can require an overwhelming amount of work. The sample-size criteria advocated by de Vries (1970) and Church et al (1987) can easily translate into samples of many tonnes. Similar practical difficulties arise with tills, debris-flow deposits, pebbly beaches, and other coarse clastic environments.…”

Section: Introductionmentioning

confidence: 99%

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Bias and precision of percentiles of bulk grain size distributions

Ferguson

Paola

1997

Earth Surf. Process. Landforms

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Percentiles such as D 50 and D 84 , calculated from weights retained on different sieves, are widely used to characterize grain size distributions (GSDs) of bulk samples of sedimentary deposits or sediment fluxes. The sampling variability of such percentiles is not well known, and few sampling guidelines exist for reliable characterization of GSDs. We report results from computer sampling experiments on the variability of sample percentiles in different-sized samples from populations with a log-normal GSD by weight and different sorting coefficients. Sample sizes are scaled by the volume of a mediansized grain so that results can be applied to any log-normal GSD. Sampling is random for the GSD by number that is equivalent to a specified GSD by weight. Results show important differences from standard sampling theory applicable to pebble-count GSDs. In small bulk samples all percentiles, including the median, are underestimated (more so for smaller samples, coarser percentiles and poorer sorting), and precision does not improve with the square root of sample size until fairly large sample sizes are exceeded. Non-dimensional equations fitted by eye to the results give good approximations to expected bias and precision in any percentile from 50 to 95 for any given sample size and population sorting coefficient. They are inverted to estimate the sample size required to avoid significant bias, or achieve specified precision, in any percentile of interest given estimates of the population D 50 and sorting coefficient. Target sample sizes are sometimes considerably smaller, but in other circumstances larger, than suggested by previous guidelines relating to estimation of the entire grain size distribution. Bias is likely in small samples of river bedload and good precision requires very large samples of poorly sorted gravel deposits.

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“…Based upon these and other observations, several organisations have recommended standards indicating the size of the bulk sample required to obtain representative results (for example the British Standards Institute, 1985, and the American Society for Testing and Materials, 1987). The majority of these are based on bulk sampling, and only the methods of de Vries (1970) and Church et al (1987) have been based on a consideration of individual size fractions. de Vries' recommendations incorporate individual fractions of fluvial sand and fine gravel and determine a minimum sample size based on the D 84 of the bed-material, the value defined by de Vries as the reference 'large' grain-size from which an estimate sample is obtained.…”

Section: Introductionmentioning

confidence: 99%

Influence of particle shape and sorting upon sample size estimates for a coarse-grained upland stream

Milan

Large

Brunsdon

1999

Sedimentary Geology

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Present bulk-sampling recommendations for the characterisation of fluvial sediments based upon ellipsoids of revolution do not take into account variations in particle shape and sorting. Disc-shaped particles with equivalent b-axes to spheres have lower relative masses and require more relaxed sampling criteria compared to existing recommendations, whereas heavier cube-and rod-shaped particles require more stringent criteria. Empirical data from the River Rede, Northumberland, UK, an upland gravel-bed channel, indicate that samples are dominated by discs. However, particle shape was not constant in every grain-size fraction; blocky material (cubes and rods) was more frequent in the 63 mm fraction in comparison to the other finer fractions. Data based on the weight of the D 99 9 particle indicate that a larger sample weight is required when the coarsest size category of that sample is dominated by blocky material. Sorting also affects the size of the sample required to characterise a deposit; the more poorly sorted the deposit, the larger the sample has to be or the finer should be the truncation grain size. This is particularly evident in samples with a high matrix concentration. Two sample reference lines, developed from these data using the 0.1% by mass criteria, recommend larger minimum sample sizes (or finer truncation) in comparison to other published standards. Data from a second site support these results, indicating that they may be applicable to other poorly sorted upland gravel-bed streams. Analysis of the size category variance demonstrates that the new guidelines returned the lowest variance levels, suggesting that they should be used where particularly accurate sampling procedures are required.

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On The Accuracy Of Bed-Material Sampling

Cited by 28 publications

References 1 publication

A hybrid method for size characterization of coarse subsurface fluvial sediments

A hybrid method for size characterization of coarse subsurface fluvial sediments

Bias and precision of percentiles of bulk grain size distributions

Influence of particle shape and sorting upon sample size estimates for a coarse-grained upland stream

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