Abstract
Many models are available to fit the curve of a grain size distribution, GSD. The article lists 61 models and 33 comparative studies of models. Examples explain how to extract stratification data from split-spoon samples and how to verify whether a model respects the internal structure of the data. This extraction is essential to determine the field hydraulic properties and in situ behavior of soils. Many tools are available to assess the goodness-of-fit, GOF. This article proves that these tools are not independent. A first new equation is obtained, which links the RMSE (root mean squared error) and (1-R2), R2 being the coefficient of determination. A second new equation is obtained, which links the AIC (Akaike information criterion) and (1-R2) for a GSD. The two novel equations help to derive a new method to assess the GOF for GSDs. The distributions of (1-R2) values clearly classify fitting models as poor, fair, good, or very good. The author’s MDM (modal decomposition method) is the only one to rank very good for any soil. Its basic assumption is verified by individual sublayers, which provide a sound basis. Its explanations are correct for in situ permeability in stratified soils. Most models do not pay attention to the data’s internal structure and distribution of residuals. The MDM respects the internal structure and yields Gaussian residuals for a GSD, which may not be the case of other models. Clear graphs illustrate underfitting and overfitting, and clear rules are given to explain how to use the MDM and extract useful information from a GSD. Free pre-programmed Excel files are made available to readers.
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Data Availability
The data used in this article were either provided in Tables for examples, or are the data that can be found in the cited references.
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Chapuis, R.P. Fitting models for a grain size distribution: a review. Bull Eng Geol Environ 82, 427 (2023). https://doi.org/10.1007/s10064-023-03444-5
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DOI: https://doi.org/10.1007/s10064-023-03444-5