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or alter the same parameters they are supposed to measure. Therefore, a need exists to
develop non-destructive pore testing methods so that pores can be viewed and measured
without altering their structure.
Pore size distributions can be estimated using correlations to other more readily
measurable soil parameters such as cumulative grain size distribution. Two approximate
methods include the Arya and Paris method (1981) and the Haverkamp and Parlange method
(1986). These two methods are based on physical properties of soils and generally work on a
similar hypothesis involving water retention. This hypothesis uses the similarity between the
shapes of the cumulative grain size distribution of a soil and its water retention curve
(Haverkamp 2002). The water retention curve for a soil can be quickly converted to the pore
size distribution by using approximate capillary pressure relationships. The Arya and Paris
and the Haverkamp and Parlange models are based on the same fundamental hypothesis of
shape similarity, but they arrive at a water retention curve (and therefore a cumulative pore
size distribution) using different routes. The Arya and Paris model is generally more widely
used than the Haverkamp and Parlange model because it is more user-friendly and applicable
to a wide variety of soil types. The shape factor required for the Arya and Paris model is
considered constant or based on soil type and cumulative grain size distribution, and the
shape function for the Haverkamp and Parlange model is typically determined
experimentally. Additionally, the Arya and Paris model is not restricted to certain soil types,
but the Haverkamp and Parlange model is limited for use only with clean sands (Haverkamp
2002). The Arya and Paris model was chosen to model the pore size distributions of the soil
materials used in this study because of its ease of use and more widespread acceptance.