Scaling parameter to predict the soil water characteristic from particle-size distribution data

The Arya-Paris model is an indirect method to estimate the soil water characteristic from particle-size data. The scaling parameter, a, in the original model was assumed constant for all soil textures. In this study, alpha is defined as alpha(i) = (log N-i/log n(i)), where n(i) is the number of spherical particles in the ith particle-size fraction (determined by the fraction solid mass, w(i), and mean particle radius, R-i) and N-i is the number of spherical particles of radius R-i required to trace the pore length generated by the same solid mass in a natural structure soil matrix, An estimate for log N-i was obtained by either relating log N-i to log n(i) using a logistic growth equation or by relating log N-i linearly to log (w(i)/R-i(3)) based on the similarity principle. For any given texture, both approaches showed that alpha was not constant but decreased with increasing particle size, especially for the coarse fractions. In addition, or was also calculated as a single-value average for a given textural class. The three formulations of or were evaluated on 23 soils that represented a range in particle-size distribution, bulk density, and organic matter content. The average alpha consistently predicted higher pressure heads in the wet range and lower pressure heads in the dry range, The formulation based on the similarity principle resulted in bias similar to that of the constant or approach, whereas no bias was observed for the logistic growth equation. The logistic growth equation implicitly accounted for bias in experimental procedures, because if was fitted to log N-i values computed from experimental soil wafer characteristic data The formulation based on the similarity principle is independent of bias that might be inherent in experimental data.