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 chara cteristic from particle-size data. The scaling parameter, a, in the origina l 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 sphe rical particles in the ith particle-size fraction (determined by the fracti on solid mass, w(i), and mean particle radius, R-i) and N-i is the number o f spherical particles of radius R-i required to trace the pore length gener ated 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 lo gistic 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 s ize, especially for the coarse fractions. In addition, or was also calculat ed as a single-value average for a given textural class. The three formulat ions of or were evaluated on 23 soils that represented a range in particle- size distribution, bulk density, and organic matter content. The average al pha consistently predicted higher pressure heads in the wet range and lower pressure heads in the dry range, The formulation based on the similarity p rinciple resulted in bias similar to that of the constant or approach, wher eas no bias was observed for the logistic growth equation. The logistic gro wth equation implicitly accounted for bias in experimental procedures, beca use if was fitted to log N-i values computed from experimental soil wafer c haracteristic data The formulation based on the similarity principle is ind ependent of bias that might be inherent in experimental data.