Resolving structural influences on water-retention properties of alluvial deposits
With the goal of improving property-transfer model (PTM) predictions of unsaturated hydraulic properties, we investigated the influence of sedimentary structure, defined as particle arrangement during deposition, on laboratory-measured water retention (water content vs. potential [θ(ψ)]) of 10 undisturbed core samples from alluvial deposits in the western Mojave Desert, California. The samples were classified as having fluvial or debris-flow structure based on observed stratification and measured spread of particle-size distribution. The θ(ψ) data were fit with the Rossi–Nimmo junction model, representing water retention with three parameters: the maximum water content (θ max ), the ψ-scaling parameter (ψ o ), and the shape parameter (λ). We examined trends between these hydraulic parameters and bulk physical properties, both textural—geometric mean, M g , and geometric standard deviation, σ g , of particle diameter—and structural—bulk density, ρ b , the fraction of unfilled pore space at natural saturation, A e , and porosity-based randomness index, Φ s , defined as the excess of total porosity over 0.3. Structural parameters Φ s and A e were greater for fluvial samples, indicating greater structural pore space and a possibly broader pore-size distribution associated with a more systematic arrangement of particles. Multiple linear regression analysis and Mallow's C p statistic identified combinations of textural and structural parameters for the most useful predictive models: for θ max , including A e , Φ s , and σ g , and for both ψ o and λ, including only textural parameters, although use of A e can somewhat improve ψ o predictions. Textural properties can explain most of the sample-to-sample variation in θ(ψ) independent of deposit type, but inclusion of the simple structural indicators A e and Φ s can improve PTM predictions, especially for the wettest part of the θ(ψ) curve.