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.