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 (ϴmax), the ψ-scaling parameter (ψo), and the shape parameter (λ). We examined trends between these hydraulic parameters and bulk physical properties, both textural—geometric mean, Mg, and geometric standard deviation, σg, of particle diameter—and structural—bulk density, ρb, the fraction of unfilled pore space at natural saturation, Ae, and porosity-based randomness index, Φs, defined as the excess of total porosity over 0.3. Structural parameters Φs and Ae 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 Cp statistic identified combinations of textural and structural parameters for the most useful predictive models: for ϴmax, including Ae, Φs, and σg, and for both ψo and λ, including only textural parameters, although use of Ae can somewhat improve ψo 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 Ae and Φs can improve PTM predictions, especially for the wettest part of the ϴ(ψ) curve.