Atmospheric inputs to forest ecosystems vary considerably over small spatial scales due to subtle changes in relief and vegetation structure. Relationships between throughfall fluxes (ions that pass through the canopy in water), topographic and canopy characteristics derived from sub-meter resolution light detection and ranging (LiDAR), and field measurements were compared to test the potential utility of LiDAR in empirical models of atmospheric deposition. From October 2012 to May 2013, we measured bulk (primarily wet) deposition and sulfate-S, chloride (Cl(-)), and nitrate-N fluxes beneath eight clusters of Douglas fir trees differing in size and canopy exposure in the Santa Cruz Mountains, California. For all trees sampled, LiDAR data were used to derive canopy surface height, tree height, slope, and canopy curvature, while tree height, diameter (DBH), and leaf area index were measured in the field. Wet season throughfall fluxes to Douglas fir clusters ranged from 1.4 to 3.8 kg S ha(-1), 17-54 kg Cl(-) ha(-1), and 0.2-4 kg N ha(-1). Throughfall S and Cl(-) fluxes were highest under clusters with large trees at topographically exposed sites; net fluxes were 2-18-fold greater underneath exposed/large clusters than all other clusters. LiDAR indices of canopy curvature and height were positively correlated with net sulfate-S fluxes, indicating that small-scale canopy surface features captured by LiDAR influence fog and dry deposition. Although tree diameter was more strongly correlated with net sulfate-S throughfall flux, our data suggest that LiDAR data can be related to empirical measurements of throughfall fluxes to generate robust high-resolution models of atmospheric deposition.