<p>Riparian zones serve as the interface between streams and the surrounding landscape, and the presence and health of riparian zone vegetation is critical to maintaining water quality in urban ecosystems. In recent years, light detection and ranging (LiDAR) has been used to characterize vegetation structure, and vegetation structural diversity has been tied to key ecosystem functions across ecosystems including productivity and nutrient dynamics. However, the extent to which LiDAR-derived structural diversity metrics reflect the functioning of riparian zones in urban environments remains poorly understood. Here we show that LiDAR-derived structural diversity metrics provide scalable assessments of riparian zone functioning in a mixed-use agricultural-urban stream system. Using elastic net models, we found that structural metrics, including vegetation area index (VAI), vertical complexity index (VCI), and 95th percentile vegetation height, are strong predictors of nitrate (<i>adj. R²</i> = 0.741), phosphate (<i>adj. R²</i> = 0.465), and total suspended solids (<i>adj. R²</i> = 0.436) when assessed at the full upstream riparian network scale. Models at local spatial scales performed poorly, emphasizing that riparian vegetation structure impacts water quality cumulatively across entire stream networks rather than at immediate upstream reaches. Land cover variables, including percent grassland and developed area, also remained important, highlighting that vegetation structure alone does not fully control water quality. By demonstrating the viability of LiDAR-derived structural diversity metrics in assessing riparian zone functioning, this study advances remote sensing-based monitoring efforts for urban riparian zones and can help direct field-based efforts to restore riparian zone health.</p>