Abstract: Nitrate-nitrogen (NO3-N) concentrations in stream water often respond uniquely to changes in inter-annual conditions (e.g., biological N uptake and precipitation) in individual catchments. In this paper, we assess (1) how the spatial distribution of NO3-N concentrations varies across a dense network of nonnested catchments and (2) how relationships between multiple landscape factors [within whole catchments and hydrologically sensitive areas (HSAs) of the catchments] and stream NO3-N are expressed under a variety of annual conditions. Stream NO3-N data were collected during two synoptic sampling events across >55 tributaries and two synoptic sampling periods with >11 tributaries during summer low flow periods. Sample tributaries drain mixed land cover watersheds ranging in size from 0.150 to 312 km2 and outlet directly to Cayuga Lake, New York. Changes in NO3-N concentration ratios between each sampling event suggest a high degree of spatial heterogeneity in catchment response across the Cayuga Lake Watershed, ranging from 0.230 to 61.4. Variations in NO3-N concentrations within each of the large synoptic sampling events were also high, ranging from 0.040 to 8.7 mg NO3-N/l (March) and 0.090 to 15.5 mg NO3-N/l (October). Although Pearson correlation coefficients suggest that this variability is related to multiple landscape factors during all four sampling events, partial correlations suggest percentage of row crops in the catchments as the only similar factor in March and October and catchment area as the only factor during summer low flows. Further, the strength of the relationships is typically lower in the HSAs of catchment. Advancing current understanding of such variations and relationships to landscape factors across multiple catchments – and under a variety of biogeochemical and hydrological conditions – is important, as (1) nitrate continues to be employed as an indicator of regional aquatic ecosystem health and services and (2) a unified framework approach for understanding individual catchment processes is a rapidly evolving focus for catchment-based science and management.