Note: TWI is topographic wetness index, NDMI is normalized difference moisture index, AIC is Akaike’s information criteria, and RMSPE is root mean square prediction error.

Fire and vegetation variables generally had stronger correlations (0.15-0.67) with log[NO₃^-] than topographic variables (0.03 – 0.32) (Table 3). Linear mixed model selection identified watershed area, riparian extent, TWI, and NDMI as the best predictors of log[NO₃^-] (Supplemental Table 1). Stream NO₃^-was positively related to riparian extent and TWI, but negatively related to watershed area and NDMI (Figure 2). Mean NDMI had the strongest correlation with log[NO₃^-] (Figure 2). In the NO₃^- MLR model, the selected predictor variables, with the exception of riparian extent, were significant and accounted for 51.4% of the variance in log[NO₃^-] (Table 4). In the NO₃^- SSN model, TWI and NDMI were the only significant predictor variables and the predictors explained 36% of variation in log[NO₃^-] (Table 4).

Topographic variables had weak correlations (<0.32) with both stream Na⁺ and NO₃^-(Table 3). Vegetation predictors generally had much stronger correlations with NO₃^- compared to Na⁺, with the exception of shrub cover (Table 3). Burn variables had slightly higher correlations with NO₃^- compared to Na⁺(Table 3). All predictor variables that were selected through linear mixed model selection were weakly correlated with water chemistry (<0.33) (Supplemental Figure 2). The one exception was a strong inverse relationship between mean NDMI and stream NO₃^- which had a correlation coefficient of -0.67 (Supplemental Figure 2).

In the Na⁺ SSN model, a majority of variation (53.1%) in log[Na⁺] was explained by flow-connected autocorrelation (Table 4). Na⁺ exhibited strong positive autocorrelation where semivariance was low at short lag distances, but increased with distance (Figure 3). When flow-connected autocovariance was modeled with a spherical fit, Na⁺had a nugget of 0.001, sill of 0.029, and range of 3700 m (Figure 3). The low nugget suggests that our sampling adequately captured variability at small spatial scales and that there is relatively little unexplained variation. The low sill reflects the low overall variance in streamwater Na⁺ concentrations. The range indicates that samples that are > 3700 m apart are no longer correlated.

In the NO₃^- SSN model, flow-connected autocorrelation explained 41.5% of variation in log[NO₃^-] (Table 4). Stream NO₃^- had high semivariance across all flow-connected distances, though semivariance peaked at intermediate lag distances (1000-5000 m) (Figure 3). When flow-connected autocovariance was modeled with an exponential fit, NO₃^- had a nugget of 0.385, sill of 0.708, and range of 8800 m which is equal to our maximum sampling distance (Figure 3). The large nugget and sill values are consistent with the substantial unexplained variance and high overall variance in stream NO₃^- concentrations. The lowest semivariance in NO₃^- is still greater than the maximum Na⁺ semivariance (Figure 3).