Autotrophic nitrate uptake in river networks: A modeling approach using continuous high-frequency data

High-frequency sensor measurements enable calculation of continuous autotrophic nitrate uptake rate based on its intrinsic relationship with gross primary production (GPP). The spatiotemporally available data offer prospects to advance process understandings across scales. We used continuous 15-min data (2011-2015) from a forest upstream reach and an agricultural downstream reach of the Selke River, Germany. Based on the high-frequency data, we developed a parsimonious approach for regionalizing the autotrophic uptake rate, considering effects of global radiation and riparian shading. For networked modeling, we integrated this approach into the fully distributed mesoscale hydrological nitrate model (mHM-Nitrate). Daily GPP-based uptake rate calculations showed distinct seasonal patterns and ranges in the agricultural and forest streams (mean values were 80.9 and 15.5 mgNm^-2d^-1, respectively). Validation in the two streams showed acceptable performance (R² = 0.47 and 0.45, respectively) and spatial transferability of the regionalization approach, given its parsimony. Networked modeling results showed high spatiotemporal variability in nitrate transport and uptake throughout the river network. The magnitude of gross uptake increased, whereas uptake efficiency decreased significantly along stream order. Longitudinal analysis in the main stem of the Selke River revealed that riparian shading and inter-annual hydrochemical variations strongly influenced daily dynamics of the uptake efficiency. This study provides a parsimonious and transferable procedure for regionalizing in-stream autotrophic nitrate uptake based on high-frequency data at reach scale. Integrating this approach in the mHM-Nitrate model allows detailed nitrate transport and in-stream uptake processes to be investigated throughout river networks.