Diel patterns in stream nitrate concentration produced by in-stream processes

Abstract

Abstract. Diel variability in stream NO3- concentration represents the sum of all processes affecting NO3- concentration along the flow path. Being able to partition diel NO3- signals into portions related to different biochemical processes would allow calculation of daily rates of such processes that would be useful for water quality predictions. In this study, we aimed to identify distinct diel patterns in high-frequency NO3- monitoring data and investigated the origin of these patterns. Monitoring was performed at three locations in a 5.1 km long stream reach draining a 430 km2 catchment. Monitoring resulted in 355 complete daily recordings on which we performed a k-means cluster analysis. We compared travel time estimates to time lags between monitoring sites to differentiate between in-stream and transport control on diel NO3- patterns. We found that travel time failed to explain the observed lags and concluded that in-stream processes prevailed in the creation of diel variability. Results from the cluster analysis showed that at least 70 % of all diel patterns reflected shapes typically associated with photoautotrophic NO3- assimilation. The remaining patterns suggested that other processes (e.g., nitrification, denitrification, and heterotrophic assimilation) contributed to the formation of diel NO3- patterns. Seasonal trends in diel patterns suggest that the relative importance of the contributing processes varied throughout the year. These findings highlight the potential in high-frequency water quality monitoring data for a better understanding of the seasonality in biochemical processes.

Metabolism and Soil Water Viscosity Control Diel Patterns of Nitrate and DOC in a Low Order Temperate Stream

“…To our knowledge, ours is the first study to report diel oscillations of [NO 3 − –N] to be driven by the viscosity effect and to show that a major shift occurs in the dormant season when biological controls are minor and the viscosity effect becomes dominant. High‐frequency solute data has improved our ability estimate and model stream river NO 3 − uptake on larger temporal and spatial scales (e.g., Greiwe et al., 2021; Heffernan & Cohen, 2010; Rode, Halbedel née Angelstein, et al., 2016; Yang et al., 2019). However, our results suggest that in gaining or loosing systems caution needs to be taken when attributing diel variation in [NO 3 − –N] to biological processing entirely (Hensley & Cohen, 2016).…”

“…To date, the focus has been on high‐flow events (Rode, Wade, et al., 2016) with much less emphasis on high‐frequency time series under baseflow conditions. At baseflow, when the impacts of storm events on solute inputs are minimal, diel oscillations in DOC and NO 3 − concentrations can be detected in streams and rivers (Greiwe et al., 2021; Heffernan & Cohen, 2010; Pellerin et al., 2012; Rode, Halbedel née Angelstein, et al., 2016). Stream biological processes are often considered the predominant driver for these patterns (Nimick et al., 2011).…”

“…Observations of similar diel cycles of chlorophyll‐α concentrations support this mechanism (Spencer et al., 2007). For NO 3 − , when present, diel cycles often show concentrations to be the lowest in the afternoon hours and the highest in the early morning (Greiwe et al., 2021; Nimick et al., 2011 and references therein; Rode, Halbedel née Angelstein, et al., 2016). This pattern has been typically attributed to higher photoautotrophic nitrogen demand and photosynthesis rates during daytime (Heffernan & Cohen, 2010; Roberts et al., 2007; Rode, Halbedel née Angelstein, et al., 2016; Valett et al., 2008), although nitrification and denitrification may play a role too (Heffernan & Cohen, 2010).…”

Catchment concentration–discharge relationships across temporal scales: A review

“…Evapotranspiration contributes to diel water table fluctuations, producing variations in C–Q responses (Bond et al, 2002; Czikowsky & Fitzjarrald, 2004; Flewelling et al, 2014; Schilling, 2007; Schwab et al, 2016). Biogeochemically‐driven diel C–Q signals are evident during steady baseflow conditions, resulting from in‐stream processing of non‐conservative solutes, such as nitrate (Greiwe et al, 2021; Heffernan & Cohen, 2010) and phosphorus (Cohen et al, 2013). However, seasonality and spatial variability (e.g., upland vs. in‐stream) of biological processing rates can obscure diel solute signals within streams (Aubert & Breuer, 2016; Hensley & Cohen, 2016; Rusjan & Mikoš, 2010).…”