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.
Highlights
In-stream processing of nutrients can significantly influence loads and concentrations transported to receiving ecosystems (Peterson et al, 2001; Roberts and Mulholland, 2007)
We aim to investigate (1) whether there are diel patterns in NO−3 concentration, (2) whether these patterns are subject to instream or transport control, and (3) how they are related to environmental conditions and potential drivers
Considering only days with complete upstream and downstream observations, i.e., comparing averages of the same day, NO−3 concentration significantly increased between S1 and S2 and significantly decreased between S2 and S3 (Fig. S2)
Summary
In-stream processing of nutrients can significantly influence loads and concentrations transported to receiving ecosystems (Peterson et al, 2001; Roberts and Mulholland, 2007). Depending on the rates of nutrient uptake and release, in-stream nutrient processing may reduce the risk of harmful eutrophication (Birgand et al, 2007). Water quality management requires knowledge of NO−3 processing rates to predict how rapidly NO−3 inputs are transformed and attenuated. This is relevant in light of a changing climate and a predicted reduction of summer flow (Austin and Strauss, 2011; Mosley, 2015; Hellwig et al, 2017)
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