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.
Subject
Earth-Surface Processes,Ecology, Evolution, Behavior and Systematics
Cited by
5 articles.
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