Using Paired In Situ High Frequency Nitrate Measurements to Better Understand Controls on Nitrate Concentrations and Estimate Nitrification Rates in a Wastewater‐Impacted River

Abstract

We used paired continuous nitrate ( NO3–) measurements along a tidally affected river receiving wastewater discharge rich in ammonium ( NH4+) to quantify rates of change in NO3– concentration ( RΔNO3) and estimate nitrification rates. NO3– sensors were deployed 30 km apart in the Sacramento River, California (USA), with the upstream station located immediately above the regional wastewater treatment plant (WWTP). We used a travel time model to track water transit between the stations and estimated RΔNO3 every 15 min (October 2013 to September 2014). Changes in NO3– concentration were strongly related to water temperature. In the presence of wastewater, RΔNO3 was generally positive, ranging from about 7 µM d−1 in the summer to near zero in the winter. Numerous periods when the WWTP halted discharge allowed the RΔNO3 to be estimated under no‐effluent conditions and revealed that in the absence of effluent, net gains in NO3– were substantially lower but still positive in the summer and negative (net sink) in the winter. Nitrification rates of effluent‐derived NH4 ( RNitrific_E) were estimated from the difference between RΔNO3 measured in the presence versus absence of effluent and ranged from 1.5 to 3.4 µM d−1, which is within literature values but tenfold greater than recently reported for this region. RNitrific_E was generally lower in winter (∼2 µM d−1) than summer (∼3 µM d−1). This in situ, high frequency approach provides advantages over traditional discrete sampling, incubation, and tracer methods and allows measurements to be made over broad areas for extended periods of time. Incorporating this approach into environmental monitoring programs can facilitate our ability to protect and manage aquatic systems.

Temporal Variability in Nitrate‐Discharge Relationships in Large Rivers as Revealed by High‐Frequency Data

“…Temperature can be an important indicator of seasonal patterns of uptake, particularly within rivers (Kraus et al, ). As the c‐Q slope is a function of both runoff generation contributions from the terrestrial landscape and in‐stream decay processes, correlations between environmental conditions and c‐Q slopes may provide information on the seasonal importance of landscape contributions versus in‐stream processing.…”

“…Recent advances in the use of in situ nutrient sensors, particularly those that measure nitrate (NO 3 − ) concentrations based on optical or chemical properties, have allowed new opportunities to better understand high temporal resolution water quality dynamics (Rode et al, ). Deployment of such sensors has the potential to increase the accuracy of load estimations, lower uncertainty, and provide a clearer understanding of the drivers of temporal NO 3 − concentration variability through near‐continuous NO 3 − concentration measurements (Duan et al, ; Kraus et al, ; Pellerin et al, ).…”

Use of Flow Cytometry and Stable Isotope Analysis to Determine Phytoplankton Uptake of Wastewater Derived Ammonium in a Nutrient-rich River

“…This observation is consistent with high rates of nitrification reported in the Sacramento River (Hager and Schemel, 1992;Parker et al, 2012a;O'Donnell 2014;Damashek et al, 2016;Kraus et al, 2017b). (Fig.…”

Quantifying Nitrate Dynamics of a Confluence Floodplain Wetland in a Disturbed Appalachian Watershed: High-Resolution Sensing and Modeling

“…A core takeaway of existing studies that have implemented this technology is the ability of high-resolution data to aid in understanding the short-term temporal dynamics of catchment processes, and the interactions between hydrology and water chemistry (see table A2 in the Appendix). To summarize, high-resolution sensing of nitrate data has shown utility in quantifying diel, event, and longer-term N loading dynamics (Heffernan and Cohen, 2010;Pellerin et al, 2012Pellerin et al, , 2014Carey et al, 2014;Burns et al, 2016;Rode et al, 2016) and improved assessments of nitrate biological processing, including continuous estimates of biotic processing rates in streams (Heffernan and Cohen, 2010;Rode et al, 2016) and the ability to partition and better understand sources and pathways of nitrate loading at the watershed scale (Koenig et al, 2017;Kraus et al, 2017;Miller et al, 2017;Wollheim et al, 2017). Despite this, few studies have assessed the utility of these data to improve numerical water quality models (Burns et al, 2019;Jiang et al, 2019).…”

“…Positive correlation of NO 3 and DOC in forest streamflow, but decoupled in areas of watershed development; timing differences of NO 3 and DOC transport were likely due to separate input sources; use of high-frequency data increased understanding of processes controlling solute variability. Kraus et al (2017) Lower stretch, Sacramento River, California N/A N/A Estimated nitrification rates and quantified rates of change of NO 3 concentration in a river that receives wastewater effluent Used paired high-resolution nitrate sensors to further understand nutrient sources and rates of transformation; sensing was also able to show that a large benthic source of nitrate was contributing to the signal downstream of the wastewater treatment plant. Miller et al Wetland reduced NO 3 concentrations by 49% and reduced loads by ~0.48 g m 2 d -1 ; when comparing low and high frequency sampling, the central nitrate concentration behavior was replicated, but high-frequency sampling obtained a much greater range of NO 3 concentrations; all low-frequency load estimates were higher than high-frequency estimates.…”