Hydrologic regimes drive nitrate export behavior in human-impacted watersheds

Abstract

Abstract. Agricultural watersheds are significant contributors to downstream nutrient excess issues. The timing and magnitude of nutrient mobilization in these watersheds are driven by a combination of anthropogenic, hydrologic, and biogeochemical factors that operate across a range of spatial and temporal scales. However, how, when, and where these complex factors drive nutrient mobilization has previously been difficult to capture with low-frequency or spatially limited data sets. To address this knowledge gap, we analyzed daily nitrate concentration (c) and discharge (Q) data for a 4-year period (2016–2019) from five nested, agricultural watersheds in the midwestern United States that contribute nutrient loads to the Gulf of Mexico. These records allow us to investigate nutrient mobilization patterns at a temporal and spatial resolution not previously possible. The watersheds span two distinct landforms shaped by differences in glacial history, resulting in natural soil properties that necessitated different drainage infrastructure across the study area. To investigate nutrient export patterns under different hydrologic conditions, we partitioned the hydrograph into stormflow and baseflow periods and examined those periods separately through the analysis of their concentration–discharge (c–Q) relationships on annual, seasonal, and event timescales. Stormflow showed consistent chemostatic patterns across all seasons, while baseflow showed seasonally dynamic c–Q patterns. Baseflow exhibited chemodynamic conditions in the summer and fall and more chemostatic conditions in the winter and spring, suggesting that water source contributions during baseflow were nonstationary. Baseflow chemodynamic behavior was driven by low-flow, low-NO3- conditions during which in-stream and near-stream biological processing likely moderated in-stream NO3- concentrations. Additionally, inputs from deeper groundwater with longer residence times and lower-NO3- concentration likely contributed to low-NO3- conditions in stream, particularly in the larger watersheds. Stormflow c–Q behavior was consistent across watersheds, but baseflow c–Q behavior was linked to the intensity of agriculture and the density of built drainage infrastructure, with more drainage infrastructure associated with higher loads and more chemostatic export patterns across the watersheds. This suggests that the way humans replumb the subsurface in response to geologic conditions has implications for hydrologic connectivity, homogenization of source areas, and, subsequently, nutrient export during both baseflow and stormflow. Our analysis also showed that anomalous flow periods greatly influenced overall c–Q patterns, suggesting that the analysis of high-resolution records at multiple scales is critical when interpreting seasonal or annual patterns.

Synthesizing the impacts of baseflow contribution on concentration–discharge (<i>C</i>–<i>Q</i>) relationships across Australia using a Bayesian hierarchical model

“…Across both long and short timescales, a consistent finding is that, within a particular catchment, the C-Q relationship (and thus export behaviour) is dependent on whether streamflow is dominated by baseflow or quickflow, i.e. the baseflow contribution to total flow (Gorski and Zimmer, 2021;Knapp et al, 2020;Minaudo et al, 2019). These studies also identified baseflow contribution as a key driver of the variation in C-Q relationships across catchments (Musolff et al, 2015;Moatar et al, 2017).…”

Tile Drainage Increases Total Runoff and Phosphorus Export During Wet Years in the Western Lake Erie Basin

“…Whereas, the transport of SRP is confined to shallower soil layers that are activated only in wetter years. 4; Gorski and Zimmer, 2021). The lack of difference in SRP C-Q slopes between the 2 years, both annually and during March-July, suggests that transport of SRP is more strongly influenced by precipitation and stream discharge than C-Q dynamics.…”

“…However, as the contributing area shrinks following precipitation events, near-stream areas with greater denitrification rates and lower nitrate concentrations contribute relatively more to stream discharge compared to upland areas with greater nitrate concentrations (Marinos et al, 2020), resulting in contributing areas with more heterogeneous nitrate concentrations and a more chemodynamic nitrate C-Q behavior. For examples Marinos et al (2020) and Gorski and Zimmer (2021) found chemodynamic nitrate C-Q behavior to be dominant at low flows, while chemostatic nitrate C-Q behavior was more common during high flow events. These observations are consistent with our results showing more chemodynamic nitrate C-Q behavior in 2018, compared to the chemostatic response observed in 2019.…”

“…Calculating the variation in nutrient concentration as function of stream discharge therefore provides insight into how watersheds store and release water and nutrients. We quantified SRP and nitrate C-Q relationships two separate ways: (1) by fitting power-law relationships between nutrient concentrations and discharge (e.g., Godsey et al, 2009;Musolff et al, 2015;Knapp et al, 2020) and ( 2) by calculating the ratio of coefficient of variation (CV) for nutrient concentrations and discharge to assess the relative variability of each (Thompson et al, 2011;Gorski and Zimmer, 2021).…”

“…March-July nitrate (NO − 3 ) concentration-discharge (C-Q) slope (C; Pearson's r = 0.16 and −0.46, respectively) and coefficient of variation (CV) ratio (D; Pearson's r = 0.07 and −0.17, respectively) vs. tile drainage during 2018 and 2019. Variability of Nutrient Concentration-Discharge Dynamics With Tile Drainage Intensity Annual and March-July SRP displayed relatively weak, enriching chemodynamic behavior as indicated by low positive SRP C-Q slopes in both 2018 and 2019 (b = 0.26-0.34; Table4;Gorski and Zimmer, 2021). The lack of difference in SRP C-Q slopes between the 2 years, both annually and during March-July, suggests that transport of SRP is more strongly influenced by precipitation and stream discharge than C-Q dynamics.…”