Checkered landscapes: hydrologic and biogeochemical nitrogen legacies along the river continuum

Abstract

Decades of agricultural intensification have led to elevated stream nitrogen (N) concentrations and eutrophication of inland and coastal waters. Despite widespread implementation of a range of strategies to reduce N export, expected improvements in water quality have not been observed. This lack of success has often been attributed to the existence of legacy N stores within the landscape. Here, we use the ELEMeNT-N model to quantify legacy accumulation and depletion dynamics over the last century (1930–2016) across 14 nested basins within the Grand River Watershed, a 6800 km2 agricultural watershed in the Lake Erie Basin. Model results reveal significant legacy N accumulation across the basin, ranging from 705 to 1071 kg ha−1, creating a checkered landscape of N legacies. The largest proportion (82%–96%) of this accumulated N is stored in soil organic N reservoirs, as biogeochemical legacy, and the remaining in groundwater, as hydrologic legacy. The fraction of N surplus accumulated in soil and groundwater is most strongly correlated with the calibrated watershed mean travel time µ, with the accumulation increasing with increases in µ. The mean travel time ranges from 5 to 34 years across the watersheds studied, and increases with increase in tile drainage, highlighting the strong control of anthropogenic management on legacy accumulation. Water quality improvement timescales were found to be heterogeneous across the watersheds, with greater legacies contributing to slower recovery.

Characterizing Catchment‐Scale Nitrogen Legacies and Constraining Their Uncertainties

“…(2017) and J. Liu et al. (2021) examine the sensitivity of the cumulative in‐stream N loading and find, similar to our results for the average subsurface N store, that the mean travel time and the two denitrification rate constants in the source zone and the subsurface are the three most influential parameters. This similarity between the sensitivity of the in‐stream N loading and the subsurface N store can be explained by the structure of the ELEMeNT model which lumps all flow paths to the stream into the subsurface store.…”

“…In previous studies of N legacies, the relative value of biogeochemical and hydrologic N legacies is highly variable. Whereas the N buildup in the subsurface store is also found to be lower than the buildup in the source zone in the Grand river basin (J. Liu et al., 2021), a subcatchment of the Iowa‐Cedar basin (Ilampooranan et al., 2019) and the Mississippi river basin (Van Meter et al., 2017), the opposite result is reported for the Susquehanna river basin (Van Meter et al., 2017). The magnitude of hydrologic N legacies in J. Liu et al.…”

“…(2019) using the SWAT‐LAG model, and J. Liu et al. (2021) and Van Meter et al. (2017) using the ELEMeNT model.…”

“…Yet, such modeling approaches are typically based on lumped transfer functions that relate the N inputs to the N stream export at catchment scale and they do not explicitly disentangle the role of biogeochemical and hydrologic legacies. Only few studies, all of them focusing on North America, explicitly consider and examine both types of N legacies at catchment scale using mechanistic models, namely a modified version of the Soil Water Assessment Tool model (SWAT‐LAG, Ilampooranan et al., 2019), the NOAA's Geophysical Fluid Dynamics Laboratory Land Model (LM3‐TAN, Lee et al., 2016), and the more parsimonious Exploration of Long‐tErM Nutrient Trajectories model (ELEMeNT, Chang et al., 2021; J. Liu et al., 2021; Van Meter et al., 2017, 2018).…”

“…10.1029/2021WR031587 3 of 32 Geophysical Fluid Dynamics Laboratory Land Model (LM3-TAN, Lee et al, 2016), and the more parsimonious Exploration of Long-tErM Nutrient Trajectories model (ELEMeNT, Chang et al, 2021;J. Liu et al, 2021;, 2018.…”