Deep denitrification: Stream and groundwater biogeochemistry reveal contrasted but connected worlds above and below.

Excess nutrients from agricultural and urban development have created a cascade of ecological crises around the globe. Nutrient pollution has triggered eutrophication in most freshwater and coastal ecosystems, contributing to a loss in biodiversity, harm to human health, and trillions in economic damage every year. Much of the research conducted on nutrient transport and retention has focused on surface environments, which are both easy to access and biologically active. However, surface characteristics of watersheds, such as land use and network configuration, often do not explain the variation in nutrient retention observed in rivers, lakes, and estuaries. Recent research suggests subsurface processes and characteristics may be more important than previously thought in determining watershed-level nutrient fluxes and removal. In a small watershed in western France, we used a multi-tracer approach to compare surface and subsurface nitrate dynamics at commensurate spatiotemporal scales. We combined 3-D hydrological modeling with a rich biogeochemical dataset from 20 wells and 15 stream locations. Water chemistry in the surface and subsurface showed high temporal variability, but groundwater was substantially more spatially variable, attributable to long transport times (10-60 years) and patchy distribution of the iron and sulfur electron donors fueling autotrophic denitrification. Isotopes of nitrate and sulfate revealed fundamentally different processes dominating the surface (heterotrophic denitrification and sulfate reduction) and subsurface (autotrophic denitrification and sulfate production). Agricultural land use was associated with elevated nitrate in surface water, but subsurface nitrate concentration was decoupled from land use. Dissolved silica and sulfate are affordable tracers of residence time and nitrogen removal that are relatively stable in surface and subsurface environments. Together, these findings reveal distinct but adjacent and connected biogeochemical worlds in the surface and subsurface. Characterizing how these worlds are linked and decoupled is critical to meeting water quality targets and addressing water issues in the Anthropocene.

What do we need to predict groundwater nitrate recovery trajectories?

Nitrate contamination affects many of the Earth's aquifers and surface waters. Large-scale predictions of groundwater nitrate trends normally require the characterization of multiple anthropic and natural factors. To assess different approaches for upscaling estimates of nitrate recovery, we tested the influence of hydrological, historical, and biological factors on predictions of future nitrate concentration in aquifers. We tested the factors with a rich hydrogeological dataset from a fractured bedrock catchment in western France (Brittany). A sensitivity analysis performed on a calibrated model of groundwater flow, denitrification, and nitrogen inputs revealed that trends in nitrate concentration can effectively be approximated with a limited number of key parameters. The total mass of nitrate that entered the aquifer since the beginning of the industrial period needs to be characterized, but the shape of the historical nitrogen input time series can be largely simplified without substantially altering the predictions. Aquifer flow and transport processes can be represented by the mean and standard deviation of the residence time distribution, offering a tractable tool to make reasonable predictions at watershed to regional scales. Apparent sensitivity to denitrification rate was primarily attributable to time lags in oxygen depletion, meaning that denitrification can be simplified to an on/off process, defined only by the time needed for nitrate to reach the hypoxic reactive layer. Obtaining these key parameters at large scales is still challenging with currently available information, but the results are promising regarding our future ability to predict nitrate concentration with integrated monitoring and modeling approaches.

Stratification of reactivity determines nitrate removal in groundwater.

Biogeochemical reactions occur unevenly in space and time, but this heterogeneity is often simplified as a linear average due to sparse data, especially in subsurface environments where access is limited. For example, little is known about the spatial variability of groundwater denitrification, an important process in removing nitrate originating from agriculture and land use conversion. Information about the rate, arrangement, and extent of denitrification is needed to determine sustainable limits of human activity and to predict recovery time frames. Here, we developed and validated a method for inferring the spatial organization of sequential biogeochemical reactions in an aquifer in France. We applied it to five other aquifers in different geological settings located in the United States and compared results among 44 locations across the six aquifers to assess the generality of reactivity trends. Of the sampling locations, 79% showed pronounced increases of reactivity with depth. This suggests that previous estimates of denitrification have underestimated the capacity of deep aquifers to remove nitrate, while overestimating nitrate removal in shallow flow paths. Oxygen and nitrate reduction likely increases with depth because there is relatively little organic carbon in agricultural soils and because excess nitrate input has depleted solid phase electron donors near the surface. Our findings explain the long-standing conundrum of why apparent reaction rates of oxygen in aquifers are typically smaller than those of nitrate, which is energetically less favorable. This stratified reactivity framework is promising for mapping vertical reactivity trends in aquifers, generating new understanding of subsurface ecosystems and their capacity to remove contaminants.

Hedgerows reduce nitrate flux at hillslope and catchment scales via root uptake and secondary effects.

Agricultural contamination of groundwater with nitrate (NO3-) is one of the most widespread and pressing environmental issues. The preservation and planting of hedgerows around agricultural fields can reduce NO3- flux, but the efficacy of hedgerows depends on the amount of NO3- in soil and groundwater, hydrological flowpath and timing, and biogeochemical conditions surrounding and below roots. Quantifying these parameters is a major challenge, usually requiring involved and destructive fieldwork. Here, we present a new analytical method to characterize NO3- stratification using water chemistry sampled during piezometer slug tests. We tested this method with a network of wells in a hillslope intersected by an oak hedgerow during high- and low-water conditions, respectively spring and autumn. We found that hedgerows had a strong seasonal effect on near-surface NO3- dynamics in the proximity of the root system, reducing annual hillslope-level fluxes by 26 to 63%, comparable to NO3- removal from cover crop techniques. Hedgerow root uptake accounted for two-thirds of this reduction, with the remaining third attributable to secondary effects, potentially hedgerow-induced microbial retention or denitrification due to increased organic carbon and heterogeneous redox conditions in the rooting zone. However, a simple scaling exercise suggested that at the catchment level, hedgerow NO3- removal has a smaller effect (ca 1-10% reduction of annual flux), due to the large legacy of NO3- in the aquifer from past fertilizer application. These results suggest that while hedgerows cannot immediately solve problems of past groundwater contamination, protection and reestablishment of hedgerow networks could substantially accelerate recovery of groundwater quality on decadal timescales.

Unexpected spatial stability of water chemistry in headwater stream networks.

Understanding how water and solutes enter and propagate through freshwater landscapes in the Anthropocene is critical to protecting and restoring aquatic ecosystems and ensuring human water security. However, high hydrochemical variability in headwater streams, where most carbon and nutrients enter river networks, has hindered effective modelling and management. We developed an analytical framework informed by landscape ecology and catchment hydrology to quantify spatiotemporal variability across scales, which we tested in 56 headwater catchments, sampled periodically over 12 years in western France. Unexpectedly, temporal variability in dissolved carbon, nutrients and major ions was preserved moving downstream and spatial patterns of water chemistry were stable on annual to decadal timescales, partly because of synchronous variation in solute concentrations. These findings suggest that while concentration and flux cannot be extrapolated among subcatchments, periodic sampling of headwaters provides valuable information about solute sources and subcatchment resilience to disturbance.