DISCUSSION
The significance of N distribution and processes in the shallow
and deep subsurface. Figure 6 suggests that the subsurface N
concentration contrast (or Cratio) arising from
different land uses predominantly control export patterns. The
representatives of shallow and deep waters, such as soil and
groundwater, have been shown before to correlate well with stream
nitrate concentration across different land uses (Sudduth et al., 2013).
The export pattern dependence on concentration contrast echoes the
decades-long End Member Mixing Approach (EMMAS) that uses end-member
concentrations to infer stream water chemistry (Hooper et al., 1990).
The spatial data synthesis across the U.S. continent from this work
enables the generalization of this idea across diverse climate, geology,
and land use conditions. The physics-based watershed reactive transport
modeling facilitates the derivation of the general equation that can be
used to estimate export patterns based on streamflow concentrations or
measured shallow and deep water concentrations.
These shallow versus deep physical contrasts originate from chemical and
physical weathering in pristine sites (Brantley et al., 2017). In urban
and agriculture sites, these contrasts arise from human engineering
efforts with tile drains, impervious surfaces, and water pipes that
modify environments (Grimm et al., 2008). The concentration differences
in shallow and deep waters arise not only from different subsurface
distribution of N source but also from different processes. In
agricultural lands, nitrate concentrations in shallow waters are high
not only because abundant N sources leach nitrate; it is also because
denitrification is limited with the presence of abundant
O2. In deeper groundwater, with limited
O2, denitrification can occur and reduce nitrate (Kolbe
et al., 2019).
Under broad conditions, the relative magnitude of shallow versus deep
water concentrations may hinge on soil properties and geologic
structure. These subsurface structures determine shallow and deep
connectivity, recharge and water table depth (Brantley et al., 2017), as
well as local biogeochemical conditions (e.g., anoxic condition, organic
carbon availability) that control the extent of denitrification and
nitrate removal (Kolbe et al., 2019; Tesoriero et al., 2015). Miller et
al. (2017) showed that nitrate export exhibits a dilution pattern in
Tomorrow River, a site with permeable sand and gravel, but a flushing
pattern in Duck Creek with low-permeability clayey soil clayey soils
developed from glacial tills. The overwhelming convergence toward highb values in agriculture lands, however, indicates that the
concentration contrasts in shallow versus deep waters are the
predominant control of export patterns.
In urban watersheds, we observe varied export patterns and a large
number of sites have higher concentrations in deep water compared to
shallow water. This is possibly caused by underground leaky sewage and
pipes that can contaminate groundwater and surface water (Divers et al.,
2013; Lerner et al., 1999; Pennino et al., 2016). A large number of
urban watersheds also exhibit chemostatic patterns, potentially due to
the co-occurrence of both shallow N sources (e.g., lawn fertilizer, pet
waste, atmospheric deposition, automobile emission) and deeper
underground input from buried sewage and septic systems. Kaushal et al.
(2014) and Newcomer Johnson et al. (2014) suggest that urban N export
can be influenced by the degree of hydrologic connectivity associated
with impervious surface, stormwater infrastructure and sewage pipe, and
stream restoration. Point source discharge from wastewater treatment
plant (WWTP) can also increase nutrient loading (Luthy et al., 2015),
potentially contributing to varied export patterns. In arid and semiarid
regions with small urban streams, high nitrate concentration from WWTP
can dominate the base flow at the dry time and become diluted under high
flow conditions, resulting in dilution pattern (Marti et al., 2010). In
fact, urban watersheds are complicated as the groundwater-soil-surface
water interactions are modified by the level of urbanization and
management, and non-point sources from leaky infrastructure and chronic
groundwater contamination (Kaushal & Belt, 2012).
Limitations, simplifications, and uncertainties . The conceptual
model in Figure 1 and the general b equation in Figure 6 emphasize two
end members in shallow and deep zones and are meant to build a simple
relationship between export patterns and major components of water
contributing to the stream. Here we lump the waters into shallow and
deep waters components to illustrate the first-order control. Such
simplification is often necessary in practice. In urban watersheds, for
example, the impervious surface often contributes to large surface
runoff in storms. Surface runoff however typically dominates as short
pulses in early stages of storm events often resulting in an overall
limited contribution of surface runoff to annual discharge (e.g., 11%
by Pellerin et al. (2008). These temporarily large contributions are
followed by rapid subsurface flow (via underground stormwater pipes)
with much longer duration. Field studies typically have incomplete
information (e.g., hydrograph separation, isotopic signature) of
contributing flow paths. It is therefore often necessary to lump
different water sources into major compartments (Barnes & Raymond,
2010), in order to capture average behaviors.
With its simplicity, the model does not take into account specifics of
individual sites, which can lead to deviations from the b curve in
Figure 6. For example, in some places, N is distributed and processed in
a way that demands more than two end members (Cowie et al., 2017; Miller
et al., 2017). The model also does not explicitly account for N removal
in streams. Instream removal depends on a wide variety of parameters
including local climate and seasonality, landscape structure (e.g.,
topography, hyporheic zone), and biogeochemical conditions (e.g.,
nitrate legacy, stream carbon source) (Dodds et al., 2002; Hill, 1996;
Mulholland et al., 2008; Vidon & Hill, 2004). Significant instream N
removal can lead to underestimation of Csw and
Cdw but to a different extent. As Csw is
estimated under high flow conditions where instream N removal is often
not efficient, it may not be heavily influenced by instream processes
(Dodds et al., 2002). The estimation of deep water concentrations
however is based on low flow conditions where instream N removal can be
highly effective such that Cdw may be underestimated.
This possible different extent of underestimation can shift
Cratio (= Csw / Cdw) and
b values to higher values, moving data points toward the top right end
of the d b curve. This may be the reason that some data points from Ag
and Mixed fall in the right-hand side of the b curve in Figure 6.
Inferring shallow and deep water chemistry from stream
chemistry. This study indicates that we can infer shallow and deep
water chemistry from streamflow chemistry under different flow regimes.
This is important as detailed subsurface characterization and
concentration measurements are often limited to only a few long-term
monitoring sites in developed countries (Brantley et al., 2018; Gran et
al., 2019), although we often claim an era of “big data”. As shown in
Figure 6, few intensively measured watersheds have both soil water and
groundwater chemistry measurements. The extrapolation of shallow and
deep water chemistry from high flow and low flow stream chemistry
therefore enables estimation of water chemistry (without digging holes
in the ground) to infer possible export patterns and loads. This
approach can be applied not only for nitrate, but also for other solutes
in general.
N export under changing climate. The agriculture sites have
increased nitrate concentrations in shallow and deep waters by 15-20
times and 9-16 times, respectively, compared to undeveloped sites
(Figure 3a). In fact, extensive tile drainage networks in agricultural
lands (e.g., 80% of the landscape in the Midwest) shortcut the shallow
water directly to stream, lowers water table (Blann et al., 2009; King
et al., 2015). In effect, these draining tiles decrease vertical
connectivity to deeper aquifers (Association, 2018) and therefore
increase concentration contrasts between shallow water (e.g., soil water
and tile drainage water) and deep groundwater, inducing pronounced
flushing patterns (Figure 6). The flushing pattern indicates that export
is sensitive to large hydrological events such as flooding, which has
been predicted to intensify as the pace of climate change accelerates
(Prein et al., 2017).
On the other hand, if high nitrate in shallow water is redirected more
to the deeper subsurface via higher vertical connectivity, the water
will reroute through longer flow paths, enhancing transformation via
denitrification and nitrate removal (Kolbe et al., 2019). The extent of
such transformation will depend on local conditions. The longer and
slower groundwater flow paths however will also lead to decade-to
century-scale time lags between anthropogenic N inputs and riverine
outputs (Sebilo et al., 2013; Van Meter & Basu, 2015). This can present
significant challenges for balancing nitrogen budget (e.g., the
‘missing’ N in mass-balance) (Boyer et al., 2002) and management
effectiveness (e.g., land-use management, N-loading reduction) (Sebilo
et al., 2013; Van Meter et al., 2017). In addition, this downward N flux
also raises tantalizing questions about long-term subsurface structure
and functioning. How and how much do these man-made, high nutrient
levels elevate carbon effluxes (Zamanian et al., 2018), accelerate
weathering processes, and alter watershed functioning (Kaushal et al.,
2013; Perrin et al., 2008)? These broader earth system responses can
have far-reaching impacts on carbon and nutrient cycles at the global
scale.