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Understanding the physics of nitrate contamination in surface and subsurface water is vital for mitigating downstream water quality impairment. Though high frequency sensor data have become readily available and computational models more accessible, the integration of these two methods for improved prediction is underdeveloped. The objective of this study was to utilize high‐frequency data to advance our understanding and model representation of nitrate transport for an agricultural karst spring in Kentucky, USA. We collected 2‐years of 15‐min nitrate and specific conductance data and analyzed source‐timing dynamics across dozens of events to develop a conceptual model for nitrate hysteresis in karst. Thereafter, we used the sensing data, specifically discharge‐concentration indices, to constrain modeled nitrate prediction bounds as well as the uncertainty of hydrologic and nitrogen processes, such as soil percolation and biogeochemical transformation. Observed nitrate hysteresis behavior at the spring was complex and included clockwise (n = 11), counterclockwise (n = 13), and figure‐eight (n = 10) shapes, which contrasts with surface systems that are often dominated by a single hysteresis shape. Sensing results highlight the importance of antecedent connectivity to nitrate‐rich storages in determining the timing of nitrate delivery to the spring. After integrating hysteresis analysis into our numerical model evaluation, simulated nitrate prediction bounds were reduced by 43 ± 12% and parameter uncertainty by 36 ± 20%. Taken together, this study suggests that discharge‐concentration indices derived from high‐frequency sensor data can be successfully integrated into numerical models to improve process representation and reduce modeled uncertainty.

 

The Ohio River Basin (ORB) is responsible for 35% of total nitrate loading to the Gulf of Mexico yet controls on nitrate timing require investigation. We used a set of submersible ultraviolet nitrate analyzers located at 13 stations across the ORB to examine nitrate loading and seasonality. Observed nitrate concentrations ranged from 0.3 to 2.8 mg L⁻¹ N in the Ohio River's mainstem. The Ohio River experiences a greater than fivefold increase in annual nitrate load from the upper basin to the river's junction with the Mississippi River (74–415 Gg year⁻¹). The nitrate load increase corresponds with the greater drainage area, a 50% increase in average annual nitrate concentration, and a shift in land cover across the drainage area from 5% cropland in the upper basin to 19% cropland at the Ohio River's junction with the Mississippi River. Time‐series decomposition of nitrate concentration and nitrate load showed peaks centered in January and June for 85% of subbasin‐year combinations and nitrate lows in summer and fall. Seasonal patterns of the terrestrial system, including winter dormancy, spring planting, and summer and fall growing‐harvest seasons, are suggested to control nitrate timing in the Ohio River as opposed to controls by river discharge and internal cycling. The dormant season from December to March carries 51% of the ORB's nitrate load, and nitrate delivery is high across all subbasins analyzed, regardless of land cover. This season is characterized by soil nitrate leaching likely from mineralization of soil organic matter and release of legacy nitrogen. Nitrate experiences fast transit to the river owing to the ORB's mature karst geology in the south and tile drainage in the northwest. The planting season from April to June carries 26% of the ORB's nitrate and is a period of fertilizer delivery from upland corn and soybean agriculture to streams. The harvest season from July to November carries 22% of the ORB's nitrate and is a time of nitrate retention on the landscape. We discuss nutrient management in the ORB including fertilizer efficiency, cover crops, and nitrate retention using constructed measures.

 

Current understanding of the relationship between nitrate (NO₃⁻) uptake and energy cycling in lotic environments comes from studies conducted in low‐nutrient (NO₃⁻ < 1 mg‐N L⁻¹), small (discharge <1 m³s⁻¹) systems. Recent advances in sensor technology have allowed for continuous estimates of whole‐river NO₃⁻uptake, allowing us to address how the relationship between nutrient uptake and metabolism changes over time and space in larger rivers. We used a six‐month, controlled nitrogen (N) waste release into the eighth order Kansas River (USA) as an ecosystem level nutrient addition experiment. We deployed four NO₃⁻and dissolved oxygen sensors along a 33 km study reach, from February to May 2018, to assess the spatiotemporal relationship between nutrient uptake and stream metabolism during the waste addition. Contrary to our prediction, we did not find evidence of uptake saturation despite an extreme increase in nutrient supply during winter, a period of generally lower biological activity. Although high uptake rates were observed across the study reach, they were uncorrelated to gross primary production. Overall, despite winter temperatures, NO₃⁻uptake rates were high compared to small streams and rivers. We provide evidence that large rivers can be effective ecosystems for retaining and transforming nutrients, while showing that the fine‐scale mechanisms that regulate nutrient retention in large rivers are still largely unknown.

 

Nitrogen removal rates can vary with time, space, and external environmental drivers, but are underreported for karst environments. We carried out a multi‐year study of a karst conduit where we: (a) measured inputs and outputs of sediment nitrogen (SN and δ¹⁵N_Sed) and nitrate (NO₃⁻and δ¹⁵N_NO3); (b) developed, calibrated, and applied a numerical model of nitrogen physics and biogeochemistry; and (c) forecasted the impacts of climate and land use changes on nitrate removal and export. Data results from conduit inputs (SN = 0.43% ± 0.07%, δ¹⁵N_Sed = 5.07‰ ± 1.01‰) and outputs (SN = 0.36% ± 0.09%, δ¹⁵N_Sed = 6.45‰ ± 0.71‰) indicate net‐mineralization of SN and increase of δ¹⁵N_Sed(p < 10⁻²). However, δ¹⁵N_Sedincrease cannot be explained by SN mineralization alone and is instead accompanied by immobilization of isotopically heavier mineral nitrogen (δ¹⁵N_NO3 = 11.25‰ ± 6.96‰). Modeled SN and δ¹⁵N_Sedsub‐routines provided a boundary condition for DIN simulation and improved NO₃⁻model performance (from NSE = 0.06 to NSE = 0.68). Modeled spatial zones of removal occur in close proximity to conduit entrances, where deposition of labile organic matter promotes a three‐fold increase in denitrification (∼60 mg N m⁻² d⁻¹). Modeled temporal periods of removal occur during the dry‐season where longer residence times cause up to 90% removal of NO₃⁻inputs. Projected effects of environmental drivers suggest an increase in denitrification (+14.1%); however, this removal is largely offset by greater nitrate soil leaching (+28.1%) from wetter regional climate. Results suggest that conduits underlying mature karst terrain experience spatiotemporal removal gradients, which are modulated by solute and sediment delivery.

 

Abstract. Water quality models serve as an economically feasible alternative to quantify fluxes of nutrient pollution and to simulate effective mitigation strategies; however, their applicability is often questioned due to broad uncertainties in model structure and parameterization, leading to uncertain outputs. We argue that reduction of uncertainty is partially achieved by integrating stable isotope data streams within the water quality model architecture. This article outlines the use of stable isotopes as a response variable within water quality models to improve the model boundary conditions associated with nutrient source provenance, constrain model parameterization, and elucidate shortcomings in the model structure. To assist researchers in future modeling efforts, we provide an overview of stable isotope theory; review isotopic signatures and applications for relevant carbon, nitrogen, and phosphorus pools; identify biotic and abiotic processes that impact isotope transfer between pools; review existing models that have incorporated stable isotope signatures; and highlight recommendations based on synthesis of existing knowledge. Broadly, we find existing applications that use isotopes have high efficacy for reducing water quality model uncertainty. We make recommendations toward the future use of sediment stable isotope signatures, given their integrative capacity and practical analytical process. We also detail a method to incorporate stable isotopes into multi-objective modeling frameworks. Finally, we encourage watershed modelers to work closely with isotope geochemists to ensure proper integration of stable isotopes into in-stream nutrient fate and transport routines in water quality models. Keywords: Isotopes, Nutrients, Uncertainty analysis, Water quality modeling, Watershed. 

Excessive nitrate threatens a wide range of water resources, aquatic habitats, and sensitive infrastructure. Despite this problem, tracing a nutrient from its eventual fate back to its origin remains an elusive challenge due to heterogeneity in how nutrient sources and hydrologic pathways are connected. Typically, this problem is underdetermined (i.e., too many unknowns, not enough equations) and cannot be solved with existing methodologies. The theory of optimal transport allows for the solution of underdetermined systems, and here we construct a novel formulation for its use in water quality modeling. Our objective was to develop an optimal transport modeling framework—coupled to Bayesian source unmixing, loadograph pathway separation, and geospatial connectivity analysis—to apportion nitrate loading from three sources (soil, fertilizer, and manure) across three pathways (quick, intermediate, and slow), resulting in nine possible source‐pathway couplings (soil‐quick, soil‐intermediate, …, manure‐slow). We apply this model to a 30 month elemental (NO₃⁻) and isotopic (δ¹⁵N and δ¹⁸O) nitrate data set from a karst watershed in Kentucky, USA. Modeling results indicate that—of the nine possible source‐pathway couplings—nearly 60% of nitrate export is facilitated by just three: fertilizer‐quick (16.4%), manure‐intermediate (15.4%), and soil‐slow (27.2%). Further, we reinforce the need to explicitly consider heterogeneity in source‐pathway connectivity as homogeneous assumptions lead to erroneous inferences. The applicability of the model, its input requirements, and transferability to other sites is discussed. Lastly, we simulated two land management scenarios (field buffers and septic repair) and demonstrate how optimal transport can be used to test nutrient reduction strategies.

 

Nutrient dynamics in karst agroecosystems remain poorly understood, in part due to limited long‐term nested datasets that can discriminate upland and in‐stream processes. We present a 10‐year dataset from a karst watershed in the Inner‐Bluegrass Region of central Kentucky, consisting of nitrate (nitrate‐N [NO₃⁻]), dissolved reactive phosphorus (DRP), total organic carbon (TOC), and total ammoniacal‐N (TAN) measurements at nested spring and stream sites as well as flowrate at the watershed outlet. Hydrograph separation techniques were coupled with multiple linear regression and Empirical Mode Decomposition time‐series analysis to determine significance of seasonal processes and to generate continuous estimates of nutrient pathway loadings. Further, we used model results of benthic algae growth and decomposition dynamics from a nearby watershed to assess if transient storage in algal biomass could explain differences in spring and downstream watershed nutrient loading. Results highlight statistically significant seasonality for all nutrients at stream sites, but only for NO₃⁻at springs with longitudinal variability showing significant decreases occurring from spring to stream sites for NO₃⁻and DRP, and significant increases for TOC and TAN. Pathway loading analysis highlighted the importance of slow flow pathways to source approximately 70% of DRP and 80% of NO₃⁻. Results for in‐stream dynamics suggest that benthic autotroph dynamics can explain summer deviations for TOC, TAN, and DRP but not NO₃⁻. Regarding upland dynamics, our findings agree well with existing perceptions in karst for N pathways and upland source seasonality but deviate from perceptions that karst conduits are retentive of P, reflecting the limited buffering capacity of the soil profile and conduit sediments in the Inner‐Bluegrass. Regarding in‐stream fate, our findings highlighted the significance of seasonally driven nutrient processing in the bedrock‐controlled streambed to influence nutrient fluxes at the watershed outlet. Contrary to existing perceptions, we found high N attenuation and an unexplained NO₃⁻sink in the bedrock stream, leading us to postulate that floating macrophytes facilitate high rates of denitrification.