Search for: All records

Preferential flow is ubiquitous in soils, and it affects water infiltration, runoff, and contaminant transport. Undisturbed soil lysimeters (n = 10; 900 cm²) were collected from an agricultural field to quantify the effect of climate, soil moisture, connectivity, and agricultural practices on water transport through the shallow vadose zone. A series of 10 rainfall simulations was conducted on each lysimeter (n = 100 events) and data were analysed within a framework of five case studies where we assessed the impact of rainfall intensity (n = 30 events), soil moisture (n = 28), and tillage (n = 21). Three lysimeters that had near‐zero flow initially were modified to investigate dynamics of direct surface connectivity through an artificial macropore in which we assessed the impacts of soil moisture (n = 12) and subsequent disruption via tillage (n = 9). Stable water isotopes were used to separate leachate into event (Q_e) and pre‐event water (Q_pe). Results showed that event water transport in leachate was not affected by rainfall intensity (Q_e/Q = 49% ± 21% to 50% ± 24%); however, event water decreased from 65% ± 5% to 23% ± 28% with increasing soil moisture. Lysimeters with artificial macropores resulted in leachate that was nearly all event water (85% ± 12% to 92% ± 4%) irrespective of soil moisture. Tillage decreased event water transport for both lysimeters with and without an artificial macropore by ~30%. Findings show how varying initial and boundary conditions produce a continuum of preferential flow. Water and tracer flux data collected in the current study are therefore essential for predicting conditions with high relevance of preferential flow and contaminant transport when assessing or modelling long‐term hydrographs where these conditions are only met during a small proportion of the flow time.

 

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.

 

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 Purpose The equilibrium sediment exchange process is defined as instantaneous deposition of suspended sediment to the streambed countered by equal erosion of sediment from the streambed. Equilibrium exchange has rarely been included in sediment transport studies but is needed when the sediment continuum is used to investigate the earth’s critical zone. Materials and methods Numericalmodeling in the watershed uplands and streamcorridor simulates sediment yield and sediment source partitioning for the Upper South Elkhorn watershed in Kentucky, USA.We simulate equilibrium exchange when uplandderived sediment simultaneously deposits to the streambed while streambed sediments erode. Sediment fingerprinting with stable carbon isotopes allowed constraint of the process in a gently rolling watershed. Results and discussion Carbon isotopes work well to partition upland sediment versus streambed sediment because sediment deposited in the streambed accrues a unique autotrophic, i.e., algal, fingerprint. Stable nitrogen isotopes do not work well to partition the sources in this study because the nitrogen isotope fingerprint of algae falls in the middle of the nitrogen isotope fingerprint of upland sediment. The source of sediment depends on flow intensity for the gently rolling watershed. Streambed sediments dominate the fluvial load for low and moderate events, while upland sediments become increasingly important during high flows and extreme events.We used sediment fingerprinting results to calibrate the equilibrium sediment exchange rate in the watershed sediment transport model. Conclusions Our sediment fingerprinting and modeling evidence suggest equilibrium sediment exchange is a substantial process occurring in the system studied. The process does not change the sediment load or streambed sediment storage but does impact the quality of sediment residing in the streambed. Therefore, we suggest equilibrium sediment exchange should be considered when the sediment continuumis used to investigate the critical zone.We conclude the paper by outlining future research priorities for coupling sediment fingerprinting with watershed modeling. 

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. 

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.

 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.