Nitrogen mass balance of a tile-drained agricultural watershed in East-Central Illinois

Field-scale evaluation of struvite phosphorus and nitrogen leaching relative to monoammonium phosphate

Struvite (MgNH4 PO4 ·6H2 O) is a wastewater-derived phosphorus (P) fertilizer with potential to reduce P as well as nitrogen (N) losses due to its low water solubility. To test hypothesized lower P and N losses from struvite relative to monoammonium phosphate (MAP), field experiments with a randomized-complete block design were conducted in central (Urbana) Illinois on an Endoaquoll-Argiudoll complex and in southern (Ewing) Illinois on a Fragiudalf-Hapludalf complex. Fertilizer was broadcast applied in the fall prior to spring planting of soybean (Glycine max L.) at a maintenance rate of 29.5 kg P ha-1 (Urbana) and 22.0 kg P ha-1 (Ewing). In the spring, soil extractable N and Mehlich 3-P at 0- to 15-cm and 15- to 35-cm depths were determined, and leached N and P were estimated using fall-installed ion-exchangeable resin (IER) lysimeters. At Urbana, soil extractable nitrate-N was higher under MAP than struvite at 0- to 15-cm depth. At Ewing, soil Mehlich 3-P under struvite was lower than MAP at both depths. At Urbana, leached P was 10-fold lower, and leached N was twofold lower under struvite than MAP. Soybean yields were similar between MAP and struvite at Urbana (4.1-4.3 Mg ha-1 ) and Ewing (3.2-3.5 Mg ha-1 ), but at Ewing yields were 23% higher under struvite compared to the P-unfertilized control. Off-season yield-scaled P and N losses under struvite were lower than MAP by 51% at Urbana and by 10% at Ewing. Our results support the hypothesized potential of struvite to reduce nutrient losses while meeting crop P needs. Additionally, we identify disproportionally greater reductions in N leaching and yield-scaled N losses by substituting struvite for MAP in fall applications, indicating that struvite can offer greater relative benefits for N loss reduction than P loss reduction.

Split fertilizer nitrogen application with a cereal rye cover crop reduces tile nitrate loads in a corn-soybean rotation

Splitting fertilizer nitrogen (N) applications and using cover crops are management strategies to reduce nitrate in tile drainage water. We investigated split fertilizer N applications to corn (Zea mays L.) on crop yields and tile nitrate loss in both corn and soybean (Glycine max L.) in rotation from 2016 through 2019. We evaluated the inclusion of cover crops in a split-N treatment. Fertilizer N treatments included 100% in the fall; 50% in the fall + 25% at planting + 25% at side-dress; 100% as spring preplant; 75% as spring preplant (reduced N rate); 50% as spring preplant + 50% at side-dress; and 50% as spring preplant + 50% at side-dress with a cover crop. We did not find significant differences between split and single full rate N application treatments for corn yields or tile nitrate loss; however, the reduced N rate treatment significantly decreased corn yield by 10%. Cumulative tile nitrate losses (over four seasons) ranged from 115 kg ha-1 for all of the N in the fall to 65 kg ha-1 for 50% as spring preplant + 50% at side-dress with a cover crop, a decrease of 43%. Tile nitrate loss responded similarly to (corn) N treatments under both corn and soybean, with 64% of the loss under corn and 36% under soybean. Our results suggest that decreasing the fertilizer N rate may impact corn yield more than nitrate loss, while split fertilizer N application with a cover crop has potential to reduce tile nitrate loss without decreasing crop yield.

Integrated Agricultural Practices and Engineering Technologies Enhance Synergies of Food-Energy-Water Systems in Corn Belt Watersheds

Interconnected food, energy, water systems (FEWS) require systems level understanding to design efficient and effective management strategies and policies that address potentially competing challenges of production and environmental quality. Adoption of agricultural best management practices (BMPs) can reduce nonpoint source phosphorus (P) loads, but there are also opportunities to recover P from point sources, which could also reduce demand for mineral P fertilizer derived from declining geologic reserves. Here, we apply the Integrated Technology-Environment-Economics Model to investigate the consequences of watershed-scale portfolios of agricultural BMPs and environmental and biological technologies (EBTs) for co-benefits of FEWS in Corn Belt watersheds. Via a pilot study with a representative agro-industrial watershed with high P and nitrogen discharge, we show achieving the nutrient reduction goals in the watershed; BMP-only portfolios require extensive and costly land-use change (19% of agricultural land) to perennial energy grasses, while portfolios combining BMPs and EBTs can improve water quality while recovering P from corn biorefineries and wastewater streams with only 4% agricultural land-use change. The potential amount of P recovered from EBTs is estimated as 2 times as much as the agronomic P requirement in the watershed, showing the promise of the P circular economy. These findings inform solution development based on the combination of agricultural BMPs and EBTs for the cobenefits of FEWS in Corn Belt watersheds.

Denitrification in Intrinsic and Specific Groundwater Vulnerability Assessment: A Review

Several groundwater vulnerability methodologies have been implemented throughout the years to face the increasing worldwide groundwater pollution, ranging from simple rating methodologies to complex numerical, statistical, and hybrid methods. Most of these methods have been used to evaluate groundwater vulnerability to nitrate, which is considered the major groundwater contaminant worldwide. Together with dilution, the degradation of nitrate via denitrification has been acknowledged as a process that can reduce reactive nitrogen mass loading rates in both deep and shallow aquifers. Thus, denitrification should be included in groundwater vulnerability studies and integrated into the various methodologies. This work reviewed the way in which denitrification has been considered within the vulnerability assessment methods and how it could increase the reliability of the overall results. Rating and statistical methods often disregard or indirectly incorporate denitrification, while numerical models make use of kinetic reactions that are able to quantify the spatial and temporal variations of denitrification rates. Nevertheless, the rating methods are still the most utilized, due to their linear structures, especially in watershed studies. More efforts should be paid in future studies to implement, calibrate, and validate user-friendly vulnerability assessment methods that are able to deal with denitrification capacity and rates at large spatial and temporal scales.

Controls on subsurface nitrate and dissolved reactive phosphorus losses from agricultural fields during precipitation-driven events

The magnitude of nitrogen (N) and phosphorus (P) exported from agricultural fields via subsurface tile drainage systems is determined by site-specific interactions between weather, soil, field, and management characteristics. Here, we used multiple regression analyses to evaluate the influence of 29 controls of precipitation event-driven discharge, nitrate (NO₃^--N) load, and dissolved reactive P (DRP) load from subsurface tile drains, leveraging a unique dataset of ~7000 precipitation events observed across 40 agricultural fields (n = 190 site years) instrumented to collect continuous water quality samples. We calculated marginal effects of significant controls and assessed the modifying influence of event rainfall, duration, and intensity, and antecedent precipitation. Tile discharge was strongly and positively influenced by previous 7-day precipitation and total rainfall and negatively influenced by daily temperature and tile spacing. Both tile NO₃^--N and DRP loads were positively influenced by transport and source variables, including event discharge and total fertilizer applied as well as soil test P (STP) in the case of tile DRP load; factors with the strongest negative influence on tile NO₃^--N and DRP loads were related to time of year. The strength and direction of both positive and negative controls also varied with precipitation characteristics. For example, the positive influence of event discharge on nutrient loads lessened as event duration, event intensity, and previous 7-day precipitation increased, while the positive influence of N and P sources strengthened, particularly in response to extreme (or maximum) events. Results here demonstrate the predominant role of transport and source controls while accounting for interactive effects among site-specific characteristics and underscore the importance of storm dynamics when managing N and P loss from agricultural fields.

Where Have All the Nutrients Gone? Long-Term Decoupling of Inputs and Outputs in the Willamette River Watershed, Oregon, United States

Better documentation and understanding of long-term temporal dynamics of nitrogen (N) and phosphorus (P) in watersheds is necessary to support effective water quality management, in part because studies have identified time lags between terrestrial nutrient balances and water quality. We present annual time series data from 1969 to 2012 for terrestrial N and P sources and monthly data from 1972 to 2013 for river N and P for the Willamette River Basin, Oregon, United States. Inputs to the watershed increased by factors of 3 for N and 1.2 for P. Synthetic fertilizer inputs increased in total and relative importance over time, while sewage inputs decreased. For N, increased fertilizer application was not matched by a proportionate increase in crop harvest; N use efficiency decreased from 69% to 38%. P use efficiency increased from 52% to 67%. As nutrient inputs to terrestrial systems increased, river concentrations and loads of total N, total P, and dissolved inorganic P decreased, and annual nutrient loads were strongly related to discharge. The N:P ratio of both sewage and fertilizer doubled over time but there was no similar trend in riverine export; river N:P concentrations declined dramatically during storms. River nutrient export over time was related to hydrology and waste discharge, with relatively little influence of watershed balances, suggesting that accumulation within soils or groundwater over time is mediating watershed export. Simply managing yearly nutrient balances is unlikely to improve water quality; rather, many factors must be considered, including soil and groundwater storage capacity, and gaseous loss pathways.

Prioritizing river basins for intensive monitoring and assessment by the US Geological Survey

The US Geological Survey (USGS) is currently (2020) integrating its water science programs to better address the nation's greatest water resource challenges now and into the future. This integration will rely, in part, on data from 10 or more intensively monitored river basins from across the USA. A team of USGS scientists was convened to develop a systematic, quantitative approach to prioritize candidate basins for this monitoring investment to ensure that, as a group, the 10 basins will support the assessment and forecasting objectives of the major USGS water science programs. Candidate basins were the level-4 hydrologic units (HUC04) with some of the smaller HUC04s being combined; median candidate-basin area is 46,600 km². Candidate basins for the contiguous United States (CONUS) were grouped into 18 hydrologic regions. Ten geospatial variables representing land use, climate change, water use, water-balance components, streamflow alteration, fire risk, and ecosystem sensitivity were selected to rank candidate basins within each of the 18 hydrologic regions. The two highest ranking candidate basins in each of the 18 regions were identified as finalists for selection as "Integrated Water Science Basins"; final selection will consider input from a variety of stakeholders. The regional framework, with only one basin selected per region, ensures that as a group, the basins represent the range in major drivers of the hydrologic cycle. Ranking within each region, primarily based on anthropogenic stressors of water resources, ensures that settings representing important water-resource challenges for the nation will be studied.

The role of policy in social-ecological interactions of nitrogen management in the Mississippi River basin

Excess nitrogen (N) loading in the Mississippi River basin is a major water quality issue, encompassing large spatial scales and feedbacks between social and biophysical entities. Effective management depends on reductions in agricultural N loading, mainly from the Corn Belt region in the upper reaches of the basin. In this study, we evaluated the role of federal Nutrient Task Force policy on N management from 2000 to 2015. We analyzed trends in nitrate (NO₃ ^- ) concentrations from monitoring data in 148 priority watersheds. We compared water quality trends with state nutrient reduction strategies, monitoring efforts, and land use. Of the 148 watersheds, 13 displayed a significant decrease in NO₃ ^- concentrations, 24 displayed a significant increase, 51 displayed a nonsignificant trend, and 60 had insufficient data to analyze. We demonstrate that policy efforts on a large scale are slow to establish, but states and watersheds that showed signs of policy acting successfully could serve as examples for improved N management moving forward. Despite considerable variability, states with the most comprehensive strategies, evidenced by word count and presence of recommended elements, were almost exclusively located in the Corn Belt region. States with more thorough nutrient reduction strategies also tended to have a larger number of monitoring sites in priority watersheds (R = .42), demonstrating the potential for adaptive management. States with the most consistent improvements in NO₃ ^- concentrations tended to have the most comprehensive policies, whereas variation in water quality trends was partly attributed to land use factors including slope and dominance of corn (Zea mays L.) and soy [Glycine max (L.) Merr.].

Influence of no-till and a winter rye cover crop on nitrate losses from tile-drained row-crop agriculture in Iowa

Artificial subsurface drainage is necessary to maintain agricultural production in the soils and climate of north-central Iowa. However, it can result in adverse environmental impacts, because it intercepts and diverts some water and soluble NO₃ -N directly to streams. We investigated the impact of no-till and a winter rye cover crop (Secale cereale L.) on seasonal and annual NO₃ -N concentration and loading in leachate from a corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotation. The eight treatments are chisel plow (CT), chisel plow with winter cereal rye (CTr), no-till (NT), and no-till with winter cereal rye (NTr), with "-C" indicating corn and "-S" indicating soybeans. Plots with artificial subsurface drainage were monitored for water quality from 2011 to 2015. The NT and CTr treatments consistently decreased NO₃ -N loss on the seasonal and annual scales compared with CT. Compared with NT, NTr did not reduce NO₃ -N loading nor concentration in leachate, probably because of low NO₃ leaching potential from NT combined with low rye cover crop biomass throughout the study with NT. The 5-yr average annual NO₃ -N concentrations were: 16.9 mg L^-1 with CT-S, 16.7 mg L^-1 with CT-C, 12.6 mg L^-1 with NT-S, 12.0 mg L^-1 with CTr-S, 11.8 mg L^-1 with CTr-C, 11.4 mg L^-1 with NTr-S and NTr-C, and 11.1 mg L^-1 with NT-C. Overall, both no-till and a cover crop showed potential for improving N management for water quality.

Comparing Machine Learning Approaches for Predicting Spatially Explicit Life Cycle Global Warming and Eutrophication Impacts from Corn Production

Agriculture ranks as one of the top contributors to global warming and nutrient pollution. Quantifying life cycle environmental impacts from agricultural production serves as a scientific foundation for forming effective remediation strategies. However, methods capable of accurately and efficiently calculating spatially explicit life cycle global warming (GW) and eutrophication (EU) impacts at the county scale over a geographic region are lacking. The objective of this study was to determine the most efficient and accurate model for estimating spatially explicit life cycle GW and EU impacts at the county scale, with corn production in the U.S.’s Midwest region as a case study. This study compared the predictive accuracies and efficiencies of five distinct supervised machine learning (ML) algorithms, testing various sample sizes and feature selections. The results indicated that the gradient boosting regression tree model built with approximately 4000 records of monthly weather features yielded the highest predictive accuracy with cross-validation (CV) values of 0.8 for the life cycle GW impacts. The gradient boosting regression tree model built with nearly 6000 records of monthly weather features showed the highest predictive accuracy with CV values of 0.87 for the life cycle EU impacts based on all modeling scenarios. Moreover, predictive accuracy was improved at the cost of simulation time. The gradient boosting regression tree model required the longest training time. ML algorithms demonstrated to be one million times faster than the traditional process-based model with high predictive accuracy. This indicates that ML can serve as an alternative surrogate of process-based models to estimate life-cycle environmental impacts, capturing large geographic areas and timeframes.

Effect of Deficit Irrigation on Nitrogen Uptake of Sunflower in the Low Desert Region of California

Nitrogen (N) accounts for more than 80% of the total mineral nutrients absorbed by plants and it is the most widely limiting element for crop production, particularly under water deficit conditions. For a comprehensive understanding of sunflower Helianthus annuus N uptake under deficit irrigation conditions, experimental and numerical simulation studies were conducted for full (100% ETC) and deficit (65% ETC) irrigation practices under the semi-arid conditions of the Imperial Valley, California, USA. Plants were established with overhead sprinkler irrigation before transitioning to subsurface drip irrigation (SDI). Based on pre-plant soil N testing, 39 kg ha−1 of N and 78 kg ha−1 of P were applied as a pre-plant dry fertilizer in the form of monoammonium phosphate (MAP) and an additional application of 33 kg ha−1 of N from urea ammonium nitrate (UAN-32) liquid fertilizer was made during the growing season. Soil samples at 15-cm depth increments to 1.2 m (8 layers, 15 cm each) were collected prior to planting and at three additional time points from two locations each in the full and deficit irrigation treatments. We used HYDRUS/2D for the simulation in this study and the model was calibrated for the soil moisture parameters (θs and θr), the rate constant factors of nitrification (the sensitive parameter) in the liquid and solid states (μw,3, and μs,3). The HYDRUS model predicted cumulative root water uptake fluxes of 533 mm and 337 mm for the 100% ETC and 65% ETC, respectively. The simulated cumulative drainage depths were 23.7 mm and 20.4 mm for the 100% ETC and 65% ETC which represented only 4% and 5% of the applied irrigation water, respectively. The soil wetting profile after SDI irrigation was mostly around emitters for the last four SDI irrigation events, while the maximum values of soil moisture in the top 30 cm of the soil profile were 0.262 cm3 cm−3 and 0.129 cm3 cm−3 for 100% ETC and 65% ETC, respectively. The 16.5 kg ha−1 (NH2)2CO (50% of the total N) that was applied during the growing season was completely hydrolyzed to NH4+ within 7 days of application, while 4.36 mg cm−1 cumulative decay was achieved by the end of the 98-day growing season. We found that 86% of NH4+ (74.25 mg cm−1) was nitrified to NO3− while 14% remained in the top 50 cm of the soil profile. The denitrification and free drainage of NO3− were similar for 100% ETC and 65% ETC, and the maximum nitrate was drained during the sprinkler irrigation period. By the end of the growing season, 30.8 mg cm−1 of nitrate was denitrified to N2 and the reduction of nitrate plant uptake was 17.1% for the deficit irrigation section as compared to the fully irrigated side (19.44 mg cm−1 vs. 16.12 mg cm−1). This reduction in N uptake due to deficit irrigation on sunflower could help farmers conserve resources by reducing the amount of fertilizer required if deficit irrigation practices are implemented due to the limited availability of irrigation water.

Springs drive downstream nitrate export from artificially-drained agricultural headwater catchments

Excessive nutrient loading from small agricultural headwaters can substantially degrade downstream water quality and ecological conditions. But, our understanding of the scales and locations to implement nutrient attenuation tools within these catchments is poor. To help inform farm- and catchment-scale management, we quantified nitrate export in nine one-kilometre-long lowland agricultural headwaters fed by tile and open tributary drains in a region with high groundwater nitrate (<1 to >15 mg L^-1 NO₃-N) over four years. Across-catchment differences in upstream spring water nitrate concentrations predicted differences in annual nitrate loads at catchment outlets (range <1-72 megagrams NO₃-N 365 d^-1), and nitrate loads were higher in wet seasons and wet years, reflecting strong groundwater influences. Partitioning the sources of variability in catchment nitrate fluxes revealed that ~60% of variation was accounted for by a combination of fluxes from up-stream springs and contributions from tile and open tributary drains (46% and 15%, respectively), with ~40% of unexplained residual variation likely due to groundwater upwellings. Although tile and open tributary drains contributed comparatively less to catchment loads (tile drains: <0.01 and up to 50 kg NO₃-N d^-1; open drains: <5 kg and up to 100 kg NO₃-N d^-1), mitigation targeted at these localised, farm-scale sources will contribute to decreasing downstream nitrate fluxes. However, high nitrate loads from groundwater mean current NO₃-N waterway management and rehabilitation practices targeting waterway stock exclusion by fencing alone will be insufficient to reduce annual NO₃-N export. Moreover, managing catchment nutrient fluxes will need to acknowledge contributions from groundwater as well as farm-scale losses from land. Overall, our results highlight how nutrient fluxes in spring-fed waterways can be highly dynamic, dominated more by groundwater than local run-off, and point to the scales and locations where nitrate attenuation tools should be implemented.

Quantifying the contribution of tile drainage to basin-scale water yield using analytical and numerical models

The Des Moines Lobe (DML) of north-central Iowa has been artificially drained by subsurface drains and surface ditches to provide some of the most productive agricultural land in the world. Herein we report on the use of end-member mixing analysis (EMMA) models and the numerical model Soil and Water Assessment Tool (SWAT) to quantify the contribution of tile drainage to basin-scale water yields at various scales within the 2370 km² Boone River watershed (BRW), a subbasin within the Des Moines River watershed. EMMA and SWAT methods suggested that tile drainage provided approximately 46 to 54% of annual discharge in the Boone River and during the March to June period, accounted for a majority of flow in the river. In the BRW subbasin of Lyons Creek, approximately 66% of the annual flow was sourced from tile drainage. Within the DML region, tile drainage contributes to basin-scale water yields at scales ranging from 40 to 16,000 km², with downstream effects diminishing with increasing watershed size. Developing a better understanding of water sources contributing to river discharge is needed if mitigation and control strategies are going to be successfully targeted to reduce downstream nutrient export.

Tile Drainage Nitrate Losses and Corn Yield Response to Fall and Spring Nitrogen Management

Nitrogen (N) management strategies that maintain high crop productivity with reduced water quality impacts are needed for tile-drained landscapes of the US Midwest. The objectives of this study were to determine the effect of N application rate, timing, and fall nitrapyrin addition on tile drainage nitrate losses, corn ( L.) yield, N recovery efficiency, and postharvest soil nitrate content over 3 yr in a corn-soybean [ (L.) Merr.] rotation. In addition to an unfertilized control, the following eight N treatments were applied as anhydrous ammonia in a replicated, field-scale experiment with both corn and soybean phases present each year in Illinois: fall and spring applications of 78, 156, and 234 kg N ha, fall application of 156 kg N ha + nitrapyrin, and sidedress (V5-V6) application of 156 kg N ha. Across the 3-yr study period, increases in flow-weighted NO concentrations were found with increasing N rate for fall and spring N applications, whereas N load results were variable. At the same N rate, spring vs. fall N applications reduced flow-weighted NO concentrations only in the corn-soybean-corn rotation. Fall nitrapyrin and sidedress N treatments did not decrease flo8w-weighted NO concentrations in either rotation compared with fall and spring N applications, respectively, or increase corn yield, crop N uptake, or N recovery efficiency in any year. This study indicates that compared with fall N application, spring and sidedress N applications (for corn-soybean-corn) and sidedress N applications (for soybean-corn-soybean) reduced 3-yr mean flow-weighted NO concentrations while maintaining yields.

Precipitation Dominates Interannual Variability of Riverine Nitrogen Loading across the Continental United States

Excessive nitrogen loading to waterways leads to increased eutrophication and associated water quality impacts. An understanding of the regional and interannual variability in nitrogen loading and associated drivers is necessary for the design of effective management strategies. Here we develop a parsimonious empirical model based on net anthropogenic nitrogen input, precipitation, and land use that explains 68% of the observed variability in annual total nitrogen flux (Q_TN) (76% of ln(Q_TN)) across 242 catchment years. We use this model to present the first spatially and temporally resolved estimates of Q_TN for all eight-digit hydrologic unit (HUC8) watersheds within the continental United States (CONUS), focusing on the period 1987-2007. Results reveal high spatial and temporal variability in loading, with spatial variability primarily driven by nitrogen inputs, but with interannual variability and the occurrence of extremes dominated by precipitation across over three-quarters of the CONUS. High interannual variability and its correlation with precipitation persist at large aggregated scales. These findings point to a fundamental challenge in managing regions with high nutrient loading, because these regions also exhibit the strongest interannual variability and because the impact of changes in management practices will be modulated by meteorological variability and climatic trends.

Drainage and Nitrate Leaching from Artificially Drained Maize Fields Simulated by the Precision Nitrogen Management Model

Environmental nitrogen (N) losses (e.g., nitrate leaching, denitrification, and ammonia volatilization) frequently occur in maize ( L.) agroecosystems. Decision support systems, designed to optimize the application of N fertilizer in these systems, have been developed using physically based models such as the Precision Nitrogen Management (PNM) model of soil and crop processes, which is an integral component of Adapt-N, a decision support tool providing N fertilizer recommendations for maize production. Such models can also be used to estimate N losses associated with particular management practices and over a range of current climates and future climate projections. The objectives of this study were to update the PNM model to include an option for simulating soil-water processes in artificially drained soils, and to calibrate the revised PNM model and test it against multiyear field studies in New York and Minnesota with different soils and management practices. Minimal calibration was required for the model. Denitrification rate constants were calibrated by minimizing the error between simulated and observed nitrate leaching for each study site. The normalized root mean squared error of cumulative daily drainage for the validation sets ranged from 10 to 23%. For cumulative daily nitrate leaching, the normalized root mean squared error ranged from 11 to 28% for the validation sets. The minimal calibration required and relatively simple data inputs make the PNM model a broadly applicable tool for simulating water and N flows in maize systems.

Evaluation of Phosphorus Filter Media for an Inline Subsurface Drainage Treatment System

Subsurface drainage from agricultural land has been identified as a contributor of both N and P into surface waters, leading to water quality degradation and eutrophication. This study evaluates the ability of P sorption media (PSM; expanded shale, expanded clay, furnace slag, and natural soil) to sorb P in both batch and column tests. Batch sorption tests estimated sorption of 3.4, 1.2, and 0.5 g P kg for expanded shale, expanded clay, and natural soil, respectively. Furnace slag sorption was evaluated for fine (FS), small (FS), and large (FS) particle sizes, with estimated sorption of 6.8, 5.1, and 3.8 g P kg, respectively. Phosphorus removal for the three furnace slag particle sizes and natural soil were tested in flow-through columns operated at residence times of 50, 17, and 7 s. A decrease in residence time reduced P removal in all columns evaluated. Following all trials, the average P removal from influent was 50% for FS, followed by 27% for FS (furnace slag-coated pea gravel), 22% for FS, and 6% for sandy loam-coated pea gravel. The data from this study provides crucial information for developing and sizing an inline tile drainage treatment system to remove P from tile drainage outlets before reaching surface waters.

An Integrated Landscape Designed for Commodity and Bioenergy Crops for a Tile-Drained Agricultural Watershed

Locating bioenergy crops on strategically selected subfield areas of marginal interest for commodity agriculture can increase environmental sustainability. Location and choice of bioenergy crops should improve environmental benefits with minimal disruption of current food production systems. We identified subfield soils of a tile-drained agricultural watershed as marginal if they had areas of low crop productivity index (CPI), were susceptible to nitrate-nitrogen (NO-N) leaching, or were susceptible to at least two other forms of environmental degradation (marginal areas). In the test watershed (Indian Creek watershed, IL) with annual precipitation of 852 mm, 3% of soils were CPI areas and 22% were marginal areas. The Soil and Water Assessment Tool was used to forecast the impact of growing switchgrass ( L.), willow ( spp.), and big bluestem ( Vitman) in these subfield areas on annual grain yields, NO-N and sediment exports, and water yield. Simulated conversion of CPI areas from current land use to bioenergy crops had no significant ( 0.05) impact on grain production and reduced NO-N and sediment exports by 5.0 to 6.0% and 3.0%, respectively. Conversion of marginal areas from current land use to switchgrass forecasted the production of 34,000 t of biomass and reductions in NO-N (26.0%) and sediment (33.0%) exports. Alternatively, conversion of marginal areas from current land use to willow forecasted similar reductions as switchgrass for sediment but significantly ( 0.01) lower reductions in annual NO-N export (18.0 vs. 26.0%).

Contrasting Nitrogen Fate in Watersheds Using Agricultural and Water Quality Information

Surplus nitrogen (N) estimates, principal component analysis (PCA), and end-member mixing analysis (EMMA) were used in a multisite comparison contrasting the fate of N in diverse agricultural watersheds. We applied PCA-EMMA in 10 watersheds located in Indiana, Iowa, Maryland, Nebraska, Mississippi, and Washington ranging in size from 5 to 1254 km with four nested watersheds. Watershed Surplus N was determined by subtracting estimates of crop uptake and volatilization from estimates of N input from atmospheric deposition, plant fixation, fertilizer, and manure for the period from 1987 to 2004. Watershed average Surplus N ranged from 11 to 52 kg N ha and from 9 to 32% of N input. Solute concentrations in streams, overland runoff, tile drainage, groundwater (GW), streambeds, and the unsaturated zone were used in the PCA-EMMA procedure to identify independent components contributing to observed stream concentration variability and the end-members contributing to streamflow and NO load. End-members included dilute runoff, agricultural runoff, benthic-processing, tile drainage, and oxic and anoxic GW. Surplus N was larger in watersheds with more permeable soils (Washington, Nebraska, and Maryland) that allowed greater infiltration, and oxic GW was the primary source of NO load. Subsurface transport of NO in these watersheds resulted in some removal of Surplus N by denitrification. In less permeable watersheds (Iowa, Indiana, and Mississippi), NO was rapidly transported to the stream by tile drainage and runoff with little removal. Evidence of streambed removal of NO by benthic diatoms was observed in the larger watersheds.

High Nitrate Concentrations in Some Midwest United States Streams in 2013 after the 2012 Drought

Nitrogen sources in the Mississippi River basin have been linked to degradation of stream ecology and to Gulf of Mexico hypoxia. In 2013, the USGS and the USEPA characterized water quality stressors and ecological conditions in 100 wadeable streams across the midwestern United States. Wet conditions in 2013 followed a severe drought in 2012, a weather pattern associated with elevated nitrogen concentrations and loads in streams. Nitrate concentrations during the May to August 2013 sampling period ranged from <0.04 to 41.8 mg L as N (mean, 5.31 mg L). Observed mean May to June nitrate concentrations at the 100 sites were compared with May to June concentrations predicted from a regression model developed using historical nitrate data. Observed concentrations for 17 sites, centered on Iowa and southern Minnesota, were outside the 95% confidence interval of the regression-predicted mean, indicating that they were anomalously high. The sites with a nitrate anomaly had significantly higher May to June nitrate concentrations than sites without an anomaly (means, 19.8 and 3.6 mg L, respectively) and had higher antecedent precipitation indices, a measure of the departure from normal precipitation, in 2012 and 2013. Correlations between nitrate concentrations and watershed characteristics and nitrogen and oxygen isotopes of nitrate indicated that fertilizer and manure used in crop production, principally corn, were the dominant sources of nitrate. The anomalously high nitrate levels in parts of the Midwest in 2013 coincide with reported higher-than-normal nitrate loads in the Mississippi River.

Illinois River Nitrate-Nitrogen Concentrations and Loads: Long-term Variation and Association with Watershed Nitrogen Inputs

The Illinois River is a major contributor of nitrate-N to the Mississippi River and the Gulf of Mexico, where nitrate is a leading cause of summertime benthic hypoxia. Corn-soybean production on tile-drained land is a leading source of nitrate-N in this river system, in addition to municipal wastewater discharge. We calculated annual nitrate-N loads in the Illinois River at Valley City from 1976 to 2014 by linear interpolation. Although there was not a significant trend in annual loads during the entire study period, there was a significant downward trend in flow-weighted nitrate-N concentration after 1990 despite high concentrations in 2013 after the 2012 drought. Multivariate regression analysis revealed a statistically significant association between annual flow-weighted nitrate-N concentration and cumulative residual agricultural N inputs to the watershed during a 6-yr window. This suggests that declines in flow-weighted nitrate-N concentration may reflect increasing N use efficiency in agriculture and a depletion of legacy N stored in the watershed. The watershed appears to have transitioned from a state of stationarity in nitrate concentration to nonstationarity. The average annual nitrate-N load at Valley City from 2010 to 2014 was 10% less than the 1980-1996 average load, indicating recent progress toward Illinois' nutrient loss reduction milestone of 15% reduction by 2025 and ultimate target of 45% reduction.

Tile Drainage Density Reduces Groundwater Travel Times and Compromises Riparian Buffer Effectiveness

Strategies to reduce nitrate-nitrogen (nitrate) pollution delivered to streams often seek to increase groundwater residence time to achieve measureable results, yet the effects of tile drainage on residence time have not been well documented. In this study, we used a geographic information system groundwater travel time model to quantify the effects of artificial subsurface drainage on groundwater travel times in the 7443-ha Bear Creek watershed in north-central Iowa. Our objectives were to evaluate how mean groundwater travel times changed with increasing drainage intensity and to assess how tile drainage density reduces groundwater contributions to riparian buffers. Results indicate that mean groundwater travel times are reduced with increasing degrees of tile drainage. Mean groundwater travel times decreased from 5.6 to 1.1 yr, with drainage densities ranging from 0.005 m (7.6 mi) to 0.04 m (62 mi), respectively. Model simulations indicate that mean travel times with tile drainage are more than 150 times faster than those that existed before settlement. With intensive drainage, less than 2% of the groundwater in the basin appears to flow through a perennial stream buffer, thereby reducing the effectiveness of this practice to reduce stream nitrate loads. Hence, strategies, such as reconnecting tile drainage to buffers, are promising because they increase groundwater residence times in tile-drained watersheds.

Comprehensive nitrogen budgets for controlled tile drainage fields in eastern ontario, Canada

Excessive N loading from subsurface tile drainage has been linked to water quality degradation. Controlled tile drainage (CTD) has the potential to reduce N losses via tile drainage and boost crop yields. While CTD can reduce N loss from tile drainage, it may increase losses through other pathways. A multiple-year field-scale accounting of major N inputs and outputs during the cropping season was conducted on freely drained and controlled tile drained agricultural fields under corn ( L.)-soybean [ (L.) Merr.] production systems in eastern Ontario, Canada. Greater predicted gaseous N emissions for corn and soybean and greater observed lateral seepage N losses were observed for corn and soybean fields under CTD relative to free-draining fields. However, observed N losses from tile were significantly lower for CTD fields, in relation to freely drained fields. Changes in residual soil N were essentially equivalent between drainage treatments, while mass balance residual terms were systematically negative (slightly more so for CTD). Increases in plant N uptake associated with CTD were observed, probably resulting in higher grain yields for corn and soybean. This study illustrates the benefits of CTD in decreasing subsurface tile drainage N losses and boosting crop yields, while demonstrating the potential for CTD to increase N losses via other pathways related to gaseous emissions and groundwater seepage.

The impact of nitrogen source and crop rotation on nitrogen mass balances in the Mississippi River Basin

Nitrogen (N) leaching to surface waters from grain farms in the Mississippi River Basin (MRB), USA, is the primary cause of hypoxia in the Gulf of Mexico. Regional-scale N mass balances indicate that a small, intensively cropped area of the upper MRB contributes disproportionately to nitrate loading. These aggregate balances miss small-scale variability, especially that caused by differences in farm management. We constructed N mass balances for a gradient of farm types, from corn-soybean monocultures to diversified grain farms that rely on biological N fixation (BNF) as a primary N source, to compare the relative efficiency of diverse farming systems in the MRB. Five-year N balances were calculated for a most and least productive field on each farm using data collected from interviews with 95 grain farmers in Iowa, Ohio, Minnesota, and Wisconsin; from legume biomass and corn grain samples collected from a subset of farms; and published values from the literature. Nitrogen balances ranged from high average annual surpluses (149 kg N x ha(-1) x yr(-1)) to large deficits (80 kg N x ha(-1) x yr(-1)), and differed based on N source and crop rotation. Fields with > 50% of total N additions from legume N sources and fields with complex crop rotations that included both annual and perennial species were approximately in balance (3.7 kg N x ha(-1) x yr(-1) and 5.7 kg N x ha(-1) x yr(-1), respectively) compared to fertilizer-based practices in corn-soybean rotations with average annual surpluses near 35 kg N x ha(-1) x yr(-1). Surplus N was also inversely related to the proportion of total N inputs from BNF for medium (80-160 kg N x ha(-1) x yr(-1)) to high (> 160 kg N x ha(-1) x yr(-1)) N rates. Diversified farmers were more likely to adjust their management practices in response to environmental variability compared to fertilizer-based farmers. Taken together, results from this study suggest that significantly reducing surplus N in agroecosystems will require reducing N inputs and increasing C availability to support the internal biological mechanisms for storing N in farm fields.

Estimating net anthropogenic nitrogen inputs to U.S. watersheds: comparison of methodologies

The net anthropogenic nitrogen input (NANI) approach is a simple quasi-mass-balance that estimates the human-induced nitrogen inputs to a watershed. Across a wide range of watersheds, NANI has been shown to be a good predictor of riverine nitrogen export. In this paper, we review various methodologies proposed for NANI estimation since its first introduction and evaluate alternative calculations suggested by previous literature. Our work is the first study in which a consistent NANI calculation method is applied across the U.S. watersheds and tested against available riverine N flux estimates. Among the tested methodologies, yield-based estimation of agricultural N fixation (instead of crop area-based) made the largest difference, especially in some Mississippi watersheds where the tile drainage was a significant factor reducing watershed N retention. Across the U.S. watersheds, NANI was particularly sensitive to farm N fertilizer application, cattle N consumption, N fixation by soybeans and alfalfa, and N yield by corn, soybeans, and pasture, although their relative importance varied among different regions.

Sources of nitrate yields in the Mississippi River Basin

Riverine nitrate N in the Mississippi River leads to hypoxia in the Gulf of Mexico. Several recent modeling studies estimated major N inputs and suggested source areas that could be targeted for conservation programs. We conducted a similar analysis with more recent and extensive data that demonstrates the importance of hydrology in controlling the percentage of net N inputs (NNI) exported by rivers. The average fraction of annual riverine nitrate N export/NNI ranged from 0.05 for the lower Mississippi subbasin to 0.3 for the upper Mississippi River basin and as high as 1.4 (4.2 in a wet year) for the Embarras River watershed, a mostly tile-drained basin. Intensive corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] watersheds on Mollisols had low NNI values and when combined with riverine N losses suggest a net depletion of soil organic N. We used county-level data to develop a nonlinear model ofN inputs and landscape factors that were related to winter-spring riverine nitrate yields for 153 watersheds within the basin. We found that river runoff times fertilizer N input was the major predictive term, explaining 76% of the variation in the model. Fertilizer inputs were highly correlated with fraction of land area in row crops. Tile drainage explained 17% of the spatial variation in winter-spring nitrate yield, whereas human consumption of N (i.e., sewage effluent) accounted for 7%. Net N inputs were not a good predictor of riverine nitrate N yields, nor were other N balances. We used this model to predict the expected nitrate N yield from each county in the Mississippi River basin; the greatest nitrate N yields corresponded to the highly productive, tile-drained cornbelt from southwest Minnesota across Iowa, Illinois, Indiana, and Ohio. This analysis can be used to guide decisions about where efforts to reduce nitrate N losses can be most effectively targeted to improve local water quality and reduce export to the Gulf of Mexico.

Miscanthus and switchgrass production in central Illinois: impacts on hydrology and inorganic nitrogen leaching

Biomass crops are being promoted as environmentally favorable alternatives to fossil fuels or ethanol production from maize (Zea mays L.), particularly across the Corn Belt of the United States. However, there are few if any empirical studies on inorganic N leaching losses from perennial grasses that are harvested on an annual basis, nor has there been empirical evaluation of the hydrologic consequences of perennial cropping systems. Here we report on the results of 4 yr of field measurements of soil moisture and inorganic N leaching from a conventional maize-soybean [Glycine max (L.) Merr.] system and two unfertilized perennial grasses harvested in winter for biomass: Miscanthus x giganteus and switchgrass (Panicum virgatum cv. Cave-in-Rock). All crops were grown on fertile Mollisols in east-central Illinois. Inorganic N leaching was measured with ion exchange resin lysimeters placed 50 cm below the soil surface. Maize--soybean nitrate leaching averaged 40.4 kg N ha(-1) yr(-1), whereas switchgrass and Miscanthus had values of 1.4 and 3.0 kg N ha(-1) yr(-1), respectively. Soil moisture monitoring (to a depth of 90 cm) indicated that both perennial grasses dried the soil out earlier in the growing season compared with maize-soybean. Later in the growing season, soil moisture under switchgrass tended to be greater than maize-soybean or Miscanthus, whereas the soil under Miscanthus was consistently drier than under maize--soybean. Water budget calculations indicated that evapotranspiration from Miscanthus was about 104 mm yr(-1) greater than under maize-soybean, which could reduce annual drainage water flows by 32% in central Illinois. Drainage water is a primary source of surface water flows in the region, and the impact ofextensive Miscanthus production on surface water supplies and aquatic ecosystems deserves further investigation.

A high-resolution assessment on global nitrogen flows in cropland

Crop production is the single largest cause of human alteration of the global nitrogen cycle. We present a comprehensive assessment of global nitrogen flows in cropland for the year 2000 with a spatial resolution of 5 arc-minutes. We calculated a total nitrogen input (IN) of 136.60 trillion grams (Tg) of N per year, of which almost half is contributed by mineral nitrogen fertilizers, and a total nitrogen output (OUT) of 148.14 Tg of N per year, of which 55% is uptake by harvested crops and crop residues. We present high-resolution maps quantifying the spatial distribution of nitrogen IN and OUT flows, soil nitrogen balance, and surface nitrogen balance. The high-resolution data are aggregated at the national level on a per capita basis to assess nitrogen stress levels. The results show that almost 80% of African countries are confronted with nitrogen scarcity or nitrogen stress problems, which, along with poverty, cause food insecurity and malnutrition. The assessment also shows a global average nitrogen recovery rate of 59%, indicating that nearly two-fifths of nitrogen inputs are lost in ecosystems. More effective management of nitrogen is essential to reduce the deleterious environmental consequences.