New phosphorus losses via tile drainage depend on fertilizer form, placement, and timing.

Agricultural phosphorus (P) losses are harmful to water quality, but knowledge gaps about the importance of fertilizer management practices on new (recently applied) sources of P may limit P loss mitigation efforts. Weighted regression models applied to subsurface tile drainage water quality data enabled estimating the new P losses associated with 155 P applications in Ohio and Indiana, USA. Daily discharge and dissolved reactive P (DRP) and total P (TP) loads were used to detect increases in P loss following each application which was considered new P. The magnitude of new P losses was small relative to fertilizer application rates, averaging 79.3 g DRP ha-1 and 96.1 g TP ha-1 , or <3% of P applied. The eight largest new P losses surpassed 330 g DRP ha-1 or 575 g TP ha-1 . New P loss mitigation strategies should focus on broadcast liquid manure applications; on average, manure applications caused greater new P losses than inorganic fertilizers, and surface broadcast applications were associated with greater new P losses than injected or incorporated applications. Late fall applications risked having large new P losses applications. On an annual basis, new P contributed an average of 14% of DRP and 5% of TP losses from tile drains, which is much less than previous studies that included surface runoff, suggesting that tile drainage is relatively buffered with regard to new P losses. Therefore old (preexisting soil P) P sources dominated tile drain P losses, and P loss reduction efforts will need to address this source.

Connecting soil characteristics to edge-of-field water quality in Ohio.

Soil health and water quality improvement are major goals of sustainable agricultural management systems, yet the connections between soil health and water quality impacts remain unclear. In this study we conducted an initial exploratory assessment of the relationships between soil chemical, physical, and biological properties and edge-of-field water quality across a network of 40 fields in Ohio, USA. Discharge, dissolved reactive P (DRP), total P (TP), and nitrate (NO3 ) losses associated with precipitation events via surface runoff and tile drainage were monitored. Agronomic soil tests and a suite of soil health indicators were measured, then predictive relationships between the field average soil properties and tile drainage and surface runoff discharge and DRP, TP, and nitrate loads were explored with random forest and multiple linear regression approaches. Among the soil health indicators, water extractable C and N were consistently found to be positively related to tile nitrate loads, but other soil health indicators had little or inconsistent importance for water quality impacts. Several other soil properties were important predictors, particularly soil P pools for surface and tile DRP and TP losses as well as Mehlich-3 (M3) extractable Fe and Al for surface and tile discharge. Thus, we did not observe strong evidence that soil health was associated with improved edge-of-field water quality across the edge-of-field monitoring network. However, additional studies are needed to definitively test the relationships between a broader array of soil health metrics and water quality outcomes.

Representing soil health practice effects on soil properties and nutrient loss in a watershed-scale hydrologic model.

Watershed-scale hydrologic models are commonly used to assess the water quality effects of agricultural conservation practices that improve soil health (e.g., cover crops and no-till). However, models rarely account for how these practices (i.e., soil health practices) affect soil physical and functional properties such as water holding capacity and soil aggregate stability, which may, in turn, affect water quality. We introduce a method to represent changes in soil physical and functional properties caused by soil health practices in the Soil and Water Assessment Tool (SWAT) model. We used the SWAT model's default representation of winter cover crops and no-till and modified soil descriptive parameters to depict soil health practice effects on soil properties. We assumed that the soil health practices would increase soil organic carbon (SOC), a principal indicator of soil health, by 0.01 g C g-1 of soil and then estimated changes in other soil properties (e.g., water holding capacity) using SOC-based predictive equations and preceding literature. Results indicated that our soil property modifications had statistically significant effects on simulated hydrology and nutrient loss, though outputs were more substantially affected by the model's default representation of cover crops and no-till. Results also indicated that soil health practices can reduce nitrogen and total phosphorus loss but may increase dissolved reactive phosphorus loss. Our representation of soil health practices provides a more complete estimate of practice efficacy but underscores a need for additional observational data to verify results and guide further model improvements.

Resolving new and old phosphorus source contributions to subsurface tile drainage with weighted regressions on discharge and season.

Agricultural losses of dissolved reactive phosphorus (DRP) emanate from both historic P applications (i.e., "old P") and recently applied fertilizer (i.e., "new P"). Understanding the relative contributions of these sources is important for mitigating DRP losses from agriculture. This study provides a proof-of-concept for resolving new P vs. old P source contributions to DRP losses in subsurface tile drainage using edge-of-field water quality data and management records from eight fields in Ohio. Weighted regressions on discharge and season (WRDS) were fitted using data from periods without P fertilizer applications and then used to predict DRP losses in tile drainage during new P loss risk periods (default length, 90 d) after fertilizer applications. Differences between observed and predicted DRP concentrations during the new P loss risk period were attributed to the new P source. Remaining losses were attributed to the old soil P source. The WRDS model performance was modest (modified Kling-Gupta efficiency ranged from -0.074 to 0.484). New P sources contributed between 0 and 17% of overall DRP losses (average, 7%), with old soil P contributing 83-100%. Individual P fertilizer applications were associated with new DRP losses up to 192 g P ha-1 . Increasing the length of the risk period for new P losses up to 180 d after fertilizer application marginally increased the estimated contribution of the new P source. The WRDS-based analysis provides a novel approach for resolving the contributions of new and old sources to edge-of-field DRP losses.

Enhancing the Soil Health-Watershed Health Nexus: Introduction.

Scientific concepts and measurements that relate soil and water resources are lacking in several areas, limiting our development of a framework or nexus to assess soil-watershed health. Current research designs rely on land management practices as a proxy for soil condition. Yet, conservation practices are often studied in isolation of each other, and adoption may be driven by state and federal farm programs that can incentivize a given management practice without accounting for current, novel farmer-driven adoption of conservation systems. Despite the value of conservation management, its ability to predict soil health is often limited if based solely on land management because chemical, physical, and biological processes vary across time, discipline, and terrain. Similarly, connections between soil health and water quality are constrained due to several "grand challenges" that include dissimilar scales and the number of metrics required to correlate soil and water systems. Equally important is soil sampling within the critical flow path(s) that determines sediment/contaminant loading. In some instances, most of the sediment/contaminant loading during a portion or entire year results from channel and bank erosion and not overland flow that may not be within conservation management hectares. Additional challenges include legacy effects of prior land management, climate variability, and varying turnover rates of soil and water systems. This special section aims to frame research issues that inspire new approaches and collaborations for tackling the challenge of leveraging soil health to strengthen water management across plot, field, and watershed scales, using models, statistics, and other novel methodologies.

Legacy phosphorus concentration-discharge relationships in surface runoff and tile drainage from Ohio crop fields.

Legacy phosphorus (P) in agricultural soils can be transported to surface waters via runoff and tile drainage, where it contributes to the development of harmful and nuisance algal blooms and hypoxia. However, a limited understanding of legacy P loss dynamics impedes the identification of mitigation strategies. Edge-of-field data from 41 agricultural fields in northwestern Ohio, USA, were used to develop regressions between legacy P concentrations (C) and discharge (Q) for two P fractions: total P (TP) and dissolved reactive P (DRP). Tile drainage TP concentration (CTP ) and DRP concentration (CDRP ) both increased as Q increased, and CTP tended to increase at a greater rate than CDRP . Surface runoff showed greater variation in C-Q regressions, indicating that the response of TP and DRP to elevated Q was field specific. The relative variability of C and Q was explored using a ratio of CVs (CVC /CVQ ), which indicated that tile drainage TP and DRP losses were chemodynamic, whereas losses via surface runoff demonstrated both chemodynamic and chemostatic behavior. The chemodynamic behavior indicated that legacy P losses were strongly influenced by variation in P source availability and transport pathways. In addition, legacy P source size influenced C, as demonstrated by a positive relationship between soil-test P and the CTP and CDRP in both tile drainage and surface runoff. Progress towards legacy P mitigation will require further characterization of the drivers of variability in CTP and CDRP , including weather-, soil-, and management-related factors.

Underestimation of N2 O emissions in a comparison of the DayCent, DNDC, and EPIC models.

Process-based models are increasingly used to study agroecosystem interactions and N2 O emissions from agricultural fields. The widespread use of these models to conduct research and inform policy benefits from periodic model comparisons that assess the state of agroecosystem modeling and indicate areas for model improvement. This work provides an evaluation of simulated N2 O flux from three process-based models: DayCent, DNDC, and EPIC. The models were calibrated and validated using data collected from two research sites over five years that represent cropping systems and nitrogen fertilizer management strategies common to dairy cropping systems. We also evaluated the use of a multi-model ensemble strategy, which inconsistently outperformed individual model estimations. Regression analysis indicated a cross-model bias to underestimate high magnitude daily and cumulative N2 O flux. Model estimations of observed soil temperature and water content did not sufficiently explain model underestimations, and we found significant variation in model estimates of heterotrophic respiration, denitrification, soil NH4+ , and soil NO3- , which may indicate that additional types of observed data are required to evaluate model performance and possible biases. Our results suggest a bias in the model estimation of N2 O flux from agroecosystems that limits the extension of models beyond calibration and as instruments of policy development. This highlights a growing need for the modeling and measurement communities to collaborate in the collection and analysis of the data necessary to improve models and coordinate future development.

Simulated Effects of Soil Texture on Nitrous Oxide Emission Factors from Corn and Soybean Agroecosystems in Wisconsin.

Soil texture is known to have an influence on the physical and biological processes that produce NO emissions in agricultural fields, yet comparisons across soil textural types are limited by considerations of time and practicality. We used the DayCent biogeochemical model to assess the effects of soil texture on NO emissions from agriculturally productive soils from four counties in Wisconsin. We validated the DayCent model using field data from 2 yr of a long-term (approximately 20-yr) cropping systems trial and then simulated yield and NO emissions from continuous corn ( L.) and corn-soybean ( L.) cropping systems across 35 Wisconsin soil series classified as either silt loam, sandy loam, or loamy sand. Silt loam soils had the highest NO emissions of all soil types, exhibiting 80 to 158% greater mean emissions and 100 to 282% greater emission factors compared with loamy sand and sandy loam soils, respectively. The model predicts that for these soils under these cropping systems, denitrification constituted the majority of the NO flux only in the silt loam soils. However, across all soil textures, locations, and years, denitrification explained the most variation (74-98%) in total NO emissions. Our results suggest that soil texture is an important factor in determining a range of NO emission characteristics and is critical for estimating future NO emissions from agricultural fields.

Seasonal nitrous oxide and methane fluxes from grain- and forage-based production systems in wisconsin, USA.

Agriculture in the midwestern United States is a major anthropogenic source of nitrous oxide (NO) and is both a source and sink for methane (CH), but the degree to which cropping systems differ in emissions of these gases is not well understood. Our objectives were to determine if fluxes of NO and CH varied among cropping systems and among crop phases within a cropping system. We compare NO and CH fluxes over the 2010 and 2011 growing seasons from the six cropping systems at the Wisconsin Integrated Cropping Systems Trial (WICST), a 20-yr-old cropping systems experiment. The study is composed of three grain and three forage cropping systems spanning a spectrum of crop diversity and perenniality that model a wide range of realistic cropping systems that differ in management, crop rotation, and fertilizer regimes. Among the grain systems, cumulative growing season NO emissions were greater for continuous corn ( L.) (3.7 kg NO-N ha) than corn-soybean [ (L.) Merr.] (2.0 kg NO-N ha) or organic corn-soybean-wheat ( L.) (1.7 kg NO-N ha). Among the forage systems, cumulative growing-season NO emissions were greater for organic corn-alfalfa ( L.)-alfalfa (2.9 kg NO-N ha) and conventional corn-alfalfa-alfalfa-alfalfa (2.5 kg NO-N ha), and lower for rotational pasture (1.9 kg NO-N ha). Application of mineral or organic N fertilizer was associated with elevated NO emissions. Yield-scaled emissions (kg NO-N Mg) did not differ by cropping system. Methane fluxes were highly variable and no effect of cropping system was observed. These results suggest that extended and diversified cropping systems could reduce area-scaled NO emissions from agriculture, but none of the systems studied significantly reduced yield-scaled NO emissions.