Impact of nitrogen fertilizer timing on nitrate loss and crop production in northwest Iowa.

In the U.S. Midwest, nitrate in subsurface tile drainage from corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] systems is detrimental to water quality at local and national scales. The objective of this replicated plot study in northwest Iowa, performed in 2015-2020, was to investigate the influence of nitrogen (N) fertilizer timing on crop production and NO3 load in subsurface (tile) drainage discharge. Four treatments applied to corn included fall anhydrous ammonia with a nitrification inhibitor (F), spring anhydrous ammonia (S), split-banded urea at planting and mid-vegetative growth (SS), and no N fertilizer (0N). Across crops and years, NO3 -N concentration in subsurface drainage discharge was the same at 11.7 mg L-1 for F and S applied anhydrous ammonia (AA). The NO3 -N concentration was statistically lower with SS urea (10 mg L-1 ) than F and S, and 0N was lower than SS at 8.3 mg L-1 . Average annual NO3 -N loads were not different between any treatments due to plot variability in drainage discharge. Corn responded to N application, with overall mean yield the same for F, S, and SS. There were no agronomic or water quality benefits for applying AA in spring compared with fall, where the F included a nitrification inhibitor and was applied to cold soils. Split-applied urea had a small positive water quality impact but no crop yield enhancement. This study shows that there were improvements to NO3 -N concentration in subsurface drainage discharge, but more nutrient reduction practices are needed than fertilizer N management alone to reduce nitrate load to surface water systems.

Multisite Evaluation of APEX for Water Quality: I. Best Professional Judgment Parameterization.

The Agricultural Policy Environmental eXtender (APEX) model is capable of estimating edge-of-field water, nutrient, and sediment transport and is used to assess the environmental impacts of management practices. The current practice is to fully calibrate the model for each site simulation, a task that requires resources and data not always available. The objective of this study was to compare model performance for flow, sediment, and phosphorus transport under two parameterization schemes: a best professional judgment (BPJ) parameterization based on readily available data and a fully calibrated parameterization based on site-specific soil, weather, event flow, and water quality data. The analysis was conducted using 12 datasets at four locations representing poorly drained soils and row-crop production under different tillage systems. Model performance was based on the Nash-Sutcliffe efficiency (NSE), the coefficient of determination () and the regression slope between simulated and measured annualized loads across all site years. Although the BPJ model performance for flow was acceptable (NSE = 0.7) at the annual time step, calibration improved it (NSE = 0.9). Acceptable simulation of sediment and total phosphorus transport (NSE = 0.5 and 0.9, respectively) was obtained only after full calibration at each site. Given the unacceptable performance of the BPJ approach, uncalibrated use of APEX for planning or management purposes may be misleading. Model calibration with water quality data prior to using APEX for simulating sediment and total phosphorus loss is essential.

Multisite Evaluation of APEX for Water Quality: II. Regional Parameterization.

Phosphorus (P) Index assessment requires independent estimates of long-term average annual P loss from fields, representing multiple climatic scenarios, management practices, and landscape positions. Because currently available measured data are insufficient to evaluate P Index performance, calibrated and validated process-based models have been proposed as tools to generate the required data. The objectives of this research were to develop a regional parameterization for the Agricultural Policy Environmental eXtender (APEX) model to estimate edge-of-field runoff, sediment, and P losses in restricted-layer soils of Missouri and Kansas and to assess the performance of this parameterization using monitoring data from multiple sites in this region. Five site-specific calibrated models (SSCM) from within the region were used to develop a regionally calibrated model (RCM), which was further calibrated and validated with measured data. Performance of the RCM was similar to that of the SSCMs for runoff simulation and had Nash-Sutcliffe efficiency (NSE) > 0.72 and absolute percent bias (|PBIAS|) < 18% for both calibration and validation. The RCM could not simulate sediment loss (NSE < 0, |PBIAS| > 90%) and was particularly ineffective at simulating sediment loss from locations with small sediment loads. The RCM had acceptable performance for simulation of total P loss (NSE > 0.74, |PBIAS| < 30%) but underperformed the SSCMs. Total P-loss estimates should be used with caution due to poor simulation of sediment loss. Although we did not attain our goal of a robust regional parameterization of APEX for estimating sediment and total P losses, runoff estimates with the RCM were acceptable for P Index evaluation.

How efficiently do corn- and soybean-based cropping systems use water? A systems modeling analysis.

Agricultural systems are being challenged to decrease water use and increase production while climate becomes more variable and the world's population grows. Low water use efficiency is traditionally characterized by high water use relative to low grain production and usually occurs under dry conditions. However, when a cropping system fails to take advantage of available water during wet conditions, this is also an inefficiency and is often detrimental to the environment. Here, we provide a systems-level definition of water use efficiency (sWUE) that addresses both production and environmental quality goals through incorporating all major system water losses (evapotranspiration, drainage, and runoff). We extensively calibrated and tested the Agricultural Production Systems sIMulator (APSIM) using 6 years of continuous crop and soil measurements in corn- and soybean-based cropping systems in central Iowa, USA. We then used the model to determine water use, loss, and grain production in each system and calculated sWUE in years that experienced drought, flood, or historically average precipitation. Systems water use efficiency was found to be greatest during years with average precipitation. Simulation analysis using 28 years of historical precipitation data, plus the same dataset with ± 15% variation in daily precipitation, showed that in this region, 430 mm of seasonal (planting to harvesting) rainfall resulted in the optimum sWUE for corn, and 317 mm for soybean. Above these precipitation levels, the corn and soybean yields did not increase further, but the water loss from the system via runoff and drainage increased substantially, leading to a high likelihood of soil, nutrient, and pesticide movement from the field to waterways. As the Midwestern United States is predicted to experience more frequent drought and flood, inefficiency of cropping systems water use will also increase. This work provides a framework to concurrently evaluate production and environmental performance of cropping systems.