Nutrient management, as described in NRCS Code 590, has been intensively investigated, with research largely focused on crop yields and water quality. Yet, due to complex processes and mechanisms in nutrient cycling (especially the nitrogen (N) cycle), there are many challenges in evaluating the effectiveness of nutrient management practices across site conditions. We therefore synthesized data from peer-reviewed publications on subsurface-drained agricultural fields in the Midwest U.S. with corn yield and drainage nitrate-N (NO3-N) export data published from 1980 to 2019. Through literature screening and data extraction from 43 publications, we obtained 577 site-years of data with detailed information on fertilization, corn yields, precipitation, drainage volume, and drainage NO3-N load/concentration or both. In addition, we estimated flow-weighted NO3-N concentrations ([NO3-N]) in drainage for those site-years where only load and volume were reported. Furthermore, we conducted a cost analysis using synthesized and surveyed corn yield data to evaluate the cost-effectiveness of different nutrient management plans. Results from the synthesis showed that N fertilizer rate was strongly positively correlated with corn yields, NO3-N loads, and flow-weighted [NO3-N]. Reducing N fertilizer rates can effectively mitigate NO3-N losses from agricultural fields; however, our cost analysis showed negative economic returns for continuous corn production at lower N rates. In addition, organic fertilizers significantly boosted corn yields and NO3-N losses compared to inorganic fertilizers at comparable rates; however, accurate quantification of plant-available N in organic fertilizers is necessary to guide appropriate nutrient management plans because the nutrient content may be highly variable. In terms of fertilizer application methods, we did not find significant differences in NO3-N export in drainage discharge. Lastly, impact of fertilization timing on NO3-N export varied depending on other factors such as fertilizer rate, source, and weather. According to these results, we suggest that further efforts are still required to produce effective local nutrient management plans. Furthermore, government agencies such as USDA-NRCS need to work with other agencies such as USEPA to address the potential economic losses due to implementation of lower fertilizer rates for water quality improvement.

Anticipated future hydroclimatic changes are expected to alter the transport and survival of fecally-sourced waterborne pathogens, presenting an increased risk of recreational water quality impairments. Managing future risk requires an understanding of interactions between fecal sources, hydroclimatic conditions and best management practices (BMPs) at spatial scales relevant to decision makers. In this study we used the Hydrologic Simulation Program FORTRAN to quantify potential fecal coliform (FC - an indicator of the potential presence of pathogens) responses to a range of mid-century climate scenarios and assess different BMP scenarios (based on reduction factors) for reducing the risk of water quality impairment in two, small agricultural watersheds - the Chippewa watershed in Minnesota, and the Tye watershed in Virginia. In each watershed, simulations show a wide range of FC responses, driven largely by variability in projected future precipitation. Wetter future conditions, which drive more transport from non-point sources (e.g. manure application, livestock grazing), show increases in FC loads. Loads typically decrease under drier futures; however, higher mean FC concentrations and more recreational water quality criteria exceedances occur, likely caused by reduced flow during low-flow periods. Median changes across the ensemble generally show increases in FC load. BMPs that focus on key fecal sources (e.g., runoff from pasture, livestock defecation in streams) within a watershed can mitigate the effects of hydroclimatic change on FC loads. However, more extensive BMP implementation or improved BMP efficiency (i.e., higher FC reductions) may be needed to fully offset increases in FC load and meet water quality goals, such as total maximum daily loads and recreational water quality standards. Strategies for managing climate risk should be flexible and to the extent possible include resilient BMPs that function as designed under a range of future conditions.

Agricultural best management practices (BMPs) reduce non-point source pollution from cropland. Goals for BMP adoption and expected pollutant load reductions are often specified in water quality management plans to protect and restore waterbodies; however, estimates of needed load reductions and pollutant removal performance of BMPs are generally based on historic climate. Increasing air temperatures and changes in precipitation patterns and intensity are anticipated throughout the U.S. over the 21st century. The effects of such changes on agricultural pollutant loads have been addressed by several authors, but how these changes will affect the performance of widely promoted BMPs has received limited attention. We use the Soil and Water Assessment Tool (SWAT) to investigate potential changes in the effectiveness of conservation tillage, no-till, vegetated filter strips, grassed waterways, nutrient management, winter cover crops, and drainage water management practices under potential future temperature and precipitation patterns. We simulate two agricultural watersheds in the Minnesota Corn Belt and the Georgia Coastal Plain with different hydro-climatic settings, under recent conditions (1950-2005) and multiple potential future mid-century (2030-2059) and late-century (2070-2099) climate scenarios. Results suggest future increases in agricultural source loads of sediment, nitrogen and phosphorous. Most BMPs continue to reduce loads, but removal efficiencies generally decline due to more intense runoff events, biological responses to changes in soil moisture and temperature, and exacerbated upland loading. The coupled effects of higher upland loading and reduced BMP efficiencies suggest that wider adoption, resizing, and/or combining practices may be needed in the future to meet water quality goals for agricultural lands.

Characterization of the uncertainty and sensitivity of model parameters is an essential facet of hydrologic modeling. This article introduces the multi-objective evolutionary sensitivity handling algorithm (MOESHA) that combines input parameter uncertainty and sensitivity analyses with a genetic algorithm calibration routine to dynamically sample the parameter space. This novel algorithm serves as an alternative to traditional static space-sampling methods, such as stratified sampling or Latin hypercube sampling. In addition to calibrating model parameters to a hydrologic model, MOESHA determines the optimal distribution of model parameters that maximizes model robustness and minimizes error, and the results provide an estimate for model uncertainty due to the uncertainty in model parameters. Subsequently, we compare the model parameter distributions to the distribution of a dummy variable (i.e., a variable that does not affect model output) to differentiate between impactful (i.e., sensitive) and non-impactful parameters. In this way, an optimally calibrated model is produced, and estimations of model uncertainty as well as the relative impact of model parameters on model output (i.e., sensitivity) are determined. A case study using a single-cell hydrologic model (EXP-HYDRO) is used to test the method using river discharge data from the Dee River catchment in Wales. We compare the results of MOESHA with Sobol's global sensitivity analysis method and demonstrate that the algorithm is able to pinpoint non-impactful parameters, demonstrate the uncertainty of model results with respect to uncertainties in model parameters, and achieve excellent calibration results. A major drawback of the algorithm is that it is computationally expensive; therefore, parallelized methods should be used to reduce the computational burden.

We have developed a time-dependent simulation model to estimate in-room concentrations of multiple contaminants [ammonia (NH), carbon dioxide (CO), carbon monoxide (CO) and dust] as a function of increased ventilation with filtered recirculation for swine farrowing facilities. Energy and mass balance equations were used to simulate the indoor air quality (IAQ) and operational cost for a variety of ventilation conditions over a 3-month winter period for a facility located in the Midwest U.S., using simplified and real-time production parameters, comparing results to field data. A revised model was improved by minimizing the sum of squared errors (SSE) between modeled and measured NH and CO. After optimizing NH and CO, other IAQ results from the simulation were compared to field measurements using linear regression. For NH, the coefficient of determination (R) for simulation results and field measurements improved from 0.02 with the original model to 0.37 with the new model. For CO, the R for simulation results and field measurements was 0.49 with the new model. When the makeup air was matched to hallway air CO concentrations (1,500 ppm), simulation results showed the smallest SSE. With the new model, the R for other contaminants were 0.34 for inhalable dust, 0.36 for respirable dust, and 0.26 for CO. Operation of the air cleaner decreased inhalable dust by 35% and respirable dust concentrations by 33%, while having no effect on NH, CO, in agreement with field data, and increasing operational cost by $860 (58%) for the three-month period.

Legumes included in corn-based crop rotation systems provide a variety of benefits to the subsequent crops and potentially to the environment. This review aims to synthesize available data from the literature on legume N credits and the effects of crop rotations on water quality, as well as to analyze the cost benefits associated with different legume-corn rotation systems. We found that there was much variation in reported values for legume N credits to subsequent corn crops, from both empirical results and recommendations made by U.S. land grant universities. But despite inherent complexity, accounting for this contribution is critical when estimating optimal N fertilizer application rates as part of nutrient management. Results from research on the influence of crop rotations on water quality show that including legumes in corn-based rotation systems generally decreases nitrate-N concentrations in subsurface drainage discharge. Our cost analysis showed that incorporating legumes in cropping systems reduced N fertilizer and pesticide costs compared to conventional cropping systems, i.e., continuous corn and corn-soybean rotations, but extended rotations, such as corn-soybean-alfalfa-alfalfa-alfalfa, are not as profitable as conventional systems in the U.S. Midwest. In comparing continuous corn and corn-soybean rotations, although their impacts on water quality are not significantly different when using overall means from the literature data, corn-soybean rotations are more profitable than continuous corn. When using data from papers that directly compared the two, we found that switching from continuous corn to corn-soybean can provide a benefit of $5 per kg N loss reduction. The cost analysis methods used could be tailored to any location or management scenario with appropriate inputs and serve as a useful tool for assessing cost benefits for other agricultural conservation practices. Legume-corn crop rotations have the potential to be an effective conservation practice with the ultimate goal of improving water quality, and, with further research, these rotations could be made even more effective by integrating them into a multi-practice system.

Worldwide, the use of uncrewed aerial vehicles (UAVs) for pesticide application has grown tremendously in the past decade. Their adoption has been slower for Midwestern row crops. This study compared droplet size, coverage, and drift potential of sprays from UAV application methods to those from ground (implement) sprayer methods on corn in the Midwest. Droplet sizes measured during UAV spray trials [geometric mean diameters of 179 and 112 μm for UAV (boom) and UAV (no boom), respectively] were substantially smaller than those deposited during implement spray trials [mean diameters of 303 and 423 μm for implement (regular) and implement (pulse)]. Droplet coverage was high and localized in the middle swath of the field for the UAV with boom (10 to 30 droplets cm) and with no boom (60 droplets cm). Droplet coverage was broader, covering the entire field width for the implement methods (10 to 40 droplets cm). Vertical coverage of droplets was more uniform for UAV methods than implement methods. Although the UAVs produced smaller droplets than the implement methods, we still observed greater potential for downwind pesticide drift during the implement spray trials. Because localized application may be beneficial for pest control and drift reduction, the findings indicate a strong potential for "spot" or "band" spray coverage using UAV methods. This is likely due to the smaller size, reduced spray volumes, and increased agility of UAVs as compared to more conventional methods.

Dissolved reactive phosphorus (DRP) export from agricultural areas is a leading cause of nutrient pollution in freshwater systems (e.g., the North American Great Lakes). A potential solution to mitigate the excessive release of DRP is the use of nutrient management. To evaluate the effectiveness of nutrient management for phosphorus (P) in the United States, we conducted a review to synthesize P management and DRP export data from peer-reviewed articles published between 2000 to 2022. We identified 15 publications and extracted 113 and 90 observations from plot- and field-scale studies, respectively. At the plot scale, mean DRP concentrations were approximately 60% lower when P application rates were below the maximum recommended rate. In addition to the lower mean value, more extreme DRP export events occurred when the P fertilization rate was greater than the maximum recommended rate. In terms of application method, subsurface placement reduced mean DRP concentrations during rainfall simulations by 88% relative to surface placement (i.e., broadcasting). For fertilizer sources, mean DRP concentrations were similar between inorganic and organic fertilizers. However, at high application rates, organic fertilizers had a greater potential to produce extreme DRP export events. At the field-scale, organic fertilizers applied at high rates had the potential to produce extreme DRP export events. However, field-scale results for the other nutrient management techniques were generally inconclusive due to a limited number of studies and confounding factors. Overall, these results displayed the potential adverse impacts of overfertilization and the surface application of P fertilizers and highlighted the need for further research into the influence of nutrient management on P losses.