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HighlightsFilter strip processes for water pollutant reductions were quantified from 74 studies with almost 300 data points.Regression was significant versus width (sediment, N, P), area ratio (sediment, atrazine), and Ks (N, P, atrazine, alachlor).This review discusses ten functional factors affecting FS efficiency as well as FS monitoring recommendations.Cost-effectiveness was assessed and varies considerably by influent load and treatment effectiveness.Abstract. Filter strips (FSs) are edge-of-field conservation practices commonly implemented to reduce flux of sediment, nutrients, and other constituents from agricultural fields. While various aspects of FS effectiveness have been reviewed, this study provides a comprehensive summary of FS efficiency data for sediment, nutrients, pesticides, and pathogens as part of a special collection focused on agricultural conservation practices. This analysis also fills an important gap by assessing performance-based FS costs and cost-effectiveness. Data from 74 U.S. and international studies with 294 different treatments and 3,050 replications were compiled and analyzed. Results showed that runoff reduction tended to increase with increasing FS width up to about 15 m and that sediment reduction was significantly related to the ratio of FS area to drainage area and to FS width, with reduction tending to increase with increasing width up to about 20 m. Total P reduction was significantly related to FS soil saturated hydraulic conductivity, and total N reduction was significantly related to both saturated hydraulic conductivity and width. Total P and total N reductions both tended to increase with increasing FS width up to about 20 m and with increasing FS slope up to about 10%. Annualized FS costs were estimated to range from $314 to $865 ha-1 year-1 for different FS implementations. A major component of the cost is the opportunity cost of taking land out of production. Costs per unit of sediment retained by FS systems ranged from $10.3 to $18.6 Mg-1. A comprehensive assessment of FS cost-effectiveness (cost:benefit) is needed. Monitoring equipment, approaches, and recommendations are discussed, acknowledging the challenges of implementing field-scale FS studies. This information is critical to guide on-farm and programmatic FS decisions and to increase the scientific understanding of this commonly used agricultural conservation practice. Keywords: Best management practice, Buffer strip, Nonpoint-source pollution, Riparian buffer, Vegetated filter strip.

Manureshed management-the strategic use of manure nutrients that prioritizes recycling between livestock systems and cropping systems-provides a comprehensive framework for sustainable nutrient management that necessitates the collaboration of many actors. Understanding the social dimensions of collaboration is critical to implement the strategic and technological requirements of functional manuresheds. To improve this understanding, we identified aspirational networks of actors involved in manureshed management across local, regional, and national scales, principally in the United States, elucidating key relationships and highlighting the breadth of interactions essential to successful manureshed management. We concluded that, although the social networks vary with scale, the involvement of a common core set of actors and relationships appears to be universal to the successful integration of modern livestock and crop production systems necessary for functional manuresheds. Our analysis also reveals that, in addition to agricultural producers, local actors in extension and advisory services and private and public sectors ensure optimal outcomes at all scales. For manureshed management to successfully integrate crop and livestock production and sustainably manage manure nutrient resources at each scale, the full complement of actors identified in these social networks is critical to generate innovation and ensure collaboration continuity.

HighlightsASABE and ISAE convened the Global Water Security Conference for Agriculture and Natural Resources in Hyderabad, India, in 2018.Recommendations represent collective contribution of attendees and presenters in seven key priorities.Continuation of a narrow focus on technical aspects will likely prevent the success of technical solutions.Scientists and engineers should work together across all disciplines and boundaries to ensure global water security. Keywords: Climate change, Crop water productivity, Food security, Irrigation efficiency, Natural resource policy, Wastewater reuse, Water resource infrastructure, Water scarcity.

HighlightsWe provide context and perspectives on 13 articles in the Global Water Security collection.Limited irrigation, precision irrigation, and sustainable water resources management were critical themes.The collection emphasizes the need for adopting location-specific technologies to achieve global water security.Advances in data acquisition, data analysis, and modeling should be utilized to aid managing water resources. Abstract. This article introduces the Global Water Security collection in this issue of Transactions of the ASABE and issue 36(1) of Applied Engineering in Agriculture. Researchers, educators, industry partners, agricultural producers, and policymakers from 19 countries met at Hyderabad, India, to discuss critical issues and advancements at the Global Water Security Conference for Agriculture and Natural Resources. The conference was organized jointly by ASABE and the Indian Society of Agricultural Engineers (ISAE). This special collection consists of 13 articles selected from the 245 meeting presentations as well as invited articles. A perspectives article in this collection summarizes seven key priorities identified for action at the conference: reduce food waste, increase wastewater reuse, increase agricultural resiliency and efficiency, optimize irrigation efficiency and increase crop water productivity, improve water supply management, improve water resource infrastructure, and enhance water resource decision-making and policy formulation. The remaining 12 articles address a wide range of water security topics grouped by four themes: sustainable management of water resources (3 articles), limited irrigation for water conservation (5 articles), precision irrigation management (2 articles), and water management in hilly regions (2 articles). While these articles are not inclusive of all water security challenges in the agriculture and natural resources sectors, they highlight selected important challenges and potential solutions. The research presented in this special collection emphasizes the importance of developing and using appropriate location-specific technologies that increase water application efficiency and water use efficiency while maintaining adequate water supplies for natural resource functions and ecosystem services to ensure global water security. Keywords: Climate change, Crop water productivity, Food security, Irrigation efficiency, Natural resource policy, Wastewater reuse, Water resource infrastructure, Water scarcity.

Agricultural runoff is an important contributor to water quality impairment. This study was conducted to evaluate the potential role of field-scale management on carbon (C), nitrogen (N), and phosphorus (P) stoichiometry in soils and runoff from agricultural fields. Cultivated and pasture fields at the Riesel watersheds in central Texas were used for this analysis, and nutrients were transformed to evaluate relative to the Redfield ratio (106 C/16 N/1 P). Using the Redfield ratio, all soil samples were P depleted relative to C and N. The majority of stormflow and baseflow runoff samples contained 9 to 19% Redfield N relative to C and P. Shifting from inorganic fertilizer application to poultry litter as a fertilizer source resulted in increased absolute C, N, and P concentrations in stormflow and baseflow runoff. Increasing rates of poultry litter application increased the Redfield P relative to Redfield C, whereas Redfield N remained relatively constant at roughly 9 to 11% in stormflow runoff from cultivated fields. This study shows how land use and management can affect C/N/P stoichiometry in stormflow and baseflow runoff.

Excessive levels of fecal indicator bacteria are a major cause of water quality impairment. Grazing and its management may significantly impact bacteria concentrations, however, other sources can contribute to water quality issues both in the presence and absence of cattle, thus confounding results. In this study, we utilize Bacteroides markers to evaluate bacteria loading from cattle versus background sources in runoff from rotationally grazed and ungrazed pastures and how grazing management, timing of runoff in relation to grazing events, and stocking rate affect Bacteroides marker (AllBac and BoBac) levels and ratios and their relation to E. coli concentrations in runoff at the small watershed scale. The data suggest that the AllBac and BoBac levels were not significantly impacted by grazing management or stocking rate, however, the timing of runoff events in relation to grazing events significantly impacted the levels of these markers found in runoff. Furthermore, the BoBac/AllBac ratio confirmed that fecal contamination present in runoff when sites were destocked for over two weeks largely originated from sources other than cattle. Thus, the magnitude and proportion of cattle impacts on fecal indicator bacteria in edge-of-field runoff were dramatically reduced shortly after de-stocking. However, background sources continued to contribute significant concentrations of E. coli.

Surface inlets route ponded surface water into subsurface drainage networks and are prevalent throughout North America. Despite serving as a nutrient loss pathway, contributing to downstream water quality degradation, surface inlets are thought to be underreported in drainage studies within the literature. Previous studies have demonstrated the footprint that surface inlets have on nutrient transport and drainage effluent but are site specific and focused on individual events. Moreover, although their ubiquitous presence is assumed, no regional surface inlet database exists. To this end, a structured review was undertaken with two goals. First, the MANAGE Drain Load database, consisting of nearly 1,500 site-years of drainage and nutrient data, was analyzed to determine distinctions between areas with and without surface inlets. The median annual total phosphorus (TP) load was greater at site-years with surface inlets (0.40 kg ha-1 ) than site-years without (0.21 kg ha-1 ). The opposite emerged for dissolved nitrogen (DN) loads as site-years with surface inlet had a smaller median annual load (3.3 kg ha-1 ) than site-years without (23.0 kg ha-1 ). This relationship is attributed to immobile TP being transported primarily through overland flow and routed to subsurface drains via surface inlets and to relatively more mobile DN being subsurface driven, bypassed in settings with surface inlets. No statistical differences were found in annual drainage or ratios of particulate P to TP between site-years with and without surface inlets. Second, a logistic regression model was developed that predicts the presence of surface inlets within MANAGE. Eighteen percent of site-years and 21% of sites were predicted to have surface inlets.

Assessment of annual and cumulative impacts of phosphorus (P) management strategies at field and watershed scales is needed to improve crop use efficiency and minimize environmental impacts. The objectives of this study were (a) to assess relationships among P balance, soil test P (STP) concentration, and runoff dissolved reactive P (DRP) concentration from fields receiving different poultry litter application rates (0.0-13.4 Mg ha-1 ) and (b) to determine the effect of long-term poultry litter application to fields on watershed DRP loss. Nutrient management practices, crop yield, STP, and runoff losses were assessed from nine fields and two watersheds located near Riesel, TX, from 2000 to 2015. Field-scale P balances were largely controlled by P application rate and exhibited a positive relationship with STP and runoff DRP flow-weighted mean concentration. Using a before-after control-impact experimental design that included monitoring at both field and watershed scales showed the influence of field P management on watershed DRP loss varied according to both source (i.e., P application rate, impacted area) and transport (i.e., hydrological connectivity) factors. Increased risk of watershed DRP loss was observed during wet years and years with two poultry litter applications to fields within the watershed. The percentage of the total watershed area receiving high rates of poultry litter also played a critical role in determining the risk of DRP loss. Findings highlight the impact of long-term P management strategies on DRP loss at both field and watershed scales and show the importance of incorporating hydrologic connectivity when assessing conservation effects on water quality.

Complex crop models have been developed to simulate the interactions among biophysical processes and to extend experimental results beyond the local soil and climate conditions. However, in-depth studies on a model’s capability to predict crop growth under different conditions are sparse, and the question of whether a crop model outperforms a simple water production function (WPF) has not been answered. The objective of this study was to compare the predictive ability of a complex crop model with simple WPFs for yield and biomass estimation at three sites (Greeley, Fort Collins, and Akron) in eastern Colorado. Specifically, the CERES-Maize crop model in the Root Zone Water Quality Model (RZWQM2), which has been applied extensively in eastern Colorado for simulating maize growth, was compared to crop WPFs based on irrigation and rainfall amounts during growing seasons. Results showed that the predictive ability of CERES-Maize depended on which datasets were used for model parameterization, and that WPFs in general performed as good as or better than CERES-Maize based on a modified F-test after considering experimental uncertainties. The ability of CERES-Maize and the WPF derived from Greeley (2008-2011) to predict maize yield in Greeley (2012-2013), Fort Collins (2006-2010), and Akron (1984-1986) depended on year and site. WPFs outperformed CERES-Maize for Greeley (2012-2013) and Fort Collins (2006-2010) but performed similarly for Akron (1984-1986). This study also identified the need to improve crop model responses to water stress, especially at different growth stages, for cropping systems models to be adequate for estimating the impacts of irrigation management on yield. Ultimately, the choice between the use of a complex crop model and a simpler WPF depends on the purpose of the user and the required accuracy. Keywords: Biomass, CERES-Maize, DSSAT, Grain yield, Irrigation management, RZWQM, Water production function.

Although many previous studies have examined patterns of antimicrobial resistance (AMR) and multidrug resistance (MDR) from domestic animals and farm environments, comparatively little is known about the environmental sources and natural reservoirs of AMR and MDR. In this study, we collected stormwater runoff and soil samples from three watersheds in Texas. Escherichia coli (E. coli) were enumerated, isolated, and analyzed for resistance patterns. E. coli from all sites, irrespective of land use, displayed the presence of AMR/MDR. Higher levels of AMR/MDR were observed in water compared to soil. More isolates were resistant to cephalothin than other antibiotics. For water isolates, 94% was resistant to cephalothin, 27% to tetracycline, and 15% to ampicillin. Across all sites, a large percentage of water isolates demonstrated MDR with 34% resistant to &ge, 2 antibiotics and 11% to &ge, 3 antibiotics. All AMR soil isolates were resistant to cephalothin (87% of the total soil isolates), but only 8.9% were MDR. High cephalothin resistance observed in both soil and water suggests the presence of native, cephalothin-resistant E. coli. Higher MDR observed within water compared to the soil populations suggests that resistance sources other than soil, such as more recent fecal depositions as opposed to residual AMR in soil, could have contributed to higher antibiotic-resistant E. coli in runoff.

A probabilistic approach is presented to assess the performance validity of the empirical Curve Number (CN) and physically-based Green and Ampt (G&A) rainfall-runoff methods in the SWAT model. Specifically, the effects of modeling uncertainties on characterization of the hydrologic budgets and streamflow regimes at various spatial scales and upstream land use conditions are investigated. A Bayesian total uncertainty assessment framework, which explicitly accounts for uncertainties from model parameters, inputs, structure, and measurement data, was employed to explore uncertainties in streamflow simulation using SWAT with different rainfall-runoff methods in a mixed-land use watershed. While the models were trained for streamflow estimation only at the watershed outlet, the performances of the models were compared at different stream locations within the watershed. At the watershed outlet, the CN method had a slightly better, but not significant, performance in terms of streamflow error statistics. Similar results were obtained for the predominantly forested and agricultural tributaries. However, in tributaries with higher percentage of developed land, G&A outperformed the CN method in simulating streamflow based on various performance metrics. In general, the 95% prediction intervals from the models with G&A method covered a higher percentage of observed streamflow especially during the high flow events. However, they were approximately 20–45% wider than the corresponding 95% prediction intervals from the CN methods. Using 95% prediction interval for estimated flow duration curves, results indicated that the models with CN methods underestimated high flow events especially in tributaries with highly developed land use. However, the CN methods generated higher water yields to streams than the G&A method. The results of this study have important implications for the selection and application of appropriate rainfall-runoff methods within complex distributed hydrologic models particularly when simulating hydrologic responses in mixed-land use watersheds. In the present study, while CN and G&A methods in the SWAT model performed similarly at the outlet of a mixed-land use watershed, G&A captured the internal processes more realistically. The subsequent effects on the representation of internal hydrological processes and budgets are discussed.

Conservation practices are widely used to reduce N and P loads from agricultural fields and minimize their impact on water quality, but research using field-scale data to model the national average impact of conservation practices for different forms of N and P is needed. Thus, we quantified the effects of conservation practices (grassed waterways, terraces, contour farming, filter strips, and riparian buffers) on total, particulate, and dissolved N and P runoff from farmlands. Specifically, we conducted a meta-analysis of the Measured Annual Nutrient loads from AGricultural Environments (MANAGE) database using propensity score matching and multilevel modeling to remove the influence of confounding factors. There is no best method for addressing this influence, so we applied two alternative methods because similar results increase confidence in our findings. Propensity score matching found that conservation practices reduced total P, particulate P, and particulate N loading by an average of 67, 83, and 67%, respectively. Multilevel modeling estimated reductions of 58, 76, and 64% for the same nutrients. Although the propensity score method only yields a mean rate of reduction, multilevel modeling further estimates the reduction for different subgroups (i.e., different crops and fertilizer application methods) when such groupings are feasible. The multilevel models indicated that conservation practices affected row crops the most (e.g., corn [ L.] and soybean [ (L.) Merr.]) and fields with injected or surface-applied fertilizers. Our analysis used field-scale data to estimate the average effectiveness of conservation practices in reducing N and P runoff, providing valuable insight for regional and national decision making.

As small-scale animal feeding operations work to manage their byproducts and avoid regulation, they need practical, cost-effective methods to reduce environmental impact. One such option is using vegetative treatment areas (VTAs) with perennial grasses to treat runoff; however, research is limited on VTA effectiveness as a waste management alternative for smaller operations. This study evaluated the efficiencies of VTAs in reducing bacteria and nutrient runoff from small-scale swine operations in three counties in Central Texas. Based on 4 yr of runoff data, the Bell and Brazos VTAs significantly reduced loads and concentrations of E. coli and nutrients (except NO3-N) and had treatment efficiencies of 73–94%. Most notably, the Bell VTA reduced loads of E. coli, NH4-N, PO4-P, total N, and total P similar to that of the background (control). In spite of significant reductions, runoff from the Brazos VTA had higher concentrations and loads than the control site, especially following installation of concrete pens and increased pen washing, which produced standing water and increased E. coli and nutrient influx. The Robertson VTA produced fewer significant reductions and had lower treatment efficiencies (29–69%); however, E. coli and nutrient concentrations and loads leaving this VTA were much lower than observed at the Bell and Brazos County sites due to alternative solids management and enclosed pens. Based on these results and previous research, VTAs can be practical, effective waste management alternatives for reducing nutrient and bacteria losses from small-scale animal operations, but only if properly designed and managed. Keywords: Bacteria, Nutrients, Swine manure, Waste management, Water quality

Soil health has traditionally been judged in terms of production; however, it recently has gained a wider focus with a global audience, as soil condition is becoming an environmental quality, human health, and political issue. A crucial initial step in evaluating soil health is properly assessing the condition of the soil. Currently most laboratory soil analyses treat soils as non-living, non-integrated systems. Plant available nutrients have traditionally been estimated with methods that utilize harsh chemical extractants in testing soil for inorganic N, P, K, and micronutrients. Complementary methods, including soil texture, pH, and total soil organic matter, also do not evaluate biological soil aspects. In this paper we introduce and describe the theory behind the Soil Health Tool, focusing on two objectives: 1) to estimate plant available N, P, and K; and 2) to provide an indication of soil health with respect to nutrient and C cycling. The Soil Health Tool is an integrative soil testing approach that measures inorganic N, P, and K with a soil extractant comprised of organic acids. It also estimates potentially mineralizable N and P as influenced by water extractable organic C and N and microbial soil respiration. The Soil Health Tool was designed for use in commercial soil testing laboratories and uses rapid, cost-effective procedures. The tool also offers insight into the complex interactions between soil chemistry and biology and providing additional value to producers through improved plant available nutrient estimates as well as an indication of the soil health status as related to C, N, and P cycling.

N ational and international open-access agricultural research databases are needed to help solve problems at watershed, regional, and national scales, and to connect productivity, soil health, and environmental quality to food quantity and quality. There are some established, open-access agricultural research networks with extensive research data in the United States, but there is a major need to improve connections between those networks and the emerging data in order to address complex questions. Improving the connections and flow of information among agricultural research networks will enhance the scientific community's ability to simultaneously increase crop yield, sustainability of natural resources, and environmental quality, as well as food, feed, and forage quality, and thus human and animal health. Establishing a network of agricultural databases is crucial for facilitating information flow among different research disciplines. Doing so will also enhance multidisciplinary research opportunities and help build transdisciplinary teams that can provide answers to complex, whole-system research questions and thus solve some of the globe's greatest challenges. GLOBAL CHALLENGES The ever-growing human population is facing one of the greatest challenges of the twenty-first century: to ensure the sustainability of agricultural and natural systems. Both are under the pressure of a changing climate and the increase in…

In 2010, the Natural Resources and Environmental Systems Hydrology Committee (NRES-21) of ASABE initiated a long-term process to develop guidelines to improve modeling practice through better understanding of the calibration, validation, and evaluation process across applications and more effective interpretation and communication of model performance. This effort generated a compilation of 23 articles with model-specific descriptions and guidance (2012), a position paper outlining guidance for evaluating, interpreting, and communicating performance of hydrologic and water quality models considering intended use (2014), and a compilation of ten articles addressing key topics related to model calibration and validation (2015). In 2016, the first draft of ASABE Engineering Practice 621 (EP621), “Guidelines for Calibrating, Validating, and Evaluating Hydrologic and Water Quality (H/WQ) Models,” was developed, subsequently revised, and ultimately approved by the ASABE Standards Committee in 2017. EP621 provides guidelines, not prescriptive requirements, and as such recommends “good” modeling practices to enhance calibration, validation, evaluation, and communication of H/WQ models through establishment of consistent terminology; model selection; compilation and processing of input data and calibration, validation, and evaluation data; determination of model performance measures; model parameterization and calibration; re-examination of input and calibration data and/or consideration of model refinement; re-evaluation of model performance; and documentation of modeling process and results. EP621 can be obtained from the ASABE Technical Library at https://elibrary.asabe.org/abstract.asp?aid=47804. The objectives of this technical note are to review the process and rationale used to develop EP621 and to briefly summarize its major components. Keywords: Hydrologic processes, Hydrology, Model calibration, Modeling, Model validation, Water quality.

Soils are the keystone of healthy and vibrant ecosystems, providing physical, chemical, and biological substrates and functions necessary to support life. In particular, it's the extensive and elaborate matrix of soil microorganisms and other life forms that contributes to soil health and utility. But soils are under constant threat from heavy use, changing climate, and in some cases poor management (1, 2). In view of soil’s key role and threatened status, we believe that there is a need for the scientific community to undertake coordinated research and development efforts that will lead to a unique asset: a National Living Soil Repository (Fig. 1). Fig. 1. A National Living Soil Repository would store agricultural cryogenic and air-dried soil samples, analyze samples for microbial community composition, assess samples for microbial viability, and serve as a potential source of living organisms for various agricultural ecosystem services. Image courtesy of Jennifer Moore-Kucera (USDA Natural Resources Conservation Service) and Daniel Manter (USDA Agricultural Research Service). Already local and national soil archives have been shown to be of great utility for studying, analyzing, and documenting long-term environmental and ecological trends. For example, the historical soil archive at Hubbard Brook helped researchers discover the link between fossil fuels and acidification of rain and snow (3); the Rothamsted Sample Archive in the United Kingdom has shown a steady increase in dioxins during the last century (4). And yet, a soil repository/archive designed to preserve native biological diversity does not currently exist. Such an archive would provide the ability to acquire data on the current biological (e.g., soil health) state of soils around the country across soil types, cropping systems, and ecosystems and over time. Further, by maintaining soil archives and a catalog of their microbial communities, we will gain a better understanding of how soil organisms are distributed … [↵][1]1To whom correspondence should be addressed. Email: Jorge.Delgado{at}ars.usda.gov. [1]: #xref-corresp-1-1

Water extractable organic carbon (WEOC) and nitrogen (WEON) are two key parameters of soil water extractable organic matter (WEOM). Proper management of manure application rate in combination with tillage and cropping management could maintain appropriate WEOC and WEON concentrations in soils while decreasing the risk of their runoff from cropland and pastures. The objective of this research was to determine the effect of poultry litter (PL) application on WEOC and WEON in soils under different crops, tillage regimes, and grazing strategies. From 2001 to 2012, PL was applied at multiple rates to cultivated fields in a corn-oat/wheat-hay rotation or to pastures grazed by cattle or ungrazed. Soil samples (0 - 15 cm) were analyzed for KCl-extractable mineral N, and WEOC, and WEON contents. In addition, Ultraviolet-visible (UV-vis) and fluorescence spectroscopies were used to characterize WEOC stability. Organic N levels were higher at the high PL application rates. The soil C:N ratio narrowed as the PL application rate increased. However, the soil from pastures which received PL tended to have a wider range of C:N ratios than soil from the cultivated fields, despite identical PL application rates. The spectral analyses indicated that WEOC properties were responsive to management and PL application rate; therefore, this parameter may be used as a guide to provide best management strategy for manure application.

Projected climate change is expected to substantially affect crop and livestock production, and water availability and quality. Concomitantly, the agricultural community is faced with a challenge of increasing food production by more than 70% to meet demand from global population increase by the mid-21st century. This article introduces a Special Collection on Climate Change and reviews principal findings from nine articles drawn from papers presented at the 2015 ASABE 1st Climate Change―Adaptation and Mitigation Symposium. Studies present simulations of crop and livestock production-system adaptations to climate change scenarios; impacts of climate change scenarios on water resources, soil erosion and nonpoint-source pollutant source areas; regional assessment of climatic shifts; and mitigation of greenhouse gas emissions from livestock production. Articles span regional issues across the U.S., southern Asia, and Brazil. These research articles clearly indicate that climate variability and change can negatively impact food production and water resources, and that innovative strategies are needed to mitigate those negative impacts.

Subsurface nitrogen (N) losses represent a major environmental concern in agriculture, particularly from fields containing artificial drainage to prevent saturated soil conditions and increase crop production. To develop sustainable intensification strategies and achieve high yields with minimal environmental impacts, N losses are increasingly evaluated with respect to crop productivity on a “yield-scaled” basis, yet little information is available to address the current challenge of balancing crop yields and drainage N losses from intensive maize production systems in the U.S. Midwest by using this metric. In the present study, a meta-analysis was conducted using 31 studies with 381 observations from a publicly available nutrient loss drainage database (Measured Annual Nutrient loads from Agricultural Environments, MANAGE) to address this issue. Results showed that increasing N rates enhanced yields but had weak effects on area- and yield-scaled drainage N losses. In contrast, yield-scaled drainage N losses responded exponentially to N surplus (estimated as N application rate minus above-ground crop N uptake). Relative precipitation during the drainage monitoring period strongly influenced area- and yield-scaled drainage N losses. Maize-soybean rotations and silt loam soils had lower yield-scaled drainage N losses compared to continuous maize and clay loam soils, respectively, whereas tillage practices had little impact on yield-scaled drainage N losses. To meet the growing challenge of achieving high yields with minimal impacts on water quality, these results suggest that evaluating drainage N losses on a yield-scaled basis may complement the more conventional approach of evaluating N losses on an areas basis for maize systems in this region.

Three different models of tipping bucket rain gauges (TBRs), viz. HS-TB3 (Hydrological Services Pty Ltd.), ISCO-674 (Isco, Inc.) and TR-525 (Texas Electronics, Inc.), were calibrated in the lab to quantify measurement errors across a range of rainfall intensities (5 mm·h− 1 to 250 mm·h− 1) and three different volumetric settings. Instantaneous and cumulative values of simulated rainfall were recorded at 1, 2, 5, 10 and 20-min intervals. All three TBR models showed a substantial deviation (α = 0.05) in measurements from actual rainfall depths, with increasing underestimation errors at greater rainfall intensities. Simple linear regression equations were developed for each TBR to correct the TBR readings based on measured intensities (R2 > 0.98). Additionally, two dynamic calibration techniques, viz. quadratic model (R2 > 0.7) and T vs. 1/Q model (R2 = > 0.98), were tested and found to be useful in situations when the volumetric settings of TBRs are unknown. The correction models were successfully applied to correct field-collected rainfall data from respective TBR models. The calibration parameters of correction models were found to be highly sensitive to changes in volumetric calibration of TBRs. Overall, the HS-TB3 model (with a better protected tipping bucket mechanism, and consistent measurement errors across a range of rainfall intensities) was found to be the most reliable and consistent for rainfall measurements, followed by the ISCO-674 (with susceptibility to clogging and relatively smaller measurement errors across a range of rainfall intensities) and the TR-525 (with high susceptibility to clogging and frequent changes in volumetric calibration, and highly intensity-dependent measurement errors). The study demonstrated that corrections based on dynamic and volumetric calibration can only help minimize—but not completely eliminate the measurement errors. The findings from this study will be useful for correcting field data from TBRs; and may have major implications to field- and watershed-scale hydrologic studies.

NSFNational Science Foundation (NSF) [1343802]; USDA NRCS Conservation Innovation Grants Program [69-3A75-13-232]; NatureNet postdoctoral fellowship from The Nature Conservancy

Grazing land models can assess the provisioning and trade-offs among ecosystem services attributable to grazing management strategies. We reviewed 12 grazing land models used for evaluating forage and animal (meat and milk) production, soil C sequestration, greenhouse gas emission, and nitrogen leaching, under both current and projected climate conditions. Given the spatial and temporal variability that characterizes most rangelands and pastures in which animal, plant, and soil interact, none of the models currently have the capability to simulate a full suite of ecosystem services provided by grazing lands at different spatial scales and across multiple locations. A large number of model applications have focused on topics such as environmental impacts of grazing land management and sustainability of ecosystems. Additional model components are needed to address the spatial and temporal dynamics of animal foraging behavior and interactions with biophysical and ecological processes on grazing lands and their impacts on animal performance. In addition to identified knowledge gaps in simulating biophysical processes in grazing land ecosystems, our review suggests further improvements that could increase adoption of these models as decision support tools. Grazing land models need to increase user-friendliness by utilizing available big data to minimize model parameterization so that multiple models can be used to reduce simulation uncertainty. Efforts need to reduce inconsistencies among grazing land models in simulated ecosystem services and grazing management effects by carefully examining the underlying biophysical and ecological processes and their interactions in each model. Learning experiences among modelers, experimentalists, and stakeholders need to be strengthened by co-developing modeling objectives, approaches, and interpretation of simulation results.

Phosphorus is an essential nutrient for plant growth but in excess is a source of environmental pollution. Fertilizer additions of P are recommended based on soil tests; however, the commonly applied P extractants are often applied outside of their design criteria (specifically soil pH). As a result, soil tests can produce inaccurate estimates of plant available P in the soil, which either increases P loss in runoff, contributing to eutrophication, or decreases crop production contributing to economic loss. In this study, 200 diverse soils from across the US were extracted with Mehlich 3, water, H3A-3, and FeAlO strips. Comparison with FeAlO was critical, as this method is accepted as the “gold standard” for plant-available P, but it is rarely used in commercial labs because of time and financial constraints. H3A-3 produced mean, median, standard deviations that are very similar to FeAlO strip results and low relative errors ( 0.96 with slopes 0.95 - 0.98). Although Mehlich 3 and water were correlated with FeAlO, Mehlich 3 (strongly acidic) extracted much more P than FeAlO, and water (low buffering capacity) extracted much less P across the range of soil pH values. Thus, H3A-3 provides an improved methodology to accurately determine plant-available P by mimicking root exudate action in the soil, while avoiding the time-consuming and costly FeAlO procedure. In the face of high-profile water quality impairments with enormous economic costs, such advancements are critical to balance agronomic production with environmental concerns.

Estimating the effect of agricultural conservation practices on reducing nutrient loss using observational data can be confounded by factors such as differing crop types and management practices. As we may not have the full knowledge of these confounding factors, conventional statistical meta-analysis methods can be misleading. We discuss the use of two statistical causal analysis methods for quantifying the effects of water and soil conservation practices in reducing P loss from agricultural fields. With the propensity score method, a subset of data was used to form a treatment group and a control group with similar distributions of confounding factors. With the multilevel modeling method, data were stratified based on important confounding factors, and the conservation practice effect was evaluated for each stratum. Both methods resulted in similar estimates of the conservation practice effect (total P load reduction avg. ~70%). In addition, both methods show evidence of conservation practices reducing the incremental increase in total P export per unit increase in fertilizer application. These results are presented as examples of the types of outcomes provided by statistical causal analyses, not to provide definitive estimates of P loss reduction. The enhanced meta-analysis methods presented within are applicable for improved assessment of agricultural practices and their effects and can be used for providing realistic parameter values for watershed-scale modeling.

Sequential fractionation coupled with phosphatase hydrolysis allows a greater understanding of the effects of animal manure on the chemical distribution of soil P. Concentrations of specific soil P fractions were determined after long-term (>10 yr) poultry litter application at rates of 4.5, 6.7, 9.0, 11.2, and 13.4 Mg manure ha⁻¹ yr⁻¹ to watershed-scale plots (cultivated and grazed–ungrazed pasture) on a calcareous Texas Blackland Vertisol. Soil total extractable P (Pₜ) and inorganic P (Pᵢ) were quantified following sequential extraction with H₂O, NaHCO₃, NaOH, and HCl. Hydrolyzable organic P (Pₑ) and non-hydrolyzable organic P (Pₙₑ) were determined in the extracted fractions following enzymatic hydrolysis. Litter application increased Pₜ regardless of land-use type compared with the control. Concentrations of H₂O-extractable Pᵢ in litter-amended plots increased by 9 to 34% (cultivated) and 7 to 30% (pasture) over the control, indicating substantial risk of soluble P runoff. Labile organic P (Pₒ) extracted with H₂O and NaHCO₃ decreased in the order monoester > nucleic acid > phytate > Pₙₑ. An average of 68% of Pₜ was extractable with HCl. Organic P comprised the majority (95%) of HCl-Pₜ; however, only trace levels of HCl-Pₒ were hydrolyzable, and litter application increased HCl-Pₙₑ up to 217%. Thus, litter application increased levels of both soluble Pᵢ and stable Pₙₑ, but the specific response varied with application rate and land management. This study increased understanding of P chemical distribution with time in litter-amended soil with high clay and CaCO₃ contents under differing land-use scenarios.

The availability of fresh water is a prerequisite for municipal development and agricultural production especially in the arid and semi-arid portions of the western U.S. Agriculture is the leading user of water in the U.S. Agricultural water use can be partitioned into green (derived from rainfall) and blue water (irrigation). Blue water can be further subdivided by source. In this research we develop a hydrologic balance by 8-Digit Hydrologic Unit Code (HUC8) using a combination of Soil and Water Assessment Tool (SWAT) simulations and available human water use estimates. These data are used partition agricultural groundwater usage blue water by sustainability and surface water usage by local source or importation. These predictions coupled with reported agricultural yield data are used to predict the virtual water contained in each ton of corn, wheat, sorghum, and soybeans produced and its source. We estimate that these four crops consume 480 km3 of green water annually and 23 km3 of blue water, 12 km3 of which is from groundwater depletion. Regional trends in blue water use from groundwater depletion highlight heavy usage in the High Plains, and small pockets throughout the Western U.S. This information is presented to inform water resources debate by estimating the cost of agricultural production in terms of water regionally. This research illustrates the variable water content of the crops we consume and export, and the source of that water.

Water quality impairment due to excessive nutrients and sediment is a major problem in the United States (U.S.). An important step in the mitigation of impairment in any given water body is determination of pollutant sources and amount. The sheer number of impaired waters and limited resources makes simplistic load estimation methods such as export coefficient (EC) methods attractive. Unfortunately ECs are typically based on small watershed monitoring data, which are very limited and/or often based on data collected from distant watersheds with drastically different conditions. In this research, we seek to improve the accuracy of these nutrient export estimation methods by developing a national database of localized EC for each ecoregion in the U.S. A stochastic sampling methodology loosely based on the Monte-Carlo technique was used to construct a database of 45 million Soil and Water Assessment Tool (SWAT) simulations. These simulations consider a variety of climate, topography, soils, weather, land use, management, and conservation implementation conditions. SWAT model simulations were successfully validated with edge-of-field monitoring data. Simulated nutrient ECs compared favorably with previously published studies. These ECs may be used to rapidly estimate nutrient loading for any small catchment in the U.S. provided the location, area, and land-use distribution are known.