Molecular evolution of Zika virus as it crossed the Pacific to the Americas.

Zika virus was previously considered to cause only a benign infection in humans. Studies of recent outbreaks of Zika virus in the Pacific, South America, Mexico and the Caribbean have associated the virus with severe neuropathology. Viral evolution may be one factor contributing to an apparent change in Zika disease as it spread from Southeast Asia across the Pacific to the Americas. To address this possibility, we have employed computational tools to compare the phylogeny, geography, immunology and RNA structure of Zika virus isolates from Africa, Asia, the Pacific and the Americas. In doing so, we compare and contrast methods and results for tree search and rooting of Zika virus phylogenies. In some phylogenetic analyses we find support for the hypothesis that there is a deep common ancestor between African and Asian clades (the "Asia/Africa" hypothesis). In other phylogenetic analyses, we find that Asian lineages are descendent from African lineages (the "out of Africa" hypothesis). In addition, we identify and evaluate key mutations in viral envelope protein coding and untranslated terminal RNA regions. We find stepwise mutations that have altered both immunological motif sets and regulatory sequence elements. Both of these sets of changes distinguish viruses found in Africa from those in the emergent Asia-Pacific-Americas lineage. These findings support the working hypothesis that mutations acquired by Zika virus in the Pacific and Americas contribute to changes in pathology. These results can inform experiments required to elucidate the role of viral genetic evolution in changes in neuropathology, including microcephaly and other neurological and skeletomuscular issues in infants, and Guillain-Barré syndrome in adults.

Simulated nitrous oxide emissions from multiple agroecosystems in the U.S. Corn Belt using the modified SWAT-C model.

Agriculture is a major source of nitrous oxide (N2O) emissions into the atmosphere. However, assessing the impacts of agricultural conservation practices, land use change, and climate adaptation measures on N2O emissions at a large scale is a challenge for process-based model applications. Here, we integrated six N2O emission algorithms for the nitrification processes and seven N2O emission algorithms for the denitrification process into the Soil and Water Assessment Tool-Carbon (SWAT-C). We evaluated the different combinations of methods in simulating N2O emissions under corn (Zea mays L.) production systems with various conservation practices, including fertilization, tillage, and crop rotation (represented by 14 experimental treatments and 83 treatment-years) at five experimental sites across the U.S. Midwest. The SWAT-C model exhibited wide variability in simulating daily average N2O emissions across treatment-years with different method configurations, as indicated by the ranges of R2, NSE, and BIAS (0.04-0.68, -1.78-0.60, and -0.94-0.001, respectively). Our results indicate that the denitrification process has a stronger impact on N2O emissions than the nitrification process. The best performing N2O emission algorithms are those rooted in the CENTURY model, which considers soil pH and respiration effects that were overlooked by other algorithms. The optimal N2O emission algorithm explained about 63% of the variability of annual average N2O emissions, with NSE and BIAS of 0.60 and -0.033, respectively. The model can reasonably represent the impacts of agricultural conservation practices on N2O emissions. We anticipate that the improved SWAT-C model, with its flexible configurations and robust modeling and assessment capabilities, will provide a valuable tool for studying and managing N2O emissions from agroecosystems.

Verifiable metamodels for nitrate losses to drains and groundwater in the Corn Belt, USA.

Nitrate leaching in the unsaturated zone poses a risk to groundwater, whereas nitrate in tile drainage is conveyed directly to streams. We developed metamodels (MMs) consisting of artificial neural networks to simplify and upscale mechanistic fate and transport models for prediction of nitrate losses by drains and leaching in the Corn Belt, USA. The two final MMs predicted nitrate concentration and flux, respectively, in the shallow subsurface. Because each MM considered both tile drainage and leaching, they represent an integrated approach to vulnerability assessment. The MMs used readily available data comprising farm fertilizer nitrogen (N), weather data, and soil properties as inputs; therefore, they were well suited for regional extrapolation. The MMs effectively related the outputs of the underlying mechanistic model (Root Zone Water Quality Model) to the inputs (R(2) = 0.986 for the nitrate concentration MM). Predicted nitrate concentration was compared with measured nitrate in 38 samples of recently recharged groundwater, yielding a Pearson's r of 0.466 (p = 0.003). Predicted nitrate generally was higher than that measured in groundwater, possibly as a result of the time-lag for modern recharge to reach well screens, denitrification in groundwater, or interception of recharge by tile drains. In a qualitative comparison, predicted nitrate concentration also compared favorably with results from a previous regression model that predicted total N in streams.

Simulating nitrate-nitrogen concentration from a subsurface drainage system in response to nitrogen application rates using RZWQM2.

Computer models have been widely used to evaluate the impact of agronomic management on nitrogen (N) dynamics in subsurface drained fields. However, they have not been evaluated as to their ability to capture the variability of nitrate-nitrogen (NO(3)-N) concentration in subsurface drainage at a wide range of N application rates due to possible errors in the simulation of other system components. The objective of this study was to evaluate the performance of Root Zone Water Quality Model2 (RZWQM2) in simulating the response of NO(3)-N concentration in subsurface drainage to N application rate. A 16-yr field study conducted in Iowa at nine N rates (0-252 kg N ha(-1)) from 1989 to 2004 was used to evaluate the model, based on a previous calibration with data from 2005 to 2009 at this site. The results showed that the RZWQM2 model performed "satisfactorily" in simulating the response of NO(3)-N concentration in subsurface drainage to N fertilizer rate with 0.76, 0.49, and -3% for the Nash-Sutcliffe efficiency, the ratio of the root mean square error to the standard deviation, and percent bias, respectively. The simulation also identified that the N application rate required to achieve the maximum contaminant level for the annual average NO(3)-N concentration was similar to field-observed data. This study supports the use of RZWQM2 to predict NO(3)-N concentration in subsurface drainage at various N application rates once it is calibrated for the local condition.

Nitrate losses and nitrous oxide emissions under contrasting tillage and cover crop management.

Agroecosystems in the upper Mississippi River Basin are highly productive but often contribute to deterioration of water quality and greenhouse gas emissions. Cover cropping and no-till are conservation strategies implemented to reduce the environmental impact of these agroecosystems. However, using multiple strategies can lead to systemwide interactions that are not fully understood. These interactions can affect not only environmental quality metrics, such as subsurface drainage nitrate losses or nitrous oxide (N2 O) emissions, but also may influence crop production potential. A field trial was initiated comparing nitrate losses, N2 O emissions, and crop production under systems with fall chisel plow tillage, fall chisel plow tillage with an oat (Avena sativa L.) cover crop (CP-oat), no-till (NT), no-till with a rye (Secale cereale L.) cover crop (NT-rye), and NT with zero N fertilizer. Pathways for nitrate losses and N2 O emissions did not appear linked and were not tied to cover crop or tillage practices. Nitrate losses were linked with drainage volumes, and cover crops and tillage had limited effect on cumulative drainage volumes. Notably, NT-rye altered the relationship between drainage volume and nitrate losses by reducing nitrate concentrations, lowering nitrate losses by 59 ±9% compared with CP-oat and 67 ± 9% compared with NT. Neither cover crop nor tillage consistently affected N2 O emissions or crop yield. Rather, N2 O emissions were closely tied with fertilizer N application and seasonal weather patterns. These findings indicate that nitrate leaching and N2 O emissions are regulated by separate mechanisms, so conservation management may require stacking multiple practices to be effective.

Both subsurface nitrate losses and nitrous oxide emissions were linked with weather. Subsurface nitrate losses were linked with cumulative annual drainage. Nitrous oxide emissions were linked with fertilizer N applications. Rye cover crop with no-till reduced nitrate losses with no yield declines.

COVID-19 Disease, Women's Predominant Non-Heparin Vaccine-Induced Thrombotic Thrombocytopenia and Kounis Syndrome: A Passepartout Cytokine Storm Interplay.

Coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) constitute one of the deadliest pandemics in modern history demonstrating cardiovascular, gastrointestinal, hematologic, mucocutaneous, respiratory, neurological, renal and testicular manifestations and further complications. COVID-19-induced excessive immune response accompanied with uncontrolled release of cytokines culminating in cytokine storm seem to be the common pathogenetic mechanism of these complications. The aim of this narrative review is to elucidate the relation between anaphylaxis associated with profound hypotension or hypoxemia with pro-inflammatory cytokine release. COVID-19 relation with Kounis syndrome and post-COVID-19 vaccination correlation with heparin-induced thrombocytopenia with thrombosis (HITT), especially serious cerebral venous sinus thrombosis, were also reviewed. METHODS: A current literature search in PubMed, Embase and Google databases was performed to reveal the pathophysiology, prevalence, clinical manifestation, correlation and treatment of COVID-19, anaphylaxis with profuse hypotension, Kounis acute coronary syndrome and thrombotic events post vaccination. RESULTS: The same key immunological pathophysiology mechanisms and cells seem to underlie COVID-19 cardiovascular complications and the anaphylaxis-associated Kounis syndrome. The myocardial injury in patients with COVID-19 has been attributed to coronary spasm, plaque rupture and microthrombi formation, hypoxic injury or cytokine storm disposing the same pathophysiology with the three clinical variants of Kounis syndrome. COVID-19-interrelated vaccine excipients as polysorbate, polyethelene glycol (PEG) and trometamol constitute potential allergenic substances. CONCLUSION: Better acknowledgement of the pathophysiological mechanisms, clinical similarities, multiorgan complications of COVID-19 or other viral infections as dengue and human immunodeficiency viruses along with the action of inflammatory cells inducing the Kounis syndrome could identify better immunological approaches for prevention, treatment of the COVID-19 pandemic as well as post-COVID-19 vaccine adverse reactions.

COVID-19: Famotidine, Histamine, Mast Cells, and Mechanisms.

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. SARS-CoV-2 infection is necessary but not sufficient for development of clinical COVID-19 disease. Currently, there are no approved pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain obscure. We have investigated several plausible hypotheses for famotidine activity including antiviral and host-mediated mechanisms of action. We propose that the principal mechanism of action of famotidine for relieving COVID-19 symptoms involves on-target histamine receptor H2 activity, and that development of clinical COVID-19 involves dysfunctional mast cell activation and histamine release. Based on these findings and associated hypothesis, new COVID-19 multi-drug treatment strategies based on repurposing well-characterized drugs are being developed and clinically tested, and many of these drugs are available worldwide in inexpensive generic oral forms suitable for both outpatient and inpatient treatment of COVID-19 disease.

Predicting unsaturated zone nitrogen mass balances in agricultural settings of the United States.

Unsaturated zone N fate and transport were evaluated at four sites to identify the predominant pathways of N cycling: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard and cornfield (Zea mays L.) in the lower Merced River study basin, California; and corn-soybean [Glycine max (L.) Merr.] rotations in study basins at Maple Creek, Nebraska, and at Morgan Creek, Maryland. We used inverse modeling with a new version of the Root Zone Water Quality Model (RZWQM2) to estimate soil hydraulic and nitrogen transformation parameters throughout the unsaturated zone; previous versions were limited to 3-m depth and relied on manual calibration. The overall goal of the modeling was to derive unsaturated zone N mass balances for the four sites. RZWQM2 showed promise for deeper simulation profiles. Relative root mean square error (RRMSE) values for predicted and observed nitrate concentrations in lysimeters were 0.40 and 0.52 for California (6.5 m depth) and Nebraska (10 m), respectively, and index of agreement (d) values were 0.60 and 0.71 (d varies between 0 and 1, with higher values indicating better agreement). For the shallow simulation profile (1 m) in Maryland, RRMSE and d for nitrate were 0.22 and 0.86, respectively. Except for Nebraska, predictions of average nitrate concentration at the bottom of the simulation profile agreed reasonably well with measured concentrations in monitoring wells. The largest additions of N were predicted to come from inorganic fertilizer (153-195 kg N ha(-1) yr(-1) in California) and N fixation (99 and 131 kg N ha(-1) yr(-1) in Maryland and Nebraska, respectively). Predicted N losses occurred primarily through plant uptake (144-237 kg N ha(-1) yr(-1)) and deep seepage out of the profile (56-102 kg N ha(-1) yr(-1)). Large reservoirs of organic N (up to 17,500 kg N ha(-1) m(-1) at Nebraska) were predicted to reside in the unsaturated zone, which has implications for potential future transfer of nitrate to groundwater.

COVID-19: Famotidine, Histamine, Mast Cells, and Mechanisms.

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. Currently, there are no pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain obscure. We explore several plausible avenues of activity including antiviral and host-mediated actions. We propose that the principal famotidine mechanism of action for COVID-19 involves on-target histamine receptor H2 activity, and that development of clinical COVID-19 involves dysfunctional mast cell activation and histamine release.

Escherichia coli transport from surface-applied manure to subsurface drains through artificial biopores.

Bacteria transport in soils primarily occurs through soil mesopores and macropores (e.g., biopores and cracks). Field research has demonstrated that biopores and subsurface drains can be hydraulically connected. This research was conducted to investigate the importance of surface connected and disconnected (buried) biopores on Escherichia coli (E. coli) transport when biopores are located near subsurface drains. A soil column (28 by 50 by 95 cm) was packed with loamy sand and sandy loam soils to bulk densities of 1.6 and 1.4 Mg m(-3), respectively, and containing an artificial biopore located directly above a subsurface drain. The sandy loam soil was packed using two different methods: moist soil sieved to 4.0 mm and air-dried soil manually crushed and then sieved to 2.8 mm. A 1-cm constant head was induced on the soil surface in three flushes: (i) water, (ii) diluted liquid swine (Sus scrofa) manure 48 h later, and (iii) water 48 h after the manure. Escherichia coli transport to the drain was observed with either open surface connected or buried biopores. In surface connected biopores, E. coli transport was a function of the soil type and the layer thickness between the end of the biopore and drain. Buried biopores contributed flow and E. coli in the less sorptive soil (loamy sand) and the sorptive soil (sandy loam) containing a wide (i.e., with mesopores) pore space distribution prevalent due to the moist soil packing technique. Biopores provide a mechanism for rapidly transporting E. coli into subsurface drains during flow events.

Impact of glyphosate-tolerant soybean and glufosinate-tolerant corn production on herbicide losses in surface runoff.

Residual herbicides used in the production of soybean [Glycine max (L.) Merr] and corn (Zea mays L.) are often detected in surface runoff at concentrations exceeding their maximum contaminant levels (MCL) or health advisory levels (HAL). With the advent of transgenic, glyphosate-tolerant soybean and glufosinate-tolerant corn this concern might be reduced by replacing some of the residual herbicides with short half-life, strongly sorbed, contact herbicides. We applied both herbicide types to two chiseled and two no-till watersheds in a 2-yr corn-soybean rotation and at half rates to three disked watersheds in a 3-yr corn/soybean/wheat (Triticum aestivum L.)-red clover (Trifolium pratense L.) rotation and monitored herbicide losses in runoff water for four crop years. In soybean years, average glyphosate loss (0.07%) was approximately 1/7 that of metribuzin (0.48%) and about one-half that of alachlor (0.12%), residual herbicides it can replace. Maximum, annual, flow-weighted concentration of glyphosate (9.2 microg L(-1)) was well below its 700 microg L(-1) MCL and metribuzin (9.5 microg L(-1)) was well below its 200 microg L(-1) HAL, whereas alachlor (44.5 microg L(-1)) was well above its 2 microg L(-1) MCL. In corn years, average glufosinate loss (0.10%) was similar to losses of alachlor (0.07%) and linuron (0.15%), but about one-fourth that of atrazine (0.37%). Maximum, annual, flow-weighted concentration of glufosinate (no MCL) was 3.5 microg L(-1), whereas atrazine (31.5 microg L(-1)) and alachlor (9.8 microg L(-1)) substantially exceeded their MCLs of 3 and 2 microg L(-1), respectively. Regardless of tillage system, flow-weighted atrazine and alachlor concentrations exceeded their MCLs in at least one crop year. Replacing these herbicides with glyphosate and glufosinate can reduce the occurrence of dissolved herbicide concentrations in runoff exceeding drinking water standards.

Corn stover harvest increases herbicide movement to subsurface drains - Root Zone Water Quality Model simulations.

BACKGROUND: Crop residue removal for bioenergy production can alter soil hydrologic properties and the movement of agrochemicals to subsurface drains. The Root Zone Water Quality Model (RZWQM), previously calibrated using measured flow and atrazine concentrations in drainage from a 0.4 ha chisel-tilled plot, was used to investigate effects of 50 and 100% corn (Zea mays L.) stover harvest and the accompanying reductions in soil crust hydraulic conductivity and total macroporosity on transport of atrazine, metolachlor and metolachlor oxanilic acid (OXA). RESULTS: The model accurately simulated field-measured metolachlor transport in drainage. A 3 year simulation indicated that 50% residue removal reduced subsurface drainage by 31% and increased atrazine and metolachlor transport in drainage 4-5-fold when surface crust conductivity and macroporosity were reduced by 25%. Based on its measured sorption coefficient, approximately twofold reductions in OXA losses were simulated with residue removal. CONCLUSION: The RZWQM indicated that, if corn stover harvest reduces crust conductivity and soil macroporosity, losses of atrazine and metolachlor in subsurface drainage will increase owing to reduced sorption related to more water moving through fewer macropores. Losses of the metolachlor degradation product OXA will decrease as a result of the more rapid movement of the parent compound into the soil. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Zika Virus: Medical Countermeasure Development Challenges.

INTRODUCTION: Reports of high rates of primary microcephaly and Guillain-Barré syndrome associated with Zika virus infection in French Polynesia and Brazil have raised concerns that the virus circulating in these regions is a rapidly developing neuropathic, teratogenic, emerging infectious public health threat. There are no licensed medical countermeasures (vaccines, therapies or preventive drugs) available for Zika virus infection and disease. The Pan American Health Organization (PAHO) predicts that Zika virus will continue to spread and eventually reach all countries and territories in the Americas with endemic Aedes mosquitoes. This paper reviews the status of the Zika virus outbreak, including medical countermeasure options, with a focus on how the epidemiology, insect vectors, neuropathology, virology and immunology inform options and strategies available for medical countermeasure development and deployment. METHODS: Multiple information sources were employed to support the review. These included publically available literature, patents, official communications, English and Lusophone lay press. Online surveys were distributed to physicians in the US, Mexico and Argentina and responses analyzed. Computational epitope analysis as well as infectious disease outbreak modeling and forecasting were implemented. Field observations in Brazil were compiled and interviews conducted with public health officials.

Data worth and prediction uncertainty for pesticide transport and fate models in Nebraska and Maryland, United States.

BACKGROUND: Complex environmental models are frequently extrapolated to overcome data limitations in space and time, but quantifying data worth to such models is rarely attempted. The authors determined which field observations most informed the parameters of agricultural system models applied to field sites in Nebraska (NE) and Maryland (MD), and identified parameters and observations that most influenced prediction uncertainty. RESULTS: The standard error of regression of the calibrated models was about the same at both NE (0.59) and MD (0.58), and overall reductions in prediction uncertainties of metolachlor and metolachlor ethane sulfonic acid concentrations were 98.0 and 98.6% respectively. Observation data groups reduced the prediction uncertainty by 55-90% at NE and by 28-96% at MD. Soil hydraulic parameters were well informed by the observed data at both sites, but pesticide and macropore properties had comparatively larger contributions after model calibration. CONCLUSIONS: Although the observed data were sparse, they substantially reduced prediction uncertainty in unsampled regions of pesticide breakthrough curves. Nitrate evidently functioned as a surrogate for soil hydraulic data in well-drained loam soils conducive to conservative transport of nitrogen. Pesticide properties and macropore parameters could most benefit from improved characterization further to reduce model misfit and prediction uncertainty.

Application of the Root Zone Water Quality Model (RZWQM) to pesticide fate and transport: an overview.

Pesticide transport models are tools used to develop improved pesticide management strategies, study pesticide processes under different conditions (management, soils, climates, etc) and illuminate aspects of a system in need of more field or laboratory study. This paper briefly overviews RZWQM history and distinguishing features, overviews key RZWQM components and reviews RZWQM validation studies. RZWQM is a physically based agricultural systems model that includes sub-models to simulate: infiltration, runoff, water distribution and chemical movement in the soil; macropore flow and chemical movement through macropores; evapotranspiration (ET); heat transport; plant growth; organic matter/nitrogen cycling; pesticide processes; chemical transfer to runoff; and the effect of agricultural management practices on these processes. Research to date shows that if key input parameters are calibrated, RZWQM can adequately simulate the processes involved with pesticide transport (ET, soil-water content, percolation and runoff, plant growth and pesticide fate). A review of the validation studies revealed that (1) accurate parameterization of restricting soil layers (low permeability horizons) may improve simulated soil-water content; (2) simulating pesticide sorption kinetics may improve simulated soil pesticide concentration with time (persistence) and depth and (3) calibrating the pesticide half-life is generally necessary for accurate pesticide persistence simulations. This overview/review provides insight into the processes involved with the RZWQM pesticide component and helps identify model weaknesses, model strengths and successful modeling strategies.

Documenting the pesticide processes module of the ARS RZWQM agroecosystem model.

We describe the theory and current development state of the pesticide process module of the USDA-Agricultural Research Service Root Zone Water Quality Model, or RZWQM. Several processes which are significant in determining the fate of a pesticide application are included together in this module for the first time, including application technique, root uptake, ionic dissociation, soil depth dependence of persistence, volatilization, wicking upward in soil and aging of residues. The pesticide module requires a large number of parameters to run (as does the RZWQM model as a whole) and it is becoming clear that RZWQM will find most interest and use as part of a 'scenario' in which all data requirements are supplied and the predictions of the system compared with a real (usually partial) data set. Such a scenario may then be modified to examine the response of the system to changes in inputs. It also has significant potential as a technology transfer or teaching tool, providing detailed understanding of a specific agronomic system and its potential impacts on the environment.

The pesticide module of the Root Zone Water Quality Model (RZWQM): testing and sensitivity analysis of selected algorithms for pesticide fate and surface runoff.

The Root Zone Water Quality Model (RZWQM) is a one-dimensional, numerical model for simulating water movement and chemical transport under a variety of management and weather scenarios at the field scale. The pesticide module of RZWQM includes detailed algorithms that describe the complex interactions between pesticides and the environment. We have simulated a range of situations with RZWQM, including foliar interception and washoff of a multiply applied insecticide (chlorpyrifos) to growing corn, and herbicides (alachlor, atrazine, flumetsulam) with pH-dependent soil sorption, to examine whether the model appears to generate reasonable results. The model was also tested using chlorpyrifos and flumetsulam for the sensitivity of its predictions of chemical fate and water and pesticide runoff to various input parameters. The model appears to generate reasonable representations of the fate and partitioning of surface- and foliar-applied chemicals, and the sorption of weakly acidic or basic pesticides, processes that are becoming increasingly important for describing adequately the environmental behavior of newer pesticides. However, the kinetic sorption algorithms for charged pesticides appear to be faulty. Of the 29 parameters and variables analyzed, chlorpyrifos half-life, the Freundlich adsorption exponent, the fraction of kinetic sorption sites, air temperature, soil bulk density, soil-water content at 33 kPa suction head and rainfall were most sensitive for predictions of chlorpyrifos residues in soil. The latter three inputs and the saturated hydraulic conductivity of the soil and surface crusts were most sensitive for predictions of surface water runoff and water-phase loss of chlorpyrifos. In addition, predictions of flumetsulam (a weak acid) runoff and dynamics in soil were sensitive to the Freundlich equilibrium adsorption constant, soil pH and its dissociation coefficient.

Test of the Root Zone Water Quality Model (RZWQM) for predicting runoff of atrazine, alachlor and fenamiphos species from conventional-tillage corn mesoplots.

The Root Zone Water Quality Model (RZWQM) is a comprehensive, integrated physical, biological and chemical process model that simulates plant growth and movement of water, nutrients and pesticides in a representative area of an agricultural system. We tested the ability of RZWQM to predict surface runoff losses of atrazine, alachlor, fenamiphos and two fenamiphos oxidative degradates against results from a 2-year mesoplot rainfall simulation experiment. Model inputs included site-specific soil properties and weather, but default values were used for most other parameters, including pesticide properties. No attempts were made to calibrate the model except for soil crust/seal hydraulic conductivity and an adjustment of pesticide persistence in near-surface soil. Approximately 2.5 (+/- 0.9), 3.0 (+/- 0.8) and 0.3 (+/- 0.2)% of the applied alachlor, atrazine and fenamiphos were lost in surface water runoff, respectively. Runoff losses in the 'critical' events--those occurring 24 h after pesticide application--were respectively 91 (+/- 5), 86 (+/- 6) and 96 (+/- 3)% of total runoff losses for these pesticides. RZWQM adequately predicted runoff water volumes, giving a predicted/observed ratio of 1.2 (+/- 0.5) for all events. Predicted pesticide concentrations and loads from the 'critical' events were generally within a factor of 2, but atrazine losses from these events were underestimated, which was probably a formulation effect, and fenamiphos losses were overestimated due to rapid oxidation. The ratios of predicted to measured pesticide concentrations in all runoff events varied between 0.2 and 147, with an average of 7. Large over-predictions of pesticide runoff occurred in runoff events later in the season when both loads and concentrations were small. The normalized root mean square error for pesticide runoff concentration predictions varied between 42 and 122%, with an average of 84%. Pesticide runoff loads were predicted with a similar accuracy. These results indicate that the soil-water mixing model used in RZWQM is a robust predictor of pesticide entrainment and runoff.

Modeling hydrology, metribuzin degradation and metribuzin transport in macroporous tilled and no-till silt loam soil using RZWQM.

Due to the complex nature of pesticide transport, process-based models can be difficult to use. For example, pesticide transport can be effected by macropore flow, and can be further complicated by sorption, desorption and degradation occurring at different rates in different soil compartments. We have used the Root Zone Water Quality Model (RZWQM) to investigate these phenomena with field data that included two management conditions (till and no-till) and metribuzin concentrations in percolate, runoff and soil. Metribuzin degradation and transport were simulated using three pesticide sorption models available in RZWQM: (a) instantaneous equilibrium-only (EO); (b) equilibrium-kinetic (EK, includes sites with slow desorption and no degradation); (c) equilibrium-bound (EB, includes irreversibly bound sites with relatively slow degradation). Site-specific RZWQM input included water retention curves from four soil depths, saturated hydraulic conductivity from four soil depths and the metribuzin partition coefficient. The calibrated parameters were macropore radius, surface crust saturated hydraulic conductivity, kinetic parameters, irreversible binding parameters and metribuzin half-life. The results indicate that (1) simulated metribuzin persistence was more accurate using the EK (root mean square error, RMSE = 0.03 kg ha(-1)) and EB (RMSE = 0.03 kg ha(-1)) sorption models compared to the EO (RMSE = 0.08 kg ha(-1)) model because of slowing metribuzin degradation rate with time and (2) simulating macropore flow resulted in prediction of metribuzin transport in percolate over the simulation period within a factor of two of that observed using all three pesticide sorption models. Moreover, little difference in simulated daily transport was observed between the three pesticide sorption models, except that the EB model substantially under-predicted metribuzin transport in runoff and percolate >30 days after application when transported concentrations were relatively low. This suggests that when macropore flow and hydrology are accurately simulated, metribuzin transport in the field may be adequately simulated using a relatively simple, equilibrium-only pesticide model.