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.     

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.     

Sensitivity analyses for four pesticide leaching models

Sensitivity analyses using a one-at-a-time approach were carried out for leaching models which have been widely used for pesticide registration in Europe (PELMO, PRZM, PESTLA and MACRO). Four scenarios were considered for simulation of the leaching of two theoretical pesticides in a sandy loam and a clay loam soil, each with a broad distribution across Europe. Input parameters were varied within bounds reflecting their uncertainty and the influence of these variations on model predictions was investigated for accumulated percolation at 1-m depth and pesticide loading in leachate. Predictions for the base-case scenarios differed between chromatographic models and the preferential flow model MACRO for which large but transient pesticide losses were predicted in the clay loam. Volumes of percolated water predicted by the four models were affected by a small number of input parameters and to a small extent only, suggesting that meteorological variables will be the main drivers of water balance predictions. In contrast to percolation, predictions for pesticide loss were found to be sensitive to a large number of input parameters and to a much greater extent. Parameters which had the largest influence on the prediction of pesticide loss were generally those related to chemical sorption (Freundlich exponent nf and distribution coefficient Kf) and degradation (either degradation rates or DT50, QTEN value). Nevertheless, a significant influence of soil properties (field capacity, bulk density or parameters defining the boundary between flow domains in MACRO) was also noted in at least one scenario for all models. Large sensitivities were reported for all models, especially PELMO and PRZM, and sensitivity was greater where only limited leaching was simulated. Uncertainty should be addressed in risk assessment procedures for crop-protection products.     

Pesticide soil sorption parameters: theory, measurement, uses, limitations and reliability

The soil sorption coefficient Kd and the soil organic carbon sorption coefficient KOC of pesticides are basic parameters used by environmental scientists and regulatory agencies worldwide in describing the environmental fate and behavior of pesticides. They are a measure of the strength of sorption of pesticides to soils and other geosorbent surfaces at the water/solid interface, and are thus directly related to both environmental mobility and persistence. KOC is regarded as a 'universal' parameter related to the hydrophobicity of the pesticide molecule, which applies to a given pesticide in all soils. This assumption is known to be inexact, but it is used in this way in modeling and estimating risk for pesticide leaching and runoff. In this report we examine the theory, uses, measurement or estimation, limitations and reliability of these parameters and provide some 'rules of thumb' for the use of these parameters in describing the behavior and fate of pesticides in the environment, especially in analysis by modeling.     

Effect of pesticide fate parameters and their uncertainty on the selection of 'worst-case' scenarios of pesticide leaching to groundwater

BACKGROUND: For the registration of pesticides in the European Union, model simulations for worst‐case scenarios are used to demonstrate that leaching concentrations to groundwater do not exceed a critical threshold. A worst‐case scenario is a combination of soil and climate properties for which predicted leaching concentrations are higher than a certain percentile of the spatial concentration distribution within a region. The derivation of scenarios is complicated by uncertainty about soil and pesticide fate parameters. As the ranking of climate and soil property combinations according to predicted leaching concentrations is different for different pesticides, the worst‐case scenario for one pesticide may misrepresent the worst case for another pesticide, which leads to ‘scenario uncertainty’. RESULTS: Pesticide fate parameter uncertainty led to higher concentrations in the higher percentiles of spatial concentration distributions, especially for distributions in smaller and more homogeneous regions. The effect of pesticide fate parameter uncertainty on the spatial concentration distribution was small when compared with the uncertainty of local concentration predictions and with the scenario uncertainty. CONCLUSION: Uncertainty in pesticide fate parameters and scenario uncertainty can be accounted for using higher percentiles of spatial concentration distributions and considering a range of pesticides for the scenario selection. Copyright © 2010 Society of Chemical Industry     

Application of the pesticide transport assessment model to a field study in a humic sandy soil in Vredepeel,The Netherlands

The Pesticide Transport Assessment model (PESTRAS) is a process-oriented model to simulate the fate and movement of water and pesticides in a cropped field soil. The model was evaluated using field data for bromide, ethoprophos and bentazone, collected from a field experiment in a humic sandy soil near Vredepeel, the Netherlands. Model predictions were generally within the 95% confidence intervals of the observations when site-specific model inputs were used. If generic parameter values were used, the model predictions sometimes deviated strongly from the observed data. This was especially true for pesticide degradation properties. The bromide simulations showed that preferential flow was not an important process for this field soil. A significant fraction of the applied ethoprophos disappeared by surface volatilization. The downward movement of this pesticide was slightly overestimated, due to not considering sorption kinetics. The depth-dependence of pesticide transformation was atypical: an important fraction of the applied bentazone was transformed under micro-aerobic to anaerobic conditions in the subsoil. © 1998 SCI     

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.     

Sensitivity analysis of a mathematical model for pesticide leaching to groundwater

The sensitivity of pesticide leaching to pesticide/soil properties and to meteorological conditions was assessed by calculations with an existing convection—dispersion model. The model assumes equilibrium sorption (Freundlich equation), first-order transformation kinetics and passive plant uptake. The extent of pesticide leaching was characterized by the percentage of the dose leached below 1 m depth. The calculations were carried out for a humic sand soil cropped with maize and exposed to Dutch weather conditions. In general, the percentage leached was found to be very sensitive to the sorption coefficient, the Freundlich exponent (describing the curvature of the isotherm) and the transformation rate. The percentage leached was moderately sensitive to weather conditions (wet/dry years), long-term sorption equilibration and the relationship between transformation rate and temperature. Sensitivity to the extent of plant uptake was only significant for pesticides with low sorption coefficients. Sensitivity to soil hydraulic properties was small. The effect of application in autumn instead of in spring was found to be very large for non-sorbing pesticides with short half-lives. The sensitivity to spatial variability in sorption coefficient and transformation rate was found to be substantial at low percentages leached.     

Pesticide paddy field model (PADDY) for predicting pesticide concentrations in water and soil in paddy fields

To evaluate the fate of pesticides in paddy fields, the pesticide paddy field model (PADDY) has been developed for predicting pesticide concentrations in paddy fields and the run-off amount of pesticides to the aquatic environment. This model focused particularly on granule formulation because these formulations have been used widely as herbicides on paddy fields in Japan. The behavior of pesticides in paddy fields was assessed by considering the main processes on the basis of a compartment system and the mass-balance equations of pesticides in the compartments were derived from kinetic data. The mathematical model, PADDY, was constructed by numerical solution techniques. A method for measuring the pesticide parameters for this model was also developed. To validate the model, a field experiment was carried out on a paddy field and the concentration changes of pesticides in water and soil were measured. These were in reasonably good agreement with those predicted by PADDY. © 1999 Society of Chemical Industry     

SWAT—A Semi-empirical Model to Predict Concentrations of Pesticides Entering Surface Waters from Agricultural Land

A semi-empirical model called SWAT has been developed to predict concentrations of agriculturally applied pesticides moving to surface waters, an aspect which is not well described by current models for pesticide fate. The model is based upon a direct hydrological link established between soil type and the amount of water moving rapidly to streams in response to rainfall. Attenuation factors describe the decrease in concentrations of pesticide between field application and loss in water moving from the site into surface waters. Evaluation of model predictions against available field data from three sites and four soil types in England shows that SWAT is capable of predicting the transient peak concentrations of a wide range of pesticides during rapid water movement to streams in response to rainfall. Predicted concentrations were too great when rainfall initiated water movement to streams very soon after pesticide application, particularly for the more mobile pesticides, and some predictions for pesticides sorbed very strongly to soil were relatively poor. Almost all of the predicted concentrations were within one order of magnitude of measured values.     

A Field Test of Root Zone Water Quality Model—Pesticide and Bromide Behavior

The Root Zone Water Quality Model (RZWQM) is a process-based model developed recently by USDA–ARS scientists. The model integrates physical, chemical and biological processes to simulate the fate and movement of water and agrochemicals over and through the root zone at a representative point in a field with various management practices. The model was evaluated using field data for the movement of water and bromide, and the transformation and transport of cyanazine and metribuzin in the soil profile. The model reasonably simulated soil water and bromide movement. Pesticide persistence was predicted reasonably well using a two-site sorption model that assumes a rate-limited (i.e. long-term) adsorption–desorption process with the additional assumption of negligible degradation of inter-aggregate adsorbed pesticides.     

Impact of correlation between pesticide parameters on estimates of environmental exposure

Monte Carlo techniques are increasingly used in pesticide exposure modelling to evaluate the uncertainty in predictions arising from uncertainty in input parameters and to estimate the confidence that should be assigned to modelling results. The approach typically involves running a deterministic model repeatedly for a large number of input values sampled from statistical distributions. A key decision in setting up a probabilistic analysis is whether there is correlation between any of the inputs to the analysis. Pesticide properties are often the most sensitive in exposure assessment. Analysis of the literature demonstrated that there are examples of both positive and negative correlation between the sorption and degradation behaviour of a pesticide, but that general trends are not apparent at present. The inclusion of even weak correlation between sorption and degradation was found to greatly influence a probabilistic analysis of leaching through soil. Correlation will reduce the predicted extent of leaching for pesticides, and it is recommended to set the correlation to zero unless the experimental data support an alternative assumption (i.e. where the correlation is statistically significant (P 相似文献   

Factors controlling degradation of pesticides in soil

Rates of pesticide degradation in soil exhibit a high degree of variability, the sources of which are usually unclear. Combining data from incubations performed using a range of soil properties and environmental conditions has resulted in greater understanding of factors controlling such degradation. The herbicides clomazone, flumetsulam, atrazine, and cloransulam-methyl, as well as the former insecticide naphthalene offer examples of degradation kinetics controlled by coupling competing processes which may in turn be regulated separately by environmental conditions and soil properties. The processes of degradation and volatilization appear to compete for clomazone in solution; sorbed clomazone is degraded only after the solution phase is depleted. Similarly, volatilization of naphthalene is enhanced when degradation has been inhibited by high nutrient levels. Degradation of the herbicide flumetsulam has been shown to be regulated by sorption, even though the compound has a relatively low affinity for the soil. The fate pathway for cloransulam-methyl shifts from mineralization to formation of metabolities, bound residues and physically occluded material as temperature increases. Atrazine degradation in soil may be controlled in part by the presence of inorganic nitrogen, as the herbicide appears to be used as a nitrogen source by micro-organisms. New insight gained from measurement of multiple fate processes is demonstrated by these examples.     

Exposure risk assessment and evaluation of the best management practice for controlling pesticide runoff from paddy fields. Part 2: model simulation for the herbicide pretilachlor

BACKGROUND: Monitoring studies revealed high concentrations of pesticides in the drainage canal of paddy fields. It is important to have a way to predict these concentrations in different management scenarios as an assessment tool. A simulation model for predicting the pesticide concentration in a paddy block (PCPF‐B) was evaluated and then used to assess the effect of water management practices for controlling pesticide runoff from paddy fields. RESULTS: The PCPF‐B model achieved an acceptable performance. The model was applied to a constrained probabilistic approach using the Monte Carlo technique to evaluate the best management practices for reducing runoff of pretilachlor into the canal. The probabilistic model predictions using actual data of pesticide use and hydrological data in the canal showed that the water holding period (WHP) and the excess water storage depth (EWSD) effectively reduced the loss and concentration of pretilachlor from paddy fields to the drainage canal. The WHP also reduced the timespan of pesticide exposure in the drainage canal. CONCLUSIONS: It is recommended that: (1) the WHP be applied for as long as possible, but for at least 7 days, depending on the pesticide and field conditions; (2) an EWSD greater than 2 cm be maintained to store substantial rainfall in order to prevent paddy runoff, especially during the WHP. Copyright © 2010 Society of Chemical Industry     

Accounting for uncertainty in pedotransfer functions in vulnerability assessments of pesticide leaching to groundwater

A simulation tool for site-specific vulnerability assessments of pesticide leaching to groundwater was developed, based on the pesticide fate and transport model MACRO, parameterized using pedotransfer functions and reasonable worst-case parameter values. The effects of uncertainty in the pedotransfer functions on simulation results were examined for 48 combinations of soils, pesticides and application timings, by sampling pedotransfer function regression errors and propagating them through the simulation model in a Monte Carlo analysis. An uncertainty factor, f(u), was derived, defined as the ratio between the concentration simulated with no errors, c(sim), and the 80th percentile concentration for the scenario. The pedotransfer function errors caused a large variation in simulation results, with f(u) ranging from 1.14 to 1440, with a median of 2.8. A non-linear relationship was found between f(u) and c(sim), which can be used to account for parameter uncertainty by correcting the simulated concentration, c(sim), to an estimated 80th percentile value. For fine-textured soils, the predictions were most sensitive to errors in the pedotransfer functions for two parameters regulating macropore flow (the saturated matrix hydraulic conductivity, K(b), and the effective diffusion pathlength, d) and two water retention function parameters (van Genuchten's N and alpha parameters). For coarse-textured soils, the model was also sensitive to errors in the exponent in the degradation water response function and the dispersivity, in addition to K(b), but showed little sensitivity to d. To reduce uncertainty in model predictions, improved pedotransfer functions for K(b), d, N and alpha would therefore be most useful.     

Uncalibrated modelling of conservative tracer and pesticide leaching to groundwater: comparison of potential Tier II exposure assessment models

The Root Zone Water Quality Model (RZWQM) and Pesticide Root Zone Model (PRZM) are currently being considered by the Office of Pesticide Programs (OPP) in the United States Environmental Protection Agency (US EPA) for Tier II screening of pesticide leaching to groundwater (November 2005). The objective of the present research was to compare RZWQM and PRZM based on observed conservative tracer and pesticide pore water and soil concentrations collected in two unique groundwater leaching studies in North Carolina and Georgia. These two sites had been used previously by the Federal Insecticide, Fungicide and Rodenticide Act (FIFRA) Environmental Model Validation Task Force (EMVTF) in the validation of PRZM. As in the FIFRA EMVTF PRZM validation, 'cold' modelling using input parameters based on EPA guidelines/databases and 'site-specific' modelling using field-measured soil and hydraulic parameters were performed with a recently released version of RZWQM called RZWQM-NAWQA (National Water Quality Assessment). Model calibration was not performed for either the 'cold' or 'site-specific' modelling. The models were compared based on predicted pore water and soil concentrations of bromide and pesticides throughout the soil profile. Both models tended to predict faster movement through the soil profile than observed. Based on a quantitative normalised objective function (NOF), RZWQM-NAWQA generally outperformed or was equivalent to PRZM in simulating pore water and soil concentrations. Both models were more successful in predicting soil concentrations (i.e. NOF < 1.0 for site-specific data, which satisfies site-specific applicability) than they were at predicting pore water concentrations.     

A Bayesian approach to the analysis of environmental fate and behaviour data for pesticide registration

With the harmonisation of data requirements for pesticide registration under EC Directive 91/414 there is need for progress on the techniques used to analyse such data and so help make consistent the judgements applied by national regulatory authorities. This paper proposes a Bayesian technique for combining data from environmental fate and behaviour studies of pesticides in soil. The method uses expert knowledge, based on degradation and adsorption data, and logistic regression methods to form a prior probability distribution for the probability that a given compound leaches. Results from lysimeter experiments are used update the prior knowledge. Data for the compounds bentazone and triclopyr are used to illustrate the techniques. The advantages of the methodology and its implications for the pesticide registration procedure are discussed in the light of possible advances using modern Bayesian statistical techniques and mathematical models. © 1998 Society of Chemical Industry     

Use of mathematical modeling and its inverse analysis for precise assessment of pesticide dissipation in a paddy environment

The extrapolability of the lysimeter test as a dissipation simulator in an actual paddy field was evaluated using mathematical models and their inverse analyses for predicting pesticide fate and transport processes in paddy test systems. As a source of experimental data, a four-year comparative experiment in lysimeters and paddy fields was conducted using various paddy pesticides. First, the dissipations for various active ingredients in granule pesticides under submerged applications were statistically compared using simple kinetic modeling. Second, the dissipation pathways, unobserved experimental components, and effect of the experimental setting were evaluated using a higher tier mathematical model with a novel inverse analysis protocol. Finally, owing to experimental constraints, the unobtainable parameters were extracted from the laboratory container test before being transferred to compare the outdoor experimental data under different formulation types.     

气候变化对农药应用风险的影响

全球气候变化的影响已成为世界关注的热点。它不仅影响作物产量,还会影响农药应用风险问题,包括农药使用量、农药环境行为、毒性效应等。我国是农药生产和使用大国,农药应用风险问题受到高度关注。本文结合国内外的相关研究分析了气温升高、降雨变化以及极端天气频发对农药应用的直接影响,气候变化所引起的土地利用变化对农药应用的间接影响,为气候变化下农药应用风险评估和控制提供科学依据和参考。