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.     

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.     

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.     

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.     

Herbicide leaching as affected by macropore flow and within-storm rainfall intensity variation: a RZWQM simulation

Within-event variability in rainfall intensity may affect pesticide leaching rates in soil, but most laboratory studies of pesticide leaching use a rainfall simulator operating at constant rainfall intensity, or cover the soil with ponded water. This is especially true in experiments where macropores are present--macroporous soils present experimental complexities enough without the added complexity of variable rainfall intensity. One way to get around this difficulty is to use a suitable pesticide transport model, calibrate it to describe accurately a fixed-intensity experiment, and then explore the affects of within-event rainfall intensity variation on pesticide leaching through macropores. We used the Root Zone Water Quality Model (RZWQM) to investigate the effect of variable rainfall intensity on alachlor and atrazine transport through macropores. Data were used from an experiment in which atrazine and alachlor were surface-applied to 30 x 30 x 30 cm undisturbed blocks of two macroporous silt loam soils from glacial till regions. One hour later the blocks were subjected to 30-mm simulated rain with constant intensity for 0.5 h. Percolate was collected and analyzed from 64 square cells at the base of the blocks. RZWQM was calibrated to describe accurately the atrazine and alachlor leaching data, and then a median Mid-west variable-intensity storm, in which the initial intensity was high, was simulated. The variable-intensity storm more than quadrupled alachlor losses and almost doubled atrazine losses in one soil over the constant-intensity storm of the same total depth. Also rainfall intensity may affect percolate-producing macroporosity and consequently pesticide transport through macropores. For example, under variable rainfall intensity RZWQM predicted the alachlor concentration to be 2.7 microg ml(-1) with an effective macroporosity of 2.2 E(-4) cm(3) cm(-3) and 1.4 microg ml(-1) with an effective macroporosity of 4.6 E(-4) cm(3) cm(-3). Percolate-producing macroporosity and herbicide leaching under different rainfall intensity patterns, however, are not well understood. Clearly, further investigation of rainfall intensity variation on pesticide leaching through macropores is needed.     

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.     

植被过滤带阻控除草剂污染的研究与应用进展

除草剂等农药在农业生产上作出了极大的贡献,但未被利用的农药因雨水和灌溉随地表径流进入水体,破坏了水生态系统,对人类健康构成威胁。本文对植被过滤带阻控除草剂污染的作用进行了阐述,综述了植被过滤带阻控除草剂污染的机理及影响其功能的主要因素,指出目前研究的局限和应用中应该考虑的问题,并对下一步研究方向进行展望。     

农田土壤中的农药残留对农产品安全的影响研究进展

农田土壤中的农药污染是威胁农产品安全的重要因素之一。在病虫草害的化学防治过程中,田间施用的农药最终会进入土壤环境并在其中转化积累,导致农田土壤环境污染。农作物能够通过根部吸收将土壤中的农药转运至植物体的各个器官和组织中,造成农产品中的农药残留,影响农产品质量和安全。本文系统地综述了土壤中农药残留进入植物体的途径,指出了可能影响土壤中农药进入植物体的内外因素,着重强调了其对农产品安全存在的潜在威胁,并针对农田土壤污染的治理和此类食品安全问题的防范提出了合理的建议。最后展望了未来研究应该关注的问题和方向。     

农药对健康及环境影响药迹模型的构建与应用

为了更好地评估农药使用对人类健康和生态环境的综合影响,利用可方便获取的农药有效成分特性数据资源,在综合考虑健康及环境影响评估的定量化、参数的代表性、测试方法的标准化、现有可获取数据的权威性和完整性,以及评估核算过程的便利性等要求基础上,构建了药迹模型及其指标体系。采用所建立的药迹模型可计算得到表征各种农药对健康和环境影响力的药迹指数,再结合农药用量数据,即可对不同时空尺度下农药使用产生的健康和环境影响进行定量化的核算和比较。通过该模型对70种代表性农药进行核算,结果表明,药迹指数为0.002~111.348 PTU/kg,单次用量药迹为0.001~41.412 PTU/hm2,不同农药品种间差距很大。该药迹模型具有广泛的应用前景,如药迹指数可用于农药危害性分类,药迹核算可用于农药减施成效评估,药迹限量可用于农药施用限量标准制定等。     

简论我国施药技术的发展趋势

环境安全和食品安全已引起世界各国的高度重视,我国政府在全面建设小康社会的同时,已把治理农业环 境、发展可持续农业列入重要的议事日程。本文试图从施药技术的3个方面--药械、农药、施药方法来探讨我 国施药技术的发展趋势,并提出了作者的一些观点,力图为我国施药技术的发展提供一些参考依据。     

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。     

Identification of key climatic factors regulating the transport of pesticides in leaching and to tile drains

BACKGROUND: Key climatic factors influencing the transport of pesticides to drains and to depth were identified. Climatic characteristics such as the timing of rainfall in relation to pesticide application may be more critical than average annual temperature and rainfall. The fate of three pesticides was simulated in nine contrasting soil types for two seasons, five application dates and six synthetic weather data series using the MACRO model, and predicted cumulative pesticide loads were analysed using statistical methods. RESULTS: Classification trees and Pearson correlations indicated that simulated losses in excess of 75th percentile values (0.046 mg m(-2) for leaching, 0.042 mg m(-2) for drainage) generally occurred with large rainfall events following autumn application on clay soils, for both leaching and drainage scenarios. The amount and timing of winter rainfall were important factors, whatever the application period, and these interacted strongly with soil texture and pesticide mobility and persistence. Winter rainfall primarily influenced losses of less mobile and more persistent compounds, while short-term rainfall and temperature controlled leaching of the more mobile pesticides. CONCLUSIONS: Numerous climatic characteristics influenced pesticide loss, including the amount of precipitation as well as the timing of rainfall and extreme events in relation to application date. Information regarding the relative influence of the climatic characteristics evaluated here can support the development of a climatic zonation for European-scale risk assessment for pesticide fate.     

A screening tool for vulnerability assessment of pesticide leaching to groundwater for the islands of Hawaii, USA

This paper describes an updated version of a screening tool for groundwater vulnerability assessment to evaluate pesticide leaching to groundwater, based on a revised version of the attenuation factor. The tool has been implemented in a geographical information system (GIS) covering the major islands of the state of Hawaii, USA. The Hawaii Department of Agriculture currently uses the tool in their pesticide evaluation process as a first-tier screening tool. The basic soil properties and pesticide properties necessary to compute the index, and estimates of their uncertainty, are included in the GIS. Uncertainties in soil and pesticide properties are accounted for using first-order uncertainty analysis. Classifications of pesticides as 'likely', 'uncertain' or 'unlikely' to leach are made on the basis of the uncertainty and a comparison of the revised attenuation factor with values and uncertainties of two reference chemicals. The reference chemicals represent what are considered to be a 'leachable' and a 'non-leachable' pesticide under Hawaii conditions. It is concluded that the tool is suitable for screening new and already used pesticides for the islands of Hawaii. However, the tool is associated with uncertainties that are not accounted for, so a conservative approach with respect to interpretation of the results and selection of pesticide parameters used in the tool is recommended.     

高效植保机械与精准施药技术进展

农药、植保机械（又称药械）与施药技术是影响农药喷施效果、防治效果和农药利用效率的3个同等重要的因素。药械与施药技术随着农药学科的发展而发展，整体来讲药械发展经历了人背机器、机器背人、人机分离、喷雾机器人4个典型时代。我国现有耕种面积大小不同的各类农场3.2亿个，总耕地面积1.2亿hm2，年均植保防治作业面积4亿～5亿hm2次，至今我国连续10多年的粮食连年增产，新型植保装备与高效施药技术的研发应用推广功不可没。与20世纪相比，在新千年前20年，国内外药械和施药技术与高速发展的绿色农药生产相互适应、相互促进，进入了快速发展的轨道，至2020年我国植保机械社会保有量突破2.5亿台，自走式喷杆喷雾机260多万台，各类果园喷雾机150多万台，植保无人机10多万台；新型植保装备与高效施药技术为农药减量提供了手段，助推了农药利用率的提高和农药的减量计划的实施。2020年全国水稻、玉米、小麦三大粮食作物的农药利用率达到40.6%，较2015年提高了4个百分点，新型植保装备与高效施药技术为解决诸如农药有效利用率低、操作人员中毒、农药残留超标和环境污染等问题做出了突出贡献。特别是在我国自走式喷杆喷雾机、...     

微生物农药在俄罗斯的应用进展

微生物农药因其副作用小、对环境兼容性好而日益成为全球农药发展的一种趋势和方向。本文以细菌杀虫剂、真菌杀虫剂、病毒杀虫剂、微生物除草剂、植物生长调节剂、农用抗生素作为微生物农药的代表,介绍了微生物农药的研究、应用现状及其在俄罗斯的研究进展,并对我国与俄罗斯在微生物农药领域的合作进行了展望。     

蔬菜安全生产过程中农药污染危害与控制途径分析

蔬菜产品从"田间到餐桌"需要经过一个较长的链条,其中蔬菜的生产在这个链条中占有重要地位。蔬菜安全生产是社会和谐发展的客观要求,是经济效益持续稳定的根本保障,生态健康也对蔬菜安全生产中农药的科学使用提出了更高要求。蔬菜生产过程中的污染包括产地环境污染和农业投入品污染,其中又以作为重要的农业投入品的农药引起的污染为主。农药是蔬菜安全生产中减少病虫草等危害损失、保障蔬菜产量的重要核心因素,但如果农药使用不科学就会污染环境、破坏生态平衡、造成蔬菜产品农药残留超标、作物药害或导致人们中毒,直接危害人类健康。国外为推行农产品质量安全从"田间到餐桌"全过程控制,随之相继出现了如良好农业规范(GAP)、良好生产规范(GMP)、危害分析和关键点控制体系(HACCP)等生产管理和控制体系。我国对农药污染控制技术手段比较薄弱,为缓解我国蔬菜生产、病虫害防治和农药污染之间的矛盾,必须对农药的使用进行全程调控。     

Dynamic plant uptake model applied for drip irrigation of an insecticide to pepper fruit plants

BACKGROUND: Drip application of insecticides is an effective way to deliver the chemical to the plant that avoids off‐site movement via spray drift and minimizes applicator exposure. The aim of this paper is to present a cascade model for the uptake of pesticide into plants following drip irrigation, its application for a soil‐applied insecticide and a sensitivity analysis of the model parameters. RESULTS: The model predicted the measured increase and decline of residues following two soil applications of an insecticide to peppers, with an absolute error between model and measurement ranging from 0.002 to 0.034 mg kg fw^?1. Maximum measured concentrations in pepper fruit were approximately 0.22 mg kg fw^?1. Temperature was the most sensitive component for predicting the peak and final concentration in pepper fruit, through its influence on soil and plant degradation rates. CONCLUSION: Repeated simulations of pulse inputs with the cascade model adequately describe soil pesticide applications to an actual cropped system and reasonably mimic it. The model has the potential to be used for the optimization of practical features, such as application rates and waiting times between applications and before harvest, through the integrated accounting of soil, plant and environmental influences. Copyright © 2011 Society of Chemical Industry     

Characterization of Spatial Variability Structure in Three Separate Field Trials on Pesticide Dissipation

Experiments were carried out on three Italian farms to assess the degree of spatial variation of pesticide field concentration during treatment and during dissipation trials. Test pesticides were chloridazon and metamitron (both sugar-beet herbicides) applied as a tank mix. The classical statistical technique and geostatistics were used to summarize and evaluate variable spatial data. The results show that the actual values of pesticide concentration for application rate and initial concentration in all three areas are lower than expected, thus indicating that under field conditions only a part of the pesticide reaches the soil during the distribution. The actual values for both herbicides in all three areas expressed as percentage of expected values ranged from 44·1% to 64·2% for application rate and from 40·5% to 99·5% for initial concentration. The coefficient of variation was similar for both pesticides and ranged from 23·8 to 74·1 for application rate, 24·1 and 58·8 for initial concentration and 11·1 and 110·0 for dissipation half-lives. The high variability in application rate and initial concentration could be ascribed to an uneven herbicide distribution, and in dissipation studies to variation in half-lives for the rate of herbicide loss from soil in different parts of the field. Geostatistic analysis indicated little spatial correlation, probably because the sampling sites were widely spaced on the field. In all cases, the data were not sufficient to estimate the range of influence, probably because of the size of the experimental fields and the sampling strategy. © 1997 SCI.     

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