Pesticide Transport Model Research Articles

Quantifying the Uncertainty of a Conceptual Herbicide Transport Model With Time‐Dependent, Stochastic Parameters

AbstractSmall streams in catchments with agricultural land use are at high risk of diffuse pollution by herbicides. Fast transport processes can cause concentration peaks that exceed regulatory requirements. These processes have a high spatio‐temporal variability and data characterizing their occurrence is often sparse. For this reason, such systems show a stochastic behavior at the resolution we observe them (same input and initial conditions lead to different output). Realistic model representations should acknowledge this pronounced apparent intrinsic stochasticity. However, a deterministic description of the physical and chemical processes at the catchment scale is state of the art in research and practice. We explore the potential of stochastic process formulations in combination with the Bayesian learning paradigm to (a) improve the quantification of the uncertainty of conceptual catchment‐scale pesticide transport models and (b) gain new mechanistic insights about the system by interpreting the temporal evolution of the stochastic processes. This is done with the help of a framework for time‐varying stochastic parameters. Thereby, we find that (a) the stochastic process formulation can lead to a more realistic characterization of the uncertainty of internal states and model output compared to the deterministic one, and that (b) the temporal dynamics of parameters resulting from the inference can highlight model deficits (and inspire improvements) such as a better sustained baseflow in dry periods. We also identify two key challenges: numerical difficulties in sampling the posterior and the question of where to introduce and how to constrain the additional degrees of freedom such that they are not misused.

Biodegradation kinetics of dichlorvos and chlorpyrifos by enriched bacterial cultures from an agricultural soil

The study focuses on the biodegradation kinetics of organophosphate pesticides (OPs), chlorpyrifos and dichlorvos by enriched cultures and its application in pesticide transport models. Pseudomonas aeruginosa and Taonella mepensis were the species identified in dichlorvos enriched culture (DEC) while Pseudomonas aeruginosa and Methylobacterium zatmanii were present in chlorpyrifos enriched culture (CPEC). DEC readily degraded dichlorvos as the sole carbon source at higher concentrations up to 1000 mg/L while CPEC rapidly degraded chlorpyrifos up to 100 mg/L. On addition of 1 g/L C of dextrose, dichlorvos degradation efficiency significantly increased only at higher pesticide concentrations while there was no effect on chlorpyrifos degradation. Cross-feed and mixed-feed studies highlighted that, CPEC degraded dichlorvos as a sole substrate and a mixture of both the pesticides effectively when compared to DEC. Edward inhibition and Haldane inhibition models satisfactorily simulated the biodegradation kinetics of dichlorvos and chlorpyrifos by DEC and CPEC respectively. The biokinetic parameters; maximum specific growth rate (µmax), half saturation constant (KC), yield coefficient (Y) and inhibition concentration (Ki) for the selected pesticides were thus estimated from the best fit biokinetic models. Further, batch determined biokinetic parameters were successfully applied to pesticide transport model and used to simulate breakthrough curves (BTCs) from flow-through pesticide soil column studies. The results indicated that the enriched microbes are promising candidates for insitu bioremediation of contaminated waters and soils. In addition, the estimated biokinetic constants can be used to assess the biodegradation capabilities of the enriched cultures and act as input parameters for transport models.

A health-based regulatory chain framework to evaluate international pesticide groundwater regulations integrating soil and drinking water standards

Pesticide residues in groundwater, mainly transported from contaminated soil, may threaten drinking water sources and cause adverse health effects. Therefore, pesticide groundwater standards were implemented by international environmental agencies to ensure the quality of groundwater, which serves as the direct drinking water source in many countries. However, regulatory inconsistencies are always found among groundwater, soil, drinking water, and even health standards due to the lack of communication among the regulatory processes. This study first developed a health-based regulatory chain framework to analyze pesticide groundwater regulations integrating soil, drinking water, and health regulations. Six regulatory indexes associated with probabilistic risk assessments and pesticide transport modeling were constructed to evaluate the performance of pesticide groundwater regulations identified from 56 countries. Worldwide pesticide groundwater regulations were analyzed by quantifying the impact on the downstream (exposure pathways in general) pesticide drinking water standards and human health and the influence from upstream (environmental pathways in general) soil regulations. The results indicated that in general, worldwide pesticide soil regulations do not encompass a sufficient number of pesticides or provide appropriate standard values to be compatible with groundwater regulations. The computed indexes between pesticide groundwater and drinking water regulations indicated more positive results than soil regulations because most European nations have groundwater regulations that are compatible with those of drinking water. However, most pesticide groundwater regulations could not protect human health according to the health-based indexes. Hopefully, the regulatory framework developed in this study will help environmental agencies comprehensively evaluate and establish pesticide groundwater regulations.

A meta-analysis of pesticide loss in runoff under conventional tillage and no-till management.

Global agricultural intensification has led to increased pesticide use (37-fold from 1960 to 2005) and soil erosion (14% since 2000). Conservation tillage, including no-till (NT), has been proposed as an alternative to conventional plow till (PT) to mitigate soil erosion, but past studies have reported mixed results on the effect of conservation tillage on pesticide loss. To explore the underlying factors of these differences, a meta-analysis was conducted using published data on pesticide concentration and load in agricultural runoff from NT and PT fields. Peer-reviewed articles (1985-2016) were compiled to build a database for analysis. Contrary to expectations, results showed greater concentration of atrazine, cyanazine, dicamba, and simazine in runoff from NT than PT fields. Further, we observed greater load of dicamba and metribuzin, but reduced load of alachlor from NT fields. Overall, the concentration and the load of pesticides were greater in runoff from NT fields, especially pesticides with high solubility and low affinity for solids. Thus, NT farming affects soil properties that control pesticide retention and interactions with soils, and ultimately their mobility in the environment. Future research is needed for a more complete understanding of pesticide-soil interactions in NT systems. This research could inform the selection of pesticides by farmers and improve the predictive power of pesticide transport models.

Assessing BMP Effectiveness and Guiding BMP Planning Using Process‐Based Modeling

AbstractThere is an increasing need for improved process‐based planning tools to assist watershed managers in the selection and placement of effective best management practices (BMPs). In this article, we present an approach, based on the Water Erosion Prediction Project model and a pesticide transport model, to identify dominant hydrologic flow paths and critical source areas for a variety of pollutant types. We use this approach to compare the relative impacts of BMPs on hydrology, erosion, sediment, and pollutant delivery within different landscapes. Specifically, we focus on using this approach to understand what factors promoted and/or hindered BMP effectiveness at three Conservation Effects Assessment Project watersheds: Paradise Creek Watershed in Idaho, Walnut Creek Watershed in Iowa, and Goodwater Creek Experimental Watershed in Missouri. These watersheds were first broken down into unique land types based on soil and topographic characteristics. We used the model to assess BMP effectiveness in each of these land types. This simple process‐based modeling approach provided valuable insights that are not generally available to planners when selecting and locating BMPs and helped explain fundamental reasons why long‐term improvement in water quality of these three watersheds has yet to be completely realized.

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

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. 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. 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.

Assessment of herbicide transport and distribution in subsurface environments of an orange field.

The demand for assessing both the variability of risk areas and the intensity of pollutant load rates on pesticide transferring to waters in China has been increasingly vigorous in recent decades. Therefore, to explore the transport of linuron with rainfall and irrigation in canopy-soil systems, an integrated pesticide transport modeling system has been selected and verified for simulating the three-phase linuron environmental fate in an orange field of the Three Gorges Reservoir (TGR) area. Results demonstrate that spatio-temporal distributions of linuron in surface soil primarily depend on its properties, rainfall, irrigation, and its applications; the peak levels of linuron in subsurface and deep soil are closely related to the cumulative and delayed effects. The findings may be used for policy supporting of soil-water-crop-pesticide management in an agricultural field of the TGR area.

A coupled stochastic/deterministic model to estimate the evolution of the risk of water contamination by pesticides across Canada

Periodic assessments of the risk of water contamination by pesticides help decision makers improve the sustainability of agricultural management practices. In Canada, when evaluating the risk of water contamination by pesticides, 2 main constraints arise. First, because the area of interest is large, a pesticide transport model with low computational running time is mandatory. Second, some relevant input data for simulations are not known, and most are known only at coarse scale. This study aims to develop a robust methodology to estimate the evolution of the risk of water contamination by pesticides across Canada. To circumvent the 2 aforementioned issues, we constructed a stochastic model and coupled it to the 1-dimensional pesticide fate model Pesticide Root Zone Model (PRZM). To account for input data uncertainty, the stochastic model uses a Monte Carlo approach to generate several pesticide application scenarios and to randomly select PRZM parameter values. One hundred different scenarios were simulated for each of over 2000 regions (Soil Landscapes of Canada [SLC] polygons) for the years 1981 and 2006. Overall, the results indicated that in those regions in which the risk increased from 1981 to 2006, the increase in risk was mainly attributable to the increased area treated by pesticides or an increase in the number of days with runoff. More specifically, this work identifies the areas at higher risk, where further analyses with finer-scale input data should be performed. The model is specific for Canadian data, but the framework could be adapted for other large countries.

Modeling the impact of nitrogen fertilizer application and tile drain configuration on nitrate leaching using SWAT

Recently, the Soil and Water Assessment Tool (SWAT) was revised to improve the partitioning of runoff and tile drainage in poorly drained soils by modifying the algorithm that computes the soil moisture retention parameter. In this study, the Revised SWAT model was used to evaluate the sensitivity and long-term effects of different nitrogen (N) application rates and tile drain spacing (SDRAIN) and depths (DDRAIN) on nitrate-nitrogen (NO3-N) losses through tile drains. Monitoring data for the 1983–1996 period measured on three experimental plots on a poorly drained Webster clay loam soil (fine-loamy, mixed, superactive, mesic Typic Endoaquoll) in southern Minnesota was used. Sensitivity analysis covered the 1983–1996 period and long-term simulations were made for the 1915–1996 period. Sensitivity analysis showed a decrease in tile flow as DDRAIN decreased and/or SDRAIN increased. The predicted NO3-N losses in tile drain decreased by 16% (from 33.8 to 28.4kgha−1) and 14% (from 34.0 to 29.4kgha−1) when SDRAIN was increased by 122% (from 27 to 60m) and 40% (from 1.5 to 0.9m), respectively. However, NO3-N losses were decreased by 67% (from 33.8 to 11.1kgha−1) when N application rate was decreased by 50% (from 200 to 100kgha−1). Long-term simulations results indicated that much greater reductions in NO3-N losses can be achieved with reduction in the N application rates than with changing the tile drain spacing and depth. Reductions in NO3-N losses were consistent with the results reported using the Agricultural Drainage and Pesticide Transport (ADAPT) model, which was developed specifically for understanding effects of tile drainage on water quality in the Upper Midwest U.S. Overall, results from sensitivity analysis and long term simulation indicated that Revised SWAT can be used to adequately evaluate the effects of tile drain configurations on drainage and associated NO3-N losses.

Comparison of the performances of DRAINMOD-NII and ADAPT models in simulating nitrate losses from subsurface drainage systems

Adequate knowledge on the movement of nitrate-nitrogen (NO3-N) under different subsurface (tile) drain configurations and management practices in the U.S. Midwest is essential for developing remedial measures for reducing hypoxic conditions in the Gulf of Mexico. In this study, DRAINMOD-NII, a daily time-step soil carbon (C) and N model, was calibrated and validated for subsurface drainage and associated NO3-N losses, and crop yield. Long term (1983–1996) monitoring data measured on three experimental plots under continuous corn (Zea mays L.) with conventional tillage practice at the University of Minnesota's Southern Research and Outreach Center near Waseca, southern Minnesota was used for this purpose. Nash-Sutcliffe efficiency (NSE), Percent Error (PE) and Index of agreement (d) were used for assessing the model performance. DRAINMOD-NII predicted monthly subsurface drainage matched well with measured data during calibration (NSE=0.81, PE=−7.8% and d=0.94) and validation (NSE=0.67, PE=−0.7% and d=0.88) periods. Performance of DRAINMOD-NII for predicting monthly NO3-N losses in subsurface drainage was also good for both calibration (NSE=0.64, PE=0.8%, and d=0.85) and validation (NSE=0.62, PE=−5.3%, and d=0.83) periods. DRAINMOD-NII predicted average (1983–1992) annual corn relative yield (93%), a ratio of crop yield in a year to the long-term average crop yield, was close to the observed relative yield (92.5%). DRAINMOD-NII simulation results were also compared and contrasted with those obtained by the Agricultural Drainage and Pesticide Transport (ADAPT) model with the same dataset. Both models performed equally well in predicting monthly subsurface drainage. However, DRAINMOD-NII performed slightly better in predicting monthly NO3-N losses and annual N budget, in addition to showing potential to simulate the effects of excess and deficit water stresses on crop yield. Studies comparing performances of different drainage models in the U.S. Midwest are useful to select an appropriate model for devising various strategies for reducing NO3-N losses from subsurface drainage systems, and thereby minimizing hypoxic conditions in the Gulf of Mexico.

ADAPT: Model Use, Calibration, and Validation

This article presents an overview of the Agricultural Drainage and Pesticide Transport (ADAPT) model and a case study to illustrate the calibration and validation steps for predicting subsurface drainage and nitrate-N losses from an agricultural system. The ADAPT model is a daily time step, field-scale water table management model that was developed as an extension of the GLEAMS model. The GLEAMS algorithms were augmented with algorithms for subsurface drainage, subsurface irrigation, deep seepage, and related water quality processes. Recently, a frost depth algorithm was incorporated to enhance the models capability to predict flow during spring and fall months. In addition to the normal GLEAMS output, ADAPT gives estimates of pesticides and nutrients in drainage. The model has four components: hydrology, erosion, nutrient transport, and pesticide transport. Predictions of surface runoff and subsurface drainage by ADAPT are very sensitive to hydrology input parameters, such as NRCS curve number, hydraulic conductivity, depth of the impeding layer, and hydraulic conductivity of the impeding layer. In the erosion component, slope, hydraulic length, and crop management are the most sensitive factors. Nutrients generally follow the trends in surface runoff and subsurface drainage. In addition, nitrogen and phosphorus concentrations in soil horizons are sensitive to nutrient losses. Recently, the ADAPT model was further calibrated and validated in southern Minnesota to evaluate impacts of subsurface drain spacing and depth, rate and timing of nitrogen application, and precipitation changes on water quality. ADAPT is written in FORTRAN, and the source code is available to interested model users. Considering the limited technical support and text editor-based input files, development of a user-friendly interface to create input files would greatly enhance ADAPTs acceptability by users involved in modeling agricultural systems equipped with subsurface drains.

Improved Box Model for Simulating Pesticide Transport in the Vadose Zone with Dispersive Flux through the Boundary Layer

AbstractA box-type transport model can be a useful tool for screening-level, long-term predictions of contamination and the relevant environmental assessment, especially when data are scarce and quick decisions are needed. In most box-type transport models, only advective flux is simulated to account for the interaction between boxes. In reality, however, significant mass transfer may also occur through the boundary between two boxes as a result of dispersion. For volatile contaminants (e.g., pesticides), the mass transfer through the boundary may involve both dissolved and vapor phases. In this study, an improved box-type analytical pesticide transport model with dispersive flux through the boundary layer (APTM-DF) was developed for simulating fate and transport of three-phase pesticides in the vadose zone, which was further divided into the surface zone, plant root zone, and deep vadose zone. The model also simulated pesticide leaching, degradation, volatilization, sorption, partition between dissolved ...

Field leaching of pesticides at five test sites in Hawaii: modeling flow and transport

Physically based tier-II models may serve as possible alternatives to expensive field and laboratory leaching experiments required for pesticide approval and registration. The objective of this study was to predict pesticide fate and transport at five different sites in Hawaii using data from an earlier field leaching experiment and a one-dimensional tier-II model. As the predicted concentration profiles of pesticides did not provide close agreement with data, inverse modeling was used to obtain adequate reactive transport parameters. The estimated transport parameters of pesticides were also utilized in a tier-I model, which is currently used by the state authorities to evaluate the relative leaching potential. Water flow in soil profiles was simulated by the tier-II model with acceptable accuracy at all experimental sites. The observed concentration profiles and center of mass depths predicted by the tier-II simulations based on optimized transport parameters provided better agreements than did the non-optimized parameters. With optimized parameters, the tier-I model also delivered results consistent with observed pesticide center of mass depths. Tier-II numerical modeling helped to identify relevant transport processes in field leaching of pesticides. The process-based modeling of water flow and pesticide transport, coupled with the inverse procedure, can contribute significantly to the evaluation of chemical leaching in Hawaii soils.

Simulating concentration of bensulphuron‐methyl in a drainage canal of a paddy block using a rice pesticide model

A pesticide fate and transport model (PCPF‐B) was developed to predict the runoff of pesticides from paddy plots to a drainage canal in a paddy block based on the plot scale model (PCPF‐1). The block‐scale model now comprises three modules: (1) a module for pesticide application, (2) a module for pesticide behaviour in paddy fields, and (3) a module for pesticide concentration in the drainage canal. The PCPF‐B model was first evaluated using published data in a single plot and then was applied to predict the concentration of bensulphuron‐methyl in one paddy block in the Sakura river basin, Ibaraki, Japan, where a detailed field survey was conducted. The PCPF‐B model simulated well the concentration of bensulphuron‐methyl in individual paddy plots. It also reflected the runoff pattern of bensulphuron‐methyl at the block outlet, although overestimation of bensulphuron‐methyl concentrations occurred due to uncertainty in water balance estimation. A sensitivity analysis showed that the soil adsorption coefficient of the herbicide had the greatest influence on the concentrations and cumulative loss of bensulphuron‐methyl to the drainage canal.

Precipitation Changes Impact Stream Discharge, Nitrate–Nitrogen Load More Than Agricultural Management Changes

Nitrate-N losses to surface waters in the Upper Midwest of the Untied States have increased in recent decades, contributing to hypoxia in the Gulf of Mexico. This paper investigates whether increasing nitrate-N export from cropland in the Upper Midwest since the late 1960s results from changes in land use or climate. The Agricultural Drainage and Pesticide Transport (ADAPT) Model simulated current and historical agricultural systems under past and recent wet climate for Seven Mile Creek in Minnesota. Simulations were run with management and climate for three distinctly different periods--namely, 1965 to 1969, 1976 to 1980, and 1999 to 2003 (wettest period). Results showed discharge and nitrate-N losses responded more to changes in climate than management. The wetter period (1999-2003) caused a simulated 70% increase in discharge under 1960s-era management compared with that period's observed climate and a simulated 51% increase in discharge under 1970s-era management compared with the 1976 to 1980 climate. The recent, wetter climate also produced a 62% increase in nitrate-N losses for 1960s-era management compared with the actual climate and a 137% increase in nitrate-N losses for 1978 management conditions compared with actual 1970s climate. Had recent climate been in place and stable since 1965, agricultural changes would have decreased discharge by 6.4% through the late 1970s and then by another 21.1% under modern management but would have increased nitrate-N losses by 184% through the late 1970s and then decreased nitrate-N losses by 13.5% between 1978 and 2001. Management changes that were important drivers included increasing N-fertilizer rates, increases in corn acreage, and increases in crop yield. But the most important factor driving increased nitrate-N losses from agriculture since the 1970s was an increasingly wetter climate.

Application of pesticide transport model for simulating diazinon runoff in California’s central valley

Dormant spray application of pesticides to almond and other stone fruit orchards is the main source of diazinon during the winter in California’s central valley. Understanding the pesticide transport and the tradeoffs associated with the various management practices is greatly facilitated by the use of physically-based contaminant transport models. In this study, performance of Joyce’s et al. (2008) pesticide transport model was evaluated using experimental data collected from two ground treatments such as resident vegetation and bare soil. The model simulation results obtained in calibration and validation process were analyzed for pesticide concentration and total load. The pesticide transport model accurately predicted the pesticide concentrations and total load in the runoff from bare field and was capable of simulating chemical responses to rainfall-runoff events. In case of resident vegetation, the model results exhibited a larger range of variation than was observed in the bare soil simulations due to increased model parameterization with the addition of foliage and thatch compartments. Furthermore, the model was applied to study the effect of runoff lag time, extent of crop cover, organic content of soil and post-application irrigation on the pesticide peak concentration and total load. Based on the model results, recommendations were suggested to growers prior to implementing certain management decisions to mitigate diazinon transport in the orchard’s spray runoff.

Monod kinetics rather than a first-order degradation model explains atrazine fate in soil mini-columns: Implications for pesticide fate modelling

Pesticide transport models commonly assume first-order pesticide degradation kinetics for describing reactive transport in soil. This assumption was assessed in mini-column studies with associated batch degradation tests. Soil mini-columns were irrigated with atrazine in two intermittent steps of about 30 days separated by 161 days application of artificial rain water. Atrazine concentration in the effluent peaked to that of the influent concentration after initial break-through but sharply decreased while influx was sustained, suggesting a degradation lag phase. The same pattern was displayed in the second step but peak height and percentage of atrazine recovered in the effluent were lower. A Monod model with biomass decay was successfully calibrated to this data. The model was successfully evaluated against batch degradation data and mini-column experiments at lower flow rate. The study suggested that first-order degradation models may underestimate risk of pesticide leaching if the pesticide degradation potential needs amplification during degradation.

Modeling Impacts of Tile Drain Spacing and Depth on Nitrate-Nitrogen Losses

Subsurface tile drainage is a major contributor of NO3–N from cropland in the Upper Midwest to the hypoxic zone in the Gulf of Mexico. Strategies to reduce NO3–N loadings to the Gulf of Mexico require better understanding of the effects of tile spacing and depth on subsurface tile drainage and NO3–N losses from subsurface tile drained fields. This study evaluated the sensitivity of NO3–N losses to changes in the spacing and depth of subsurface tile drainage systems. For this purpose, the Agricultural Drainage and Pesticide Transport (ADAPT) model was calibrated and validated using monthly subsurface tile drainage and NO3–N losses measured in tile drains during 1999 to 2003 from two commercial fields (west and east) in south-central Minnesota. For the calibration period, there was good agreement between observed and predicted subsurface tile drainage and NO3–N losses, with Nash–Sutcliffe modeling efficiencies of 0.75 and 0.56, respectively. Better agreements were observed for the validation periods. The calibrated model was used to evaluate the effects of tile drain spacing and depth with a 50-yr record (1954–2003) of daily precipitation. Simulation results indicated that reductions in NO3–N losses are possible by decreasing the depth or increasing the spacing of tile drains. For instance, for a tile drain spacing of 40 m, reducing the drain depth from 1.5 to 0.9 m reduced NO3–N losses by 31% (but reduced crop yield by 60%), while for a tile drain depth of 1.5 m, increasing the tile drain spacing from 27 to 40 m reduced NO3–N losses by 50% (while reducing crop yield by 7%). Increased tile drain spacing or decreased tile drain depth could be a potential remedy for excess NO3–N loadings entering the Gulf of Mexico.

Numerical Simulation of Pesticide Transport and Fate for Water Management in the Fucino Plain, Italy

A three-phase pesticide transport model is used to verify by numerical simulation, the influence of different parameters on infiltration through soil and/or surface runoff processes. Simulations are performed for a typical sandy loam potato field of Italy’s Fucino Plain, to explain the occurrence of measured concentrations of pesticides (mainly Linuron) in both surface waters and groundwater. Simulations take into account agricultural practices, climatic conditions, and soil characteristics. Results focus on the role of rainfall events and irrigation, of related infiltration amount and distribution, and of root zone thickness in influencing pesticide fate and its possible concentration increase through the years. Modeling results positively fit with the background knowledge of the Plain hydrology, showing the prevalence of surface transport and a scarce possibility for pesticides to reach groundwater in an average rainfall/irrigation scenario. Meanwhile, specific water management strategies are suggested to limit the occurrence of local groundwater pollution, related to high aquifer vulnerability zones, controlling inappropriate irrigation and pesticide application.

Spatially distributed pesticide exposure assessment in the Central Valley, California, USA

Field runoff is an important transport mechanism by which pesticides move into the hydrologic environment of intensive agricultural regions such as California's Central Valley. This study presents a spatially explicit modeling approach to extend Pesticide Root Zone Model (PRZM), a field-scale pesticide transport model, into basin level. The approach was applied to simulate chlorpyrifos use in the Central Valley during 2003–2007. The average value of loading as percent of use (LAPU) is 0.031%. Results of this study provide strong evidence that surface runoff generation and pesticide application timing are the two influencing factors on the spatial and temporal variability of chlorpyrifos sources from agricultural fields. This is one of the first studies in coupling GIS and field-scale models and providing simulations for the dynamics of pesticides over an agriculturally dominated landscape. The demonstrated modeling approach may be useful for implementations of best management practice (BMP) and total maximum daily load (TMDL).