Comparison of predicted pesticide concentrations in groundwater from <scp>SCI‐GROW</scp> and <scp>PRZM‐GW</scp> models with historical monitoring data

Estes, Tammara L.; Pai, Naresh; Winchell, Michael

doi:10.1002/ps.4097

Cited by 11 publications

(3 citation statements)

References 3 publications

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“…Similarly, Charnay et al [18] concluded that pesticides degradation rates vary spatially possibly due to the dynamics of peculiar biodegraders. Such uncertainty can therefore be relevant in environmental risk assessment studies, where the practice is to average the available information and predict one time-series of environmental concentrations [26,30]. The reduction of uncertainty in pesticide biodegradation kinetic values might be achieved through studies aiming at better understanding what are the factors the favor or limit microbial communities in removing pesticides at the global scale; at the European scale, a similar investigation was carried out by Pierre et al, [74] in the context of chloroethene-contaminated aquifers.…”

Section: Discussionmentioning

confidence: 99%

Influential sources of uncertainty in glyphosate biochemical degradation in soil

Cecilia

Maggi

2020

Mathematics and Computers in Simulation

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Section: Discussionmentioning

confidence: 99%

Influential sources of uncertainty in glyphosate biochemical degradation in soil

Cecilia

Maggi

2020

Mathematics and Computers in Simulation

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“…To achieve groundwater concentrations appropriate for comparison to monitoring data, many of the USEPA model input parameters and assumptions would need to be revised to better represent actual agricultural fields near shallow groundwater wells, for example, using realistic rather than negligible runoff and erosion. The validity of PRZM-GW for exposure modeling and assessments has been addressed by previous publications (including HC and USEPA 2012;Estes et al 2015), and so it was not necessary to revisit here. Additional sources of uncertainty in the model results may be introduced by the spatially varying soil and weather input parameters.…”

Section: Uncertaintymentioning

confidence: 99%

Development of groundwater pesticide exposure modeling scenarios for vulnerable spring and winter wheat‐growing areas

Padilla¹,

Winchell²,

Peranginangin

et al. 2017

Integr Envir Assess & Manag

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Wheat crops and the major wheat-growing regions of the United States are not included in the 6 crop-and region-specific scenarios developed by the US Environmental Protection Agency (USEPA) for exposure modeling with the Pesticide Root Zone Model conceptualized for groundwater (PRZM-GW). The present work augments the current scenarios by defining appropriately vulnerable PRZM-GW scenarios for high-producing spring and winter wheat-growing regions that are appropriate for use in refined pesticide exposure assessments. Initial screening-level modeling was conducted for all wheat areas across the conterminous United States as defined by multiple years of the Cropland Data Layer land-use data set. Soil, weather, groundwater temperature, evaporation depth, and crop growth and management practices were characterized for each wheat area from publicly and nationally available data sets and converted to input parameters for PRZM. Approximately 150 000 unique combinations of weather, soil, and input parameters were simulated with PRZM for an herbicide applied for postemergence weed control in wheat. The resulting postbreakthrough average herbicide concentrations in a theoretical shallow aquifer were ranked to identify states with the largest regions of relatively vulnerable wheat areas. For these states, input parameters resulting in near 90 th percentile postbreakthrough average concentrations corresponding to significant wheat areas with shallow depth to groundwater formed the basis for 4 new spring wheat scenarios and 4 new winter wheat scenarios to be used in PRZM-GW simulations. Spring wheat scenarios were identified in North Dakota, Montana, Washington, and Texas. Winter wheat scenarios were identified in Oklahoma, Texas, Kansas, and Colorado. Compared to the USEPA's original 6 scenarios, postbreakthrough average herbicide concentrations in the new scenarios were lower than all but Florida Potato and Georgia Coastal Peanuts of the original scenarios and better represented regions dominated by wheat crops.

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“…PELMO and PRZM use the tipping bucket approach (Carsel et al, 1984) to simulate water flow across discrete soil layers and the convection–dispersion equation to simulate solute transport. Both models have been used in various studies on pesticide leaching (Ferrari et al, 2005; Estes et al, 2016; among others). PRZM was later extended to PRZM‐3, which includes a module (VADOFT) that also solves the Richards equation for water flow (Carsel et al, 2003).…”

mentioning

confidence: 99%

Assessing the Potential Exposure of Groundwater to Pesticides: A Model Comparison

Diamantopoulos

Šimůnek

Oberdörster

et al. 2017

Vadose Zone Journal

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Many pesticide-leaching studies rely on the use of numerical models that account for various physicochemical and biological processes at a range of temporal and spatial scales. In leaching assessments for the registration of pesticides in the European Union and the United States, one-dimensional models are used that describe the vertical transport of soil water and pesticides to groundwater. One-dimensional models are most representative for spray and broadcast applications of pesticides, but they may not be adequate for spatially nonuniform applications such as microdrip irrigation. We tested whether an advanced numerical model capable of one-, two-, and three-dimensional flow and pesticide transport simulation [HYDRUS (2D/3D)] provides results consistent with one-dimensional numerical models commonly used for pesticide registration (PEARL, PELMO). Model comparison was used to assess conceptual uncertainty in soil physical representation of pesticide transport among numerical models across a range of applications. Simulations of soil water flow and pesticide and heat transport were conducted for four different hypothetical pesticides and nine European regulatory standard pedoclimatic scenarios (FOCUS). The results show that the predicted annual amount of pesticide mass leached below the depth of 1 m, for all substances, locations, and simulation years, was on the same order of magnitude among the three models. Additionally, the simulated 80th percentile of annual pesticide concentrations at the 1-m depth was not statistically different among models. HYDRUS (2D/3D) can, therefore, be used as an alternative model for pesticide assessment studies and provides a conceptual framework consistent with PEARL and PELMO but capable of two-and three-dimensional applications as well.

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Comparison of predicted pesticide concentrations in groundwater from SCI‐GROW and PRZM‐GW models with historical monitoring data

Cited by 11 publications

References 3 publications

Influential sources of uncertainty in glyphosate biochemical degradation in soil

Influential sources of uncertainty in glyphosate biochemical degradation in soil

Development of groundwater pesticide exposure modeling scenarios for vulnerable spring and winter wheat‐growing areas

Assessing the Potential Exposure of Groundwater to Pesticides: A Model Comparison

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