Modeling the Influence of Sorption and Transformation on Pesticide Leaching and Persistence

Boesten, J.J.T.I.; Linden, A.M.A. van der

doi:10.2134/jeq1991.00472425002000020015x

Cited by 237 publications

(139 citation statements)

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“…A change of a factor of two in herbicide sorption input parameters for modeling could result in a 10 times difference in herbicide leaching potential within a soil (Boesten and van der Linden, 1991). Such a difference in herbicide sorption occurred in this study with soil depth (Table 1), and among slope positions within the A horizon (Table 2).…”

Section: Discussionmentioning

confidence: 74%

Spatial variability of soil properties and 2,4-D sorption in a hummocky field as affected by landscape position and soil depth

Gaultier¹,

Farenhorst²,

Crow³

2006

Can. J. Soil. Sci.

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Gaultier, J., Farenhorst, A. and Crow, G. 2006. Spatial variability of soil properties and 2,4-D sorption in a hummocky field as affected by landscape position and soil depth. Can. J. Soil Sci. 86: 89-95. Since pesticide fate and leaching models increasingly incorporate spatial variability, the objective of this study was to quantify the variability of soil properties and 2,4-D sorption within a hummocky field as affected by landscape position and soil depth. Seventy-two soil cores collected at 5-m intervals along a transect were segmented by soil horizon (A, B and C) and landscape position (upper, mid, lower and depression). As expected, soil organic carbon content significantly decreased, and soil pH and soil carbonate content significantly increased with soil depth, while clay content was significantly greater in the B horizon than the A and C horizon. Soils from the depressional area generally had higher soil organic carbon content, soil carbonate content, clay content and soil pH than soil samples from other slope positions. The sorption of 2,4-D by soil was positively correlated with soil organic matter content and negatively correlated with soil carbonate content. These soil properties and herbicide sorption varied along the transect and with soil depth. Regardless of whether or not the landscape was segmented by landscape position, for both the A and C horizon, predictions of 2,4-D sorption by soil were generally good using simple regression models that contained soil organic carbon content and carbonate content as the only parameters. However, for the B horizon, the prediction of 2,4-D sorption by soil was very poor when all sampling points along the transect were considered, but greatly improved for the mid-and depressional slope positions when soils were segmented by landscape position. We conclude that segmentation by slope position could be a useful additional tool when predicting pesticide fate and leaching at the large-scale. As well, the negative association between soil carbonate content and 2,4-D sorption warrants further attention as a large portion of Canadian agriculture encompasses calcareous soils. . Comme il fallait s'y attendre, la teneur en carbone organique diminue significativement alors que le pH et la concentration de carbonates augmentent significativement avec la profondeur; parallèlement, il y a sensiblement plus d'argile dans l'horizon B que dans les horizons A et C. Le sol des dépressions contient généralement plus de carbone organique, de carbonates et d'argile que le sol prélevé ailleurs sur la pente et son pH est plus élevé. La sorption du 2,4-D par le sol présente une corrélation positive avec la concentration de matière organique et une autre, négative, avec la concentration de carbonates. Ces propriétés du sol et la sorption de l'herbicide varient avec l'emplacement le long du transect et la profondeur. Les modèles à régression simple n'ayant pour seuls paramètres que la concentration de carbone organique et de carbonates prévoient généralement bien la sorption du 2,4-D p...

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Section: Discussionmentioning

confidence: 74%

Spatial variability of soil properties and 2,4-D sorption in a hummocky field as affected by landscape position and soil depth

Gaultier¹,

Farenhorst²,

Crow³

2006

Can. J. Soil. Sci.

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“…Parameter ranges related to potato crops, obtained by databases and tables included in the IPTM-CS program [41][42][43][44] are shown in Table 1. Other crops, less represented in the Plain, were not considered in this paper.…”

Section: Methodsmentioning

confidence: 99%

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

Petitta¹,

Mariňo²

2010

JWARP

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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.

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“…A complete water balance is simulated: root water uptake is calculated using the model described by Jarvis (1989); flow and transport to drainage systems is calculated by the Hooghoudt equation and seepage potential theory. Pesticide degradation is described by first-order kinetics, with the rate coefficient given as a function of soil temperature, according to the Arrhenius equation (Boesten and Van der Linden, 1991) and moisture content, following a modified Walker function (Walker, 1974). In this study, sorption is described with a linear isotherm, although MACRO can deal with non-linear Freundlich sorption isotherms.…”

Section: The Macro Model and Its Calibrationmentioning

confidence: 99%

Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty

Steffens

Larsbo

Moeys

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. Assessing climate change impacts on pesticide leaching requires careful consideration of different sources of uncertainty. We investigated the uncertainty related to climate scenario input and its importance relative to parameter uncertainty of the pesticide leaching model. The pesticide fate model MACRO was calibrated against a comprehensive one-year field data set for a well-structured clay soil in southwestern Sweden. We obtained an ensemble of 56 acceptable parameter sets that represented the parameter uncertainty. Nine different climate model projections of the regional climate model RCA3 were available as driven by different combinations of global climate models (GCM), greenhouse gas emission scenarios and initial states of the GCM. The future time series of weather data used to drive the MACRO model were generated by scaling a reference climate data set for an important agricultural production area in south-western Sweden based on monthly change factors for 2070-2099. 30 yr simulations were performed for different combinations of pesticide properties and application seasons. Our analysis showed that both the magnitude and the direction of predicted change in pesticide leaching from present to future depended strongly on the particular climate scenario. The effect of parameter uncertainty was of major importance for simulating absolute pesticide losses, whereas the climate uncertainty was relatively more important for predictions of changes of pesticide losses from present to future. The climate uncertainty should be accounted for by applying an ensemble of different climate scenarios. The aggregated ensemble prediction based on both acceptable parameterizations and different climate scenarios has the potential to provide robust probabilistic estimates of future pesticide losses.

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Modeling the Influence of Sorption and Transformation on Pesticide Leaching and Persistence

Cited by 237 publications

References 0 publications

Spatial variability of soil properties and 2,4-D sorption in a hummocky field as affected by landscape position and soil depth

Spatial variability of soil properties and 2,4-D sorption in a hummocky field as affected by landscape position and soil depth

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

Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty

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