Application date as a controlling factor of pesticide transfers to surface water during runoff events

Boithias, Laurie; Sauvage, Sabine; Srinivasan, Raghavan; Leccia, Odile; Sánchez‐Pérez, José‐Miguel

doi:10.1016/j.catena.2014.03.013

Cited by 46 publications

(25 citation statements)

References 42 publications

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“…In the present study, the simulation of triazine herbicides was affected by pesticide availability in the runoff interaction layer which was mainly influenced by the application date, pesticide sorption, degradation rate, and timing of rainfall event. This finding is in agreement with a study by Boithias et al (2014) who carried out a sensitivity study for SWAT using plausible ranges of application dates for two contrasting pre-emergence herbicides; the authors showed that the effect of the application date was a pesticide-specific factor influenced by their bioavailability.…”

Section: Uncertainty Analysissupporting

confidence: 92%

“…Uncertainty analyses showed that pesticide application date was the most critical input parameter. These results agree with the findings of other studies (Boithias et al, 2014;Boulange et al, 2012;Holvoet et al, 2005). Holvoet et al (2005) suggested that application date had greater impact than application rate and rainfall errors to simulate atrazine emissions based on a sensitivity analysis for SWAT.…”

Section: Uncertainty Analysissupporting

confidence: 90%

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Modelling triazines in the valley of the River Cauca, Colombia, using the annualized agricultural non-point source pollution model

Villamizar

Brown

2016

Agricultural Water Management

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Section: Uncertainty Analysissupporting

confidence: 92%

Section: Uncertainty Analysissupporting

confidence: 90%

Modelling triazines in the valley of the River Cauca, Colombia, using the annualized agricultural non-point source pollution model

Villamizar

Brown

2016

Agricultural Water Management

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“…The influence of uncertainties on model results varies depending on the 285 sensitivity of the parameters; higher uncertainties on the most sensitive parameters would generate a 286 greater impact on the accuracy of the simulation. Sensitivity analysis of pesticide fate models including SPIDER and MACRO have shown that simulations are greatly influenced by the quality and adequacy of precipitation data (Dubus and Brown, 2002;, pesticide sorption and degradation parameters (Dubus and Brown, 2002) and pesticide usage details, particularly application dates (Boithias et al, 2014;Holvoet et al, 2005). For many years, the UK Meteorological Office (2010) has used the tipping-bucket rain gauge for the automatic recording of rainfall.…”

Section: Uncertainty Analysismentioning

confidence: 99%

A modelling framework to simulate river flow and pesticide loss via preferential flow at the catchment scale

Villamizar

Brown

2017

CATENA

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A modelling framework with field-scale models including the preferential flow model MACRO was developed to simulate transport of six contrasting herbicides in a 650 km 2 catchment in eastern England. The catchment scale model SPIDER was also used for comparison. The catchment system was successfully simulated as the sum of multiple field-scale processes with little impact of instream processes on simulations. Preferential flow was predicted to be the main driver of pesticide transport in the catchment. A satisfactory simulation of the flow was achieved (Nash-Sutcliffe model efficiencies of 0.56 and 0.34 for MACRO and SPIDER, respectively) but differences between pesticide simulations were observed due to uncertainties in pesticide properties and application details. Uncertainty analyses were carried out to assess input parameters reported as sensitive including pesticide sorption, degradation and application dates; their impact on simulations was chemical-specific. The simulation of pesticide concentrations in the river during low flow periods was very sensitive to uncertainty from rain gauge measurements and the estimation of evapotranspiration. Highlights  The catchment system can be simulated as the sum of multiple field-scale processes 20  Pesticide concentrations in stream flow were driven by field-scale processes 21  In-stream processes had little effect on simulations 22  Uncertainties in rain gauge recording affected the simulation of low-flow periods 23  SPIDER simulates important lateral flow losses that can occur when drains are not flowing 24

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“…Processes driving pesticide fate and transport are on the whole well-known and are incorporated in various pesticide models operating at plot or watershed spatial scales, such as the crop model STICS (Simulateur mulTIdiscplinaire pour les Cultures Standard), MACRO (Water and solute transport in macroporous soils), PEARL (Pesticide Emission Assessment at Regional and Local scales), PRZM (Pesticide Root Zone Model), and SWAT (Soil and Water Assessment Tool) [20,21]. Several studies have already shown that the watershed-scale SWAT model was an efficient tool to model pesticides fate and transport [22][23][24][25]. However, the SWAT model performance can be restricted by its two-phase partitioning approach, which is inadequate when it comes to simulating pesticides with limited dataset.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Fate and Transport of Malathion in the Pagsanjan-Lumban Basin, Philippines

Ligaray

Kim

Baek

et al. 2017

Water

Self Cite

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Exposure to highly toxic pesticides could potentially cause cancer and disrupt the development of vital systems. Monitoring activities were performed to assess the level of contamination; however, these were costly, laborious, and short-term leading to insufficient monitoring data. However, the performance of the existing Soil and Water Assessment Tool (SWAT model) can be restricted by its two-phase partitioning approach, which is inadequate when it comes to simulating pesticides with limited dataset. This study developed a modified SWAT pesticide model to address these challenges. The modified model considered the three-phase partitioning model that classifies the pesticide into three forms: dissolved, particle-bound, and dissolved organic carbon (DOC)-associated pesticide. The addition of DOC-associated pesticide particles increases the scope of the pesticide model by also considering the adherence of pesticides to the organic carbon in the soil. The modified SWAT and original SWAT pesticide model was applied to the Pagsanjan-Lumban (PL) basin, a highly agricultural region. Malathion was chosen as the target pesticide since it is commonly used in the basin. The pesticide models simulated the fate and transport of malathion in the PL basin and showed the temporal pattern of selected subbasins. The sensitivity analyses revealed that application efficiency and settling velocity were the most sensitive parameters for the original and modified SWAT model, respectively. Degradation of particulate-phase malathion were also significant to both models. The rate of determination (R 2) and Nash-Sutcliffe efficiency (NSE) values showed that the modified model (R 2 = 0.52; NSE = 0.36) gave a slightly better performance compared to the original (R 2 = 0.39; NSE = 0.18). Results from this study will be able to aid the government and private agriculture sectors to have an in-depth understanding in managing pesticide usage in agricultural watersheds.

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Application date as a controlling factor of pesticide transfers to surface water during runoff events

Cited by 46 publications

References 42 publications

Modelling triazines in the valley of the River Cauca, Colombia, using the annualized agricultural non-point source pollution model

Modelling triazines in the valley of the River Cauca, Colombia, using the annualized agricultural non-point source pollution model

A modelling framework to simulate river flow and pesticide loss via preferential flow at the catchment scale

Modeling the Fate and Transport of Malathion in the Pagsanjan-Lumban Basin, Philippines

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