Modifications to the SWAT code for modelling direct pesticide losses

2008 ◽  
Vol 23 (1) ◽  
pp. 72-81 ◽  
Author(s):  
K. Holvoet ◽  
A. van Griensven ◽  
V. Gevaert ◽  
P. Seuntjens ◽  
P.A. Vanrolleghem
Keyword(s):  
Pesticide Losses

PESTICIDE FORMULATION AND APPLICATION TECHNIQUE EFFECTS ON SURFACE PESTICIDE LOSSES

1997 ◽  
Vol 40 (6) ◽  
pp. 1617-1622 ◽  
Author(s):  
A. L. Kenimer ◽  
J. K. Mitchell ◽  
A. S. Felsot ◽  
M. C. Hirschi
Keyword(s):  
Application Technique ◽  
Pesticide Formulation ◽  
Pesticide Losses

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

2013 ◽  
Vol 10 (8) ◽  
pp. 10461-10494 ◽  
Author(s):  
K. Steffens ◽  
M. Larsbo ◽  
J. Moeys ◽  
E. Kjellström ◽  
N. Jarvis ◽  
...  
Keyword(s):  
Climate Change ◽  
Parameter Uncertainty ◽  
Climate Model ◽  
Climate Scenario ◽  
Climate Scenarios ◽  
Data Set ◽  
South West ◽  
Climate Uncertainty ◽  
Pesticide Losses ◽  
Pesticide Leaching

Abstract. The assessment of climate change impacts on the risk for pesticide leaching needs 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 south-west 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 (1970–1999) for an important agricultural production area in south-west 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 could provide robust probabilistic estimates of future pesticide losses and assessments of changes in pesticide leaching risks.

PLIERS: Pesticide Losses in Erosion and Runoff Simulator

1989 ◽  
Vol 32 (1) ◽  
pp. 0127-0136 ◽  
Author(s):  
A. L. Kenimer ◽  
S. Mostaghimi ◽  
T. A. Dillaha ◽  
V. O. Shanholtz
Keyword(s):  
Pesticide Losses

Modeling pesticide losses with surface runoff in Germany

1998 ◽  
Vol 223 (2-3) ◽  
pp. 177-191 ◽  
Author(s):  
A. Huber ◽  
M. Bach ◽  
H.G. Frede
Keyword(s):  
Surface Runoff ◽  
Pesticide Losses

scholarly journals A new conceptual model of pesticide transfers from agricultural land to surface waters with a specific focus on metaldehyde

2020 ◽  
Vol 22 (4) ◽  
pp. 956-972
Author(s):  
M. J. Whelan ◽  
A. Ramos ◽  
R. Villa ◽  
I. Guymer ◽  
B. Jefferson ◽  
...  
Keyword(s):  
Conceptual Model ◽  
Surface Waters ◽  
Agricultural Land ◽  
Environmental Deterioration ◽  
Specific Focus ◽  
Pesticide Losses

Pesticide losses from agricultural land to water can result in the environmental deterioration of receiving systems.

PeLM: Modeling of Pesticide-Losses Through Runoff and Sediment Transport

2004 ◽  
Vol 39 (4) ◽  
pp. 613-626 ◽  
Author(s):  
Bing Chen ◽  
Yifan Li ◽  
Guo H. Huang ◽  
Yuefei Huang ◽  
Yueren Li
Keyword(s):  
Sediment Transport ◽  
Pesticide Losses

Development and Testing of a Comprehensive Model of Pesticide Losses from Turf

2009 ◽  
pp. 183-196
Author(s):  
Antoni Magri ◽  
Douglas A. Haith ◽  
A. Martin Petrovic ◽  
Laosheng Wu ◽  
Robert L. Green
Keyword(s):  
Comprehensive Model ◽  
Pesticide Losses
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