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000014524 0247_ $$2pmid$$apmid:21308955
000014524 0247_ $$2DOI$$a10.1002/ps.2066
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000014524 084__ $$2WoS$$aAgronomy
000014524 084__ $$2WoS$$aEntomology
000014524 1001_ $$0P:(DE-Juel1)129548$$aVanderborght, J.$$b0$$uFZJ
000014524 245__ $$aEffect of pesticide fate parameters and their uncertainty on the selection of worst-casescenarios of pesticide leaching to groundwater
000014524 260__ $$aNew York, NY$$bWiley Interscience$$c2011
000014524 300__ $$a294 - 306
000014524 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article
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000014524 440_0 $$014421$$aPest Management Science$$v67$$x1526-498X$$y3
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000014524 500__ $$aRecord converted from VDB: 12.11.2012
000014524 520__ $$aFor the registration of pesticides in the European Union, model simulations for worst-case scenarios are used to demonstrate that leaching concentrations to groundwater do not exceed a critical threshold. A worst-case scenario is a combination of soil and climate properties for which predicted leaching concentrations are higher than a certain percentile of the spatial concentration distribution within a region. The derivation of scenarios is complicated by uncertainty about soil and pesticide fate parameters. As the ranking of climate and soil property combinations according to predicted leaching concentrations is different for different pesticides, the worst-case scenario for one pesticide may misrepresent the worst case for another pesticide, which leads to 'scenario uncertainty'.Pesticide fate parameter uncertainty led to higher concentrations in the higher percentiles of spatial concentration distributions, especially for distributions in smaller and more homogeneous regions. The effect of pesticide fate parameter uncertainty on the spatial concentration distribution was small when compared with the uncertainty of local concentration predictions and with the scenario uncertainty.Uncertainty in pesticide fate parameters and scenario uncertainty can be accounted for using higher percentiles of spatial concentration distributions and considering a range of pesticides for the scenario selection.
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000014524 588__ $$aDataset connected to Web of Science, Pubmed
000014524 650_2 $$2MeSH$$aClimate
000014524 650_2 $$2MeSH$$aComputer Simulation
000014524 650_2 $$2MeSH$$aEnvironmental Monitoring
000014524 650_2 $$2MeSH$$aEuropean Union
000014524 650_2 $$2MeSH$$aPesticides: analysis
000014524 650_2 $$2MeSH$$aPesticides: chemistry
000014524 650_2 $$2MeSH$$aRisk Assessment
000014524 650_2 $$2MeSH$$aSoil Pollutants: analysis
000014524 650_2 $$2MeSH$$aSoil Pollutants: chemistry
000014524 650_2 $$2MeSH$$aUncertainty
000014524 650_2 $$2MeSH$$aWater Pollutants, Chemical: analysis
000014524 650_2 $$2MeSH$$aWater Pollutants, Chemical: chemistry
000014524 650_7 $$00$$2NLM Chemicals$$aPesticides
000014524 650_7 $$00$$2NLM Chemicals$$aSoil Pollutants
000014524 650_7 $$00$$2NLM Chemicals$$aWater Pollutants, Chemical
000014524 650_7 $$2WoSType$$aJ
000014524 65320 $$2Author$$apesticide leaching
000014524 65320 $$2Author$$agroundwater
000014524 65320 $$2Author$$ascenarios
000014524 65320 $$2Author$$apesticide registration
000014524 65320 $$2Author$$auncertainty
000014524 7001_ $$0P:(DE-HGF)0$$aTiktak, A.$$b1
000014524 7001_ $$0P:(DE-HGF)0$$aBoesten, J.J.T.I.$$b2
000014524 7001_ $$0P:(DE-Juel1)129549$$aVereecken, H.$$b3$$uFZJ
000014524 773__ $$0PERI:(DE-600)2003455-6$$a10.1002/ps.2066$$gVol. 67, p. 294 - 306$$p294 - 306$$q67<294 - 306$$tPest management science$$v67$$x1526-498X$$y2011
000014524 8567_ $$uhttp://dx.doi.org/10.1002/ps.2066
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