Calibration of pesticide leaching models: critical review and guidance for reporting

Dubus, Igor G.; Beulke, Sabine; Brown, Colin D.

doi:10.1002/ps.526

Cited by 48 publications

(33 citation statements)

References 75 publications

(121 reference statements)

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“…A major concern in relation to modeling and multivariate analysis is the degree of uncertainty and representativeness of the data generated in dissipation studies (Beulke et al, 2000; Dubus et al, 2002; Dubus et al, 2003; Massey and Lenoir, 2003; van der Keur and Iversen, 2006). Thus, sampling from deeper soil horizons and incubating in batch may cause a bias in the results, and the representativeness of the results generated by techniques such as batch experiments, column experiments, and in‐field experiment is an important issue for debate.…”

Section: Discussionmentioning

confidence: 99%

Impact of Basic Soil Parameters on Pesticide Disappearance Investigated by Multivariate Partial Least Square Regression and Statistics

et al. 2008

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Dissipation time is a key parameter when studying and modeling the environmental fate of pesticides. This study was conducted to characterize the variability of pesticide disappearance in soil and to identify possible controlling parameters related to intrinsic soil properties and microbiology. Multivariate data analysis was used to study spatial variability in three horizons from 24 sandy soil profiles. The time for 50% disappearance (DT(50)) was characterized for two herbicides, metribuzin (MBZ) and MCPA, and methyltriazine amine (MTA; transformation product of metsulfuron-methyl, tribenuron-methyl, thifensulfuron-methyl, and chlorsulfuron). Normal and log-normal distributions were compared for DT(50) and soil properties and descriptive statistics were calculated. Conformity with log-transformed distributions was observed and assuming normality of the DT(50) data would cause 5 to 35% overestimation. Mean DT(50) were: MCPA 9.5, MBZ 168, and MTA 127. Significant effect of soil depth on DT(50) was shown for MCPA and MBZ, with low values in deeper horizons. Simple linear correlation for combinations of MCPA, MTA, pH, and total organic carbon (TOC) was observed. Using partial least squares regression (PLS) 71 to 85% of the total DT(50) variance was explained. A specific predictor variable could not be identified as the controlling components differed within horizons and compounds. For MCPA the overall important predictor variables were microbiology and TOC, whereas for MTA and MBZ it was inorganic variables (Al, Fe, cation exchange capacity, base saturation percent, and pH) and microbiology. The study indicates that PLS generated input data can improve pesticide fate modeling and reduce the uncertainty in dissipation estimation.

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Section: Discussionmentioning

confidence: 99%

Impact of Basic Soil Parameters on Pesticide Disappearance Investigated by Multivariate Partial Least Square Regression and Statistics

et al. 2008

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“…Besides, a detailed description of the models was provided. The interested reader is referred either to review compiled databases such as CAMASE (Bergamaschi and Putti 1999), REM (Register of Ecological Models 2006), or to review papers such as (Vink et al 1997;Vanclooster et al 2000, (FOCUS 2000Jones and Russell 2001;Dubus et al 2002;Garratt et al 2003). Vink et al (1997) studied unsaturated transport of the nematicide aldicarb and the herbicide simazine in a cracked clay soil.…”

Section: Constructed Wetland Modelingmentioning

confidence: 99%

Mitigation of agricultural nonpoint-source pesticide pollution in artificial wetland ecosystems

et al. 2008

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International audienceContamination caused by pesticides in agriculture is a source of environmental poor water quality in some of the European Union countries. Without treatment or targeted mitigation, this pollution is diffused in the environment. Pesticides and some metabolites are of increasing concern because of their potential impacts on the environment, wildlife and human health. Within the context of the European Union (EU) water framework directive context to promote low pesticide-input farming and best management practices, the EU LIFE project ArtWET assessed the efficiency of ecological bioengineering methods using different artificial wetland (AW) prototypes throughout Europe. We optimized physical and biological processes to mitigate agricultural nonpoint-source pesticide pollution in artificial wetland ecosystems. Mitigation solutions were implemented at full-scale demonstration and experimental sites. We tested various bioremediation methods at seven experimental sites. These sites involved (1) experimental prototypes, such as vegetated ditches, a forest microcosm and 12 wetland mesocosms, and (2) demonstration prototypes: vegetated ditches, three detention ponds enhanced with technology of constructed wetlands, an outdoor bioreactor and a biomassbed. This set up provides a variety of hydrologic conditions, with some systems permanently flooded and others temporarily flooded. It also allowed to study the processes both in field and controlled conditions. In order to compare the efficiency of the wetlands, mass balances at the inlet and outlet of the artificial wetland will be used, taking into account the partition of the studied compound in water, sediments, plants, and suspended solids. The literature background necessary to harmonize the interdisciplinary work is reviewed here and the theoretical framework regarding pesticide removal mechanisms in artificial wetland is discussed. The development and the implementation of innovative approaches concerning various water quality sampling strategies for pesticide load estimates during flood, specific biological endpoints, innovative bioprocess applied to herbicide and copper mitigation to enhance the pesticide retention time within the artificial wetland, fate and transport using a 2D mixed hybrid finite element model are introduced. These future results will be useful to optimize hydraulic functioning, e.g., pesticide resident time, and biogeochemical conditions, e.g., dissipation, inside the artificial wetlands. Hydraulic retention times are generally too low to allow an optimized adsorption on sediment and organic materials accumulated in artificial wetlands. Absorption by plants is not either effective. The control of the hydraulic design and the use of adsorbing materials can be useful to increase the pesticides residence time and the contact between pesticides and biocatalyzers. Pesticide fluxes can be reduced by 50-80% when hydraulic pathways in artificial wetlands are optimized by increasing ten times the retention time, by recirculation of w...

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“…Scientists speak of calibrating models for a number of reasons, including the parameterization of models, model verification, extrapolation and parameter estimation (cf. Dubus, Beulke, & Brown, 2002).…”

Section: Calibrating Modelsmentioning

confidence: 95%

Calibrating and constructing models of protein folding

Ramsey

2006

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Prediction is more than testing established theory by examining whether the prediction matches the data. To show this, I examine the practices of a community of scientists, known as threaders, who are attempting to predict the final, folded structure of a protein from its primary structure, i.e., its amino acid sequence. These scientists employ a careful and deliberate methodology of prediction. A key feature of the methodology is calibration. They calibrate in order to construct better models. The construction leads to knowledge of how to construct or build an object. Thus, prediction serves a cognitive goal of model construction and not just model or theory testing. The kind of knowledge that results is relevantly different than theoretical knowledge.Keywords Chemistry · Protein folding · Models Although philosophers of science usually list prediction and explanation as important-perhaps even the two most important-epistemic goods provided by science, we pay relatively little attention to prediction. We assume prediction is subservient to explanation, and our account of a worthwhile prediction amounts to not much more than "it matches the data." 1 Yet a normative account of prediction is needed. Many scientists are engaged in predictive modeling, so a philosophical account can provide analyses of the hows and whys of predictive science and thus provide a more complete epistemological analysis of the sciences as a whole. In addition, it is often claimed that predictive models are simply sophisticated "garbage in, garbage out" affairs. Whether this is the exception or the rule must be investigated instead of 1 It is much as if we were to say courage and wisdom are two important character virtues and then proceed to offer an account of wisdom that amounted to only "use your head." Socrates would not be pleased.

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Calibration of pesticide leaching models: critical review and guidance for reporting

Cited by 48 publications

References 75 publications

Impact of Basic Soil Parameters on Pesticide Disappearance Investigated by Multivariate Partial Least Square Regression and Statistics

Impact of Basic Soil Parameters on Pesticide Disappearance Investigated by Multivariate Partial Least Square Regression and Statistics

Mitigation of agricultural nonpoint-source pesticide pollution in artificial wetland ecosystems

Calibrating and constructing models of protein folding

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