Browsing by Author "Dubus, Igor G."
Now showing 1 - 3 of 3
Results Per Page
Sort Options
Item Open Access Calibration of pesticide leaching models(2002-09) Dubus, Igor G.; Brown, Colin D.Complex deterministic models are being used within the context of pesticide registration to assess the potential for crop protection products to impact on the environment. Although calibration is in many ways at the heart of pesticide fate modelling, it has received little attention in the past. Sensitivity analyses were carried out for the four main leaching models used for pesticide registration in Europe (PELMO, PRZM, PESTLA and MACRO) using four different leaching scenarios and two approaches to sensitivity assessment (one-at-a-time and Monte Carlo sensitivity analyses). Also, an inverse modelling approach was used to estimate values for sorption and degradation parameters from leaching data for seven lysimeters using the PESTRAS model. The overall conclusions of the PhD can be summarised as follows: 1. Sensitivity analyses for the four leaching models mainly used for pesticide registration in Europe demonstrated that predictions for pesticide loss are most sensitive to parameters related to sorption and degradation. In a small number of scenarios, hydrological parameters were found to also have a large influence on predictions for pesticide loss. 2. Sensitivity analysis proved to be an effective approach not only for ranking parameters according to their influence on model predictions, but also for investigating model behaviour in a more general context. However, the research questioned the robustness of the Monte Carlo approach to sensitivity analysis as issues of replicability were uncovered. 3. Inverse modelling exercises demonstrated that non-uniqueness is likely to be widespread in the calibration of pesticide leaching models. Correlation between parameters within the modelling, such as that between sorption and degradation parameters when predicting pesticide leaching, may prevent the robust derivation of values through an inverse modelling approach. Depending on the calibration system considered, these parameters may act as fitting variables and integrate inaccuracies, uncertainties and limitations associated with experimental data, modelling and calibration. 4. A special implementation of error surface analysis termed lattice modelling was proposed in the PhD as an efficient technique to i) assess the likely extent of nonuniqueness issues in the calibration of pesticide leaching models; and, ii) replace traditional parameter estimation procedures where non-uniqueness is expected. Care should be exercised when assessing the results obtained by both modelling and inverse modelling studies. Suggestions to improve the reliability in the calibration of pesticide leaching models have been proposed.Item Open Access Evaluation of probabilistic modelling approaches against data on leaching of isoproturon through undisturbed lysimeters(Elsevier, 2004-11-15) Beulke, Sabine; Brown, Colin D.; Dubus, Igor G.; Fryer, Christopher J.; Walker, AllanThis study evaluated probabilistic modelling approaches against data on leaching of isoproturon through two contrasting soil types. Leaching through undisturbed lysimeters from a sandy loam (Wick series) and a moderately structured clay loam (Hodnet series) was investigated in seven replicates. The variability of soil properties and of sorption and degradation of isoproturon was estimated by taking 6-14 samples within the areas of lysimeter extraction in the field. Normal distributions were assigned to Koc and DT50 and a large number of values for these two parameters were sampled from each distribution. Parameter values were used to simulate movement of isoproturon through the lysimeters with the preferential flow model MACRO. Uncertainty in output distributions was compared with the variability of measured data. A constrained probabilistic assessment varying only degradation and sorption properties was sufficient to match the observed variability in cumulative leaching from the coarse-textured Wick soil (CV = 79%). Variation of pesticide properties alone could not match observed variability in cumulative leaching from the structured Hodnet soil (CV = 61%) and variability in a number of soil properties was incorporated. For both soils, constrained probabilistic approaches where only the top few most sensitive model inputs were varied were sufficient to match or exceed observed variability.Item Open Access Using a linked soil model emulator and unsaturated zone leaching model to account for preferential flow when assessing the spatially distributed risk of pesticide leaching to groundwater in England and Wales(Elsevier Science B.V., Amsterdam., 2004-01-05T00:00:00Z) Holman, Ian P.; Dubus, Igor G.; Hollis, J. M.; Brown, Colin D.Although macropore flow is recognized as an important process for the transport of pesticides through a wide range of soils, none of the existing spatially distributed methods for assessing the risk of pesticide leaching to groundwater account for this phenomenon. The present paper presents a spatially distributed modelling system for predicting pesticide losses to groundwater through micro- and macropore flow paths. The system combines a meta version of the mechanistic, dual porosity, preferential flow pesticide leaching model MACRO (the MACRO emulator), which describes pesticide transport and attenuation in the soil zone, to an attenuation factor leaching model for the unsaturated zone. The development of the emulator was based on the results of over 4000 MACRO model simulations. Model runs describe pesticide leaching for the range of soil types, climate regimes, pesticide properties and application patterns in England and Wales. Linking the MACRO emulator to existing spatial databases of soil, climate and compound-specific loads allowed the prediction of the concentration of pesticide leaching from the base of the soil profile (at 1 m depth) for a wide range of pesticides. Attenuation and retardation of the pesticide during transit through the unsaturated zone to the watertable was simulated using the substrate attenuation factor model AQUAT. The MACRO emulator simulated pesticide loss in 10 of 12 lysimeter soil-pesticide combinations for which pesticide leaching was shown to occur and also successfully predicted no loss from 3 soil-pesticide combinations. Although the qualitative aspect of leaching was satisfactorily predicted, actual pesticide concentrations in leachate were relatively poorly predicted. At the national scale, the linked MACRO emulator / AQUAT system was found to predict the relative order of, and realistic regional patterns of, pesticide leaching for atrazine, isoproturon, chlorotoluron and lindane. The methodology provides a first-step assessment of the potential for pesticide leaching to groundwater in England and Wales. Further research is required to improve the modelling concept proposed. The system can be used to refine regional groundwater monitoring system designs and sampling strategies and improve the cost-effectiveness of the measures needed to achieve “good status” of groundwater quality as required by the Water Framework Direct