Calibration of pesticide leaching models

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.Ph

Documented spatial data set containing the subdivision of the basins into groundwater systems and subsystems, the selected locations per subsystem and a description of these sites, available data and projected additional measurements and equipment

The establishment of tools for trends analysis in groundwater is essential for the prediction and evaluation of measures taken within context of the Water Framework Directive and the draft Groundwater Directive. This report describes the spatial data sets which will be used for the purpose of detection, aggregation and extrapolation of temporal trends in groundwater quality. Trend analysis methods will be applied and tested at various scales and in various hydrogeological situations. The report contains a description of the studied sub-basins in TREND 2, including information on hydrogeology, land use and pressures, available data and projected additional measurements. Major differences between the sub-basins and the data sets are described to examine consequences for the work on trend detection. One of the challenges for TREND 2 is to define criteria for the application of various statistical and deterministic trend approaches for a range of hydrogeological conditions, spatial scales and types of groundwater monitoring. An overview of these conditions, scales and monitoring types is provided in the present report.FP6 Integrated Project AquaTerra Integrated Modelling of the river-sediment-soil-groundwater system; advanced tools for the management of catchment areas and river basins in the context of global change (Project no. 505428 - GOCE

Evaluation of probabilistic modelling approaches against data on leaching of isoproturon through undisturbed lysimeters

This 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

Calibration of pesticide leaching models

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