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Sensitivity and First-Step Uncertainty Analyses for the Preferential Flow Model MACRO

Cranfield Centre for EcoChemistry, Cranfield University, Silsoe, Bedfordshire, MK45 4DT, UK

View larger version (21K): [in a new window]   Fig. 1. Comparison between Koc and DT50 values of the two theoretical pesticides considered in the present study (closed squares) and those for pesticides registered for use in the UK (open circles). Properties for registered compounds were taken from Lewis and Bardon (1998). Only those registered pesticides with Koc < 500 mL g-1 and DT50 < 100 d are shown.

View larger version (38K): [in a new window]   Fig. 2. Rainfall data and pesticide leaching breakthrough at a 1-m depth predicted by MACRO for the four base-case scenarios.

View larger version (41K): [in a new window]   Fig. 3. Classification into broad classes of the 15 most influential parameters for predictions of pesticide losses for the four scenarios (one-at-a-time approach). Parameters are classified by decreasing influence according to their maximum absolute ratio of variation (MAROV) value.

View larger version (41K): [in a new window]   Fig. 4. Variations of the water retention curves in the one-at-a-time (top two charts) and Monte Carlo (bottom two charts) approaches. Water retention curves generated in the sensitivity analyses (black lines) are compared with those from the base-case scenarios (open circles). All curves are modeled using the Brooks and Corey equation implemented in MACRO.

View larger version (41K): [in a new window]   Fig. 5. Variations of the hydraulic conductivity curves in the one-at-a-time (top two charts) and Monte Carlo (bottom two charts) approaches. Hydraulic conductivity retention curves generated in the sensitivity analyses (black lines) are compared with those from the base-case scenarios (open circles).

View larger version (17K): [in a new window]   Fig. 6. Box plots describing the distributions of predictions for pesticide losses for the four scenarios (Monte Carlo approach).