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Modeling Macropore Flow Effects on Pesticide Leaching

Inverse Parameter Estimation Using Microlysimeters

Department of Soil Sciences, SLU, Box 7014, 750 07 Uppsala, Sweden

View larger version (38K): [in a new window]   Fig. 1. (a) Daily precipitation and (b) potential evaporation (calculated with the Penman equation) during the field phase of the experiment.

View larger version (20K): [in a new window]   Fig. 2. Comparison between measured and simulated accumulated water percolation for one example column from each landscape element: (a) hilltop, (b) slope, and (c) hollow.

View larger version (38K): [in a new window]   Fig. 3. Measured and simulated tracer flux concentration for (a) hilltop, (c) slope, and (e) hollow and tracer resident concentration for (b) hilltop, (d) slope, and (f) hollow. The term EF is the model efficiency calculated using Eq. [13].

View larger version (61K): [in a new window]   Fig. 4. Response surfaces of the objective function in the (a) (n*, d) and (b) (Dv, d) planes for one hilltop column. The cross identifies the parameter values estimated by the inverse procedure and the hatched area defines the posterior uncertainty domains for these estimates. The shaded scale indicates the values of the goal function.

View larger version (92K): [in a new window]   Fig. 5. Response surface of the objective function in the (n*, d) plane for one slope column. The cross identifies the parameter values estimated by the inverse procedure and the hatched area defines the posterior uncertainty domains for these estimates. The shaded scale indicates the values of the goal function.

View larger version (39K): [in a new window]   Fig. 6. Measured and simulated pesticide flux concentration for (a) hilltop, (c) slope, and (e) hollow and resident concentrations for (b) hilltop, (d) slope, and (f) hollow. The term EF is the model efficiency.