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Simulating Solute Transport in a Structured Field Soil

Uncertainty in Parameter Identification and Predictions

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

View larger version (30K): [in a new window]   Fig. 1. Location map and layout of the drainage system in the experimental field at Lanna.

View larger version (28K): [in a new window]   Fig. 2. Measured flux concentrations of bromide (triangles) compared with the 5th and 95th percentiles of the generalized likelihood uncertainty estimation (GLUE) behavioral simulations obtained using all observations (gray lines) (n = 235) and the GLUE simulations with the largest overall model efficiency (black line). The percentile curves include values from different simulations.

View larger version (25K): [in a new window]   Fig. 3. Measured flux concentrations of bentazone (triangles) compared with the 5th and 95th percentiles of the generalized likelihood uncertainty estimation (GLUE) behavioral simulations obtained using all observations (gray lines) (n = 235) and the GLUE simulations with the largest overall model efficiency (black line). The percentile curves include values from different simulations.

View larger version (29K): [in a new window]   Fig. 4. Resident concentration profiles of bromide on five sampling occasions. Measured values (triangles) compared with the 5th and 95th percentiles of the generalized likelihood uncertainty estimation (GLUE) behavioral simulations obtained using all observations (gray lines) (n = 235) and the GLUE simulation with the largest overall model efficiency (crosses). Note the different scales on the x axes.

View larger version (18K): [in a new window]   Fig. 5. Resident concentration profiles of bentazone on three sampling occasions. Measured values (triangles) compared with the 5th and 95th percentiles of the generalized likelihood uncertainty estimation (GLUE) behavioral simulations obtained using all observations (gray lines) (n = 235) and the GLUE simulation with the largest overall model efficiency (crosses). Note the different scales on the x axes.

View larger version (75K): [in a new window]   Fig. 6. Model efficiencies (EFtot) for all generalized likelihood uncertainty estimation (GLUE) simulations (gray) and for the GLUE simulations with parameter values that lie within all sequential uncertainty fitting (SUFI) posterior uncertainty domains (black). The EFtot values were calculated using all observations. The horizontal lines indicate the threshold for behavioral simulations. The term Kb is the saturated micropore hydraulic conductivity, Koc is the soil organic carbon partition coefficient, dtop and dsub are the diffusion pathlengths in the topsoil and subsoil, respectively, and µtop and µsub are the degradation rate coefficients in the topsoil and subsoil, respectively.

View larger version (37K): [in a new window]   Fig. 7. Cumulative likelihood distributions for parameter conditioning with generalized likelihood uncertainty estimation (GLUE) using different combinations of observations. The number of behavioral simulations included in each combination of groups is denoted by n. The term Kb is the saturated micropore hydraulic conductivity, Koc is the soil organic carbon partition coefficient, dtop and dsub are the diffusion pathlengths in the topsoil and subsoil, respectively, and µtop and µsub are the degradation rate coefficients in the topsoil and subsoil, respectively.

View larger version (32K): [in a new window]   Fig. 8. Comparison of predictions of maximum concentrations of bentazone in drainflow and accumulated losses of bentazone through drainflow for sequential uncertainty fitting (SUFI) and generalized likelihood uncertainty estimation (GLUE) using different combinations of observations. The number of predictive simulations is denoted by n.