ABSTRACT cedure is, therefore, required. Intuitively, the greater de-Dual-permeability models have been developed to account for the significant effects of macropore flow on contaminant transport, but gree of complexity of dual-permeability models would imply an increase in the data requirements for efficient their use is hampered by difficulties in estimating the additional pa- calibration (Jarvis, 1999, 2001), but no attempts have rameters required. Therefore, our objective was to evaluate data re- yet been made to quantify this. quirements for parameter identification for predictive modeling with Inverse modeling has become a popular calibration the dual-permeability model MACRO. Two different approaches were compared: sequential uncertainty fitting (SUFI) and generalized likelihood uncertainty estimation (GLUE). We investigated six parameters controlling macropore flow and pesticide sorption and degradation, applying MACRO to a comprehensive field data set of bromide and bentazone [3-isopropyl-1H-2,1,3-benzothiadiazin-4(3H)-one-2,2di-oxide] transport in a structured soil. The GLUE analyses of paramete
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