We evaluated the performance of nine published pedotransfer functions (PTFs) for estimating saturated hydraulic conductivity (K-s) in modeling the stormflow generated in a rainforest catchment. Using available input data consisting of particle size distribution. bulk density, and saturated moisture content information, these empirically-based PTFs were found to be inadequate in estimating K-s for this catchment. At shallow depths (0-0.1 m). PTFs commonly underestimated K-s by variable amounts with the exception of the Jabro PTF, which either overestimated K-s or was not significantly different from measured values. At subsequent depths (0.1-0.4 m), PTFs typically overestimated K-s by variable amounts, the exception being the Campbell and Shiozawa PTF, which typically underestimated K-s. We used TOPOG_SBM to model storm flow generation by replacing measured K-s values from the 0 to 0.1 m depth interval with PTF-estimated K-s values. The simulation set using Rosetta SSC (PTF with input of % sand. silt, clay) K-s values overestimated runoff for all events, and overland flow occurred across the entire catchment for all events. Simulations using Rosetta SSC-BD (PTF with input of % sand, silt, clay, and bulk density) K-s values predicted hydrograph attributes as well as the simulations using measured K-s values, but the Rosetta SSC-BD simulation set predicted a much larger spatial frequency of overland flow across the catchment than the measured K-s simulation set. Model simulations using the Jabro PTF, which generated large estimates of K-s, produced hydrographs that overestimated total runoff and time of rise but underestimated peak runoff. This model predicted much less overland flow than other models. Currently published PTFs used in this study are inadequate in estimating K-s for the La Cuenca catchment, which in turn make them inadequate for modeling storm flow generation. Enhanced model performance could likely be achieved by utilizing PTFs that better account for the influence of macroporosity. (C) 2001 Elsevier Science BN. All rights reserved.