Electrofishing is considered a reliable tool to assess the assemblages and biodiversity of fish in wadeable streams. The most widely used electrofishing techniques (point [P], single-pass [S-P], and multiple-pass [M-P]) vary as to the effort needed for sample collection, and this may potentially influence the degree of accuracy. Moreover, little is known about the comparability of the methods and their specific performance in streams with different fish assemblages. The aim of this investigation was to validate (using M-P sampling as reference) the use of P and S-P electrofishing techniques to accurately assess the richness, density and size distribution of fishes in small streams at both regional and global scale independently of fish assemblages and geographical region. We sampled 50-m-long reaches in a total of 33 lowland stream reaches that were located in different climatic and biogeographical regions (Uruguay and Denmark) and hosted different fish assemblages. Subtropical fish communities exhibited higher richness (Uy: 12-32, Dk: 1-9) and densities (Uy: 1.3-5.2, DK: 0.1-4.9 in. m(-2)) than temperate streams. We applied both "global models" using the entire database (33 sites) and "local models" including the same number of sites but using the climatic region as a model variable. Regression analyses revealed that the P, S-P and M-P methods all provided an adequate picture of the species composition and size distribution, and transfer equations for comparison between methods are thus not required. Conversely, richness was better predicted by S-P and by P techniques for regional and global models, respectively. Transfer equations obtained for abundance revealed that the P and S-P models can accurately transform catch data into M-P estimations. The transfer equations provided here may have great relevance as they allow relatively reliable comparisons to be made between data obtained by different techniques. We also show that less intensive sampling techniques may be equally useful for monitoring purposes as those requiring more intensive efforts (and costs). We encourage validation of our developed transfer equations on data from other regions of the world.