Our study investigated whether algae-based water-quality assessments are affected by differences between algal assemblages on hard substrates (rocks, wood) and soft substrates (fine-grained sediments). We analyzed a US Geological Survey National Water-Quality Assessment (NAWQA) program data set that consisted of 1048 pairs of samples collected from hard and soft substrates at 551 river sampling locations throughout the US. Biovolume and diversity of algal assemblages, biovolume of major taxonomic groups, and abundance of motile diatoms differed significantly between samples collected from hard and soft substrates at the same sites. Ordinations of assemblages from hard and soft substrates were highly concordant and provided similar information on environmental gradients underlying species patterns. The strengths of relationships between composition of algal assemblages and water chemistry parameters (conductivity, pH, total P, and total N) did not differ consistently between substrate types. Performance of weighted averaging (WA) inference models did not differ between models based on assemblages from hard and soft substrates. Moreover, the predictive power of inference models developed from single-substrate data sets was not reduced when these models were applied to samples collected from other substrates. We concluded that the choice of substrate to sample should depend on the assessment indicators to be used. If indicators based on the autecologies of many algal taxa (e.g., inference models or autecological indices) are used, restricting samples to a single type of substrate is unnecessary. If algal diversity, total algal biovolume, or abundance of specific algal taxa is used, samples should be collected from a single type of substrate.