Hydrologic indices can be used in macroecological models of fish species richness. I used fish distributions and river flow records from 89 river basins in the Pacific Northwest (USA) to identify robust associations between aspects of flow and fish species richness. I calculated 148 hydrologic indices for each basin, created single-predictor regression models for each hydrologic index, and tested for significant relationships between native fish species richness and specific components of flow. I used multiple regression to test the significance and fit of models that combined hydrologic indices that were not highly collinear indices. Significant linear relationships (p ≤ 0.05) were detected for 85 indices. Coefficients of determination (r²) ranged from 0.04 to 0.33 (median = 0.19, coefficient of variation [CV] = 0.55). I identified 2 multiple-regression models, each including 3 hydrologic indices, as best based on information-theoretic model comparisons. One included median large flood rise rate, CV of 1-d maximum flow, and CV of annual flow. The other included mean annual flow, median high flow timing, and CV of small flood timing. Four major themes emerged from the analyses: 1) fish species richness and a variety of indices of flow magnitude were positively related; 2) the strength of the positive association between fish species richness and flow magnitude was inversely related to flow magnitude and the strongest associations were observed during low-flow winter months; 3) flow variability, indicated by the CVs of hydrologic indices, was negatively associated with fish species richness; 4) indicators of episodic high-flow events (e.g., floods and annual maximum flows) were particularly well represented in the best multiple-regression models of fish species richness. These results can provide a baseline for comparison with other rivers and can be used to help formulate a general, flow-mediated theory of fish species richness in lotic ecosystems.