On the basis of that and derivative research, modern physical river science and eco-engineering are dominated by theories and practices emphasizing central tendency, ignoring data variability as noise (Chen et al., 2014;Doyle et al., 2007). However, rivers exhibit a large array of spatially correlated physical processes that depend on river size and shape varying downstream, thus not remaining constant at central-tendency dimensions (Kleinhans, 2010;Wilkinson et al., 2008;Wyrick & Pasternack, 2014). As near-census (∼1 m resolution) topographic data sets equitably representing nested scales of variance become ubiquitous, river science must make a paradigm shift away from roots in central tendency toward one embracing coherent varying patterns. To highlight the importance of variability over central tendency, this study presents a novel analysis of a unique regional-scale field-derived geomorphic data set.Many rivers around the world exhibit variability in the form of alternating sequences of riffle and pool landforms. The velocity-reversal hypothesis was one of the seminal mechanisms proposed to explain pool-riffle couplet persistence, here termed self-maintenance (Keller, 1971;Tinkler, 1970;Yang, 1971). The