Hierarchical Controls on Fluvial Connectivity: Insights from Geomorphic Covariance Structures

Understanding how hydraulic and geomorphic variables co-evolve along river corridors remains a central challenge in fluvial geomorphology, particularly in systems where multiple process domains and structural controls coexist. In this study, a network-based framework is applied to quantify geomorphic covariance structures across alluvial and bedrock reaches, valley confinement classes, and contrasting lithologic substrates. Using correlation-derived Geomorphic Covariance Networks (GCNs), this study moved beyond pairwise relationships to examine how channel geometry, flow hydraulics, and sediment-related metrics interact as integrated systems. In-phase and out-of-phase relationships among key variables are first identified, and the analysis is then extended spatially using rolling correlations and spatial cross-correlation functions to assess how the strength and sign of covariance vary along the river corridor. Network metrics (density, mean degree, and edge weight), together with centrality measures, reveal systematic differences in network organization between process domains. Alluvial reaches exhibit fewer but stronger connections, with shear stress, flow velocity, and total stream power acting as dominant hubs, indicating tightly coupled, process-driven feedbacks. In contrast, bedrock reaches show broader but weaker connectivity, with specific stream power, bank geometry, and coarse-grain-scale metrics emerging as central controls, reflecting structural and lithologic constraints on channel adjustment. Valley confinement and lithology further modulate network coherence, with partly confined reaches and mechanically uniform substrates producing the most densely connected and strongly coupled networks. Spectral properties and low clustering indicate that these systems do not conform to small-world network behavior but are instead hub-dominated and physically constrained. Overall, the results demonstrate that GCNs provide a powerful quantitative framework for diagnosing hierarchical controls, feedback strength, and spatial variability in fluvial systems, offering new insights into channel sensitivity and morphodynamic organization across contrasting geomorphic settings.