Process-based similarity revealed by discharge-dependent relative submergence dynamics of thousands of large bed elements

Relative submergence of macroroughness elements such as boulders and bedrock outcrops, or large bed elements (LBEs), collectively, is a primary control on hydraulics and morphodynamics in steep, coarse-bedded rivers. However, in practice, the property is typically represented by singular, often reach- or cross-section-averaged values that mask bed-surface heterogeneity and joint distributions of local flow depths. By coupling sub-meter resolution two-dimensional (2D) hydrodynamic modeling with spatially explicit mapping of LBEs from a 13.2 km segment of a boulder-bedded mountain river, we present complete distributions of LBE relative submergences at multiple spatial scales and explore their dynamism across discharges. Through distribution fitting and statistical analysis of resultant discharge-dependent LBE relative submergence datasets, it was confirmed that segment- and reach-scale datasets exhibited similar statistical properties and were able to be drawn from the same type of distribution. Further, the rate at which statistical and parametric properties changed between discharge-dependent datasets were statistically equivalent between spatial domains, which we term process-based similarity. Commonality in distribution type and the uniform between discharge-scaling relationships suggest mutual self-organizing processes associated with the size-frequency distribution, spatial arrangement, and submergence of LBEs were present between most domains.

Automated summary

The relative submergence of macroroughness elements plays a crucial role in the hydraulics and morphodynamics of steep, coarse-bedded rivers. Through hydrodynamic modeling and mapping of large bed elements (LBEs), this study presents complete distributions of LBE relative submergences at different spatial scales and explores their dynamics across different discharges. Statistical analysis reveals that segment- and reach-scale datasets exhibit similar properties and can be drawn from the same distribution type, indicating process-based similarity between spatial domains.