Landscape response to tectonic forcing: Digital elevation model analysis of stream profiles in the Mendocino triple junction region, Northern California

The topographic evolution of orogens is fundamentally dictated by rates and patterns of bedrock-channel incision. Quantitative field assessments of process-based laws are needed to accurately describe landscape uplift and denudation in response to tectonics and climate. We evaluate and calibrate the shear stress (or similar unit stream-power) bedrock-incision model by studying stream profiles in a tectonically active mountain range. Previous work on emergent marine terraces in the Mendocino triple junction region of northern California provides spatial and temporal control on rock-uplift rates. Digital elevation models and field data are used to quantify differences in landscape morphology associated with along-strike northwest to southeast changes in tectonic and climatic conditions. Analysis of longitudinal profiles supports the hypothesis that the study-area channels are in equilibrium with current uplift and climatic conditions, consistent with theoritical calculations of system response time based on the shear-stress model. Within uncertainty, the profile concavity (θ) of the trunk streams is constant throughout the study area (θ ≈0.43), as predicted by the model. Channel steepness correlates with uplift rate. These data help constrain the two key unknown model parameters, the coefficient of erosion (K) and the exponent associated with channel gradient (n). This analysis shows that K cannot be treated as a constant throughout the study area, despite generally homogeneous substrate properties. For a reasonable range of slope-exponent values (n), best-fit values of K are positively correlated with uplift rate. This correlation has important implications for landscape-evolution models and likely reflects dynamic adjustment of K to tectonic changes, due to variations in orographic precipitation, and perhaps channel width, sediment load, and frequency of debris flows. The apparent variation in K makes a unique value of n impossible to constrain with present data.