Abstract
<p>Bedrock channel erodibility is a nonunique model-dependent parameter that scales hydraulic forcing to fluvial bedrock erosion. In landscape evolution modeling, erodibility coefficients are often assumed constant and uniform, and are often empirically calibrated to the form of natural landscapes. This approach lumps a wide range of variables into erodibility, including not only rock properties but also erosion processes (and their possible variations with discharge), climatic controls on hydrographs and rock weathering, and effects of coarse sediment supply.  Our goals are to better understand (a) how field measurements of rock properties could be combined to better quantify bedrock erodibility, (b) how bedrock erodibility may vary with discharge as different fluvial erosion processes become more or less dominant, and (c) how flood discharge variability and coarse sediment load influence “effective” erodibility in simple stream power incision model formulations.</p><p>Building on previous work, we first present new equations to calculate erodibility. Our rather complex erodibility model incorporates core-scale (i.e. unfractured) rock strength, discontinuity spacing (fractures, bedding planes), and climate-dependent bedrock susceptibility to weathering (which influences strength and fracturing), and accounts for abrasion and block plucking erosion processes. The model attempts to include feedbacks between these factors in a physical way, using variables that could be constrained from field data. Second, we explore the parameter space of these erodibility equations by modeling bedrock channel profile evolution for a range of conditions and varying rock properties, using preliminary constraints from field data collected in the semi-arid and lithologically variable Guadalupe Mountains, New Mexico and Texas, USA. Finally, we generalize our results by estimating uncertainties that may arise from assuming constant and uniform erodibility coefficients in simple stream power erosion models, compared to erodibilities that potentially vary spatially and temporally.</p>
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