Modeling memory in gravel-bed rivers: A flow-history-dependent relation for evolving thresholds of motion

Abstract

Thresholds of motion (τcg-) strongly control bedload transport in gravel-bed rivers. Uncertainty in τcg-limits the accuracy of predictions of transport and morphologic change. To improve our quantitative understanding of morphodynamic feedbacks in rivers, we propose a flow-history-dependent model where τcg-evolves temporally as a function of bed shear stress. Relatively low shear stresses strengthen the bed, increasing τcg-And reducing transport. Larger floods rapidly weaken the bed, decreasing τcg-And increasing transport. We calibrate the model to a 23-year record of flow and bedload transport from the Erlenbach torrent, Switzerland, and find that the model predicts the field-based τcg-record more accurately than assuming a constant τcg-. Calibrated parameters describing strengthening are more tightly distributed than weakening parameters, which suggests that magnitudes of bed weakening may be more variable and difficult to accurately predict as a function of flood characteristics than bed strengthening during lower flows.