Abstract
The use of site-calibrated models for predicting bedload transport in gravel-bed rivers remains relatively rare, despite advances in methodology and computing technology, and its notable advantages in terms of predictive accuracy. This article presents a new algorithm for site calibration of the Parker–Klingeman (1982) model, along with a detailed discussion of considerations that influence model selection and calibration methodology. New visualization techniques are explored to demystify the calibration process, using three examples with progressively more challenging calibration conditions. The new method is particularly well suited to streams with high sediment loads, or cases where extrapolation of transport function estimates is necessary.
Highlights
Estimating bedload transport in gravel-bed rivers is difficult in practice
Comparison of the bedload plotted against average shear stress versus water discharge for each site reveals less scatter when shear stress is used as a predictor of bedload
This is evident at Oak Creek, where six of the samples were taken during hydraulic conditions that necessitated a different water surface elevation—to discharge rating curve
Summary
Estimating bedload transport in gravel-bed rivers is difficult in practice. Efforts to produce bedload models for practical applications relied on simple functions of stream power (e.g., [4]) or bed shear stress (e.g., [5]) in excess of a critical threshold for particle mobility. This critical shear stress, or critical Shields stress in non-dimensional form [6], was often assumed to be a constant, even though there were various interpretations of what that value should be, as summarized in the thorough review by Buffington and Montgomery [7]. Thresholds for grain mobility are not well represented by a single number, but depend on both the riverbed grain size distribution and the degree of surface coarsening [8,9]
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