Author(s): Jasna Muskatirovic; Peter Goodwin; Mark Morehead
Linked Author(s): Peter Goodwin
Keywords: Gravel-bed rivers; Bedload database; Bedload transport; Limited supply
Abstract: The complex task of prediction of bedload transport rates in gravel-bed rivers is analyzed utilizing field data for rivers and streams in Central Idaho. These analyses have revealed a set of problems related to the prediction of bedload transport rates in gravel-bed rivers under conditions of a stable armor layer and limited sediment supply. Sand and fine gravel prevailing in the bedload for wide ranges of flow discharges and modest availability of this material in the bed surface, indicate an significant role of external sediment supply on the bedload transport rates. Several approaches are evaluated to develop a better predictive equation for bedload transport rates in supply limited mountain gravel-bed rivers with coarse bed material: - the simple approach adopts a form of power law, similar to a sediment discharge rating curve. Although the approach lacks a physical basis, it does provide a simple equation with known error bounds for the available data. An evaluation of the coefficient and exponent also provides a way of analyzing differences between watershed and channel characteristics. The rating coefficient and exponent of the rating curve are evaluated using linear- and multiple-regression analysis; - the complex approach adopts a multiple-regression analysis of bedload samples. Following the general approach of Brownlie (1981), dimensionless numbers that represent local hydraulic and watershed conditions are derived to identify the significant processes and factors influencing bedload transport. The power law and multiple-regression equations for better prediction of bedload transport rates in gravel-bed rivers with stable armor layers are proposed, based on the regional dataset. In order to present the quality of proposed equations for prediction of bedload transport rates, comparison of the statistical parameters was performed. Median value and 16% and 84% values of the predicted versus measured bedload rates are determined for 8 bedload transport equations.