Abstract
Sediment load estimations are often limited by the difficulty in finding an adequate calculation method adapted to infrequent sediment concentration data. In this article, classic calculation methods (averaging estimators, ratio estimators and rating curves) are tested using 61 river basin datasets from the French river quality database (infrequent but longβterm datasets). The analyses and results show that averaging methods are inadequate in deriving sediment fluxes from datasets with daily discharge (Q) data and infrequent sediment concentration (C) data. Considering classic powerβrating curves, analyses of C(Q) relations for the 61 datasets show significant differences between seasons, flow variations and in function of the antecedent conditions of flows. The subdivision of datasets is thus essential before performing any C(Q) fitting. Moreover, the C = aQ^b^ relation only relates instantaneous C and Q values, disregarding the influence of temporal flow dynamics. Rating curve equations, including the dynamic of discharge time series, are established and tested. One equation and approach is selected: an improved rating curve approach (IRCA), which combines a fitting based on the description of sediment stock dynamics with the flow variation subdivision [between rising limbs (RL) and falling limbs (FL) of the hydrograph]. This method was validated with daily datasets from the US Geological Survey (USGS) database. This rating curve equation can be used to quantify sediment exports from infrequent data, for numerous river basins in temperate areas. Copyright Β© 2010 John Wiley & Sons, Ltd.