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Summary: We consider estimating the total load from frequent flow data but less frequent concentration data. There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO x ) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO x Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated. [Copyright &y& Elsevier]

Interactions between catchment variables and sediment transport processes in rivers are complex, and sediment transport behaviour during high-flow events is not well documented. This paper presents an investigation into sediment transport processes in a short-duration, high-discharge event in the Burdekin River, a large sand- and gravel-bed river in the monsoon- and cyclone-influenced, semi-arid tropics of north Queensland. The Burdekin's discharge is highly variable and strongly seasonal, with a recorded maximum of 40 400 m3 s−1. Sediment was sampled systematically across an 800 m wide, 12 m deep and straight reach using Helley-Smith bedload and US P-61 suspended sediment samplers over 16 days of a 29-day discharge event in February and March 2000 (peak 11 155 m3 s−1). About 3·7 × 106 tonnes of suspended sediment and 3 × 105 tonnes of bedload are estimated to have been transported past the sample site during the flow event. The sediment load was predominantly supply limited. Wash load included clay, silt and very fine sand. The concentration of suspended bed material (including very coarse sand) varied with bedload transport rate, discharge and height above the bed. Bedload transport rate and changes in channel shape were greatest several days after peak discharge. Comparison between these data and sparse published data from other events on this river shows that the control on sediment load varies between supply limited and hydraulically limited transport, and that antecedent weather is an important control on suspended sediment concentration. Neither the empirical relationships widely used to estimate suspended sediment concentrations and bedload (e.g. Ackers & White, 1973) nor observations of sediment transport characteristics in ephemeral streams (e.g. Reid & Frostick, 1987) are directly applicable to this river. [ABSTRACT FROM AUTHOR]