Hydrological regimes, sampling strategies, and assessment of errors in mass load estimates for United Kingdom rivers

Abstract A computational framework is presented for heuristic investigation of the performance of different algorithms and sampling frequencies for estimating river mass loads. The approach adopted is to generate a time series of synthetic concentration, from a time series of obsereved streamflow, on the basis of available information on the covariation of flow and concentration for the determinand and site of interest. A reference mass load for the whole, or any part, of the time series is calculated from the flow and synthetic concentration time series. Combinations of different estimation algorithms and (periodic) sampling intervals can be applied and the resultant mass load estimated compared with the reference value. For a chosen estimation algorithm, the distribution of mass load estimates derived from replicated samples leads to measures of accuracy (bias) and precision (random error). A qualitative comparison of the performance of two mass load estimation algorithms, specified by the Paris Commission for monitoring fluvial inputs to the North Sea, is presented using the hydrological regime of a 20-km2 catachment in southwest England and two general cases of hysteretic concentration behaviour: concentration increases with flow and concentration decreases with flow. In each case, a better estimate of river mass load is obtained when the variation in flow between concentration samples is taken into account.