Monitoring nutrient transport in large rivers

Abstract

The problem of estimating nutrient transport in large rivers and the uncertainty of such load estimates was studied both empirically and theoretically. In the empirical part of the study, time series of data from the Rhine, Meuse, Vistula and Oder Rivers were examined. The results of this data analysis justify the use of linear interpolation to estimate concentrations prevailing between sampling occasions. A special study of the spatial variation of concentrations within different cross-sections of the Vistula river showed that such variation can contribute substantially to the uncertainty of load estimates. In general, however, sampling at one point in the cross-section did not result in biased load estimates. In the theoretical part of the study, simple ARMA (autoregressive-moving average) models were used to derive generally applicable formulas for the expected mean square error of load estimates based on serially dependent concentration data. These formulas were then used to estimate the uncertainty of calculated nutrient loads in the Rhine and the Vistula, respectively.