Methodology for improving reliability of river discharge measurements

Abstract

Programs to monitor water characteristics are undertaken to identify any possible water pollution of a river. To compute reliable water pollution loads, accurate river discharge and pollutant/tracer concentrations are required. When pollutants/tracers are measured with sufficient precision, the accuracy of river discharge measurements becomes the most critical parameter of the pollutant load computation, as well as the largest error source. The absence of permanent measuring equipment in many rivers is a common difficulty for the implementation of monitoring programs. Alternatively, quick measurement methods which are low in cost and reliability (e.g. floats) are often employed to get an estimate of river discharges, when there are budgetary and time restrictions. In this paper, an original technique, mainly for use in ungauged rivers, is proposed for correcting river discharge measurements which have low levels of accuracy; this in turn would correct pollutant concentrations. A nonlinear optimization problem is developed based on water volume and pollutant mass conservation principles for river balance nodes, taking into consideration non-measurable latent quantities. Parallel measurements of discharge and tracers for representative cross-sections of a river and its tributaries are required. The measurement conditions should refer to the steady-state hydraulic conditions usually prevailing in the flow under consideration. In order to test the reliability of the method, a virtual river example is built, defining the real values of water characteristics and generating measurement sets via Monte-Carlo simulations combining random and systematic errors. For more than 92% of the generated measurement sets, the proposed technique results in a successful and acceptable correction for the total of the measured cross-sections. Finally, the method is applied to a real river and the measurements are corrected successfully.

Keywords: Measurement error-correction; Nonlinear optimization; River flowrate measurement; Tracer mass conservation; Water pollution load; Water volume conservation.