Calculation of river sediment fluxes from uncertain and infrequent measurements

This paper addresses feasibility issues in the calculation of fluxes of suspended particulate matter (SPM) from degraded-quality data for flow discharge (Q) and sediment concentration (C) under the additional constraints of infrequent and irregular sediment concentration samplings. A crucial setting of the scope involves establishing the number of data required to counterbalance limitations in the measurement accuracy and frequency of data collection. This study also compares the merits and drawbacks of the classical rating curve (C = aQ(b)) with those of an improved rating curve approach (IRCA: C=aQ(b) + a1 delta S) in which the correction term is an indicator of the variations in sediment storage, thus relating it to flow dynamics. This alternative formulation remedies the known systematic underestimations in the classical rating curve and correctly resists the degradation in data quality and availability, as shown in a series of problematic though realistic cases. For example, monthly concentration samplings (in average) with a random relative error in the [-30%, +30%] range combined with daily discharge records with a systematic relative error in the [-5%, +5%] range still yield SPM fluxes within factors of 0.60-1.65 of the real value, provided that 15 years of data are available. A shorter 5-day time interval (on average) between samplings lowers the relative error in the SPM fluxes to below 10%, a result directly related to the increased number of Q-C pairs available for fitting. For regional-scale applications, this study may be used to define the data quality level (uncertainty, frequency and/or number) compatible with reliable computation of river sediment fluxes. Provided that at least 200 concentration samplings are available, the use of a sediment rating curve model augmented to account for storage effects fulfils this purpose with satisfactory accuracy under real-life conditions. (C) 2013 Elsevier B.V. All rights reserved.