Fitting sediment rating curves using regression analysis: a case study of Russian Arctic rivers

• Published in: Proceedings of the International Association of Hydrological Sciences
• Main Author: N. I. Tananaev
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2015
• Subjects: Environmental sciences; GE1-350; Geology; QE1-996.5; Arctic; Hooke
• Online Access: https://doi.org/10.5194/piahs-367-193-2015; https://doaj.org/article/b244938ae5fa409396a10db8809a4d63

Published suspended sediment data for Arctic rivers is scarce. Suspended sediment rating curves for three medium to large rivers of the Russian Arctic were obtained using various curve-fitting techniques. Due to the biased sampling strategy, the raw datasets do not exhibit log-normal distribution, which restricts the applicability of a log-transformed linear fit. Non-linear (power) model coefficients were estimated using the Levenberg-Marquardt, Nelder-Mead and Hooke-Jeeves algorithms, all of which generally showed close agreement. A non-linear power model employing the Levenberg-Marquardt parameter evaluation algorithm was identified as an optimal statistical solution of the problem. Long-term annual suspended sediment loads estimated using the non-linear power model are, in general, consistent with previously published results.