Evaluation of quasi-maximum likelihood and smearing estimator to improve sediment rating curve estimation

Salarijazi, Meysam; Abdolhosseini, Mohammad; Ghorbani, Khalil; Eslamian, Saeid

doi:10.1504/ijhst.2016.079352

Cited by 8 publications

(1 citation statement)

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“…It is clear that differences in methods of estimating the suspended sediment quantity can lead to quite different estimations of annual longterm sediment load of a given basin [16][17]. Methods for estimating suspending sediment load of rivers often fallen into the two categories of "hydrological methods" and "hydraulic methods", the former being considered as more suitable in practice due to its ease of use [18]. The Conventional model of Sediment Rating Curve (SRC) is a simple well-known hydrological method for estimating suspended sediment load of rivers, which takes advantage of a power regression equation between suspended sediment load (dependent variable) and river flow discharge (independent variable) [19].…”

Section: Introductionmentioning

confidence: 99%

Developing a Sediment Rating Curve Model Using the Curve Slope

Ghadim¹,

Salarijazi²,

Ahmadianfar³

et al. 2020

Pol. J. Environ. Stud.

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There are different ways to estimate suspended sediment load of a river. The conventional sediment rating curve model has been used widely due to its simplicity and required parameters. The most important limitation of the conventional SRC model is its relatively low precision and underestimation of the suspended sediment load in most studies. However, in this study, the concept of SRC model segmentation is introduced based on the curve slope under the title of developed SRC-S model. The most important feature is the simplicity of the presented application. To compare the conventional SRC and the developed SRC-S models, data from two hydrometry stations in northern Iran were selected. Graphical study of the models shows that the developed SRC-S model enjoys more fitting precision in comparison with the conventional SRC model, and also has improved underestimation error of suspended sediment load in higher rates of river flow discharge. Six numerical criteria for model accuracy (Nash-Sutcliffe, root-mean-square error, and mean absolute error, difference ratio, efficiency ratio improved and index of agreement) are used for quantitative comparison of the results of conventional and developed models. Accordingly, we found that the mentioned criteria have improved significantly compared to the conventional model.

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Section: Introductionmentioning

confidence: 99%