Showing papers on "Bed material load published in 2018"
TL;DR: The proposed model can be an efficient alternative to conventional approaches for the simulation of bed material load transport rates providing comparable accuracy and has a better performance than a specific version of decision tree method.
Abstract: This study is trying to develop an alternative approach to the issues of sediment transport simulation. A machine learning method, named least square support vector regression (LSSVR) and a meta-heuristic approach, called particle swarm optimization (PSO) algorithm are used to estimate bed material load transport rate. PSO algorithm is utilized to calibrate the parameters involved in the model to facilitate a desirable simulation by LSSVR. Implementing on a set of laboratory and field data, the model is capable of performing more satisfactorily in comparison to candidate traditional methods. Similarly, the proposed method has a better performance than a specific version of decision tree method. To enhance the model, the variables are scaled in logarithmic form, leading to an improvement in the results. Thus, the proposed model can be an efficient alternative to conventional approaches for the simulation of bed material load transport rates providing comparable accuracy.
22 citations
TL;DR: In this article, in the absence of measured bed load data, the authors tested bed load computed using selected bed load sediment transport for Indian rivers. But the results were limited to Indian rivers only.
Abstract: Bed load data are scarcely measured continuously for Indian rivers. In the absence of measured bed load data, the present study tests bed load computed using selected bed load sediment transport fu...
3 citations
12 Dec 2018
2 citations
29 Nov 2018
TL;DR: In this article, the authors evaluated the reliability of the virtual velocity approach and the morphological method applied at the same dam-regulated study sector of the Parma River (Italy).
Abstract: Estimating the bed material transport in large gravel-bed rivers represents a challenging task. Among the alternatives to achieve estimates of such key process, the virtual velocity approach represents one of the most promising possibilities. The research aims at improving the virtual velocity approach and at evaluating the reliability of its transport estimates using an independent and robust procedure as the morphological method applied at the same dam-regulated study sector of the Parma River (Italy). After field and remote sensing data collection, we performed the coarse sediment transport calculations using the two selected approaches and compared the estimates obtained at the same river cross-sections. Since the two methods provided remarkably similar transport results over the period April 2016 - April 2017, the virtual velocity approach can be considered as a viable tool for achieving reliable bed material load estimates in large gravel-bed rivers.
1 citations