Open AccessA new method to predict average flow velocity and conveyance capacity of meandering streams
Author(s) -
Cristopher Alexander Gamboa-Monge,
Ana María Ferreira-Da-Silva,
Laura Segura-Serrano,
Isabel Guzmán-Arias
Publication year - 2020
Publication title -
tecnología en marcha
Language(s) - English
Resource type - Journals
eISSN - 2215-3241
pISSN - 0379-3982
DOI - 10.18845/tm.v33i6.5286
Subject(s) - streams , flow resistance , flow (mathematics) , geology , hydrology (agriculture) , alluvium , crossover , geotechnical engineering , bedform , open channel flow , flow conditions , mechanics , stream bed , environmental science , geometry , geomorphology , mathematics , sediment transport , physics , sediment , computer science , computer network , artificial intelligence
This paper aims to be a contribution to the evaluation of the resistance factor of the alluvial meandering streams of natural origin. The well-known “divided resistance” approach, commonly adopted nowadays for straight streams with a bed covered by ripples and dunes is extended to include an additional term that considers the resistance due to the meandering of the stream. For the present analysis, 40 laboratory experiments and 285 field observations are evaluated, where it is found that the contribution of the meandering of the stream to its overall resistance may vary from negligible to very substantial, which depends on the stream geometric and flow conditions.
In addition, it is determined that the most influential components for the resistance factor in meandering conditions depend on the relation between channel-averaged flow depth (hav) and the average grain size of the bed material (D50), the deflection angle of a meandering flow at the crossover Oi (θ0), and also the relation between flow width (B) and the channel-averaged flow depth (hav); these relations are used to develop a mathematical expression capable to predict the resistance to flow due to the meandering of the stream. It is shown that the equation introduced in this paper leads to considerably improved predictions of average flow velocity and conveyance capacity of meandering streams, which is of significance for an improved management of inland waterways.