Abstract

River flow velocity is determined by the energy available for flow motion and the energy fraction lost by flow resistance. We compared the performance of different equations for the Darcy-Weisbach resistance coefficient (f) and empirical equations to predict flow velocity. The set of equations was tested using data from the Quinuas headwater mountain river in the Andean region. The data was collected in three Cascades, two Step-pools, and one Plane-bed covering a wide range of velocity magnitudes. The results reveal that nondimensional hydraulic geometry equations (NDHG) with a Nash-Sutcliffe efficiency index (EF) varying from 0.6–0.85 provide the most accurate velocity prediction. Furthermore, the study proposes a methodology applicable to all morphologies for defining the NDHG parameters using easily measured field data. The results show an improvement in predictability with EF values in the range of 0.81–0.86. Moreover, the methodology was tested against data from the literature, which was not divided into morphologies providing EF values of around 0.9. The authors encourage the application of the presented methodology to other reaches to obtain additional data about the NDHG parameters. Our findings suggest that those parameters could be related to reach characteristics (e.g., certain characteristic grain size), and in that case, the methodology could be useful in ungauged streams.

Highlights

  • Prediction of the mean velocity in a river is important from a scientific and practical point of view

  • Nondimensional hydraulic geometry equations (NDHG) are capable of directly estimating the mean velocity but have parameters that vary according to the river morphology [1]

  • Water 2021, 13, 2207 river morphology consisting of three Cascades, two Step-pools, and one Plane-bed

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Summary

Introduction

Prediction of the mean velocity in a river is important from a scientific and practical point of view. Nondimensional hydraulic geometry equations (NDHG) are capable of directly estimating the mean velocity but have parameters that vary according to the river morphology [1]. Mountain river characteristics such as steep slopes (bed slope (S0 ) greater than 0.2%) [3], an average depth comparable to bed material size [4], and a coarse, poorly sorted clast [5] result in resistance patterns that differ from plane rivers. Mountain river morphologies such as Step-pools [6,7,8,9], Cascades [10,11], and Plane-beds [8] add complexity to resistance analysis as each morphology possesses different resistance characteristics. Authors have estimated PEE uncertainties of 30% [5]

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