Abstract
Due to the presence of boulders and different morphologies, mountain rivers contain various resistance sources. To correctly simulate river flow using 1-D hydrodynamic models, an accurate estimation of the flow resistance is required. In this article, a comparison between the physical roughness parameter (PRP) and effective roughness coefficient (ERC) is presented for three of the most typical morphological configurations in mountain rivers: cascade, step-pool, and plane-bed. The PRP and its variation were obtained through multiple measurements of field variables and an uncertainty analysis, while the ERC range was derived with a GLUE procedure implemented in HEC-RAS, a 1-D hydrodynamic model. In the GLUE experiments, two modes of the Representative Friction Slope Method (RFSM) between two cross-sections were tested, including the variation in the roughness parameter. The results revealed that the RFSM effect was limited to low flows in cascade and step-pool. Moreover, when HEC-RAS selected the RSFM, only acceptable results were presented for plane-bed. The difference between ERC and PRP depended on the flow magnitude and the morphology, and as shown in this study, when the flow increased, the ERC and PRP ranges approached each other and even overlapped in cascade and step-pool. This research aimed to improve the roughness value selection process in a 1-D model given the importance of this parameter in the predictability of the results. In addition, a comparison was presented between the results obtained with the numerical model and the values calculated with the field measurements
Highlights
Flow resistance in a river is given by the energy losses due to the interaction of water with its flowing contour
The results revealed that the Representative Friction Slope Method (RFSM) influence on model performance was limited to the morphology and the magnitude of the flow, and that the effective and real physical parameters differed
The right-sided likelihood curve in plane-bed is formed when, in the solution, the Hydrologic Engineering Center (HEC)-RAS numerical model presents the critical depths as a response
Summary
Flow resistance in a river is given by the energy losses due to the interaction of water with its flowing contour. In 1-D and 2-D models, based on Saint-Venant/shallow water equations, the energy losses are expressed by an “effective roughness coefficient,”. The inherent uncertainties present in the application of a 1-D hydrodynamic model lead to discrepancies between the “effective roughness coefficient” (ERC) and the “physical roughness parameter” (PRP) calculated using field measurement data. Natural uncertainties deal with the natural variation in a phenomenon [4], while epistemic uncertainties are related to the lack of knowledge of a system. These uncertainties include: (a) model structure, due to simplifications performed in the model to bring a natural phenomenon into a mathematical representation [5,6];
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