Robust estimators for turbulence properties assessment

TL;DR

This paper introduces robust estimators and filtering techniques for accurately assessing various turbulence properties from water level measurements, improving upon classic methods in terms of prediction accuracy.

Contribution

It proposes new robust estimators and compares their effectiveness with traditional methods in turbulence assessment from high-frequency water level data.

Findings

Robust estimators improve accuracy of turbulence quantity predictions.

Filtering techniques influence the estimation results.

Robust methods outperform classic techniques in the case study.

Abstract

Robust estimators and different filtering techniques are proposed and their impact on the determination of a wide range of turbulence quantities is analysed. High-frequency water level measurements in a stepped spillway are used as a case study. The studied variables contemplated: the expected free surface level, the expected fluctuation intensity, the depth skewness, the autocorrelation timescales, the vertical velocity fluctuation intensity, the perturbations celerity and the one-dimensional free surface turbulence spectrum. When compared to classic techniques, the robust estimators allowed a more accurate prediction of turbulence quantities notwithstanding the filtering technique used.