Improving the accuracy of hydrodynamic model predictions using lagrangian calibration

Neda Mardani; K Suara; Helen Fairweather; R Brown; Adrian B McCallum; Roy C Sidle

doi:10.3390/w12020575

Back

Improving the accuracy of hydrodynamic model predictions using lagrangian calibration

Journal article

Open access

Peer reviewed

Improving the accuracy of hydrodynamic model predictions using lagrangian calibration

Neda Mardani, K Suara, Helen Fairweather, R Brown, Adrian B McCallum and Roy C Sidle

Water, Vol.12(2), pp.1-20

2020

DOI: https://doi.org/10.3390/w12020575

Files and links (2)

pdf

PDF - Published Version (Open Access)4.43 MBDownload View

Published VersionCC BY V4.0, Open Access

url

https://doi.org/10.3390/w12020575View

Published Version

Abstract

estuary

eulerian instruments

hydrodynamic model accuracy

lagrangian drifters

model calibration

While significant studies have been conducted in Intermittently Closed and Open Lakes and Lagoons (ICOLLs), very few have employed Lagrangian drifters. With recent attention on the use of GPS-tracked Lagrangian drifters to study the hydrodynamics of estuaries, there is a need to assess the potential for calibrating models using Lagrangian drifter data. Here, we calibrated and validated a hydrodynamic model in Currimundi Lake, Australia using both Eulerian and Lagrangian velocity field measurements in an open entrance condition. The results showed that there was a higher level of correlation (R2 = 0.94) between model output and observed velocity data for the Eulerian calibration compared to that of Lagrangian calibration (R2 = 0.56). This lack of correlation between model and Lagrangian data is a result of apparent difficulties in the use of Lagrangian data in Eulerian (fixed-mesh) hydrodynamic models. Furthermore, Eulerian and Lagrangian devices systematically observe different spatio-temporal scales in the flow with larger variability in the Lagrangian data. Despite these, the results show that Lagrangian calibration resulted in optimum Manning coefficients (n = 0.023) equivalent to those observed through Eulerian calibration. Therefore, Lagrangian data has the potential to be used in hydrodynamic model calibration in such aquatic systems.

Details

Title: Improving the accuracy of hydrodynamic model predictions using lagrangian calibration
Authors: Neda Mardani (Author) - University of the Sunshine Coast
K Suara (Author) - Queensland University of Technology
Helen Fairweather (Author) - University of the Sunshine Coast
R Brown (Author) - Queensland University of Technology
Adrian B McCallum (Author) - University of the Sunshine Coast
Roy C Sidle (Author) - University of the Sunshine Coast
Publication details: Water, Vol.12(2), pp.1-20
Publisher: MDPI AG
Date published: 2020
DOI: 10.3390/w12020575
ISSN: 2073-4441
Copyright note: Copyright © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Grants: Innovative Global Navigation Satellite Systems (GNSS) - enabled technology for monitoring regular and flooded flows in Australian Waters., LP150101172, Australian Research Council (Australia, Canberra) - ARC
Organisation Unit: K'gari Research Cluster; School of Science and Engineering - Legacy; Indigenous and Transcultural Research Centre; Cancer Research Cluster; School of Science, Technology and Engineering; Sustainability Research Cluster
Language: English
Record Identifier: 99451271902621
Output Type: Journal article

Metrics

74 File views/ downloads

79 Record Views

24 Times Cited - Web of Science

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types: Domestic collaboration; International collaboration
Web Of Science research areas: Environmental Sciences; Water Resources

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

Source: InCites