Case Studies
Jul 8, 2021

Hydrometeorological Data-Based Methodology for Navigability Risk Analysis at Waterways: Case Study for Magdalena River

Publication: Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 147, Issue 5

Abstract

The characterization and quantification of risk in port activities are essential to determine the main factors that may cause incidents and to establish risk mitigation strategies to improve the safety and operability of ports. This study presents a novel methodology to analyze the hydrometeorological risk of navigation in fairways and port activities, which is applied to the study case of the 22-km section of the lower Magdalena River, near the port of Barranquilla (Colombia). The methodology is based on probabilistic models of dominant hydrometeorological variables (e.g., water depth, flow velocity, wind magnitude, and wave height) identified via hazard and operative (HAZOP) studies. It allowed for quantifying likelihood and vulnerability levels obtained by empirical functions representing monthly spatio-temporal risk. It can be applied at any stage of fairway design and is highly replicable at other geographical conditions. The results for the study area show that the main risk factors for the reference vessel (i.e., SUPRAMAX) are the wave height and the fairway depth, which on up to 15% of the cases restrict navigation and induce deviations and economic losses to the port authority.

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Acknowledgments

The authors acknowledge the assistance of the Observatory of the Magdalena River of the Universidad del Norte. Additional support has been provided by Cormagdalena with the provision of essential information for this research under Agreement 1-0009-2019 Cormagdalena-Uninorte. Ronald R. Gutierrez acknowledges the research group GERDIS (Pontificia Universidad Católica del Peru) for supporting this contribution.

Notation

The following symbols are used in this paper:
Fnh
dimensionless Froude number of the vessel;
F(x)
probability in a cumulative distribution function of a random variable X;
F−1(x)
inverse of a cumulative distribution function;
L(FX(x))
empirical likelihood level function for a random variable X;
V(FX1(x))
empirical vulnerability level function for a random variable X; and
X
random or aleatory variable.

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Go to Journal of Waterway, Port, Coastal, and Ocean Engineering
Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 147Issue 5September 2021

History

Received: Mar 17, 2021
Accepted: May 27, 2021
Published online: Jul 8, 2021
Published in print: Sep 1, 2021
Discussion open until: Dec 8, 2021

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Authors

Affiliations

Research Assistant, Laboratory of Computational Hydraulics, Institute of Hydraulic and Environmental Studies (IDEHA), Dept. of Civil and Environmental Engineering, Universidad del Norte, Km 5 via Puerto Colombia, Bloque K, L3-2K, Barranquilla, CO 081007 (corresponding author). ORCID: https://orcid.org/0000-0003-2435-6207. Email: [email protected]
Associate Professor, Institute of Hydraulic and Environmental Studies (IDEHA), Dept. of Civil and Environmental Engineering, Universidad del Norte, Km 5 via Puerto Colombia, Bloque K, 9-03K, Barranquilla, CO 081007. ORCID: https://orcid.org/0000-0002-8064-9584. Email: [email protected]
Ronald R. Gutierrez, Ph.D. [email protected]
Associate Professor, GERDIS Research Group, Dept. of Engineering, Pontificia Universidad Católica del Perú, Av. Universitaria 1801, Lima 32, Lima, PE. Email: [email protected]

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