Abstract

Due to their low-lying coastal location, ports are vulnerable to climate change induced increases to flooding, waves, extreme winds, and the associated costly damages to port infrastructure and operational disruptions. For these reasons, there is an increasing need for ports to undertake regular risk assessments of the vulnerability of their infrastructure and operations due to the impacts of climate change.

A digital twin, cloud-based climate change modelling solution has been developed to enable in-house risk assessments of climate change vulnerability to be undertaken for any port. Once set-up, the system supports the continued sustainable operation of ports and enhancing stakeholder confidence in corporate sustainability strategies by allowing in-house re-evaluation of the ports climate risk as new predictions are released.

The basis of the digital twin model of the port are numerical wave and hydrodynamic models, configured with the actual port geography and bathymetry enabling highly detailed simulations of the ports physical environment. The numerical model simulations are supplemented with observations of wind, rainfall, and sea level to identify trends and extreme event probabilities under the historic climate conditions. Scenarios describing the predicted impacts of climate change can be superimposed on the historical climate via a web-based interface where the user (port) selects a planning horizon (e.g., 2050), storm event frequency (e.g., 100-year storm), and climate change predictions (e.g. RCP8.5). The resulting climate change simulations shows great potential to enable port-specific predictions of future impacts of extreme occurrences of wind, waves, water levels, and currents. The ports asset portfolio is incorporated in the risk assessment through dynamic GIS layouts and damage curves identifying the damage cause and cost for each vulnerable port asset.

As new climate science becomes available, this cloud-based digital twin model enables ports to rapidly complete updated risk assessments and respond to stakeholder queries and concerns.

The capability of the tool was validated by comparing the model results against a large conventional study of the region, and a historical flood event of 2011. Both validation exercises displayed a reasonable agreement increasing confidence in the model’s capacity as a predictive tool. Additionally, six climate change scenarios were modelled for one of Australia’s fastest growing container ports, Port of Brisbane and the results were successfully incorporated in the ports overall sustainability strategy.

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