How does data analytics contribute to maritime and coastal design?

Modern maritime and coastal design goes far beyond site visits and historical records. Data analytics enables designers to:

Maritime and coastal design projects draw on a wide range of data, including:

• Bathymetric and topographic surveys (mapping seabed and land)
• Metocean data (waves, tides, currents, wind, water levels)
• Sediment transport and erosion rates
• Climate projections (sea level rise, storm intensity)
• Ecological and habitat data
• Socio-economic and land use information
• Asset and infrastructure inventories
• Community feedback and historical records

For a major port authority, our geotechnical investigations combined soil sampling, groundwater measurements and historical data to guide stormwater basin design, all informing the final report.

Maritime and coastal design teams use a range of analytics methods, including:

Numerical modelling

Simulating waves, tides, sediment movement and storm surges using computer models is a cornerstone of modern coastal design.

Statistical analysis

Assessing the likelihood of extreme events, such as one-in-100-year storms, and combining different hazard scenarios is essential for risk-based planning.

GHD and Systems Engineering Australia developed a CHAS for a local government area covering coastal communities. The CHAS used the SEAsim model to simulate storm tide risks, combining synthetic cyclone climatology with hydrodynamic and wave models. This provided probabilistic storm tide level predictions for both present and future climate scenarios, including allowances for sea level rise and increased cyclone intensity.

Geospatial analysis and mapping

Using a geographic information system to overlay hazard zones, infrastructure and land use helps planners visualise risks and adaptation pathways. In addition to this, we routinely develop bathtub modelling to assess potential inundation extents resulting from coastal hazards. This approach enhances our understanding of vulnerability and informs more targeted and resilient planning strategies.

Remote sensing and drone surveys

Collecting up-to-date imagery and elevation data to monitor shoreline change or habitat health is increasingly common. We have used drone technology to monitor the spread of invasive species and inform targeted conservation actions for coastal habitats.

Drone surveys are increasingly employed for condition inspection and assessment purposes. This approach mitigates onsite risks and offers cost efficiencies for clients — for instance, by eliminating the need for vessel hire. The data collected through these surveys can be integrated into machine learning and AI systems to support the early identification of environmental changes or areas requiring attention.

Machine learning and AI

Emerging approaches use AI to detect patterns in large datasets, such as predicting erosion hotspots or automating the classification of coastal features.

While data analytics offers huge benefits, it’s not without challenges.

• Data quality and availability: Maritime and coastal environments are vast and variable, and collecting high-quality, long-term data can be expensive or logistically difficult.
• Model uncertainty: All models are simplifications. Uncertainties in climate projections, sediment dynamics or storm behaviour can affect the reliability of predictions.
• Integration of diverse datasets: Combining physical, ecological and social data requires careful management and sometimes creative solutions.
• Communicating complexity: Translating technical results into actionable insights for decision-makers and communities is an ongoing challenge.
• Adapting to change: As new data becomes available or conditions shift (e.g., after a major storm), analytics and design approaches need to be updated.

Overcoming these obstacles will be crucial to fully unlocking the potential of data analytics and keeping coastal management effective and responsive. The iterative, trigger-based adaptation pathways developed through the Pilot Coastal Hazard Adaptation Strategy (CHAS) for Townsville City Council demonstrate how data-driven design can remain flexible and promptly solve problems.