
Sea Level Rise
Sea level rise is one of the most significant global consequences of climate change and has become a major focus of international scientific research and coastal management.
- Evidence-led
- Traceable assumptions
- Decision-ready outputs
- Methods proportionate to risk
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Clarity before a decision is made
Sea Level Rise
Clarity before a decision is made
Sea level rise is one of the most significant global consequences of climate change and has become a major focus of international scientific research and coastal management.
Numerical modeling provides a comprehensive scientific approach for evaluating the combined effects of global sea level rise and local coastal processes on future shoreline evolution. This integrated approach combines coastal inundation models, which incorporate high-resolution topographic data, with ocean circulation models driven by tides, currents, waves, and wind forcing.

Decision Supported
Define the approach, priorities, and actions for sea level rise using traceable evidence.

Risk Controlled
Environmental impact, design failure, operational disruption, uncontrolled cost, and weak assumptions.

Success Criteria
Comparable options, quantified risk, and implementable recommendations.
What is assessed and why it matters

Shoreline position and change rate
This aspect is assessed to clarify its implications for sea level rise.

Waves, currents, tides, and sediment
This aspect is assessed to clarify its implications for sea level rise.

Sea-level rise and land subsidence
This aspect is assessed to clarify its implications for sea level rise.

Coastal structures and human activity
This aspect is assessed to clarify its implications for sea level rise.

Erosion–accretion scenarios
This aspect is assessed to clarify its implications for sea level rise.

Protection and adaptation alternatives
This aspect is assessed to clarify its implications for sea level rise.
A traceable evidence base

Observations
Field surveys, in-situ measurements, laboratory results, historical records, and operating information as required.

Remote sensing & GIS
Satellite imagery, mapping, spatial analysis, temporal change, and integration of multiple data sources.

Modeling & scenarios
Model setup, calibration, validation, existing–planned–extreme scenarios, and sensitivity analysis.

Quality assurance
Metadata, quality controls, assumptions, limitations, data versions, and processing lineage are documented.
Decision-ready information

Initial assessment & data gaps
Objectives, study area, available data, additional needs, initial risks, and recommended level of detail.

Datasets, maps & indicators
Quality-controlled data, thematic maps, time series, indicators, and comparable visualizations.

Scenarios & risk evaluation
Comparison of existing conditions, alternatives, extremes, sensitivities, consequences, and mitigation options.

Report & executive brief
Methods, results, limitations, recommendations, action priorities, and stakeholder presentation materials.
Benefits for decision makers and policy leaders

Reduce uncertainty
Assumptions, data, variability, and limitations are stated so decision risk is not hidden.

Compare options objectively
Alternative locations, designs, operations, or policies are assessed using consistent indicators.

Optimize cost and time
Data needs and analysis depth are proportionate to risk so resources are used efficiently.

Increase stakeholder confidence
Findings and recommendations are transparent for technical, management, regulatory, and partner review.
A clear process from need to recommendation
- 01

Need definition
Objectives, users, location, project phase, problems, constraints, and the decision to support.
- 02

Scope & work plan
Methods, data, surveys, models, schedule, team, deliverables, review gates, and resource estimate.
- 03

Acquisition & quality control
Collection, inspection, harmonization, documentation, and data-sufficiency assessment.
- 04

Analysis & scenario testing
Processing, modeling, validation, option comparison, sensitivity, and risk evaluation.
- 05

Recommendation & handover
Maps, report, executive brief, presentation, supporting data, and follow-up plan.
Full technical basis and contextOpen this section to read the complete source technical narrative.
Sea level rise is one of the most significant global consequences of climate change and has become a major focus of international scientific research and coastal management. Rising global temperatures accelerate the melting of glaciers and polar ice sheets. This melting adds freshwater to the oceans, while increasing ocean temperatures cause thermal expansion, reducing seawater density and increasing the overall volume of the world's oceans. Long-term observations from tide gauges around the world consistently demonstrate a rising trend in mean sea level. Numerous scientific studies have projected future sea level rise under various climate change scenarios. One of the most direct consequences for coastal areas is the gradual landward migration of the shoreline. Therefore, accurate shoreline change assessments must consider not only erosion and accretion caused by waves and sediment transport, but also the long-term impacts of global sea level rise.
Numerical modeling provides a comprehensive scientific approach for evaluating the combined effects of global sea level rise and local coastal processes on future shoreline evolution. This integrated approach combines coastal inundation models, which incorporate high-resolution topographic data, with ocean circulation models driven by tides, currents, waves, and wind forcing. Coastal inundation modeling is particularly important for low-gradient (gently sloping) coastal plains, where even a relatively small increase in sea level can result in extensive shoreline retreat and widespread coastal flooding. Long-term simulation scenarios, ranging from several years to multiple decades, enable coastal planners and decision-makers to evaluate future shoreline changes, identify vulnerable areas, and develop effective adaptation and coastal protection strategies.
The modeling framework typically integrates several numerical modeling modules. Hydrodynamic Models simulate tidal circulation, coastal currents, and water level variations. Spectral Wave Models, Wave Analysis Tools, and Boussinesq Wave Models evaluate wave energy, wave setup, and wave-induced water level increases. Overland Flood Models simulate coastal inundation by incorporating topographic data together with projected sea level rise scenarios. Coastal Morphology Models predict long-term shoreline evolution resulting from the combined effects of sea level rise and coastal processes. Finally, all simulation outputs are integrated within a Marine Geographic Information System (Marine GIS) to support spatial analysis, vulnerability mapping, and science-based coastal planning.
The numerical modeling modules commonly applied for sea level rise assessments include:
Share the need, location, available data, and the decision to be supported.
The CORZ team will review the objective, scope, data availability, risk level, schedule, and required outputs to prepare a proportionate approach.
- Location and project phase
- Decision or objective to support
- Primary problems and risks
- Available data
- Expected outputs and schedule