Probabilistic Coastal Inundation (File Download)

Map layers showing the extent of potential future coastal inundation have been developed for the coastline of Australia. These can be used for hazard assessment, in conjunction with information about local inundation effects and historic inundation events. An example application of the hazard layers using the Australian Exposure Information Platform (AEIP) to generated exposure reports is also provided for 2100.
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Click here for: Coastal Inundation States/Territories - LGA's

Coastal inundation layers are available for all Local Government Areas (LGAs) within Australia for different annual probabilities of coastal inundation (greater than 95%, between 95% and 50%, between 50% and 5% and less than 5%) for a given average recurrence interval (ARI) extreme coastal water level. The layers are at 5 metre resolution and are available in vector spatial file formats (.geoJSON .shp).

The layers available for download represent 20-year periods centred on 2005 (baseline) and projected future periods centred on 2050 and 2100 for two different global socioeconomic pathways (SSP1-2.6 and SSP5-8.5L*) including a low-confidence, high impact scenario that assumes high-end future greenhouse gas emissions and rapid ice sheet loss (SSP5-8.5L*). Two flood frequencies are available to identify land that will be likely flooded every year (1 year ARI) and land that will have a 1% chance of being flooded in a year (100 year ARI, when conceptualised in a stationary climate). AEIP exposure reports are provided for the year 2100 for both SSPs and a 100 year ARI return level.

On request layers are also available for 20-year periods centred on 2030, 2050, 2090, 2100 and 2150 for five different global socioeconomic pathways (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5), plus a low-confidence, high impact scenario that assumes high-end future greenhouse gas emissions and rapid ice sheet loss (SSP5-8.5L) for a range of ARIs. Extraction of exposure reports from the AEIP is also posible for requested hazard layers. 

Zipped folders representing different time periods, SSPs, and ARI combinations include both shapefile and geoJSON files for the resulting hazard layers. An automated report, ending in "report.html," is also generated. This report details the values used to create the hazard layers and includes tables of extreme water levels, plots showing return levels and future water level predictions, as well as low-resolution plots of the input domains and the resulting hazard layers. The geoJSON files for the hazard layers include graphical attributes that can be displayed when uploaded into web mapping software (e.g. National Map) A shapefile is also provided which details the input data and calculated water levels (i.e. the metadata)

*The high-end scenario was selected because it in part addresses the significant uncertainty in the possible SLR estimates (beyond the IPCC likely range) from the contribution of glacial melt, and regional variations in mean sea levels (Fox-Kemper et al 2021). Also the high-end scenario (SSP 5-8.5) covers the range of state government policy benchmarked SLR allowance, which are designed to manage future risk associated with coastal flooding and erosion. For example, South Australia has a sea level planning benchmark of 1 metre by 2100, which is much higher than the AR6 upper range value of 0.92 for 2100 for a 4C global warming level (SSP3-7.0). The upper range value of SSP 5-8.5 Low Confidence is also the only scenario that covers a previous national coastal risk assessment which adopted 1.1 m as a plausible value for sea-level rise based on post AR4 science.  

Tech Report link avalible soon.


O'Grady, Julian; Gregory, Rebecca; Erwin, Tim; & Hemer, Mark (2024): Probabilistic Coastal Inundation. v1. CSIRO. Service Collection. 

Conditions of use and acknowledgement


Use of the data is subject to the CSIRO AgData Shop conditions of use ( In addition:

Further information and feedback

You are encouraged to contact us at if you require assistance with the data, including its interpretation. Feedback on the data, including on its utility, documentation, pricing and conditions of use is welcome.