Science - Details for Coastal Inundation Risk Report
Sea Level Rise Model
In the "Land Check" analysis, we check the land against a range of the sea level rise projections, up to NOAA’s ‘Extreme’
sea level rise projection of 2.5m by 2100 (Sweet et al. 2017).
For the 'House Check', we apply sea level rise projections under a range of climate change scenarios, as provided by the Intergovernmental Panel on Climate Change, as published in its 5th Assessment Report, and the 'extreme' scenario developed by National Oceanic and Atmospheric Association. Whilst these scenarios are considered to be the best science currently available, actual sea level rise levels may fall outside of this range over the course of time. You should refer to the relevant scientific publications for a full explanation of their respective levels of confidence and limitations.
Probabilistic Risk Engines
Climate Valuation uses cloud based servers running specialist software built specifically to analyse extreme weather and climate change impacts to location specific assets. This is proprietary software owned by Climate Risk Pty Ltd and based on national and international patent applications. Some of Australia’s largest infrastructure utilities use this software. Find out more at ClimateRisk.com.au.
Tectonic movements mean that different locations are moving up and down over time relative to the Australian Height Datum. This information is needed alongside tidal and wave data to estimate the future probabilities of inundation. We use a Glacial Isostatic Adjustment model to calculate this change. The nearest modelled point may be shown on the map in your Climate Valuation report if it is near your nominated address. These points exist at all major tidal gauges around Australia, and therefore provide relatively fine scale data.
Tide Gauge Data
The model does not consider the impact of tides and tidal forcing on estuaries, rivers or other inland water bodies (nor any other risk associated with such inland flooding). Whilst tidal forcing can, in some areas, heavily impact on estuarine flood risk many kilometres from the ocean, in other areas they are less prone to wave set-up and tidal impacts. This is highly locationally specific, and universal scientific data is not currently available. You should seek specific advice on the risk to your property from estuarine and other inland flood risks under relevant climate change scenarios.
The model potentially underestimates the impacts of cyclonic events on coastal inundation risks in tropical and sub-tropical areas, all else being equal. Cyclonic events data is not separately factored into the Climate Valuation model. Whilst the Canute 2.0 tidal dataset purports to account for cyclonic impacts on sea level measurements, this methodology may not accurately capture the full extent of cyclones as the modelling capabilities have advanced considerably in the time since its conception, and the inclusion of Cyclones in this data set is considered to be somewhat simplified.
Digital Elevation Model
The Climate Valuation system uses a digital elevation model (DEM) at a 5-metre grid resolution of populated coastal areas around Australia to estimate the ground height of properties being analysed. The ‘bare earth’ DEM provides vertical elevations referenced to the Australian Height Datum (AHD). The sourced datasets are generally consistent with the Australian ICSM LiDAR Acquisition Specifications, which require a fundamental vertical accuracy of at least 0.30m (95% confidence) and horizontal accuracy of at least 0.80m (95% confidence). Geoscience Australia's ELVIS portal provides access and information about this dataset. This dataset covers most populated areas along the coast and therefore potentially impacted by Coastal Inundation. However there are some areas that are missed. In this case we use the elevation data from Google’s Elevation API which uses an edited version of the STRM Dataset, accurate to around 30m. There are known discrepancies between the LiDAR elevation data and some surveying control points used - which may be of the order of a 1cm. The discrepancy is likely due to the vertical resolution of the LiDAR available, and surface accuracy, which in this model is to 5 square metres. Survey control points will be single points of greater elevation accuracy, however no houses rest on these Control Points, so using this data would also be inaccurate.
This system does not currently include the impacts from riverine flooding. The combined effects of riverine flooding and coastal inundation could impact many more properties than coastal inundation alone. Estuaries can also be impacted by tides and at this point we are not sure with which the system estimates these impacts.
The presence of waves is important in understanding potential coastal inundation impacts. Our model applies scientific data on 'wave set-up', which has the effect of elevating the effective sea level after waves have broken. This can increase coastal inundation beyond the shoreline. Our wave set-up data is based on joint probability analysis of data obtained from deep-water wave buoys (or, where such observational data is not available, their locational proxies) around Australia, in combination with tidal data (Haigh et. al, 2012).
The model defaults to the nearest deep-water buoy to the subject property. Proxy wave buoys have been added to the dataset where concerns about capturing different wave trains were raised. These two locations are Cape York on the eastern side, as waves on the western side will have different properties. The second proxy buoy is located in western Victoria to avoid using the wave train data from Tasmania. You can see a list of the available deep-water buoys below. The tool also provides you with an option to exclude the impact of wave and wave set-up from the modelling where you consider that the property is sheltered from wave impacts by other factors (such as bay, harbour or sea wall barriers).
Note that the model does not account for the effects of wave run-up, which is a phenomenon that occurs only where the wave meets the shoreline, and which can propel the water much higher up the beach (or other relevant immediate shoreline area) – but it is a very localised effect. It also currently excludes the impact of extreme weather events, including Cyclones and storm tides, which may be added to the analysis going forwards as robust, localised scientific data becomes available.
The location of the available buoys in latitude and longitude are:
Technical Reports and Papers
The Climate Valuation analytics use innovative computational techniques that are the subject of a series of technical and academic papers being prepared for publication. These will be shared on the ClimateValuation.com site as they are published.
Systems Under Development
As we refine our system we will be adding the capabilities below, which will further refine the analysis.
A thirty year hindcast model of wave characteristics exist for the globe with nested high resolution data for Australia and the Pacific Islands. With this dataset we will be able to accurately calculate the AEP of wave set up at resolutions around 7km.
The slope of the bay is very important to the calculation of wave set-up, as it will influence the amount of wave set-up that will occur. Due to this we will be calculating a range of set-up based on the type of bathymetry that is typically seen.
A tool to enable the user to determine where their risk is coming from will be trialled in the coming months. By including more detailed information about the construction of the house, for example building materials, and the age of the property, users can better understand their risks and therefore devise solutions.
The analysis is currently based on the centre of the building. If your block of land is steeply sloped, it’s possible the analysis may not be applicable over the whole land parcel or block. Further analysis may be required. In up-coming versions of Climate Valuation, the user will have the ability to move the locator for more accurate results, or to enter a specific latitude and longitude.
This tool aims to use the most up-to-date data for sea level rise projections, extreme water level analysis, relative land changes, and elevations. We have also used recent papers to determine how to combine all of this information to calculate your results.
Sea Level Rise Projections
Church, J.A., P.U. Clark, A. Cazenave, J.M. Gregory, S. Jevrejeva,
A. Levermann, M.A. Merri eld, G.A. Milne, R.S. Nerem, P.D. Nunn,
A.J. Payne, W.T. Pfeffer, D. Stammer and A.S. Unnikrishnan, 2013:
Sea Level Change. In: Climate Change 2013: The Physical Science
Basis. Contribution of Working Group I to the Fifth Assessment
Report of the Intergovernmental Panel on Climate Change [Stocker,
T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A.
Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA.
Sweet W., Kopp R. E., Weaver C. P., Obeysekera J., Horton R. M., Thieler E. R. & Zervas C. (2017) Global and regional sea level rise scenarios for the United States.
Haigh, I., Wahl, T., Rohling, E., Price, R., Pattiaratchi, C., Calafat, F. and Dangendorf, S. (2014). Timescales For Detecting a Significant Acceleration In Sea Level Rise. Nature Communications, 5.
DeConto, R. and Pollard, D. (2016). Contribution of Antarctica to past and future sea-level rise. Nature, 531(7596), pp.591-597.
Dicks, L., Almond, R. and McIvor, A. (2011). Arctic Climate Issues 2011: Changes in Arctic Snow, Water, Ice and Permafrost. Oslo: Arctic Monitoring and Assessment Programme, p.99.
Hansen, J., Sato, M., Hearty, P., Ruedy, R., Kelley, M., Masson-Delmotte, V., Russell, G., Tselioudis, G., Cao, J., Rignot, E., Velicogna, I., Tormey, B., Donovan, B., Kandiano, E., von Schuckmann, K., Kharecha, P., Legrande, A., Bauer, M. and Lo, K. (2016). Ice melt, sea level rise and superstorms: evidence from paleoclimate data, climate modeling, and modern observations that 2 °C global warming could be dangerous. Atmospheric Chemistry and Physics, 16(6), pp.3761-3812.
Land movement change
W.R. Peltier, 2004. Global Glacial Isostasy and the Surface of the Ice-Age Earth: The ICE-5G (VM2) Model and GRACE, Ann. Rev. Earth and Planet. Sci., 32, 111-149.
Tide Gauge Data
Haigh ID, Wijeratne EMS, MacPherson LR, Mason MS, Pattiaratchi CB,
Crompton RP & George S 2012, Estimating Present Day Extreme Total
Level Exceedance Probabilities Around the Coastline of Australia,
Climate & Ecosystems Cooperative Research Centre, Hobart, Tasmania.
National Tidal Centre, (2011). The Australian Baseline Sea Level Monitoring Project Annual Sea Level Data Summary Report July 2010 - June 2011. Kent Town: Australian Bureau of Meteorology, pp.6-8.
Geoscience Australia, (2016). Australian Height Datum - Geoscience
Australia. [online] Ga.gov.au. Available at:
[Accessed 20 Mar. 2016].
Geoscience Australia (2016). Geoscience Australia Metadata for Digital Elevation Model (DEM) of Australia derived from LiDAR 5 Metre Grid. [online] Available at: http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_89644 [Accessed 8 Feb. 2016].
Bom.gov.au. (2016). Tide Predictions for Australia, South Pacific and Antarctica. [online] Available at: http://www.bom.gov.au/australia/tides/ [Accessed 4 Apr. 2016].
New.mhl.nsw.gov.au, (2016). MHL Wave: Glossary. [online] Available
http://new.mhl.nsw.gov.au/data/realtime/wave/Glossary [Accessed 18
Data.qld.gov.au. [online]. Available from: https://data.qld.gov.au/dataset/coastal-data-system-historical-wave-data [Accessed January 29, 2016].
Transport.wa.gov.au. [onlin] Available from: https://www.transport.wa.gov.au/imarine/tide-and-wave-data-current.asp [Accessed January 26, 2016].
Nguyen, X., Tanaka, H. and Nagabayashi, H. (2007). Wave Setup at
and Inlet Entrances during the Low Pressure System in 2006.
Of Coastal Engineering, JSCE, 54, pp.321-325.
Office of Environment and Heritage, (2015). Floodplain Risk Management Guide. Sydney: Office of Environment and Heritage, pp.1-31.
Pugh, D. (1987). Tides, Surges, and Mean Sea-Level. Chichester: J. Wiley.
Stephens, S., Wadhwa, S., Gorman, R., Goodhue, N., Pritchard, M., Ovenden, R. and Reeve, G. (2013). Coastal inundation by storm-tides and waves in the Auckland region. Auckland, pp.1-138.
Kamphuis J. (1991) Incipient wave breaking. Coastal Engineering 15, 185-203.
Mallon, Methodology Report, AdaptWater. A climate change adaptation tool for the Australian water industry, 2013
McInnes, K.L., Church, J., Monselesan, D., Hunter, J.R., O’Grady, J.G., Haigh, I.D. and Zhang, X. (2015), Information for Australian Impact and Adaptation Planning in response to Sea-level Rise. Australian Meteorological and Oceanographic Journal 65, 127-49.
McInnes, K., Lipkin, F., O'Grady, J. and Inman, M. (2012). Modelling and Mapping of Coastal Inundation Under Future Sea Level Rise. Mapping and Responding to Coastal Inundation. Sydney: CSIRO Publishing.
Middelmann M. (2002) Flood Risk in South East Queensland, Australia. In: Water Challenge: Balancing the Risks: Hydrology and Water Resources Symposium 2002 p. 244. Institution of Engineers, Australia.
Hawkes, P. (2000). The joint probability of waves and water levels. Oxford: HR Wallingford.
Hunter, J., 2012. A simple technique for estimating an allowance for uncertain sea-level rise, Climatic Change, DOI 10.1007/s10584-011-0332-1.
Hancock, R. and Rea, M. (2016). Australian Storms and Floods: White Paper. Sydney: Zurich Australia Limited, pp.1-40.
Dean B., Collins I., Divoky D., Hatheway D. & Scheffner C. N. (2005) FEMA Coastal Flood Hazard Analysis and Mapping Guidelines Focused Study Report.
BMT WBM, (2010). Burrill and Conjola Lakes Floodplain Risk Management Studies and Plans.