The ClimateIndex™ Report Methodology

Flooding

• We have utilised Ambiental floodmap datasets to identify the extents and depths of fluvial (river), tidal (coastal), and pluvial (surface water) flooding across the whole of NSW.
• We have utilised data delineating areas benefiting from flood defences and mitigated the risk in these areas according to the standard of protection they offer.
• We have conducted comprehensive flood risk assessments based on the maximum risks to the property boundary (with consideration given to areas benefiting from flood defences where possible) using multiple modelled flood scenarios, including 1 in 20 year (5% annual chance), 1 in 100 year (1% annual chance), and 1 in 500 year (0.2% annual chance) flood events.
• Flood depths exceeding 1m are flagged as they can cause more catastrophic damage to property sites and pose a threat to human life.
• Flood depths exceeding 0.2m are flagged as they align with average doorstep heights and can enter your property (assuming no resilience measures have been applied to the property).

Bushfires

• We have conducted a comprehensive assessment of bushfire risk to the property based on all areas of land considered bushfire prone (as classified in the bushfire prone land dataset) within a radius of the property. 
• Our assessment is based on NSW Bushfire Prone Land data, considering the vulnerability classification of the bushfire prone areas and multiple supplementary datasets.
• Forest Fire Danger Index data is used to indicate the likelihood and severity of weather conditions (vegetation dryness, air temperature, wind speed and humidity) in each bushfire prone area which influences the risk of ignition. Specifically, we use CSIRO-modelled FFDI data, considering three modelled exceedance probabilities (1 in 20 year – 5% annual chance, 1 in 100 year- 1% annual chance, and 1 in 500 year – 0.2% annual chance) to reflect severity and likelihood. 
• Our bushfire climate risk assessment is calculated based on the same modelled FFDI data used in our today assessment, but modelled for 30 years into the future based on the SRES A1FI emissions scenario. 
• We use historic fire data within bushfire prone areas in our calculators to increase (wildfire) or reduce (prescribed burns) the risk rating. More recent wildfires have a greater influence on increasing the risk rating for a bushfire prone area, and similarly more recent prescribed burns reduce the risk more, indicating a more current fire risk mitigation strategy is in place. We use the Department of Planning and Environment Fire History and Fire extent and severity mapping data to determine historic wildfires and prescribed burns.
• Lightning strikes are a dominant natural cause of wildfire ignition in Australia. Accordingly, Groundsure has sourced data on the average annual number of lightning strikes per 1km2 and we increase the risk in bushfire prone areas related to their relative historic lightning strike occurrence.
• Bushfires in bushfire prone areas in close proximity to built-up urban landscapes are less likely to pose a threat to adjacent properties as they will be subject to more rapid identification, suppression and emergency response. Conversely, bushfires in rural areas are more likely to grow and spread before being identified. We, therefore, use an urban landscapes dataset from Geoscience Australia and slightly reduce the risk for bushfire prone land inside and in close proximity to these urban areas.
• To assess risk to the property, we consider all (if present) bushfire prone land within a radius of the property. We measure the distance and average slope angle (based on the relative height above sea level of the property and bushfire prone land) between the property and all bushfire prone land within the radius, reducing risk with increased distance and reduced uphill angle to the property. Bushfire travels faster uphill and bushfire prone land downhill from a property presents a higher risk to said property, and the steeper this angle the greater the risk.
• The highest score from all bushfire prone land within the radius of the property, after scores are amended by distance and slope between the property and bushfire prone land, is then applied to the property. It may therefore be that the closest bushfire prone land to the property doesn’t drive the highest risk to the property, based on our multifaceted approach. 

Coastal erosion

• Our property level coastal erosion risk rating is primarily calculated by projecting local historic erosion rates forward in time and estimating the time to coastline collision with the property. 
• Distance between the property and the nearest coastline dataset, either the Geoscience Australia Smartlines coastline or the Digital Earth Australia 2021 coastline is measured. The maximum (highest) local annual erosion rate (calculated between 1988 and 2021) is calculated from the DEA rate of change point dataset. 
• The erosion rate is adjusted depending on the local coastline geomorphology, specifically the fabric (dominant coastline material constituents) and form (dominant slope and steepness of the coastline). Coastlines more susceptible to erosion given future climate change (increased severity and frequency of storm and storm surges, increased sea acidity, and rising sea levels) are adjusted with an erosion rate multiplier which reflects the vulnerability. Historic erosion rates are increased by a multiplier which combines the local fabric and form classifications to account for increased erosion with ongoing climate change. 
• Based on this geomorphology-multiplied historic erosion rate we finally calculate the number of years for the coastline to meet the property from today and a baseline of 30 years in the future. This time is classified into a risk rating for the property.