Description
Coastal floods can lead to significant economic impacts by damaging infrastructure, disrupting businesses, and imposing substantial costs on communities for recovery and resilience efforts. The Coastal Flood Historical Baseline Risk dataset captures historical risk of coastal flooding across the world using modeled flood hazard data, incorporating land subsidence and sea level rise scenarios. This product can be used to assess both the relative and absolute risk of coastal flood at different locations.
Technical Description
The Global Coastal Flood Risk products capture the historical risk of flooding across the globe using underlying data from the World Resource Institute Aqueduct Floods v2.0 dataset. The WRI data represent riverine and coastal flood depths for return periods of 2, 5, 10, 25, 50, 100, 250, 500, and 1000-years under both historical baseline conditions and future projections for the years 2030, 2050, and 2080, based on Representative Concentration Pathway (RCP) 4.5 (steady carbon emissions) and RCP 8.5 (rising carbon emissions). Coastal flood hazard data incorporate land subsidence and sea level rise scenarios. Flood probabilities are calculated based on return periods, while damage risks are computed by fitting data to a polynomial curve modeled using JRC global generic infrastructure data and subsequently applying the Trapezoidal Rule for frequency curve integration. Modeled damage risks do not account for flood protection infrastructure.
This dataset contains the following fields:
- flood_probability: The maximum annual flood probabilities per pixel representing the annual rate of flood occurrence; e.g., a pixel with a value of 0.2 expects flooding every 5 years, on average. The maximum value is 0.5, as the shortest return period in the data is 2 years. The range of values is between 0 and 0.5.
- avg_annual_damage_risk: The average annual damage risk per pixel, modeled using a combination of flood depth data across nine return periods. Values are calculated by integrating a depth exceedance frequency-damage curve. The result provides an estimate of potential average annual loss at a specific location. This value is represented at a 1 km/pixel resolution and assumes no flood protections or building-specific measures and therefore may overestimate risk. The maximum value is 0.5, as the shortest return period in the data is 2 years. The range of values is between 0 and 0.5.
- avg_annual_damage_risk_class: The average annual damage risk classification for each value. Values are integers from 1 to 5 representing the following classes: Very Low Risk (1), Low Risk (2), Moderate Risk (3), High Risk (4), and Very High Risk (5). Values are categorized using the 44th, 67th, 84th, and 94th percentiles of the respective historical avg_annual_damage_risk field, exclusive of '0' values.