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Fluvial Flood, Historical, Baseline, Global (v1.0)

Description

Fluvial floods can lead to significant economic impacts by damaging infrastructure, disrupting businesses, and imposing substantial costs on communities for recovery and resilience efforts. The Fluvial Flood Historical Baseline Risk dataset captures historical risk of fluvial flooding across the world using inundation data derived from historical streamflow data. This product can be used to assess both the relative and absolute risk of fluvial flood at different locations.

Categories:
flood, hazard, river, fluvial, static, historical, global, spatiafi
Temporal Extent:
1980-01-01 to 2014-01-01
Region:
Global
Resolution:
1 km
Product Version:
1.0

Technical Description

The Fluvial Flood Historical Risk product captures the recent near-historical risk of fluvial (riverine) flooding across the world using inundation data derived from historical streamflow data. By combining multiple fluvial flood extent maps across different return periods, we can understand the annual probability of fluvial flood occurring at locations across the globe. This product can be used to assess both the relative and absolute risk of fluvial flood at different locations.

This dataset contains the following fields:

  • flood_probability: Probabilities of fluvial flood event (flood depths > 10 mm) occurrence at pixel locations in the historical period. Technically unitless but represents the annual rate of flood occurrence. For instance, a value of 0.1 would indicate an annual average 10-year flooding event rate (flood depths > 10 mm) of 0.1 between 1980 – 2013. The risk of flooding in a given location is calculated as the inverse of the smallest return period for a flooding event to exceed a flood threshold (> 10 mm) at each grid cell. For example, if the magnitude of a 10-year flooding event at a given cell is 15 mm, the flood risk assigned to that cell would be 1/10. Alternatively, if the magnitude of the 10-year flooding event at a cell is 5 mm, the model continues to iterate through the other return periods until it finds the smallest flooding event that exceeds 10 mm. The shortest return period available in the dataset is 10 years, which means that the largest flood probability obtained using this current approach is 10%. The range of values is between 0.0 and 0.1.