New estimates of flood exposure in developing countries using high-resolution population data.

Area of Science:

• Environmental science
• Demography
• Risk assessment

Background:

• Current global flood exposure estimates rely on homogenous population data, leading to significant miscalculations.
• Existing demographic datasets inaccurately represent population distribution in flood-prone areas, overestimating exposure.

Purpose of the Study:

• To assess global flood exposure using high-resolution population data.
• To demonstrate the impact of population distribution on flood exposure calculations.
• To highlight the need for revising current flood risk assessment methodologies.

Main Methods:

• Utilized ~90m resolution hydrodynamic inundation models for flood hazard data.
• Integrated new, highly resolved population datasets.
• Analyzed flood exposure in 18 developing countries across Africa, Asia, and Latin America.

Main Results:

• High-resolution population data shows humans are risk-averse and avoid flood zones.
• Current demographic datasets misrepresent population concentrations, spreading exposed populations over larger areas.
• Flood exposure calculations differ significantly when using refined population data.

Conclusions:

• Human population distribution is more risk-averse than previously estimated.
• Existing methods for calculating flood exposure require significant revision based on refined population data.
• Accurate population data is crucial for effective flood risk management.