Future Flood Susceptibility Maps for 2050, 2070, and 2100 Under SSP Scenarios

Projected future flood susceptibility maps for 2050, 2070, and 2100 were generated using an XGBoost model trained on major floods from 2005 to 2023. The model, created by Natural Resources Canada, was applied to future climate scenarios under SSP 245 and SSP 585, using temperature and precipitation time series. These maps represent model projections and should be interpreted as indicators of potential flood susceptibility, not precise forecasts.

Use Cases

• Assessing regional flood risk under different climate scenarios based on SSP 245 and SSP 585 projections.
• Incorporating machine learning-based susceptibility indicators into broader climate adaptation planning.
• Comparing future flood susceptibility trends across multiple time horizons (2050, 2070, 2100).
• Validating hydrological or flood models using susceptibility maps derived from historical flood data (2005-2023).

Strengths

• Model trained on 19 years of major flood data (2005-2023).
• Provides projections for three distinct future time points (2050, 2070, 2100) under two SSP scenarios.
• Part of a broader collection offering historic data, trends, and associated publications for context.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect geographic bias inherent to the source platform (open_canada).

Provenance

Source

Natural Resources Canada

Collection Method

Generated using an XGBoost machine learning model applied to future climate scenarios.

Time Range

Projections for 2050,我们发现2070, and 2100; model trained on data from 2005 to 2023.

Freshness

Last updated 2026-04-24 11:31:04.718412; freshness should be verified.

Geography

Likely covers Canada, but specific spatial coverage is not detailed in the provided description.