The [Southern Lakes flood hazard mapping study](https://flood-atlas.service.yukon.ca/pages/final-flood-maps) was completed between November 2022 and April 2024. Learn more by visiting the [Yukon Flood Atlas](https://flood-atlas.service.yukon.ca/pages/final-flood-maps).In the Resources section below, you can find the project summary, technical report, "What We Heard" report, GIS data files, and flood maps for specific areas."AEP" in the flood map filenames below refers to "Annual Exceedance Probability", the annual likelihood of a flood occurring, expressed as a percentage.The flood scenarios used for mapping in the Yukon are the following:- 0.5% event (1-in-200 chance of occurring in any year),- 1% event (1-in-100 chance of occurring in any year), and- 5% event (1-in-20 chance of occurring in any year).For more information see [What is flood mapping?](https://flood-atlas.service.yukon.ca/pages/flood-mapping) or email [FloodMapping@yukon.ca](mailto:floodmapping@yukon.ca).### See also- [Carmacks flood hazard maps](https://open.yukon.ca/data/datasets/carmacks-flood-hazard-maps)- [Teslin flood hazard maps](https://open.yukon.ca/data/datasets/teslin-flood-hazard-maps)

This series of historic flood susceptibility maps comes from an XGBboost machine learning model trained on major floods from 2005 to 2023. The trained model is then run for each year from 2000 to 2023, including unique temporal characteristics of temperature, precipitation, land use land cover and Normalized Difference Vegetation Index (NDVI), to predict the flood susceptibility of any given year.Parent Collection:- **[Collection - Flood Susceptibility Mapping- Cartographic Product Collection](https://open.canada.ca/data/en/dataset/1074f781-85d3-4c86-86cb-fd1c339197dc)**

The [Teslin flood hazard mapping study](https://flood-atlas.service.yukon.ca/pages/final-flood-maps) was completed between May 2023 and October 2024. Learn more by visiting the [Yukon Flood Atlas](https://flood-atlas.service.yukon.ca/pages/final-flood-maps).In the Resources section below, you can find the project summary, technical report, "What We Heard" report, GIS data files, and flood maps for specific areas."AEP" in the flood map filenames below refers to "Annual Exceedance Probability", the annual likelihood of a flood occurring, expressed as a percentage.The flood scenarios used for mapping in the Yukon are the following:- 0.5% event (1-in-200 chance of occurring in any year),- 1% event (1-in-100 chance of occurring in any year), and- 5% event (1-in-20 chance of occurring in any year).For more information see [What is flood mapping?](https://flood-atlas.service.yukon.ca/pages/flood-mapping) or email [FloodMapping@yukon.ca](mailto:floodmapping@yukon.ca).### See also- [Carmacks flood hazard maps](https://open.yukon.ca/data/datasets/carmacks-flood-hazard-maps)- [Southern Lakes flood hazard maps](https://open.yukon.ca/data/datasets/southern-lakes-flood-hazard-maps)

The [Carmacks flood hazard mapping study](https://flood-atlas.service.yukon.ca/pages/final-flood-maps) was completed between April 2023 and May 2024. Learn more by visiting the [Yukon Flood Atlas](https://flood-atlas.service.yukon.ca/pages/final-flood-maps).In the Resources section below, you can find the project summary, technical report, "What We Heard" report, GIS data files, and flood maps for specific areas."AEP" in the flood map filenames below refers to "Annual Exceedance Probability", the annual likelihood of a flood occurring, expressed as a percentage.The flood scenarios used for mapping in the Yukon are the following:- 0.5% event (1-in-200 chance of occurring in any year),- 1% event (1-in-100 chance of occurring in any year), and- 5% event (1-in-20 chance of occurring in any year).For more information see [What is flood mapping?](https://flood-atlas.service.yukon.ca/pages/flood-mapping) or email [FloodMapping@yukon.ca](mailto:floodmapping@yukon.ca).### See also- [Southern Lakes flood hazard maps](https://open.yukon.ca/data/datasets/southern-lakes-flood-hazard-maps)- [Teslin flood hazard maps](https://open.yukon.ca/data/datasets/teslin-flood-hazard-maps)

The Canada Flood Map inventory shows areas in Canada where a copy of a flood hazard map has been collected by Natural Resources Canada (NRCan). The inventory does not display flood zones or extents, but provides information on how to access these flood hazard maps. Depending on the license and availability status to the public, there may be links for download, along with reference information to the original source and/or data owner. NRCan collaborates with provincial and territorial governments to gather flood hazard maps from provinces, territories, municipalities, and other agencies responsible for flood mapping. The inventory is regularly updated to improve its completeness and accuracy. Disclaimer: The Canada Flood Map (CFM) does not include every flood hazard map in Canada and may be incomplete or contain inaccuracies. It should not be relied upon as the official source of flood mapping information. Furthermore, if a map appears to be missing, this does not necessarily mean that the area has never been mapped. For the official version of a map, updated information, or confirmation of applicable regulations, please contact the local authority responsible for flood mapping.Note: Data and maps in the Inventory can be made available upon request to federal and contributing partners.

This series of projected future flood susceptibility maps were generated using an XGBoost machine learning model trained on major floods from 2005 to 2023. The trained model was applied to future climate scenarios for 2050, 2070, and 2100, under two scenarios: 245 and 585. The model uses temperature and precipitation time series to estimate potential future flood susceptibility. These maps represent model projections and should be interpreted as indicators of potential flood susceptibility, not precise forecasts. **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

This series of projected future flood susceptibility maps were generated using an XGBoost machine learning model trained on major floods from 2005 to 2023. The trained model was applied to future climate scenarios for 2050, 2070, and 2100, under two scenarios: 245 and 585. The model uses temperature and precipitation time series to estimate potential future flood susceptibility. These maps represent model projections and should be interpreted as indicators of potential flood susceptibility, not precise forecasts. **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

This series of projected future flood susceptibility maps were generated using an XGBoost machine learning model trained on major floods from 2005 to 2023. The trained model was applied to future climate scenarios for 2050, 2070, and 2100, under two SSP scenarios: 245 and 585. The model uses temperature and precipitation time series to estimate potential future flood susceptibility. These maps represent model projections and should be interpreted as indicators of potential flood susceptibility, not precise forecasts.

This collection of flood susceptibility products captures temporal patterns of historic flood events from 2000 to 2023, derived from flood susceptibility maps. The layers are designed to support decision-making by providing easily interpretable information for planning, screening, and other management purposes.This collection contains several datasets which explore the suite of rasters from 2000 to 2023:- Extreme wet and extreme dry years and the associated average flood susceptibility, processed by NHN WU, as found by Generalized Extreme Value (GEV) analysis- Flood susceptibility envelope, which is derived from the above wet and dry years- Trend slope, for each pixel the value for each year is extracted and the linear trend is computed, greater than 1000 is increasing flood susceptibility and below 1000 is decreasing flood susceptibility. - Trend Class, as identified by wet and dry scores, applied to NHN WU- Current flood susceptibility, which represents the estimated average value of present-day flood susceptibility- Current interquartile range, which provides and indication of the temporal variability of a given pixel under the current regime.

This series of historic flood susceptibility maps comes from an XGBboost machine learning model trained on major floods from 2005 to 2023. The trained model is then run for each year from 2000 to 2023, including unique temporal characteristics of temperature, precipitation, Land Use Land Cover (LULC) and Normalized Difference Vegetation Index (NDVI), to predict the flood susceptibility of any given year. **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**