This polygon layer reflects short-range (up to 84 hours) accumulated precipitation forecasts from the Regional Deterministic Prediction System (RDPS), a high-resolution (~10 km) weather model developed by Environment and Climate Change Canada (ECCC). It supports flood forecasting, hydrological modeling, and operational planning by providing refined, near-real-time precipitation guidance for Canada and surrounding areas.Short-Range Forecasts: RDPS runs multiple times per day, offering precipitation outlooks for days 0–3.5 with updates every six hours. High Resolution: At ~10 km, RDPS captures critical mesoscale phenomena like localized downpours, lake-effect snow, and terrain-driven precipitation. Hydrological Utility: Especially valuable for sub-basin-level flood risk assessment and water resource management in near-term scenarios. Technical Basis: The RDPS is a limited-area configuration of the GEM model, using initial/boundary conditions from ECCC’s Global Deterministic Prediction System (GDPS).

The Ministry of the Environment, the Fight against Climate Change, Wildlife and Parks (MELCCFP) is developing and operating a system for forecasting the level and flow of certain waterways in southern Quebec. The purpose of these hydrological forecasts is to allow more informed planning of interventions, both for flood or low water situations and under more common hydrological conditions.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This feature layer showcases ultra-fine (2.5 km) short-range precipitation forecasts from the High Resolution Deterministic Prediction System (HRDPS), a convection-permitting model by Environment and Climate Change Canada. It identifies local-scale rainfall or snowfall patterns up to 48 hours, supporting urban flood forecasting, severe weather response, and detailed water resource planning.Convection-Permitting: The HRDPS can explicitly resolve thunderstorms and other small-scale weather events by running at ~2.5 km. Short-Range Focus: Typically provides forecasts out to 36–48 hours, updated several times daily. Local Impact: Valuable for pinpointing high-impact precipitation in complex terrain or urban environments, aiding emergency managers and hydrologists in short-lead-time decisions. Nested Model: Receives lateral boundary conditions from RDPS, maintaining consistency with regional forecasts while refining detail in local domains.

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.This dataset forms part of a broader collection of flood susceptibility datasets, offering related information and analyses. The collection includes an overview page with associated publications, historic susceptibility values, temporal trends, and future projections.- [Collection – Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/1074f781-85d3-4c86-86cb-fd1c339197dc)- [Trends and Extremes – Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/3202e0a0-0afb-4120-b102-b0c41f0fb9eb)- [Future - Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/c00f95a3-7bab-4d28-b9cc-b30f06b5afd2)

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 dataset forms part of a broader collection of flood susceptibility datasets, offering related information and analyses. The collection includes an overview page with associated publications, historic susceptibility values, temporal trends, and future projections.- [Collection – Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/1074f781-85d3-4c86-86cb-fd1c339197dc)- [Historic - Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/ea1384df-bf4a-4743-97bb-870dc43f8d77)- [Trends and Extremes – Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/3202e0a0-0afb-4120-b102-b0c41f0fb9eb)

Data on flood zones include mapping carried out as part of the mapping program of the Canada-Quebec Convention from 1976 to 2001, the Program for the determination of flood ratings from 2001 to 2004 (PDCC), as well as the mapping carried out after that date by the Centre d'expertise du Québec (CEH) and its various partners.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This polygon layer displays 84-hour accumulated precipitation forecasts from the Regional Deterministic Prediction System (RDPS), aggregated at the sub-basin level. This layer helps hydrologists, water resource managers, and emergency responders identify watersheds with potentially higher rainfall or snowfall, facilitating short-term flood risk analysis and operational planning.Model & Domain: The RDPS is Environment and Climate Change Canada’s regional numerical weather prediction model, running at ~10 km resolution to capture mesoscale weather patterns over Canada and adjacent regions. Forecast Integration: It produces short-range forecasts (up to 84 hours), updated 4 times daily with boundary conditions from the global GEM model (GDPS). Sub-Basin Aggregation: This layer averages forecasted precipitation across each sub-basin polygon, providing a convenient snapshot of expected accumulations for hydrological modeling and water management. Key Applications:Flood Forecasting – Identifying basins at risk of heavy runoff. Resource Allocation – Positioning crews and equipment in vulnerable watersheds. Planning – Adapting reservoir release schedules, urban drainage controls, and agricultural activities

## Get data on boundaries of local climatic areas used for forest fire weather forecasting. This dataset shows the boundaries of administrative areas used for forest fire weather forecasting. North of the French River, boundaries correspond closely with Environment Canada’s areas for public weather forecasting. South of the French River, 25 Environment Canada areas are combined into six larger areas for provincial forecasting.

The [Southern Lakes flood hazard mapping study](https://floods.service.yukon.ca/pages/final-flood-maps) was completed between November 2022 and April 2024. Learn more by visiting the [Yukon Flood Hub](https://floods.service.yukon.ca).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://floods.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/carmacks-flood-hazard-maps)- [Dawson City / Klondike Valley flood hazard maps](https://open.yukon.ca/data/dawson-city-klondike-valley-flood-hazard-maps)- [Old Crow flood hazard maps](https://open.yukon.ca/data/old-crow-flood-hazard-maps)- [Teslin flood hazard maps](https://open.yukon.ca/data/teslin-flood-hazard-maps)- [Upper Liard flood hazard maps](https://open.yukon.ca/data/upper-liard-flood-hazard-maps)

This polygon layer shows the spatial distribution of forecasted accumulated precipitation across watershed sub‑basins using data derived from the Regional Ensemble Prediction System (REPS). In other words, it aggregates precipitation amounts—computed from processed REPS forecast output (converted from GRIB2 files into raster [TIF] format)—over defined watershed boundaries to provide a detailed view of expected rainfall over a typical 72‑hour forecast period. This information supports regional hydrological forecasting, flood risk analysis, and water resource management.REPS forecast data are first processed to extract the accumulated precipitation field (APCP) and converted into high‑resolution raster images. These “REPS APCP rasters” represent the spatial distribution of forecast precipitation (in millimeters) over the region. Next, using pre‑defined watershed or sub‑basin boundaries, zonal statistics are applied to compute the average precipitation for each sub‑basin. The final layer displays these averaged values as polygon features, highlighting variations in forecasted rainfall across different drainage areas. This approach helps users pinpoint regions that may receive higher or lower rainfall, thereby enhancing hydrological assessments and emergency planning.