Ottawa – On September 21, 2023, Environment and Climate Change Canada announced $8 million in funding toward flood mapping and climate adaptation. As part of this amount, $3 million has been awarded to universities and non-profit organizations under the Flood Hazard Identification and Mapping Program to develop flood science and integrate the impacts of climate change and uncertainty in flood mapping.
These are some of the funded projects:
Future scenarios of meteorological-forcing variables for hydrologic modelling and flood estimation in watersheds across Canada
Recipient: Pacific Climate Impacts Consortium – University of Victoria – $150,000
This project will create historical and future high-resolution datasets of meteorological variables such as temperature, precipitation, humidity, and wind speed, as well as estimates of rainfall intensity-duration-frequency to assess potential flood hazards across Canada. The project is estimated to conclude on March 31, 2024, and the data products will be made available on public repositories.
Developing scenarios of hydrologic change for gauged and ungauged basins across Canada
Lead Recipient: University of Calgary – $840,000
Consortium with Laval University, McMaster University, University of Saskatchewan
The overall aim of this project is to advance the use of climate information in water resources planning and management, and to identify hydrologic indicators that provide information that is readily usable by end-users, including experts and non-experts. This project will produce a set of hydrologic datasets that showcase current capabilities in hydrologic prediction for flood zone mapping.
Improving hydrologic simulations in the Canadian Earth System Model
Recipient: University of Saskatchewan – $165,000
This project will improve hydrologic simulations in the open-source collaborative version of the Canadian Earth System Model, resulting in improved future projections of hydrologic change. These improved hydrologic projections can be used to inform future climate change adaptation efforts related to freshwater resources and their impacts on flood zones.
Leveraging ECCC runoff products for high resolution and locally relevant peak streamflow estimation in ungauged basins in the Great Lakes/Ottawa River and Fraser River Basins
Recipient: University of Waterloo – $160,000
The project aims to enhance our understanding of local water systems. High-resolution models will be developed for two major regions in Canada: the Great Lakes/Ottawa River Basin and the Fraser River Basin in British Columbia. These models use the latest version of Environment and Climate Change Canada’s reanalysis data. The overall goal is to improve water resource management through a better understanding of local hydrologic processes.
Setup and deployment of machine-learning based models to simulate peak streamflows across the Great Lakes/Ottawa River Basin and the Fraser River Basin
Recipient: University of Waterloo – $115,313
This project focuses on deploying machine learning models to simulate hydrologic variables across large regions in Canada. The goal is to improve the accessibility and performance of these models by integrating them into a hydrologic modelling framework. The project aims to advance hydrologic simulations, benefitting water resource management in the region.
Developing a twin model for assessing the impacts of land use changes and forest fires on peak flows used in flood frequency analyses
Recipient: McMaster University – $95,000
This project aims to quantify the impact of land use, land cover, and forest fires on flood regimes in selected Canadian regions using a physically based and a machine-learning based hydrologic model. Model performances were evaluated as regards their ability to estimate peak flows.
High resolution, vector-based, lake-river routing networks for ECCC hydrometric gauges across Canada, using the national hydrometric network basin polygons v.2 geospatial dataset
Recipient: University of Waterloo – $90,000
Lake and river routing networks are a necessary component of hydrologic models used to understand flood zone distribution. This study concentrates on watershed models to improve the understanding of extreme streamflow. Watersheds were defined upstream of thousands of Environment and Climate Change Canada streamflow gauges across the country.
Interpolation of precipitation extremes for the development of intensity-duration-frequency (IDF) curves in Eastern Canada
Recipient: Polytechnique Montréal – $53,000
The objective of this project is to estimate intensity-duration-frequency (IDF) curves, which are essential for hydraulic modelling to identify floods. Presently, Environment and Climate Change Canada provides IDF curves solely for surface stations, leaving some regions without coverage. This project aims to expand coverage to areas lacking gauging stations and enhance estimates in regions with existing gauging stations.
Analysis and comparison of simple methods for estimating flood discharge in support of large-scale floodplain mapping in Canada
Recipient: Institut national de la recherche scientifique – $114,330
The project aims to link rainfall and flooding by identifying characteristics of rainfall sequences that influence peak streamflows and flood levels. Special focus is on factors affecting the magnitude of spring floods, including winter precipitation, spring liquid precipitation, and surface temperature changes.
Improved meteorological forcing of hydrologic models through the application of run-time empirical bias corrections of global and regional climate models
Recipient: Ouranos – $246,100
This project will apply the Canadian Centre for Climate Modelling and Analysis (CCCma) novel run-time empirical bias correction that has been shown to improve future projections for strong climate change, to regional climate models meteorological output fields used to drive hydrologic models (e.g. surface temperature, precipitation, humidity, wind speed).
Exploiting methods to constrain future climate projections over Canada for the hydrologic community
Recipient: Ouranos – $228,265
The goal of this project is to create datasets that include information collected during other funded projects into our applications to create better predictive models for hydrologic conditions, with the impacts of climate change taken into account. A paper summarizing the method and results of this multi-model study will be published in 2024.