Learn More
1 Project info
The presented material has been developed with the support of (i) the Natural Sciences and Engineering Research Council of Canada (NSERC) and Chaucer Syndicates Ltd collaborative research grant “Linking hazard, exposures and risk across multiple hazards”; (ii) the Université du Quebec a Montréal; and the Institute for Catastrophic Loss Reduction.
Project team: Prof. Slobodan P. Simonovic, Prof. Mohit Mohanty, and Dr. Andre Schardong.
1.1 Disclaimer
Flood hazard and flood risk maps provided on this website are generated using the CaMa-Flood model [1]. These maps are intended for use at national, provincial, or regional scales and can serve as a guide for identifying areas that require further investigation. Flood Hazard maps for current and future (climate change-affected) conditions, as well as Flood Risk maps, are available at a 1 km resolution. Due to uncertainties in the modeling process and variability in results, these maps serve as a starting point for identifying opportunities to enhance solutions through further exploration. For additional details on the use of the maps please review the User Guide section of the website.
This software tool is provided "as is", without warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose and non-infringement. In no event shall the authors or copyright holders be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, arising from, out of or in connection with the software or the use or other dealings in the software.
This tool requires the use of browsers with Javascript and jQuery compatibility. The latest versions of Chrome, Firefox and Microsoft Edge were tested and compatible.
The flood risk assessment tool is intended to empower users with the general information needed to make informed decisions about flood preparedness and mitigation. However, all outputs should be considered as part of a broader decision-making process involving local expertise and data. We encourage you to explore this tool for actionable insights into flood risk management at your location.
The data used in this work are publicly available.
- NARR data: https://psl.noaa.gov/data/gridded/data.narr.html and
- CMIP6 climate data: https://pcmdi.llnl.gov/CMIP6/
The information provided should be used at your own risk. By using this tool you agree with these terms.
1.2 Third party software used to build the tool:
- Angular: Angular is a TypeScript-based free and open-source web application framework led by the Angular Team at Google and by a community of individuals and corporations. Angular is a complete rewrite from the same team that built AngularJ.
- Angular Material: Angular Material is a UI component library for Angular JS developers. Angular Material components help in constructing attractive, consistent, and functional web pages and web applications while adhering to modern web design principles like browser portability, device independence, and graceful degradation. It helps in creating faster, more beautiful, and responsive websites. It is inspired by the Google Material Design
- Leftlet: Leaflet is the leading open-source JavaScript library for mobile-friendly interactive maps. The map information and photographic imagery contain trade names, trademarks, service marks, logos, domain names, and other distinctive brand features. (http://leafletjs.com/)
- Geoserver: GeoServer is an open-source server written in Java that allows users to share, process and edit geospatial data. Designed for interoperability, it publishes data from any major spatial data source using open standards.
- Google Geocoding API: converts physical addresses into geographic coordinates (latitude and longitude), enabling integration of precise location functionality into applications. It is widely used for mapping, navigation, and other location-based services. Accessing the functionalities requires an API key, that needs to be registered with Google by the maintainers of this tool.
2. Methodology
2.1 Flood Hazard Maps
The flood hazard maps available for viewing and download were developed using an original methodology developed by Mohanty and Simonovic [1, 2, 3, 4, 5]. Key elements of the methodology are presented here and the users are advised to consult available references for further details.
The provided flood hazard maps are developed using globally available data. Fourteen maps are created to present current conditions, and twenty-eight maps are created to capture changes in flood hazard regimes over Canada due to climate change. All the generated maps have 1km by 1 km grid resolution. Tables 1 through 3 list the maps available within the tool.
Table 1. Flood hazard maps for the current conditions| NARR 1979-2010 | CMIP6 1980-2019 | ||
| HNARR25 | NARR 1979-2010 25 yr | H25 | CMIP6 historical 25 yr |
| HNARR50 | NARR 1979-2010 50 yr | H50 | CMIP6 historical 50 yr |
| HNARR100 | NARR 1979-2010 100 yr | H100 | CMIP6 historical 100 yr |
| HNARR150 | NARR 1979-2010 150 yr | H150 | CMIP6 historical 150 yr |
| HNARR200 | NARR 1979-2010 200 yr | H200 | CMIP6 historical 200 yr |
| HNARR300 | NARR 1979-2010 300 yr | H300 | CMIP6 historical 300 yr |
| HNARR500 | NARR 1979-2010 500 yr | H500 | CMIP6 historical 500 yr |
| SSP2 (4.5) | SSP5 (8.5) | ||
| NF225 | Near future SSP2 25 yr | NF525 | Near future SSP5 25 yr |
| NF250 | Near future SSP2 50 yr | NF550 | Near future SSP2 50 yr |
| NF2100 | Near future SSP2 100 yr | NF5100 | Near future SSP2 100 yr |
| NF2150 | Near future SSP2 150 yr | NF5150 | Near future SSP2 150 yr |
| NF2200 | Near future SSP2 200 yr | NF5200 | Near future SSP2 200 yr |
| NF2300 | Near future SSP2 300 yr | NF5300 | Near future SSP2 300 yr |
| NF2500 | Near future SSP2 500 yr | NF5500 | Near future SSP2 500 yr |
| SSP2 (4.5) | SSP5 (8.5) | ||
| FF225 | Far future SSP2 25 yr | FF525 | Far future SSP5 25 yr |
| FF250 | Far future SSP2 50 yr | FF550 | Far future SSP2 50 yr |
| FF2100 | Far future SSP2 100 yr | FF5100 | Far future SSP2 100 yr |
| FF2150 | Far future SSP2 150 yr | FF5150 | Far future SSP2 150 yr |
| FF2200 | Far future SSP2 200 yr | FF5200 | Far future SSP2 200 yr |
| FF2300 | Far future SSP2 300 yr | FF5300 | Far future SSP2 300 yr |
| FF2500 | Far future SSP2 500 yr | FF5500 | Far future SSP2 500 yr |
The generic methodology used in the development of the flood hazard maps includes the following steps:
- Use runoff observations as input into the flood hazard mapping process;
- Fit an extreme value model to the continuous runoff data to derive 25, 50, 100, 150, 200, 300 and 500-yr runoff values;
- Feed the runoff values to the CaMa-Flood global hydrodynamic flood model;
- Feed the relevant River Basin characteristics and topographic information to the CaMa-Flood global hydrodynamic flood model;
- Run CaMa-Flood model simulations to derive flood hazard inundation outputs, e.g., river channel floodwater depth, discharge and velocity, and overland floodwater depth;
- Generate the simulated flood hazard maps for 25, 50, 100, 150, 200, 300 and 500-yr return periods from the CaMa-Flood model outputs.
- Step 1 involves downloading the runoff data from the respective websites. Maps H25 to H500 use the runoff data obtained from the CMIP6 ensemble for the period 1980 – 2019. The Coupled Model Intercomparison Project (CMIP) was introduced by the World Climate Research Programme (WCRP) in 1995. At the moment, the program is in Phase 6 (CMIP6). It utilizes advanced climate models for deeper insights into understanding the processes and mechanisms that influence the hydro-climatological phenomenon due to climate variability. The CMIP6 dataset provides gridded daily runoff over Canada in the form of a multi-model ensemble of 17 GCMs from the CMIP6 project. The 17 GCMs are selected based on their common availability in three periods for (i) historical: 1980 to 2019, (ii) near-future: 2020 to 2060, and (iii) far-future: 2061 to 2100. In the flood hazard mapping process, we consider both SSP2 4.5 (medium range of future forcing pathway) and SSP5 8.5 (high range of future forcing pathway) scenarios for the analysis. The CMIP6 climate projections propose the new Shared Socioeconomic Pathways (SSPs) that consider a wider range of air pollutant emissions, and address socioeconomic narratives as well. There are five different scenarios in the proposed SSPs, namely SSP1, SSP2, SSP3, SSP4, and SSP5. These scenarios were developed keeping in mind what the future might look like if climate policies were nonexistent, and how uniting the mitigation targets could address diverse levels of climate change mitigation. Maps HNARR25 to HNARR500 use the runoff data from the North American Regional Reanalysis (NARR) dataset for the period 1979 to 2010. NARR is a high-resolution atmospheric and land surface hydrology dataset covering North America. The observational dataset in NARR system uses an Eta 32-km atmospheric model and a 3D-VAR assimilation approach and has been found to represent extreme events such as floods and droughts adequately. NARR outputs are available every 3 h from 1979 to present at a grid resolution of 0.3◦. The runoff obtained from the NARR and CMIP6 ensemble is aggregated to a daily time scale to compare with the runoff at the corresponding Environment and Climate Change Canada observation stations.
- Step 2 generates a gridded runoff matrix for 1 in 25, 50, 100, 150, 200, 300 and 1 in 500-yr from NARR and CMIP6 runoff time-series data. The time series of runoff is fitted to Generalized Extreme Value (GEV) distribution to obtain gridded runoff values.
- Step 3 involves the use of 25, 50, 100, 150, 200, 300 and 500-yr runoff values by the CaMa-Flood model to produce Canada-wide flood hazard maps. The calibrated version of the CaMa-Flood model is used to simulate runoff on a regional scale. The CaMa-Flood global hydrodynamic model is widely used for large spatial scale distributed river routing. It is designed to simulate the hydrodynamics (i.e. river channel water level and discharge, overland water level, and inundation extent) over large regions. The model is driven by runoff forcing derived from either a land surface model or gridded observations such as reanalyses (maps HNARR25 to HNARR500) or GCMs (maps H25 to H500). The model quantifies the river channel and overland flood hazard hydrodynamics by considering a set of relevant global hydrologic details. An elaborate description of the structure of the model can be found in the attached references. The major advantage of the CaMa-Flood model over other global flood models is the explicit representation of the flood stage (water level and flooded area).
- Step 4 involves the integration of global hydrological details, such as Flow Direction Map, Global River Width, and Global Water Map with the runoff data to support CaMa-Flood model simulations. The CaMa-Flood model discretizes river basins into a set of hydrological units known as unit-catchments for efficient flow computation. The model set-up considers the most updated and readily available sub-grid river cross-section and channel roughness parameters for ensuring the least uncertainty in flood inundation parameters during calibration.
- Step 5 involves the use of calibrated CaMa-Flood model for simulating hydrodynamics over Canada. The model demonstrated high computational efficiency and suitability for parallel processing. Many studies have reported superior performance of CaMa-Flood. After model simulation, a post-processing diagnostic downscaling procedure is executed on the simulated Canada-wide flood hazard maps to improve the final resolution of the maps.
- Step 6 involves the generation of flood hazard maps for 25, 50, 100, 150, 200, 300 and 500-yr return periods. These maps contain quantitative information on river channel and overland water level (m), and overland inundation extent (km2).
2.2 Flood Risk Assessment
This module offers an advanced tool for assessing general flood risk at specific locations, using previously conducted flood hazard mapping [5]. Users can input their addresses to receive a general flood risk assessment based on current and projected future climate conditions.
The map and the risk assessment for the Current Conditions are developed by combining selected maps for CMIP6 (1980-2019) from Table 1. For each grid cell, the risk classification is grounded in the frequency of flooding events, following a comprehensive return-period analysis. The flood hazard maps for 25, 100, 200, and 500-year return periods are selected, and the most severe condition (highest probability) determines the level of risk:
- Extreme Risk: Areas with a 25-year return period (4% or higher chance of flooding annually)
- High Risk: Areas with a 100-year return period (1% - 4% annual flood probability).
- Moderate Risk: Areas with a 200-year return period (0.5% - 1% annual flood probability).
- Low Risk: Areas with a 500-year return period (0.2% annual flood probability or lower)
The following examples showcase the methodology:
Example 1:
- Flood Hazard Map Analysis:
- 25-year return period: Affected.
- 100-year return period: Affected.
- 200-year return period: Affected.
- 500-year return period: Affected.
- Risk Classification: Extreme Risk
Rationale: The area falls within the 25-year return period, indicating a 4% or higher annual chance of flooding.
Example 2:
- Flood Hazard Map Analysis:
- 25-year return period: Not affected.
- 100-year return period: Not affected.
- 200-year return period: Affected.
- 500-year return period: Affected.
- Risk Classification: Moderate Risk
Rationale: The most severe condition is a 200-year return period, corresponding to a 0.5% - 1% annual flood probability.
For more information on how to use the Risk Assessment, please refer to the User guide.
The same procedure is employed to generate the risk maps for the Future Conditions, which combine the maps from Table 2 and Table 3, resulting in the following four scenarios:
- Near future (2022-2060) - SSP2 (4.5)
- Near future (2022-2060) - SSP5 (8.5)
- Far future (2061-2100) - SSP2 (4.5)
- Far future (2061-2100) - SSP5 (8.5)
To access the Risk Assessment for the Future Conditions, please refer to the User guide.
2.2.1 Adaptation Recommendations:
Along with flood risk assessments, the tool provides general adaptation recommendations. These suggestions serve as initial guidance and should be adapted and refined to account for local conditions, infrastructure, and socioeconomic factors. Multiple national support is reviewed in support of provided general recommendations: (i) Canada’s National Disaster Mitigation Program (NDMP https://housing-infrastructure.canada.ca/dmaf-faac/index-eng.html ) provides grants and resources for flood mapping, public awareness, and local resilience projects. Additionally; (ii) Flood Ready (https://www.canada.ca/en/campaign/flood-ready.html ), an initiative supported by Public Safety Canada, provides Canadians with guidelines on individual flood preparedness, focusing on property modifications, emergency kits, and participation in flood warning systems; and (iii) The Canada Mortgage and Housing Corporation (CMHC https://www.cmhc-schl.gc.ca/professionals/housing-markets-data-and-research/housing-research/research-reports/housing-needs/research-insight-impact-catastrophic-flooding-canadas-housing-market ) also offers information on flood-resistant building techniques, encouraging proactive adaptation based on local flood risks.
Canada's varying flood-prone areas showcase a range of individual adaptations supported by federal and provincial guidance, aiming to minimize flood impact across different risk levels.
- Home Elevation or Floodproofing: Elevate the structure, especially essential living areas, or apply floodproofing techniques (e.g., water-resistant materials, barriers).
- Relocation: Consider relocating if repetitive severe flooding poses safety risks and significant financial impact.
- Backflow Prevention Systems: Install backflow valves on sewage lines to prevent floodwater from entering the home.
- Emergency Supplies and Flood Kit: Maintain a well-stocked emergency kit with food, water, medicine, and waterproof documentation.
- Evacuation Plan: Develop and practice an evacuation plan, keeping maps of safe routes and emergency contacts.
- Flood Insurance: Ensure robust flood insurance coverage if availale, as damage costs can be significant with frequent flooding.
- Home Modifications: Elevate utilities (e.g., electrical panels, heating systems) above flood levels. Use water-resistant finishes for walls and floors.
- Basement Waterproofing: Waterproof basement walls and install sump pumps with battery backups to manage floodwater.
- Drainage Improvements: Clear gutters, downspouts, and drainage systems regularly to facilitate water flow away from the home.
- Rain Gardens or Swales: Landscape with vegetation that helps absorb excess water around the property, minimizing runoff into living areas.
- Sandbags or Flood Barriers: Keep sandbags or temporary barriers handy to create a protective buffer around doors and windows.
- Flood Insurance: Obtain flood insurance if available to cover potential damages.
- Elevate Essential Appliances: Raise major appliances and electrical units above anticipated flood levels, especially in garages or basements.
- Floodproof Doors and Windows: Install flood-resistant doors, windows, and sealant on vulnerable entry points to minimize water intrusion.
- Landscape Grading: Adjust the grading around your property to direct water away from foundations and entryways.
- Store Valuables Safely: Keep important documents, electronics, and valuables on upper floors or high shelves.
- Know Emergency Contacts: Keep local emergency contacts and alert systems updated in case of unexpected floods.
- Flood Insurance Consideration: Flood insurance may still be valuable, particularly for valuable assets or homes with partial exposure to lower ground levels.
- Basic Home Preparation: Ensure property drainage systems (gutters, downspouts) are maintained to reduce flood potential.
- Elevate Critical Documents: Store critical documents and valuables in elevated, waterproof containers.
- Monitor Weather Warnings: Pay attention to weather advisories, especially during severe storms that might cause flash flooding.
- Emergency Preparedness Kit: Have a basic emergency kit ready, even though the likelihood of flooding is low.
- Awareness of Flood Zones: Be aware of your property's flood risk and local flood response plans, ensuring readiness for rare but severe events.
- Optional Flood Insurance: Consider flood insurance for added security, especially for properties with high-value assets.
- While this location is not at risk of river flooding, it may still be vulnerable to other types of flooding, such as urban, coastal, or groundwater flooding. It is important to consider these possibilities when assessing overall flood risk.
The above recommendations are based on the available international and national practices.
2.2.2 International experience
International experiences show how individuals have adapted to varying flood risks based on flood frequency. These examples provide insight into practical measures that have been effectively implemented around the world.
High-Frequency Flooding (Extreme Risk)
- Bangladesh: Many residents in flood-prone areas have elevated their homes on stilts. This traditional adaptation, commonly seen in rural areas along rivers, helps protect homes from regular seasonal flooding.
- United Kingdom (Thames Valley): Individuals use modular flood barriers and flood boards to seal doors and windows during high-risk flood seasons. This temporary solution is effective and affordable for residents in frequent flood zones.
- United States (Louisiana): In regions like New Orleans, people have raised electrical outlets, air conditioning units, and appliances to higher floors or platforms above flood levels, minimizing damage from frequent floods. Flood insurance is mandatory in high-risk areas, providing financial resilience for repeated flood events.
Medium-Frequency Flooding (High Risk)
- Japan: In moderately flood-prone areas, residents use sandbags and portable flood barriers, which are deployed when heavy rain is forecast. In addition, homes are often constructed with flood-resistant materials and waterproof coatings on lower levels to withstand occasional flooding.
- Netherlands: Many Dutch homeowners use rain gardens and permeable paving around their properties to absorb excess water. Home drainage systems are maintained regularly to ensure effectiveness during storms.
- Germany: In moderately flood-prone regions along the Rhine, homeowners have invested in basement waterproofing and sump pumps with backup power systems. This combination helps manage minor floods without costly structural damage.
Low-Frequency Flooding (Moderate Risk)
- Australia (Brisbane): Residents along the Brisbane River use landscape grading and water-tolerant plants in their gardens. This helps to absorb minor floodwaters and direct them away from buildings.
- Thailand: In some rural Thai villages, homes are raised on flood-resistant foundations, even in areas with moderate flood frequency. This proactive design not only mitigates flood risks but also protects against rising groundwater.
- Italy (Venice): While Venice is a unique case, many residents install temporary barriers for homes on lower floors and use specialized door seals to guard against the seasonal acqua alta, or high water, which is unpredictable but not frequent.
Rare Flooding (Low Risk)
- United Kingdom (Somerset Levels): Residents in low-frequency flood zones maintain emergency kits and sign up for flood alert systems, so they’re informed of rare flood events. In addition, low-lying property owners store valuables in waterproof containers.
- Canada (Prairies): In areas where flooding is rare, residents implement simple drainage solutions, such as clearing gutters and downspouts and keeping sump pumps in good condition to manage any sudden storm surges.
- France (Loire Valley): Homeowners monitor river levels during heavy rain seasons, even in low-risk areas. They store valuables in elevated spaces and have waterproof document storage in case of sudden flooding.
These measures reflect a mix of traditional and modern techniques that help people adapt to flood risks based on frequency, balancing resilience with cost-effectiveness.
2.2.3 National experience
High-Frequency Flooding (Extreme Risk)
- Red River Valley, Manitoba: Residents frequently face spring flooding due to snowmelt. Many homes are built with elevated foundations or are raised on stilts. Sandbagging is a common seasonal practice, with local governments and communities mobilizing resources to protect homes and property.
- Quebec (Richelieu River Region): In this flood-prone area, some homeowners use portable flood barriers and water-resistant materials on the lower levels of their homes. The Quebec government also offers support to relocate frequently flooded homes, as repeated floods have made permanent relocation a viable adaptation measure for some.
- British Columbia (Fraser Valley): Residents in this region, especially those near rivers and floodplains, commonly use backflow prevention systems and reinforce basements with waterproofing measures. Sandbags and temporary barriers are also widely used during flood season.
Medium-Frequency Flooding (High Risk)
- Ontario (Ottawa River): The Ottawa River has seen major floods in recent years. In response, residents have adopted sump pumps with backup power, reinforced doors and windows with waterproof barriers, and elevated essential utilities like furnaces and electrical panels. Flood preparedness training is also common among residents in higher-risk areas.
- Southern Alberta (Bow River Floodplain): After the devastating 2013 floods, many residents in moderately flood-prone areas elevated electrical outlets, re-landscaped to improve drainage, and added rain gardens around homes. The province also offers flood mapping and risk assessments to encourage at-risk homeowners to adopt protective measures.
Low-Frequency Flooding (Moderate Risk)
- Saskatchewan (Qu’Appelle Valley): In areas where flooding is rare but possible, homeowners manage risks by maintaining robust drainage systems around properties and storing important documents and valuables in waterproof and elevated locations. Residents also often use temporary flood barriers if forecasts predict heavy rain or snowmelt.
- New Brunswick (Saint John River): The province faces occasional riverine flooding in low-risk areas, especially during spring thaw. Homeowners often elevate appliances and keep sump pumps ready for unexpected events. Many also participate in emergency preparedness programs, which include guidelines on responding to rare flood events.
Rare Flooding (Low Risk)
- Ontario (Lake Ontario Coastal Areas): In low-risk flood zones along Lake Ontario, residents focus on preventive landscaping measures, such as permeable paving to allow water infiltration and the use of water-tolerant plants in gardens. Emergency kits and access to government flood warning systems are also standard practice for residents in areas that could experience occasional flooding.
- Prairie Provinces (General): Flooding is rare on the Prairies, but some regions are at risk of flash floods after intense rain events. Here, property owners ensure that downspouts and gutters are well-maintained, and they may add simple drainage solutions like gravel beds around foundations to channel water away from homes.
2.3 Geocoding Feature Overview
The geocoding feature used by the Flood Risk Canada tool is designed to simplify the process of translating physical addresses into precise geographic coordinates (latitude and longitude). When a user provides an address, the tool seamlessly processes it and converts it into a latitude and longitude pair. This transformation is powered by the Google Maps Geocoding API, a sophisticated service that combines Google's mapping data with algorithms to ensure accuracy and reliability (see section 1.2). The tool then uses this pair of coordinates to extract information from the maps and provide the Risk Assessment for the requested location.
2.3.1 How the Geocoding Feature Works
The process begins when a user inputs an address into the search box. This input can range from a simple street name to a fully detailed address, including city, state, and postal code. The tool then forwards the entered address to the Google Maps Geocoding API, which uses its algorithms to analyze and match the input with its extensive database of locations.
After processing the address, the API returns a structured response containing the latitude and longitude of the location. In addition to these coordinates, the API provides a standardized version of the address, known as the "formatted address.", which is displayed with the risk assessment. This ensures consistency and helps users confirm the accuracy of their input.
From the user’s perspective, the geocoding process is smooth and effortless. After entering an address, the tool processes the information in the background and delivers the results almost instantly. The location is displayed as a marker on the tool's interactive map.
3. Data
The development of flood hazard maps available with the tool utilized various sources of data. The runoff data required as input into the flood hazard mapping process and extreme value analysis (Step 1 and Step 2) is obtained from two sources. Maps HNARR25 to HNARR500 used the reanalyses data, which is considered an alternate data option for regions where gauge stations are sparsely distributed or unavailable. In the presented work, runoff observations from NARR, a widely used reanalysis source, are considered as hydraulic inputs to a flood model. The NARR data is available at https://psl.noaa.gov/data/gridded/data.narr.html. For the rest of the maps, the runoff data is obtained from CMIP6 data repository for 17 selected GCMs. The CMIP6 observations are made available by the World Climate Research Programme at https://esgf-node.llnl.gov/projects/cmip6/. Table 4 presents the 17 models used in this work.
Table 4. List of GCMs from CMIP6 project used in this study| Sl. No. | GCM | Institution | Reference |
|---|---|---|---|
| 1 | MIROC6 | JAMSTEC, AORI, NIES, R-CCS, Japan | Tatebe & Watanabe (2018) |
| 2 | BCC-CSM2-MR | Beijing Climate Center, China | Wu et al. (2018) |
| 3 | CanESM5 | Canadian Centre for Climate Modelling and Analysis, Canada | Swart et al. (2019) |
| 4 | MRI-ESM2-0 | Meteorological Research Institute, Japan | Yukimoto et al. (2019) |
| 5 | NIMS-KMA.KACE-1-0-G | National Institute of Meteorological Sciences (NIMS) and Korea Meteorological Administration (KMA) | Young et al. (2016) |
| 6 | MPI-ESM1-2-LR | Max Planck Institute for Meteorology, Germany | Wieners et al. (2019) |
| 7 | INM-CM5-0 | Institute of Numerical Mathematics, Russian Academy of Sciences, Russia | Volodin et al. (2019) |
| 8 | INM-CM4-8 | Institute of Numerical Mathematics, Russian Academy of Sciences, Russia | Volodin et al. (2019) |
| 9 | MPI-ESM1-2-HR | Max Planck Institute for Meteorology, Germany | Jungclaus et al (2019) |
| 10 | CMCC.CMCC-CM2-SR5 | Euro-Mediterranean Center on Climate Change, Italy | Lovato et al. (2020) |
| 11 | CCCR-IITM.IITM-ESM | Indian Institute of Tropical Meteorology, India | Raghavan et al. (2019) |
| 12 | IPSL.IPSL-CM6A-LR | Institute Pierre Simon Laplace, France | Boucher et al. (2018) |
| 13 | NorESM2-MM | Norwegian Climate Centre, Norway | Bentsen et al. (2019) |
| 14 | NorESM2-LM | Norwegian Climate Centre, Norway | Seland et al. (2019) |
| 15 | EC-Earth-Consortium.EC-Earth3 | EC-Earth Consortium, Europe | EC-Earth (2019) |
| 16 | CSIRO-ARCCSS.ACCESS-CM2 | Commonwealth Scientific and Industrial Research Organisation (CSIRO) and ARCCSS (Australian Research Council Centre of Excellence for Climate System Science) | Dix et al. (2019) |
| 17 | GFDL-CM4 | NOAA Geophysical Fluid Dynamics Laboratory, USA | Guo et al. (2018) |
In addition to NARR and CMIP6 runoff data, the daily hydrometric data for 1980 to 2019 from the Reference Hydrometric Basin Network (RHBN) available from Environment and Climate Change Canada is obtained from comprehensive HYDAT database ( https://www.canada.ca/en/environment-climate-change/services/water-overview/quantity/monitoring/survey/data-products-services/national-archive-hydat.html) for all gauging stations located across Canada. The RHBN stations data include a minimum of 20-years of observations and have had minimal changes in land-use, withdrawals, and regulation over the years. The daily runoff values of RHBN stations lying within the same grid of each reanalysis and CMIP6 dataset are compared with the accumulated gridded daily runoff values from 1979 to 2010 through comparison metrics. As runoff is the primary parameter influencing flood inundation, larger variations in comparison to the ground truth will lead to significant uncertainties in the flood inundation statistics. The motive behind this quick comparison is to ensure fair estimates of runoff in NARR and GCMs; thereby preventing larger uncertainties in flood inundation outputs.
Along with runoff inputs, CaMa-Flood also considers a set of other relevant data to define the topographic and hydraulic conditions of the river channel and overland bathymetry. TheMulti-Error-Removed Improved-Terrain or MERIT DEM (~3 arcsecond) describes the overland bathymetry of the region. The MERIT Hydro (~3 arcsecond) describes the direction of flow within the river network. The Global Width Database for Large Rivers or GWD-LR (~3 arcsecond) portrays the details on effective and bank-to-bank river width. The data possess high accuracy as it is validated with the actual existing river widths of major river basins. The Global Water Map or G3WBM (~3 arc-second) is a global water body map created comprehensively from a set of 33,890 multi-temporal satellite images from Landsat. G3WBM presents a clear demarcation between permanent and temporal water bodies to ensure precise identification of surface water bodies and flood hazards. The Open Street Map water layer or OSM water layer contains footprints of global surface water bodies derived from the Open Street Map. It should be noted that the chances of generating any form of significant errors in the outputs from CaMa-Flood are minimal, as it considers the most updated dataset in practice.
4. Frequently Asked Questions - FAQ
A flood hazard is an area of land that is prone to flooding. A flood hazard is a generally flat area of land next to a river or stream. This area gets covered in water when the river floods.
A 100-yr flood is a flood that statistically has a 1% (1/100) chance of occurring in any given year.
A 200-yr flood is a flood that statistically has a 0.5 % (1/200) chance of occurring in any given year.
Reanalysis is the process that combines past short-range weather forecasts with observations through data assimilation.
General Circulation Models (GCMs) are numerical models representing physical processes in the atmosphere, ocean, cryosphere and land surface. They are the most advanced tools currently available for simulating the response of the global climate system to increasing greenhouse gas concentrations. GCMs depict the climate using a three-dimensional grid over the globe, typically having a horizontal resolution of between 100 and 600 km, 10 to 20 vertical layers in the atmosphere and sometimes as many as 30 layers in the oceans. GCMs are one of the primary means for scientists to understand how the climate has changed in the past and may change in the future. These models simulate the physics, chemistry and biology of the atmosphere, land and oceans in great detail, and require significant computational power generate their climate projections.
The Coupled Model Intercomparison Project (CMIP) is created to understand better past, present and future climate changes arising from natural, unforced variability or in response to changes in radiative forcing in a multi-model context. The 2021 Intergovernmental Panel on Climate Change (IPCC) sixth assessment report (AR6) features new state-of-the-art CMIP6 climate models. CMIP6 consists of the “runs” from many distinct climate models being produced across 49 different modelling groups. CMIP6 represents a substantial expansion over previous projects, in terms of the number of modelling groups participating, the number of future scenarios examined and the number of different experiments conducted. CMIP aims to generate a set of standard simulations that each model will run.
Shared Socioeconomic Pathways (SSPs) are scenarios of projected socioeconomic global changes up to 2100. They are used to derive greenhouse gas emissions scenarios with different climate policies. The scenarios are: SSP1: Sustainability (Taking the Green Road); SSP2: Middle of the Road; SSP3: Regional Rivalry (A Rocky Road); SSP4: Inequality (A Road divided); and SSP5: Fossil-fueled Development (Taking the Highway). They have been used to help produce the IPCC Sixth Assessment Report on climate change, published on 9 August 2021 and available from IPCC website https://www.ipcc.ch/assessment-report/ar6/. The SSPs provide narratives describing alternative socioeconomic developments. These storylines are a qualitative description of logic relating elements of the narratives to each other. In terms of quantitative elements, they provide data accompanying the scenarios on national population, urbanization and GDP (per capita). The SSPs can be combined with various Integrated Assessment Models (IAMs), to explore possible future pathways both with regards to socioeconomic and climate pathways.
The Representative Concentration Pathway (RCP) is a greenhouse gas concentration (not emissions) trajectory adopted by the IPCC. Four pathways were used for climate modeling and research for the IPCC Fifth Assessment Report (AR5) in 2014. The pathways describe different climate futures, all of which are considered possible depending on the volume of greenhouse gases (GHG) emitted in the years to come. The RCPs – originally RCP2.6, RCP4.5, RCP6, and RCP8.5 – are labelled after a possible range of radiative forcing values in the year 2100 (2.6, 4.5, 6, and 8.5 W/m2, respectively. RCPs set pathways for greenhouse gas concentrations and, effectively, the amount of warming that could occur by the end of the century. The RCPs also do not consider any socioeconomic ‘narratives’ as they focus more on the greenhouse gas concentrations. These narratives explain how the socioeconomic factors (e.g. urbanization, human population, economic growth, educational and technological development) may change in future periods. To address these issues, the CMIP6 climate projections propose the new Shared Socioeconomic Pathways (SSPs) that are different from the RCPs, as they consider a wider range of air pollutant emissions and address socioeconomic narratives as well. The SSPs set the stage on which reductions in emissions will – or will not – be achieved. These scenarios are developed keeping in mind what the future might look like if climate policies were nonexistent, and how uniting the mitigation targets of RCPs with SSPs could address diverse levels of climate change mitigation.
5. References (all references are open access)
- Mohanty, M. and S. P. Simonovic (2020). A comprehensive framework for regional floodplain mapping. Water Resources Research Report no. 109, Facility for Intelligent Decision Support, Department of Civil and Environmental Engineering, The University of Western Ontario, London, Ontario, Canada, 58 pages. ISBN: (online) 978-0-7714-3148-7, open access https://www.eng.uwo.ca/research/iclr/fids/publications/products/109.pdf.
- Mohanti, M. and S.P. Simonovic (2021). A generic framework to quantify changes in floodplain regimes by incorporating climate change impacts over large regions. Water Resources Research Report no. 112, Facility for Intelligent Decision Support, Department of Civil and Environmental Engineering, London, Ontario, Canada, 55 pages. ISBN: (online) 978-0-7714-3158-6, open access https://www.eng.uwo.ca/research/iclr/fids/publications/products/112.pdf.
- Mohanty, M. and S.P. Simonovic (2021) “Fidelity of Reanalysis Datasets in Floodplain Mapping: Investigating Performance at Inundation Level over Large Regions”, Journal of Hydrology, Vol. 597, 125757, available online at https://doi.org/10.1016/j.jhydrol.2020.125757.
- Mohanty, M. and S.P. Simonovic (2021) “Changes in floodplain regimes over Canada due to climate change impacts: observations from CMIP6 models”, Science of the Total Environment, 792, 148323, open access https://doi.org/10.1016/j.scitotenv.2021.148323.
- Mohanty, M.P., and S.P. Simonovic (2022) “A comprehensive approach for flood hazard mapping through identification of hazard using publicly available data sets over Canada,” Water, 14, 2280, open access https://www.mdpi.com/2073-4441/14/14/2280/pdf).