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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”; and (ii) the Université du Quebec a Montréal.
Project team: Prof. Slobodan P. Simonovic, Prof. Mohit Mohanty, and Dr. Andre Schardong.
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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. Please check the Learn section for more information.
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.
Methodology
The flood maps available for viewing and download were developed using an original methodology developed by Mohanty and Simonovic [1, 2, 3, 4]. Key elements of the methodology are presented here and the users are advised to consult available references for further details.
The provided floodplain 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 floodplain 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. Floodplain maps available within the tool for the current conditionsNARR 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 floodplain maps includes the following steps:
- Use runoff observations as input into the floodplain 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 floodplain inundation outputs, e.g., river channel floodwater depth, discharge and velocity, and overland floodwater depth;
- Generate the simulated floodplain 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 101 and 201 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 floodplain 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 102 and 202 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 floodplain 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 floodplain 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 floodplain maps to improve the final resolution of the maps.
- Step 6 involves the generation of floodplain 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).
Data
The development of floodplain maps available with the tool utilized various sources of data. The runoff data required as input into the floodplain 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 studySl. 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 floodplains. 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.
Frequently Asked Questions - FAQ
A floodplain is an area of land that is prone to flooding. A floodplain 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.
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.