Future Changes in Flood Hazards across Canada under a Changing Climate

Abstract

Climate change has induced considerable changes in the dynamics of key hydro-climatic variables across Canada, including floods. In this study, runoff projections made by 21 General Climate Models (GCMs) under four Representative Concentration Pathways (RCPs) are used to generate 25 km resolution streamflow estimates across Canada for historical and future (2061-2100) time-periods. These estimates are used to calculate future projected changes in flood magnitudes and timings across Canada. Results obtained indicate that flood frequencies in the northernmost regions of Canada, and south-western Ontario can be expected to increase in the future. As an example, the historical 100-year return period events in these regions are expected to become 10-60 year return period events. On the other hand, northern prairies and north-central Ontario can be expected to experience decreases in flooding frequencies in future. The historical 100-year return period flood events in these regions are expected to become 160-200 year return period events in future. Furthermore, prairies, parts of Quebec, Ontario, Nunavut, and Yukon territories can be expected to experience earlier snowmelt-driven floods in the future. The results from this study will help decision-makers to effectively manage and design municipal and civil infrastructure in Canada under a changing climate.Basin Network (RHBN) catchments in Canada were examined by [28]. A decreasing trend in annual maximum flows for catchments located in southern Canada, and an increasing trend in catchments located in northern Canada was obtained. In addition, a robust signal of increases in spring snowmelt driven peak flow was obtained in the months of March and April, whereas a decrease in June month peak flow was obtained. These findings highlight that the behavior of extreme floods has changed across Canada as a consequence of climate change. Therefore, as advocated in previous research [29,30], it is important to obtain reliable flood frequency estimates under a non-stationary climate, such that they can be used to design climate resilient civil and municipal infrastructure across Canada.General Climate Models (GCMs) simulate complex bio-geophysical and chemical processes occurring within the earth system and their interactions [20]. Land surface schemes are the interface within the GCMs that host important energy budget and water balance calculations occurring within a GCM grid-cell. GCM simulations are performed at a coarse spatial resolution of~110-550 km, which hinders the accurate representation of some of the important physical processes, such as convection that shapes the earth's climate [22]. As a result, large uncertainties have been obtained in GCM projections, especially for variables linked to precipitation [22]. For making future flows and flooding projections at catchment(s) scales, typically, coarse resolution climate projections from GCMs are downscaled, and they are used to generate streamflow responses using a hydrologic model. This approach has been adopted in ...

Climate Change Impacts on Reservoir Inflow in the Prairie Pothole Region: A Watershed Model Analysis

“…In a different study [21], it was indicated that impact of climate change will likely cause a 26% difference in the availability of water resources including significant shifts in the intensity, duration, and frequency of precipitation events over the Qu'Appelle watershed that lies within the Canadian prairie region. Other studies such as those by [22][23][24][25] suggested an earlier snowmelt due to increasing temperature which may then affect an earlier spring peak runoff and drier late summer.…”

Flood-Drought Hazard Assessment for a Flat Clayey Deposit in the Canadian Prairies

“…Data is captured at one station only NOAA-AVHRR 1 and Radarsat (Domenikiotis, et al, 2003), (Wilson et al, 2005) Measures spatial extent of flood Satellite may not receive signal through clouds Statistical CaMa 2 -floodplain (Ikeuchi et al, 2015), (Gaur et al, 2018) Simulates hydrodynamic flow in rivers Evaporation and infiltration are not considered Multivariate stochastic rainfall (Efstratiadis et al, 2010), (Asong et al, 2016) Captures spatio-temporal variations in rainfall for calculating flood Requires long-term rainfall data Drought Estimation Precipitation based drought index (SPI) (Quiring et al, 2003), Compares dryness degree based on a minimum 30-year record Does not account for climatic parameters affecting evaporation Multi-index drought (Sun et al, 2012), (Chen et al, 2018) Combines NDI 3 , PDSI 4 , and SPI of drought Applicable only for agricultural drought ranges Measurement Satellite and Radar (Hanesiak et al, 2011), (De Jesús et al, 2016) Measures drought from vegetation maps Requires frequently captured vegetation maps Variable infiltration capacity (Liang et al, 1994), (Wen et al, 2011) Measures drought from soil moisture data Cannot process physical objects on ground Statistical Time series (Chipanshi et al, 2006), (Hao et al, 2018) Uses historical data of precipitation to calculate drought Does not capture soil moisture Artificial intelligence (Sadri, 2010), (Hao et al, 2018) Models nonlinear interactions in various drought indicators…”

“…Research related to flood hazard assessment in the Canadian Prairies include the following: (i) constructing intensityduration-frequency (IDF) curves for Saskatoon using the observed daily precipitation from 1992 to 2009 (Alam et al, 2015); (ii) developing dimensionless flood frequency curves for five homogeneous regions in southwestern Alberta using regression analysis and flood index with the precipitation data of 1912 to 1978 (Xu, 1999); (iii) investigating factors affecting 2013 southern Alberta flood using measured precipitation data (Teufel et al, 2017); (iv) identifying the areal extent of 1997 flood in the Red River Valley using satellite imagery from 27 April 1997 to 1 July 1997, (Wilson et al, 2005); and (v) estimating stream flow across Canada for historical (1961 ~ 2005) and future (2061 ~ 2100) time-periods by using Catchmentbased Macro-scale (CaMa) method (Gaur et al, 2018). Likewise, studies related to drought hazard assessment in the Canadian Prairies focused on the following: (i) monitoring agricultural drought in 43 districts using 1920 ~ 1999 precipitation and temperature data (Quiring et al, 2003) (ii) investigating agricultural drought in 34 regions using multiple drought indices and 1976 ~ 2003 crop yield data (Sun et al, 2012); (iii) identifying healthy and stressed vegetation through satellite imagery in southern Alberta from 2000 ~ 2006 (Hanesiak et al, 2011); (iv) calculating daily moisture anomalies over 1950 ~ 2009 using variable soil infiltration capacity (Wen et al, 2011); and (v) classifying consecutive drought events using time series analysis from daily and monthly precipitation totals of 1959of ~ 2000of and 1909of ~ 2000of (Chipanshi et al, 2006.…”

Extreme Floods and Droughts under Future Climate Scenarios

“…A majority of the Special Issue authors presented their research dealing with projected streamflow extremes in various rivers around the world [9][10][11][12]. The projected streamflow characteristics, including frequency and timing of future flooding in Canada, were calculated [9]. This paper determined the changes for all regions in the country and provided a comprehensive assessment of the uncertainties in their estimates.…”