Modelling Future Flood Risk Across Canada Under Climate Change

Slobodan P. SimonovićFCAE, FCSCE, FASCE, FIWRA

Department of Civil and Environmental EngineeringWestern University

INTRODUCTION 2|

Funding• NSERC CRD with Chaucer Synd.: 2015-2019 $1,375,600

Research team• Prof. Slobodan P. SIMONOVIC• Mrs. Ayushi GAUR • Mr. Abhishek GAUR

Research support

CONCLUSIONS 3|• First Canada-wide assessment of future changes in flood

hazard and risk• Comprehensive assessment of uncertainty by considering

large ensemble of future runoff projections• Northern provinces of Canada, south-western Ontario, north-

eastern Quebec, and southern prairies are expected to face increase in frequency of flooding

• Northern prairies and north-central Ontario will experience decrease in frequency of flooding

• Larger parts of Canada are expected to experience earlier-than-usual snowmelt driven floods

• Southern Ontario cities are associated with highest increases in future flood risk

• Flood characteristics will change at majority of the flow regulation locations highlighting the importance of revising long-term regulatory rules to adopt to changing conditions

INTRODUCTION 4|

• Introduction • Research objectives• Methodology• Models and data used• Analysis and results• Conclusions

Overview

INTRODUCTION 5| Canada – observed climate change

INTRODUCTION 6| Canada – climate model predictions

INTRODUCTION 7| Flood modelling

• Flow on floodplains is controlled by topography and friction

• Complex spatial patterns of water depth and velocity (2D in space and dynamic in time)

• Large scale modelling possible

• Simplified 2D hydraulic models

• Faster computers

RESEARCH OBJECTIVES 8|

• Investigate changes in the frequency and magnitude of 100-year and 250-year return period flood events across Canada;

• Investigate changes timing of peak flood events across Canada;

• Assess the future flood risk to Canadian cities and flow regulation infrastructure

• Assess the uncertainty introduced by multiple GCMs and emission scenarios in projecting future changes in flood frequency and magnitude

METHODOLOGY9| Flood modelling

METHODOLOGY10|Runoff projections

METHODOLOGY11|Flood modelling – CaMa-Flood model

• CaMa-Flood (Catchment-based Macro-scale Floodplain) global hydrodynamic model (University of Tokyo)

• Grid –based river and floodplain routing calculations

• Input - runoff forcing from land surface schemes within GCMs

• Flow calculation in each grid (specific unit-catchment)

• Output - water storage• Flexible Location of Waterways ( FLOW ) method

– Up-scaled river network map preparation– Sub-grid characteristics (channel length, channel altitude,

distance to downstream, unit-catchment area and flood elevation profile)

• River network map is prepared tracing the fine resolution flow direction map.

MODELS AND DATA12| Data sources• Daily historical and future GCM runoff data: Daily runoff

data for historical (1961-2005) and future (2061-2100) timelines collected for future emission scenarios.

• Historical reanalysis flow data: Daily NARR reanalysis flow data obtained for the duration 1993-2007.

• Daily historical river discharge data from HYDAT: Daily river discharge data collected for RHBN stations located in Canada for the duration 1993-2007.

• Population data: Population data for 100 most populous cities of Canada obtained from Statistics Canada (2017) for the year 2015.

ANALYSES AND RESULTS 13| Flood simulations• Continuous daily simulation of historical (1961-2005)

and future flow projections (2061-2100) across Canada• Input daily flow data obtained from 21 Global Climate

Models taking all available emission scenarios (84 future and 21 historical runs)

• Change in 100-year and 250-year return period flood magnitude estimated

• Flood frequency analysis is performed by fitting the annual maximum flows using Generalized Extreme Value (GEV) distribution– Scale, shape and location parameters estimated

using method of moments

ANALYSES AND RESULTS 14| Computational challenges

• Challenge - to perform flow and flood inundation calculations at over 1 million model grids located in Canada, and for over 3 million days including different climate models, emission scenarios, and time-periods.

• Solution - SHARCNET computations utilizing 24 cores on one node of “copper” system. – Installation of WinSCP and PuTTY.exe programs on local machine.– Specify paths to gcc and ifort compilers on SHARCNET in the MKinclude file

of CamaFlood model. – Specify appropriate simulation settings in the model including the number

of cores for parallel computations.– Submit job to run CamaFlood model on SHARCNET using following sqsub

command:sqsub –q threaded –n 24 –r 4h –mpp=16g –o outputfile.txt global_15min.sh

– Copy outputs from SHARCNET to local machine for post-processing.

ANALYSES AND RESULTS - FREQUENCY 15| Single model results - 100-year: BCC-CSM-1-1

ANALYSES AND RESULTS - FREQUENCY 16| Aggregated median results - 100-year

ANALYSES AND RESULTS - FREQUENCY 17| Robust median results - 100-year

ANALYSES AND RESULTS - FREQUENCY 18| Uncertainty analyses

ANALYSES AND RESULTS - TIMING 19| Robust median – 100 year

ANALYSES AND RESULTS - TIMING 20| Robust median – 100 year

ANALYSES AND RESULTS - RISK 21| 100 most populated cities – 1072 FRI locations

ANALYSES AND RESULTS - RISK 22| 100 most populated cities – 100 year flood RCP 8.5

ANALYSES AND RESULTS - RISK 23| Selected cities – robust median

• 40%-60% of Canada’s 100 most populated cities are high at risk of increased riverine flooding under climate change.

City RCP 2.6 RCP 4.5 RCP 6.0 RCP 8.5 100 year 250 year 100 year 250 year 100 year 250 year 100 year 250 year

Toronto 22 37 32 46 32 39 15 23 Montreal 26 38 22 32 18 25 11 16 Edmonton 104 >500 200 >500 200 >500 284 104 Hamilton 37 56 151 78 200 67 27 56 Winnipeg 198 >500 200 >500 200 >500 200 >500 Kitchener 26 47 200 86 200 57 29 60

Pierrefonds district of Montreal, May 2017 Pierrefonds district of Montreal, May 2019

https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&ved=2ahUKEwing4bNmLfiAhVBi1kKHR86AjsQjRx6BAgBEAU&url=https://www.cbc.ca/news/canada/montreal/montreal-flood-plans-1.4301413&psig=AOvVaw1omSSuQt8PayqLqSr_MwsV&ust=1558891226716326https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&ved=2ahUKEwing4bNmLfiAhVBi1kKHR86AjsQjRx6BAgBEAU&url=https://www.cbc.ca/news/canada/montreal/montreal-flood-plans-1.4301413&psig=AOvVaw1omSSuQt8PayqLqSr_MwsV&ust=1558891226716326

City

RCP 2.6

RCP 4.5

RCP 6.0

RCP 8.5

100 year

250 year

100 year

250 year

100 year

250 year

100 year

250 year

Toronto

22

37

32

46

32

39

15

23

Montreal

26

38

22

32

18

25

11

16

Edmonton

104

>500

200

>500

200

>500

284

104

Hamilton

37

56

151

78

200

67

27

56

Winnipeg

198

>500

200

>500

200

>500

200

>500

Kitchener

26

47

200

86

200

57

29

60

ANALYSES AND RESULTS - RISK 24| 1072 flow regulation infrastructure locations – 100 year flood

• 45%-60% expected to experience increases in flood magnitudes

• 25%-60% expected to experience changes in flood timing

CONCLUSIONS 25|• First Canada-wide assessment of future changes in flood

hazard and risk• Comprehensive assessment of uncertainty by considering

large ensemble of future runoff projections• Northern provinces of Canada, south-western Ontario, north-

eastern Quebec, and southern prairies are expected to face increase in frequency of flooding

• Northern prairies and north-central Ontario will experience decrease in frequency of flooding

• Larger parts of Canada are expected to experience earlier-than-usual snowmelt driven floods

• Southern Ontario cities are associated with highest increases in future flood risk

• Flood characteristics will change at majority of the flow regulation locations highlighting the importance of revising long-term regulatory rules to adopt to changing conditions

RESOURCES26|• Gaur, A., A. Gaur and S. P. Simonovic (2017). Modelling of High Resolution Flow

from GCM Simulated Runoff using a Mesoscale Hydrodynamic Model: CAMA-FLOOD. Water Resources Research Report no. 101, Facility for Intelligent Decision Support, Department of Civil and Environmental Engineering, London, Ontario, Canada, 44 pages. ISBN: (print) 978-0-7714-3154-8; (online) 978-0-7714-3155-5.

• Gaur, A., A. Gaur, and S.P. Simonovic, (2018) “Future changes in flood hazard across Canada under changing climate”, Water, Feature Paper, Special Issue Extreme Floods and Droughts under Future Climate Scenarios ,10(1441):21, open access, PDF Version: http://www.mdpi.com/2073-4441/10/10/1441/pdf

• Gaur, A. Gaur, A. and S.P. Simonovic (2019) “Modelling of Future Flood Risk Across Canada Under Climate Change”, WIT Transactions on Engineering Sciences, 121:149-161, available online: https://www.witpress.com/elibrary/wit-transactions-on-engineering-sciences/121/36682

• Gaur, A., A. Gaur, and S.P. Simonovic, (2019) “Future changes in the hazard and risk of flooding in Canada’s most populated cities and flow regulation infrastructure”, Water, Feature Paper, Special Issue on Extreme Floods and Droughts under Future Climate Scenarios: 11(1), 63; doi:10.3390/w11010063., open access http://www.mdpi.com/2073-4441/11/1/63/pdf

http://www.eng.uwo.ca/research/iclr/fids/publications/products/101.pdfhttp://www.mdpi.com/2073-4441/10/10/1441/pdfhttps://www.witpress.com/elibrary/wit-transactions-on-engineering-sciences/121/36682http://www.mdpi.com/2073-4441/11/1/63/pdf

THANK YOU 27|

QUESTIONS

www.slobodansimonovic.com

http://www.slobodansimonovic.com/

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