MNRF CWRA Technical Workshop March 6 2018 Rob Grech and Robert Muir City of Markham
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Presentations by Rob Grech and Rob Muir, City of Markham on climate change and modelling uncertainty including past rainfall intensity trends, future climate projections, application of IDF data, and ROI and cost considerations for flood risk remediation.
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Semelhante a MNRF CWRA Technical Workshop March 6 2018 Rob Grech and Robert Muir City of Markham
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MNRF CWRA Technical Workshop March 6 2018 Rob Grech and Robert Muir City of Markham
- 1. Woodbine Floodplain Mapping Knowledge Transfer Workshop Climate Change and Modelling Uncertainty Rob Grech and Rob Muir City of Markham March 6-7, 2018 Vaughan, Ontario
- 2. Toronto Island flooding a new normal ? Or an old extreme ? 2017 1973 2
- 3. data shows mostly an old extreme http://www.cityfloodmap.com/2017/09/toronto-island-flooding-2017-were-lake.html 74 74.2 74.4 74.6 74.8 75 75.2 75.4 75.6 75.8 1915 1925 1935 1945 1955 1965 1975 1985 1995 2005 2015 MonthlyLevel(m) Year Lake Ontario Historical May - August Levels May Average August Average Source: 1918-2016 http://www.tides.gc.ca/C&A/network_means-eng.html 2017 http://tides-marees.gc.ca/C&A/pdf/Bulletin1708.pdf May 5 cm above record August not a record 3
- 4. This is rare ….. 4
- 5. But this is non-existent ... 5
- 6. Woodbine Outline 6 • What Is Driving Changes in Flood Risk? – Lower Southern Ontario Extreme Rainfall Trends – Higher Urbanization & Intensification • Uncertainty Considerations: – Local IDF Trends – Projected Future IDF (Climate Change) – Design Hyetograph • Project Related Uncertainties – Hydrology/Hydraulic Modelling – Costs & ROI
- 7. 7
- 8. Southern ON Extreme Rain Trends Decreasing http://www.cityfloodmap.com/2016/01/climate-change-ontario-short-duration.html Significant Decr. Decrease Increase Significant Incr. Source: Environment Canada Engineering Climate Dataset ftp://ftp.tor.ec.gc.ca/Pub/Engineering_Climate_Dataset/IDF/ Idf_v2-3_2014_12_21_trends.txt in IDF_Additional_Additionnel_v2.30.zip 8
- 10. Urbanization Extensive Since Mid-1960s http://www.cityfloodmap.com/2016/08/land-use-change-drives-urban-flood-risk.html 10 http://www.cityfloodmap.com/2016/08/urbanization-and-runoff-explain.html Markham
- 11. Local IDF Trends (Past) 200 210 220 230 240 250 260 270 280 290 300 1975 1995 2015 2035 2055 2075 2095 11 Buttonville Airport (Markham) Pearson Airport (Mississauga) Observed Bloor Street (Toronto) Markham Design Standard RainIntensitymm/hr(5minute100-year)
- 12. Future IDF Uncertainty (Above & Below Standards) 200 210 220 230 240 250 260 270 280 290 300 1975 1995 2015 2035 2055 2075 2095 12 Markham Mississauga Observed Toronto Markham Design Standard RainIntensitymm/hr(5minute100-year) Predicted Future Safety Factors Future Stress Test
- 13. Future IDF Uncertainty (Scenarios / Methods / Stations) 200 210 220 230 240 250 260 270 280 290 300 1975 1995 2015 2035 2055 2075 2095 Observed Predicted Markham Design Standard RainIntensitymm/hr(5minute100-year) 13 Markham Mississauga Toronto 13
- 14. What is Critical Data to Support Decision Making? Intensity-Duration- Frequency curves are to water resources engineering what flour is to chocolate chip cookies … i.e., just one ingredient, but not the most important part. 14
- 15. Design Hyetograph Uncertainty 15 0 50 100 150 200 250 300 0 100 200 300 400 500 RainfallIntensity(mm/hr) Time (minutes) Markham Storm (3 Hr AES) 100 Year TRCA Storm (AES 12 Hr) 100 Year IDF 100-Yr TRCA 100-Yr Markham 100-Yr TRCA 100-Yr Risk Gap ? Markham 100-Yr
- 19. Design Standard Upgrades vs Climate Change Adaptation 19 Old 5-Yr Design Design Standard Upgrade (high loss reduction) Today’s 100-Yr For New Design Future 100-Yr For New Design Climate Adaptation (lower ROI) Culvert Enclosures Reduce Level of Service to Less Than 5-Yr Further Climate Adaptation (lower incremental return on investment) ROI Diminishing Returns $72M Level of Service
- 20. Uncertainties at the Project Level: Don Mills Channel 20
- 21. Project Delivery Identify Project Goals & Level of Service Hydrology Hydraulics Assess Mitigation Methods Determine Costs and ROI 21 • IDF/Rainfall Volumes • Storm Distribution • Model Parameters • Design Flows • Model Approach • Model Selection • Model Parameters • Water Levels
- 22. Identify Project Goals & Level of Service Hydrology Hydraulics Assess Mitigation Methods Determine Costs and ROI Project Delivery 22*Note: Conveyance Improvements are all that is accepted for floodline changes in Ontario • Project Costs • Community Benefits • Damage Reduction • Return on Investment • Conveyance* • Storage • Hybrid • Policy/Non-Infrastructure
- 23. Study Area Overview 23 Steeles Ave E John Street Denison St
- 24. Flood Prediction Modelling • A tool to be used to better understand where flooding will occurs and how to mitigate flood damages • Significantly improved technologically, but based on older technical guidance • Only as good as the quality of the information used for its construction • Based on several estimated parameters and founded on managing uncertainties • Heavily Dependant on Judgements Made by Individuals • An exact science • Heavily impacted by the estimate of any one parameter (assuming correct modelling principles are applied) • Ever going to account for every thing that can happen during a flood 24 IS: IS NOT:
- 25. Engineering – Hydrology - Flow 25 Study By Date Hydrologic Model Storm Distribution 5-Year Flow (m3/s) 100-Year Flow (m3/s) MMM 1964 Rational Method Rational Method 28 n/a CPW 1985 Rational Method Rational Method 21 n/a Dillon 1989 Otthymo 24-hour SCS n/a 102 MMM (TRCA) 2004 Otthymo 12-hour SCS* - 61 Cole 2010 Infoworks 24-hour SCS* 23 26** Cole (TRCA) 2011 Otthymo 12-hour SCS* - 74 TMIG 2017 PCSWMM 3-hour AES 19 21** *Custom storm distribution **Dynamic Model Output
- 26. 26 Engineering – Hydrology – Drainage Area & SWM Controls
- 27. Engineering Uncertainties - Hydraulics 27
- 28. Engineering Uncertainties - Hydraulics 28
- 29. Engineering Uncertainties - Hydraulics 29
- 30. Uncertainty in Project Cost Estimation 30 Pre-Project Identifi- cation Project Identifi- cation Environ- mental Assessment Detailed Design Construc- tion • Specific Locations • Causes • Mitigations Options • Best Mitigation Option • What needs to be Built and Where • Mapped Site Conditions • Construction Market Conditions • Detailed Site Conditions • What needs to be Built and Where • Mapped Site Conditions • Construction Market Conditions • Detailed Site Conditions LOW CONFIDENCE LOW TO MEDIUM CONFIDENCE MEDIUM TO HIGH CONFIDENCE + 60% + 30%-50% • Construction Market Conditions • Detailed Site Conditions + 10%-20% HIGH TO VERY HIGH CONFIDENCE + 0%-10% PROJECT STAGE: CONFIDENCE IN ESTIMATE: • Detailed site conditions • If Flooding is even a problem • Specific Locations • Causes • Mitigations Options • Best Mitigation Option • What needs to be Built and Where • Mapped Site Conditions • Construction Market Conditions • Detailed Site Conditions NO CONFIDENCE + 80% OR MORE UNKNOWNS :
- 31. Calculating Flood Damages • MNRF Flood Damages Curves (Ontario) • HEC FIA (Army Corps of Engineers) • HEC FDA (Army Corps of Engineers) • Estimation based on Property Values • Estimation based on Historical Damages (Insurance Companies) • DOS Based Programs! 31 Methods Uncertainty • Several Items very difficult to assess • Information sharing on past data is unavailable • No standardized process • Non-Tangible Benefits
- 32. Project Findings • A 5 year level of service goal is preferred for the following reasons: – The cost of mitigation was manageable (~$70M vs. $350M initial investment for 100 year) – The damages were reduced significantly (approximately $3.6M/yr -> 600k/yr) – Policy and non-infrastructure methods are to be incorporated to increase level of service in the longer term • Despite project uncertainties, modelling tools are effective in characterizing a system and developing mitigation options • Dynamic modelling significantly improves the ability to understand the system and to assess risk, but lacks policy direction • Flood damage assessment and ROI calculations need better guidance, data sharing and standardization 32
- 33. Woodbine Conclusions 33 • Higher urbanization & intensification increase flood risk despite decreasing extreme rain trends in Southern Ontario • Original design levels of service are a key indicator of where flooding will occur • Practitioners can embrace uncertainty in several engineering parameters through the use of conservative methods in modelling – potential climate change impacts should be incorporated into project uncertainty • Modelling methods and approaches need more discussion beyond IDF/Climate change uncertainties • Cost and benefit considerations have to be looked at more critically and be better incorporated into decision making – Sometimes, choosing a lower level of service makes sense
- 34. We have always had flooding Engineers don’t let that stop them in in their quests … 34