Fargo, ND May 31 2007 An investment model for large-scale green infrastructure: re-mosaicking the prairies 3rd International Sustainable Wetland Plant Management Conference Henry David (Hank) Venema, PhD, PEng
Acknowledgements
Outline What we ve lost What we ve gained What we ve learned The Future recovering what we ve lost, sustaining what we ve gained ecological design, climate finance
Hardware vs Software AT&T (c. 2007) had exclusive iphone contract and committed to unlimited data supply Experienced 100 000% increase in bandwidth demand in 3 years Expanding conventional infrastructure was not an option Revolutionary software innovation allowed AT&T to meet demand with conventional infrastructure network
NATURAL CAPITAL RESTORATION RNC = Restored Natural Capital EGS = Ecological Goods and Services Source: Aronson, J., Clewell, A. F., Blignault, J. N., & Milton, S. J. (2006). Ecological restoration: A new frontier for nature conservation and economics. Journal for Nature Conservation, 14, 135-139.
The Palliser Expedition and the Palliser Triangle
The Modern Prairies
Manitoba 1867
1870 - Natural landscape dominated by prairies with large tracks of forests and significant wetland and marsh areas. Source: Hanuta, 2006
Past Experience with Extreme Events 1906; 1936-38 (quarter million people displaced); 1961; 1976-77; 1980; 1984-85; 1988; 2001-2003 ( the worst ever? $3.6 B Ag /$5.8 B GDP/ 41 000 jobs lost
Landscapes Simplified Ecosystem Services Eliminated Reliance on Hardware Source: http://www.ducks.ca/aboutduc/news/archives/ pdf/ncapital.pdf
Climate Change Motivates a Reliance on Software figuratively and literally. International Capital is an ally but we have to do the design work
Global Motivation https://uploads.guim.co.uk/2016/05/10/5_9_16_andrea_tempspiraledhawkins.gif
Regional Context: Highlights from www.climateatlas.ca
Shifting Extremes Change in the Number of Very Hot Days High Carbon Low Carbon 1981-2010 Annual number of days 30 C 0 4 8 12 16 20 24 28 32 36 40 44 48+ Recent Past Near Future Far Future Data Source: Pacific Climate Impacts Consortium (PCIC), University of Victoria, (2014). Statistically Downscaled Climate Scenarios. Downloaded from pacificclimate.org.
Shifting Extremes Change in the Number of Very Hot Days High Carbon Low Carbon 2021-2050 Annual number of days 30 C 0 4 8 12 16 20 24 28 32 36 40 44 48+ Recent Past Near Future Far Future Data Source: Pacific Climate Impacts Consortium (PCIC), University of Victoria, (2014). Statistically Downscaled Climate Scenarios. Downloaded from pacificclimate.org.
Shifting Extremes Change in the Number of Very Hot Days High Carbon Low Carbon 2021-2050 Annual number of days 30 C 0 4 8 12 16 20 24 28 32 36 40 44 48+ Recent Past Near Future Far Future Data Source: Pacific Climate Impacts Consortium (PCIC), University of Victoria, (2014). Statistically Downscaled Climate Scenarios. Downloaded from pacificclimate.org.
Shifting Extremes Change in the Number of Very Hot Days High Carbon Low Carbon 2051-2080 Annual number of days 30 C 0 4 8 12 16 20 24 28 32 36 40 44 48+ Recent Past Near Future Far Future Data Source: Pacific Climate Impacts Consortium (PCIC), University of Victoria, (2014). Statistically Downscaled Climate Scenarios. Downloaded from pacificclimate.org.
Shifting Extremes Change in the Number of Very Hot Days High Carbon Low Carbon 2051-2080 Annual number of days 30 C 0 4 8 12 16 20 24 28 32 36 40 44 48+ Recent Past Near Future Far Future Data Source: Pacific Climate Impacts Consortium (PCIC), University of Victoria, (2014). Statistically Downscaled Climate Scenarios. Downloaded from pacificclimate.org.
Temperature Change ( o C) from 1981-2010 2051-2080 ΔT: RCP8.5 6.5 6.0 5.5 5.0 4.5 4.0 3.5 3.0 Edmonton Regina Winnipeg 2.5 2.0 1.5 1.0 0.5 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Summer Precipitation
Prairie Precipitation Projected Changes in Total Summer Precipitation High Carbon Low Carbon 1981-2010 Total Summer Precipitation (mm) 70 90 110 130 150 170 190 210 230 250 270 290+ Recent Past Near Future Far Future Data Source: Pacific Climate Impacts Consortium (PCIC), University of Victoria, (2014). Statistically Downscaled Climate Scenarios. Downloaded from pacificclimate.org.
Prairie Precipitation Projected Changes in Total Summer Precipitation High Carbon Low Carbon 2021-2050 Total Summer Precipitation (mm) 70 90 110 130 150 170 190 210 230 250 270 290+ Recent Past Near Future Far Future Data Source: Pacific Climate Impacts Consortium (PCIC), University of Victoria, (2014). Statistically Downscaled Climate Scenarios. Downloaded from pacificclimate.org.
Prairie Precipitation Projected Changes in Total Summer Precipitation High Carbon Low Carbon 2021-2050 Total Summer Precipitation (mm) 70 90 110 130 150 170 190 210 230 250 270 290+ Recent Past Near Future Far Future Data Source: Pacific Climate Impacts Consortium (PCIC), University of Victoria, (2014). Statistically Downscaled Climate Scenarios. Downloaded from pacificclimate.org.
Prairie Precipitation Projected Changes in Total Summer Precipitation High Carbon Low Carbon 2051-2080 Total Summer Precipitation (mm) 70 90 110 130 150 170 190 210 230 250 270 290+ Recent Past Near Future Far Future Data Source: Pacific Climate Impacts Consortium (PCIC), University of Victoria, (2014). Statistically Downscaled Climate Scenarios. Downloaded from pacificclimate.org.
Prairie Precipitation Projected Changes in Total Summer Precipitation High Carbon Low Carbon 2051-2080 Total Summer Precipitation (mm) 70 90 110 130 150 170 190 210 230 250 270 290+ Recent Past Near Future Far Future Data Source: Pacific Climate Impacts Consortium (PCIC), University of Victoria, (2014). Statistically Downscaled Climate Scenarios. Downloaded from pacificclimate.org.
% Change from 1981-2010 2051-2080 ΔPPT: RCP8.5 50 45 40 35 30 25 20 15 10 Edmonton Regina Winnipeg 5 0-5 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec -10-15 -20-25
Agricultural Water Management: Lessons from 2011
Hypothesis: Agriculture is not at the table on Green Infrastructure dangerous omission as agriculture lies at the heart of a large class of climate solutions
The solution: US example North Ottawa project http://www.bdswd.com/ Project Benefits: Flood Damage Reduction (Primary objective): Provides 16,000 acre feet of gatecontrolled storage which is equivalent to 75% of the estimated 100 year spring runoff. This is expected to reduce peak flows on the Bois de Sioux River at Wahpeton/Breckenridge by about 5%. Downstream Flow Augmentation: Release of about 5 cfs flow during the ice free season in most years. Water Quality: Improvement via sedimentation and nutrient uptake by wetland plants Habitat Enhancement: Feeding and resting areas for migrating waterfowl and shorebirds and stream flow maintenance for downstream fish habitat.
The solution: MB example
Stacked Benefits of Surface Water Retention: Not just for flood management GHG emissions reduction Biomass harvest Habitat/Biodiversity Phosphorus capture Flood control Water Recharge Pelly s Lake water retention site - near Holland, Manitoba
Pelly s Lake Fall 2015 Cattail Harvesting Dries up in the fall (September) - suitable conditions for harvesting with conventional agricultural equipment
Reduction in GHG emissions Cumulative greenhouse gas flux (CO2 + CH4 + N20, expressed as CO2 equivalents; mean +/- SE) for harvested and non-harvested cattail plots in the Pelly s Lake retention area
The big picture Boutique projects are necessary but insufficient Finance, Treasury, Feds can not deal with the granularity of high-performance adaptation projects Structural adaptation means aggregation and bundling for green bond issues. High performance computational platform for benefit aggregation, economic performance, visualization (and institutional gap analysis)
Precision Infrastructure Designing Advanced and Resilient Infrastructure: Big Spatial Data CyberGIS
Global Motivation: Agriculture as crucial climate solution space
Global Motivation need to invest heavily in resilient infrastructure
Aggregation and Systems Design: Re-mosaicking the landscape Key parameters: Retention area = 4750 km2 = 1840 sections = 3.4% of ag land base Storage Volume @ 1m depth = 4.75 Gm3 = 3.85 M ac-ft = 80.6% of 2011 flood Biomass / Phosphorus @ 8t/ha = 3.8 Mt biomass = 3.8 kt phosphorus (100% of Lk Winnipeg policy target)
Aggregating Costs and Benefits (direct monetization and engineering substitution costs) Cost @ $1000/acre-foot + $400/acre + 50% contingency = $6.3 Billion Co-Benefit Stack Irrigation @ 10% of storage @ $500 acre-ft = $192 Million/year Biomass Production @ $30/t = $114 M/year GHG emissions reduction Fuel Switch @ $30/t CO2e = $114 M/year Sequestration @ $30/t CO2e @ 10t/ha = $142 M/year Water Quality @ $50/kg P = $190 Million/year Flood Risk Reduction [omitted] Drought Resiliency [omitted] Habitat [omitted] Co-Benefit Stack Total = $753 M/year
Blunt Force Investment Analysis 50 years Cash Flow $2,000,000,000 $1,000,000,000 $0 -$1,000,000,000 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 -$2,000,000,000 -$3,000,000,000 -$4,000,000,000 -$5,000,000,000 -$6,000,000,000 -$7,000,000,000 IRR = 12.2% NPV @ 3% = $12.75B net Benefit-Cost Ratio = 2.04
Motivation the $64 trillion dollar question (actually $90T) Recent climate-aligned bonds in Canada:
The enablers (technical) LiDAR for proper geospatial and hydrodynamic modelling (technical) Hydro-climatic modelling (ECCC-MESH model) (technical) High performance computational platform for benefit aggregation, economic performance, watershed visualization (policy) hard commitment to climate leadership/green economy/cleantech and green value chain development (policy) institutional flexibility on carbon/water quality/biodiversity offsetting (policy) investment aggregation/leveraging: green infrastructure/p3 (policy) institutional and governance innovation
Case Study: Virden, MB Harvesting Technology Equipment R&D and Enterprise Logistics Landscape/ Watershed Design Downstream Processing Green Infrastructure design/bond primarily resilience benefits Biorefinery systems design Green Infrastructure design/bond resilience + GHG mitigation benefits
The Prize: Deep Innovation Deep Driver for Economic Development and Growth Climate Resilience International Leadership in Precision Infrastructure design, implementation and management A new class of cyberinfrastructure technology crucial to climate resilience, water and food security: Biorefining Biomaterials Systems Design and Logistics Geospatial Analytics Smart Hydrology and Hydraulics Ecosystem Modeling and Visualization Low-impact Agricultural Harvesting
Next Steps