|Mississauga climate change. Just playing around with rain ...
ignoring the sciences of hydrology and practice of hydraulic
engineering with oversimplified analysis and unreliable results.
Mississauga is used a the test case for storm damages, specifically river flood plain damages. The analysis estimates expected annual damages today and in the future under various climate change scenarios. The Community Impact Analysis Tool (CIAT-Flood) was developed to allow other communities to apply the analysis - the spreadsheets "within which the calculations and data are stored to estimate direct and secondary expected annual damages (EAD) for each of the climate related extreme events of relevance to this project."
A review of the methodology suggests that results should be viewed with caution due to several inappropriate assumptions that have been made - the absolute value of damages will be overestimated and incremental climate change impacts will be overestimated.
|Is runoff volume or rate proportional to average rainfall
intensity across all durations as assumed in this study? No.
Half the rain produces less than half the runoff for pervious
surfaces as shown in the standard SCS Curve Number chart.
- non-linearity between rainfall and the runoff volumes affecting peak flows means half the rain results in less than half the flow (see standard SCS runoff-rainfall relationships above - a 5 year storm with say 50 mm or 2 inches of rain has very little runoff from the pervious surfaces in a watershed),
- no-one builds within a 5-10 year flood plain (except maybe ancillary structure / sheds).
|Cooksville Creek flood master study class EA in Mississauga shows river drainage system
|Is flood depth proportional to average rainfall intensity across all durations
in an IDF curve as assumed in this study? No - it is not. That assumption
skips over the science of hydrology and the practice of hydraulic engineering.
The example in HEC-RAS at right shows how depth increases only marginally as flow increases. This would result in lower flood depths and incremental flood damages for future climate scenarios compared to the baseline climate. As roadways would generally be over-topped during extreme events (e.g., see Cooksville Creek example table above), resulting in "weir flow" conditions, further non-linearities are expected with the flow regime, dampening depth increases even more. Undergraduate fluid mechanics and hydraulic engineering classes all learn weir flow capacity increases with a 1.5 exponent power function relative to depth, not linearly with a 1.0 exponent. The Green Team Analytics analysis ignores basic hydraulic engineering principles.
To check the analysis issues noted above, real flood plain hydraulic model results with real flood depths for multiple return period events below the 100 year event were reviewed. Data are for a GTA municipality, screened for residential properties. These data are derived from engineered floodlines that properly consider urban hydrology and floodplain hydraulics. Real data shows diminishing counts for properties flooded for smaller return period events, accurately reflecting common hydrology trends in watersheds and hydraulics in river systems. The real depth of flooding decreases to zero for small return period events. Using property count and depth as an indicator of flood damages, using rain frequency to estimate flood depths over estimates the absolute flood risk by 55%. Given non-linearity in flood damage curves, absolute flood damages would be overestimated by even more (> 55%). The Green Team Analytics report does not consider fundamental hydrology and hydraulics to estimate flood damages, and as a result incorrectly overestimates small storm damages.
|Comparing Mississauga Flood Damage Estimate Approach to Using Real Flood Data:
using rain intensity and no hydrology, or hydraulics, overestimates flood damages compared to using real data.
The report "Evaluating flood damages: guidance and recommendations on principles and methods" (January 2007) by FLOODSite describes critical data needed for flood damage estimation. FLOODsite is co-funded by the European Community Sixth Framework Programme for European Research and Technological Development (2002-2006). From the report (page 17-18):
"...it is on the critical parameters upon which attention should be focused in seeking to improve the estimates of the parameters. It is also on these parameters upon which risk management should be focused. In general, it is those benefits and costs which occur early in the life of the intervention strategy and/or occur frequently which are likely to be critical. These include:
• Capital costs
• Operation and Maintenance costs
• Flood levels as estimated from ground levels and water levels
• Damages from frequent floods
• Land uses at low levels including below ground land uses"
The report The Economic Impacts of The Weather Effects of Climate Chance on Communities does not address bullet items 3 or 4 with any focus: no estimate of flood levels (i.e., depths) using water levels and ground levels are used (depths were estimated from rainfall); no damages from frequent floods are calculated (depths and damages were estimated based on rainfall with no flood hydrology considerations, nor flood hydraulics considerations).
Here are the Green Team Analytics study's flood damage assumptions:
Page 163 Appendix B. Key Data and Assumptions – Direct Impact Estimates in Mississauga:
Spatially explicit GIS flood extent data for the historical 100 year return period was available167 and was used in this analysis but no additional flood extent data existed for other return periods or climate change scenarios. Therefore, the relative changes in IDP based on data from the IDF_CC Tool was used as a proxy to alter the flood depths across the existing buildings within the historical 100 year return period flood extent. This allowed for an estimate of the flood extent across all above return periods both for the historic time period (baseline climate change scenario) and the future time periods while accounting for climate change (moderate and high climate change scenarios).
Firstly, the return period values of the IDF curves for three time periods were utilized: baseline (1960-1990), and two future periods under a climate change scenario (2015-2045 and 2035-2065). The rainfall intensity was provided for several durations (5 mins, 10 mins, 15 mins, 30 mins, 1 hr, 2 hr, 6 hr, 12 hr and 24 hr) measured in mm/hr, and across each return period (2yrs, 5yrs, 10yrs, 25yrs, 50yrs and 100yrs). The average relative rainfall intensity across all durations was calculated between the baseline period (1960-1990) and the two future time periods (2015-2045 and 2035-2065) under the climate change scenario. These relative results provided a proxy to estimate the relative change in flood depth across return periods between the baseline time period (recent historic climate) and the two future time periods under a changing climate (midpoints: 2035 and 2050). Additionally, the average relative rainfall intensity across the durations was calculated between the baseline 100 year return period values and the other baseline return periods considered in this analysis (2yrs, 5yrs, 10yr, 50yrs). Since data was only available for the 100 year historic flood extent, the flood extent for the other baseline return periods were calculated by multiplying this relative change in rainfall intensity as a simple proxy to estimate the flood depths at each building across all of other return periods considered. Once the baseline flood depths versus return periods were calculated for the baseline historic climate change scenario, then the flood depths versus return periods were calculated for the future time periods assuming the given future climate change scenario using the relative change in rainfall intensity as a proxy.
The report estimates that by 2020 expected annual damage (EAD) attributed to climate change increases by 2.4% (moderate climate change) to 2.5% (high climate change) relative to the corresponding baseline scenario. And by 2040, EAD increases by 6% (high climate change) to 13% (moderate climate change) relative to the baseline. Given issues with the assumed flood depth - rainfall intensity relationship, EAD values would likely increase by a lower amount (say less than 5% for high climate change and less than 10% for moderate climate change) if a more appropriate non-linear rainfall-runoff-design flow relationship, and more appropriate non-linear design flow-flood stage elevation (flood depth) relationship were used.
The study analysis related to river flooding and the CIAT-Flood Tool are intended to quantify flood damages to guide investments in adaptation measures. The report indicates that the analysis does so at the community-level:
"Thus, to help identify areas where adaptation investments may be justified, there is a need to quantify, at a community-specific level, the expected impacts to communities from such events. Within this context, the current project focuses on quantifying the impacts of climate-related extreme events at the community scale."
Therefore, the report and the tool coarsely apply (or skip over) engineering principles and makes recommendations on flood impacts to guide adaptation investments. The report does not recognize that engineering data or models are need to complete the analysis. On input data, engineering or public works departments are not identified as a key data source:
"Data requirements: The data required to conduct an impact analysis of climate-related extreme
events is dispersed across numerous municipal departments and organizations, which means that
the completion of an analysis such as this necessarily requires a minimum degree of engagement
from many departments (such as parks, forestry, water, power, planning, economic development and
geographic information systems) and organizations (conservation authorities and power utilities)."
Public works departments, where traditionally engineering is practiced at municipalities, are noted as users of the analysis tool.
"6.2 Target Audience
The CIAT is primarily designed to be used by municipal staff across a range of departments including, but not limited to planning, economic development, environment, parks, forestry, finance, risk management, and transportation and public works departments. Water and sewer services departments and local electrical distribution utility providers may also find the tool useful or be engaged through data sharing."
Overall, the role of engineering analysis is limited. Input from conservation authorities may contain usually engineering data (watershed hydrology or river hydraulics), but this is has not been appropriately used in the report or the tool. Expected annual damages should not have been estimated by extrapolating 100-year damages to more frequent event damages (where there are often no damages for small events), and changes in flood depth that drive damages should not have been estimated based on changes in rainfall intensity (using multiplication as a 'simple proxy' for proper engineering analysis).
Vit Klemes RIP would be thoroughly annoyed at the efforts put toward the flood damage analysis in the report above. I remember he introduced concepts of non-linearity in flood risk hydraulics in an undergraduate civil engineering class guest lecture at U of T (Galbraith Room 305 I think?). It's time to brush up on some of his classics like Dilettantism in hydrology: transition or destiny?. Or if you have not read it please see his key note address to International Interdisciplinary Conference on Predictions for Hydrology, Ecology, and Water Resources Management: Using Data and Models to Benefit Society, entitled Political Pressures in Water Resources Management. Do they influence predictions? This graphic is from the presentation:
In his address Klemes notes:
"[P]olitical pressures often set the agenda for what is to be (or not to be) predicted, and sometimes even try to impose the prediction result thus transforming prediction into prescription."
It is possible that Team Green Analytics was working towards a prescribed result, or at least a plausible result, and accepted the prescribed prediction, shunning the Kahneman System 2 thinking that is required for the complex analysis task. ... or the budget was tight?
Like in his key note address where Vit relates a story from his early career in Czechosolvakia "around 9 o’clock, my boss walked into my office and said 'Vít, by quarter to eleven I need the cost for the Teplice [dam] project' ”, Team Green Analytics had to get a result within the constraints they were given.
Vit related his dilemma : What can one do about an impossible request like that? The command of the professional ethics is clear: Refuse to cooperate, period! But in the 1950s in the communist Czechoslovakia where people were disappearing without trace? Where the gallows, worn out by the recent “liquidation of the enemies of the people”, were being diligently repaired; where a shade of hesitation could mean “sabotaging socialism”, be sent to the mines to “regain the confidence of the working class”, or at best lose the job and be black-listed for any job except window washing or street sweeping? With two kids and the predictable firing and black-listing of my wife?
We'll never know how/if Team Green Analytics was backed into a corner like Vit to produce an impossible result for their report. In the end Vit did what he had to do:
I made my choice: by quarter to eleven I gave my boss the figure – 713 million Czech crowns. This
figure has been haunting me ever since and I made a resolution NEVER AGAIN!
And so they did what they had to do to get this impossible result. The absolute values are too high (improper extrapolation of flood depths by rain intensities to storm with no flooding) and the incremental 2020 and 2040 damages increases are too high (ignored non-linearities in hydrologic transformation of rain to runoff and flow to flood elevation/depth) :