Are Water Damages Increasing in Canada? Insured Losses for Flood, Rain, Storm and Hurricane Perils Show Decreasing Trend

The Insurance Bureau of Canada, Intact Centre for Climate Adaptation and International Institute for Sustainable Development released a report on natural infrastructure for flood resiliency called "Combatting Canada’s Rising Flood Costs: Natural infrastructure is an underutilized option", available here.

The report states:

"The financial impacts of climate change and extreme weather events are being felt by a growing number of
homeowners and communities across Canada. The increase in P&C insurance losses is indicative of the growing costs associated with these events. These losses averaged $405 million per year between 1983 and 2008, and $1.8 billion between 2009 and 2017. Water damage is the key driver behind these growing costs."

A review of loss data suggests that water damage is not the key driver behind growing costs, represents less than a third of total losses and is decreasing slightly as a percentage of total losses. The following chart from the report shows total losses:

And this next chart shows the distribution of water damage peril losses up to 2008 and after 2008:

The values for the chart above are summarized in the following table:

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A review of the "Combatting Canada’s Rising Flood Costs" report on the effectiveness of wetlands for flood risk reduction is explored in this post: https://www.cityfloodmap.com/2018/10/wetlands-and-natural-infrastructure-for.html

A review of the thoroughness of cost-benefit analysis (often meta-analysis, or incomplete analysis) in the "Combatting Canada’s Rising Flood Costs" report is in this post:  https://www.cityfloodmap.com/2018/11/storm-warts-floods-awaken-new-hope-for.html

Urban Flood Risk Evaluation to Guide Best Practices and Projects - Tiered Vulnerability Assessment and Risk Mapping for Storm, Wastewater and River Systems from Flood Plain to Floor Drain

A tiered vulnerability assessment framework for existing flood risk in urban systems was developed to support best practices development in Canada as published in this previous post. Risk mapping is critical to defining areas of interest for implementation of no-regrets policies and practically deployed programs that can reduce risk in a cost-effective and technically effective manner. Examples of such include stormwater management peak flow control policies, or construction by-laws, and low-cost programs to reduce stresses on infrastructure systems (e.g., sanitary or combined sewer downspout disconnection) or to isolate flood-prone properties from sewer back-up risk (e.g., plumbing protection through backwater valve installation or foundation drain disconnection/sump pump installation).

A review of vulnerability assessment methods was prepared for the Ontario Urban Flooding Collaborative to share risk mapping approaches being considered as part of an Ontario-wide strategy being developed to reduce existing urban flood risks. The September 13, 2018 webinar presentation is below:

Urban Flood Risk Mapping - Tiered Vulnerability Assessment in Risk Mitigation Frameworks for Existing Communities from Robert Muir

The presentation illustrates examples of tiered vulnerability assessment in areas with existing urban flooding interests and demonstrates how progressively more advanced risk characterization methods (e.g., monitoring, modelling) are considered commensurate with the level of risk. Simple methods including mapping of reported flooding to identify areas of interest for no-regrets initiatives (policies and programs) to more advanced hydrodynamic modelling methods to support economic analysis and design/implementation of viable projects are shown.

An early example of layering of multiple risk factors related to construction practices (e.g., type of drain connections to the municipal sewer network), overland flow (pluvial) flooding risks, and storm sewer surcharge back-up potential is shown, i.e., the presentation author's Stratford City-wide Storm System Master Drainage Plan. The range of simple to advanced risk characterization methods that were combined in the overall system screening and prioritization are illustrated on the following slide:

Urban Flood Risk Mapping - City of Stratford City-wide Storm System Master Plan. Dillon Consulting Limited. 

Several recent examples of multiple risk factor screening are shown in a recent blog post - the following map illustrates how era of construction (design standards inferred from dwelling age), topographic risk factors like catchment slope, overland flow path design (i.e., pluvial flooding risk) and reported historical flooding are related in a north Toronto neighbourhood:

Era of Dwelling Construction, Overland Flow and Catchment Slope, and Flood Report History - Risk Factors Affecting Reported Basement Flooding During Extreme Rainfall Events, City of Toronto Flood Reports.

While there are numerous examples where the risk factors explain the observed flooding, there are equally as many examples of risk factors not explaining the observed flooding. So mapped risk factors can explain overall trends, however there is considerable scatter in the data meaning a high degree on uncertainty when it comes to defining actions required to address priority flood risk reduction measures. As a result, local, detained risk assessments as part of comprehensive studies are required to support and infrastructure investments after areas of interest are screened though high level vulnerability assessment.

A holistic process of tiered flood risk vulnerability assessment to identify no-regrets, low-cost policies and programs (i.e., best practices) and then, commensurate with risks, more advanced assessments to define capital projects is shown in the following slide from the presentation above.

Process for Defining Policies, Programs and Projects for Urban Flood Risk Reduction Including Tiered Vulnerability Assessment (Risk Mapping).

Some 'best practices' can be identified with high level, simple to intermediate risk screening as shown below:

Defining No-regret, Low-Cost, Practically-Deployed Policies and Programs  for Urban Flood Risk Reduction With Simple and Intermediate Vulnerability Assessment (Risk Mapping).

When considering sanitary / wastewater collection systems, this holistic process for assessing risk and defining policies, programs and projects is illustrated below, including example risk factor thresholds that may be used to guide progression to more advanced tiers of assessment, and ultimately design and economic screening.

Sanitary / Wastewater System Risk  Assessment Process to Implement Policies, Programs and Capital Projects - Simple to Advanced Risk Mapping and System Analysis to Prioritize Actions with an Urban Flood Risk Reduction Strategy 

Similarly, storm systems can be assessed in a holistic manner with progressively more and more advanced / detailed risk characterization.

Sanitary / Wastewater System Risk  Assessment Process to Implement Policies, Programs and Capital Projects - Simple to Advanced Risk Mapping and System Analysis to Prioritize Actions with an Urban Flood Risk Reduction Strategy

For illustrative purposes, the City of Toronto financial screening threshold for basement flood mitigation projects is shown ($32k per benefiting property) to evaluate advanced evaluation projects. A benefit/cost of 2 is also shown, which is based on the eligible Disaster Mitigation Adaptation Fund project Return on Investment (ROI) threshold. Alternative thresholds for benefit/cost ratios (from under unity to 1.3) to support pubic investment in flood mitigation infrastructure are discussed by Watt in Hydrology of Floods in Canada.

A holistic approach to urban flood risk mitigation will focus on high risk areas and deliver risk reduction in a timely and cost-effective manner. Across Canada and Ontario, many communities were designed and constructed under design standards with limited flood resiliency compared to today's modern standards. The proportion of existing residential communities that have resiliency limitations can be estimated according to Statistics Canada data on dwelling construction date ("Dwelling Condition (4), Tenure (4), Period of Construction (12) and Structural Type of Dwelling (10) for Private Households of Canada, Provinces and Territories, Census Divisions and Census Subdivisions, 2016 Census"). Data tables for various geographies (i.e., Canada and Ontario), and for various ground dwelling types (i.e., single detached house, semi-detached house, row house, and other single attached house) have been used to estimate the proportion of residential development within various eras of construction to classify resiliency and risk mitigation needs. The graphs below illustrate the number and proportion of these types of dwelling construction in different construction eras based on Statistics Canada's 2016 Census data.

Ground Dwelling Era of Construction - Ontario and Canada - Design Standards and Flood Resiliency. Dwelling Count and Cumulative Fraction of Dwellings Using Statistics Canada 2016 Census Data.

Ground Dwelling Era of Construction - Ontario - Design Standards and Flood Resiliency. Dwelling Count and Cumulative Fraction of Dwellings Using Statistics Canada 2016 Census Data.

Pre-1990 construction accounts for about 65% of residential ground dwellings in Canada and in Ontario (i.e., excluding apartments). Generally, design standards after 1990 offer high resiliency (very low risk) such that risk mitigation through remediation is not a priority. Lower risks are expected in post-1980's construction where wastewater systems are fully separated (i.e., about 14% of Ontario construction), and moderate to high risks are expected in communities constructed before 1980. Tiered vulnerability assessments will typically begin with the 65% of pre-1990 areas, and progressively refine risks associated with systems within those areas.  To illustrate this, sanitary system upgrades to address flood risks in the City of Markham, determined after advanced risk assessments, may account for less that 2% of the total sanitary sewer length - modelling revealed that only 1.8% of sanitary maintenance holes exhibited surcharge during a 100-year event that would be considered a basement flooding risk.

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More reading:

i) costs and benefits of green and grey infrastructure

An Economic Analysis of Green v. Grey Infrastructure from Robert Muir

ii) technical and financial constraints with green infrastructure / low impact development implementation

Ontario Society of Professional Engineers OSPE Green Infrastructure Roundtable - Green Infrastructure – Cost Effectiveness and Technical Challenges for Flood Mitigation from Robert Muir

iii) Weathering the Storms with Ontario's Environment Plan - Understanding Challenges and Opportunities for Flood Resilience in Ontario

Thinking Fast and Slow About Extreme Weather and Climate Change

Thinking, Fast and Slow is a best-selling^[1] 2011 book by Nobel Memorial Prize in Economics winner Daniel Kahneman which summarizes research that he conducted over decades, often in collaboration with Amos Tversky.^[2][3] It covers all three phases of his career: his early days working on cognitive biases, his work on prospect theory, and his later work on happiness.

The book's central thesis is a dichotomy between two modes of thought: "System 1" is fast, instinctive and emotional; "System 2" is slower, more deliberative, and more logical.

The book delineates cognitive biases associated with each type of thinking, starting with Kahneman's own research on loss aversion. From framing choices to people's tendency to substitute an easy-to-answer question for one that is harder, the book highlights several decades of academic research to suggest that people place too much confidence in human judgment.

Source - Wikipedia

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Why talk about this book on this blog? Because it can explain, through the lens of Kahneman's research, biases in our thinking and understanding of extreme weather, flooding and climate change.

Kahneman's research helps explain to how the media, the public, and groups without scientific resources substitute an easy to answer question on meteorology for the harder ones on urban hydrology, infrastructure hydraulics, multi-objective decision making, extreme value statistics and risk assessment.  Here are some examples of the biases in thinking:

Heuristic biases

Anchoring or focalism is a cognitive bias that describes the common human tendency to rely too heavily on the first piece of information offered (the "anchor") when making decisions. In the context of extreme weather and climate change, most people have been exposed to well-documented temperature trend data for example from Al Gore in An Inconvenient Truth, and may use this "anchor" when making decisions about extreme rainfall trends (i.e., they assume historical rainfall trends are the same as temperature trends):

Exposure to temperature trend data anchors decision making on rainfall trends.  Exposure to trend data on annual rainfall (e.g., frequency of days with precipitation during a year) anchors decision making on frequency of short duration rainfall events that cause flooding - this is despite the fact that days with precipitation represents even minuscule 'trace' rainfall events (< 0.5 mm depth) while flood events typically require 100 times that threshold of rain (e.g., 50 mm depth).

Having weather personalities report that after extreme storms we had more than a month's rain in x hours, for example, anchors the public's perception about the frequency, or rarity, of the event when in fact a statistical evaluation of rainfall extremes would show that exceeding average summer monthly rainfall totals is not rare.

For example, after the July 8, 2013 storm in Toronto, where 126.0 mm of rainfall was recorded at Pearson Airport, the National Post reported "Before Monday, the highest rainfall ever experienced in Toronto for July 8 was 29.2 mm set in 2008 — a record that was more than tripled".  Tripling records sounds extreme when referred to a particular calendar day and anchors perception of rarity - but calendar days statistics are irrelevant given that summer convective storms are uncommon and 2/3 of July days are dry - furthermore daily totals of a similar magnitude were recorded twice before in 1980 and 1954 (119.9 mm and 137.4 mm respectively), and the previous July 8 record was exceeded by 200% in 7 other years between 1950 and 2013.  Headlines or course try to emphasize the rarity of events, not the commonplace.

In presenting Insurance Bureau of Canada and Institute for Catastrophic Loss Reduction's  "Telling the Weather Story" to the Empire Club in 2012 (YouTube) Dr. McBean first presents trends on temperature and discusses them for five minutes showing undeniable trends in warming, and warming rate - this anchors listeners.  He then switches to rainfall but shows no data, and instead only a theoretical bell curve frequency shift (see 13:10 in the video), but then concludes storm frequency is increasing as well. The listeners' cognitive bias due to anchoring on temperature will allow them to readily accept rainfall increases as facts as well, as opposed to recognizing rainfall increases as theoretical speculation as fully explored in this blog post and slide deck and in fact confirmed by Environment Canada and the CBC in response to inaccurate reporting.

The availability heuristic is a mental shortcut that occurs when people make judgments about the probability of events by how easy it is to think of examples.  In the context of extreme rainfall, 24-hour weather broadcasting, and 24-hour new channels give the public many example of flooding events that skew the perceived probability of occurrence. Hurricane Katrina and Hurricane Sandy are examples of extreme flooding that the public can recall in the context of flooding, but that have little relevance to urban flooding caused by convective thunderstorms. Likewise for Tsunamis.  Other types of flood events caused in large part by operational issues and inherent vulnerabilities are recalled and mistakenly associated with extreme rainfall as the sole cause (Union Station flooding June 1, 2012 was due to construction pump bypass capacity specifications, GO Train flooding July 8, 2013 due to rail line vulnerability (being below known moderate frequency flood levels)). 

Go Train Flood - Don River Floodplain - July 8, 2013

The availability heuristic leads to systematic biases, demonstrated in the judged frequency of repeated events.  It is irrelevant

Stranded GO Train in 1981 in same location as the
stranded GO Train in 2013 in the Don River valley.

that GO Train rail area flooding occurred on December 25, 1979, January 11, 1980, March 21, 1980, April 14, 1980, February 11, 1981 and May 11, 1981.  Under the availability heuristic people tend to heavily weigh their judgments toward more recent information, making new opinions biased toward that latest news. Nobody knows that the May 29, 2013 flood was worse (higher rainfall in East York, higher flow and flood levels at Todmorden gauge near the site) - because the train schedule missed the flood timing! Nobody remembers Ivan Lorant's flood inquiry report for Premier Bill Davis in the early 1980's.  Nobody asked the Toronto and Region Conservation Authority if this was a flood prone area and if this extent of flooding was unusual at the GO Train flood site. Nobody asked the Port Authority if the lack of Keating Channel dredging in the past few years contributed to flooding, just like it did in the early 1980's before the inquiry. 

Attribute substitution is a psychological process thought to underlie a number of cognitive biases and perceptual illusions. It occurs when an individual has to make a judgment that is computationally complex target attribute, and instead substitutes a more easily calculated heuristic attribute. This substitution is thought of as taking place in the automatic intuitive judgment system (System 1), rather than the more self-aware reflective system (System 2). Hence, when someone tries to answer a difficult question, they may actually answer a related but different question, without realizing that a substitution has taken place. This explains why individuals can be unaware of their own biases, and why biases persist even when the subject is made aware of them.

System 2 thinking about flooding must consider rain, runoff, flow and
flooding processes - a slow, effortful. complex and reliable approach.

As rain first causes runoff, which then creates flow, which then causes flooding, it is easy to mistakenly correlate increased flooding to increased rainfall.  The alternative is analyzing the complex problems of urban hydrology changes that influence runoff, the stormwater management mitigation measures that can lessen some impacts of some development at some scales, hydraulic interaction in the flow systems including riverine systems (Lisgar District Basement Water Infiltration Assessment is a wonderful example in Mississauga, or Basement Flooding Areas 4 and 5 in Toronto (see page 4 in the Executive Summary on Black Creek interaction)) with the overland, underground separated, combined and partially separated sewers, hydraulic impacts of operational constraints (bypass pumping during construction, inadequate dredging), hydraulic impacts of environmental protection measures (provincial F-5-5 compliance, federal Fisheries Act compliance, etc.), and hydraulic impacts of development intensification on overland flow routes and interactions with underground systems and private systems.  It is much easier to focus only on rainfall. And, conveniently, everyone has an opinion about the weather.

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Many prominent organizations and individuals have established a cognitive bias based on temperature trends and have since applied Kahneman's fast and error-prone System 1 thinking approach to rainfall extremes.  The anchoring bias in media report emphasizes the rarity / frequency of events and ignores past events and other causes (operational or intrinsic vulnerability) of flooding - Environment Canada's extreme rainfall frequency and trend data is ignored. The availability bias of extreme flooding events reported through the media skews the public's perception on the true probability of events - it is very easy to find examples of flooded underpasses because these are designed to lower flood standards, but flood a lawyer's Ferrari in an underpass and it will be ingrained in the public's mind for a long time. Attribute substitution bias allows the public to simplify and explain flooding with rainfall (rain = flood) as opposed to thinking about the actual complex system (rain = baseline runoff + development runoff +- mitigation measures = flow +- capacity constraints +- operational factors = flooding).

Media support attribute substitution by ignoring even the most fundamental physical facts. For example, the GO Train flood on July 8, 2013 was cited as a 2013 Top Weather Story by CBC News as they associated the record at Pearson Airport with the flooding (record rain somewhere = flooding somewhere else).  They ignored the fact that Pearson is in the Etobicoke Creek Watershed, three watersheds away from the Don River Watershed where the GO Train flooded - this is basic hydrology: Mississauga rain = runoff in Etobicoke Creek, not in Don River). They ignored that no record rainfall occurred in the Don River Watershed as they were anchored to the Mississauga data 25 km away.

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System 2 Mode of Thought -  Data and Analysis - Slow, Methodical.
Source: Environment Canada Engineering Climate Datasets ver 2.3.

Evidence-based policies require us to check facts: 

“There will still be times when someone accuses us of having lost our way, of having chosen the wrong priorities, and I know that can be hard to hear. But in moments in great and important choice, when the stakes are high, and the consequences are long-lasting, we have to test our assumptions.” Premier Kathleen Wynne, AGM, June 6, 2015 

System 1 Mode of Thought - Infographics and Heuristics - Fast, Emotional.
Source: Environmental Commissioner of Ontario,
Connecting the Dots on Climate Data in Ontario.

Testing assumptions requires Kahneman's "System 2" thinking - slow, deliberate and logical, as opposed to fast, instinctive and emotional in order to overcome heuristic biases in our thinking. 

Please. More Data.

Fewer Infographics.

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"People are not accustomed to thinking hard, and are often content to trust a plausible judgment that comes to mind."


Daniel Kahneman, American Economic Review 93 (5) December 2003, p. 1450



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Robert Muir's presentation on infrastructure adaptation to the WEAO OWWA Joint Climate Change Committee explores in significant detail the trends in Southern Ontario rainfall extremes that affect flood risk and that drive mitigation priorities:

Infrastructure Resiliency and Adaptation for Climate Change and Today’s Extremes from Robert Muir

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Tada! "Thinking Fast and Slow" themes in the above post have been expanded and are now published in the Journal of Water Management Modelling with the title "Evidence Based Policy Gaps in Water Resources: Thinking Fast and Slow on Floods and Flow":

https://www.chijournal.org/C449