Has Extreme Rainfall Become More Severe in Canada? - Research Shows Rain Intensities Mostly Unchanged (Stationary)

A research paper Assessment of non-stationary IDF curves under a changing climate: Case study of different climatic zones in Canada in the August 2021 Journal of Hydrology: Regional Studies by Silva et al. evaluated trends in historical annual maximum rainfall across Canada for a range of durations at climate stations with long-term records (over 50 years) (link: https://www.sciencedirect.com/science/article/pii/S2214581821000999). Projected future IDF curves are discussed in a future post.
Regarding observed rainfall maxima, the paper comments on the lack of consistent trends observed:
"There is no clear spatial pattern of trend in precipitation among the considered regions of Canada. Only the Moncton station shows a significant non-stationary behaviour in GEV modelling over most of the durations. No change pattern (i.e., trend detection) is confirmed for all durations at two sites under the influence of Great Lakes (London and Hamilton)."
The following Table 2 excerpt from the paper shows where annual maximum precipitation is stationary (not changing, as noted with the symbol "I") and non-stationary (changing) over the observation period.

Table 2. The best GEV model for each station and different durations in the historical period*.

Duration (minutes)Selected Station
10VI (0.030)IIIIII
15IIIVI (0.043)II
30IIIV (0.030)II
60IIIII (0.003)II
120IIIVII (0.047)II
360IIIII (0.041)VII (0.011)I
720II (0.036)IIII (0.016)II
1440IIIII (0.002)IVII (0.025)

The best GEV model is shown using I to IX, according to the list of models in Appendix A. I corresponds to the stationary model, while values from II to IX correspond to the non-stationary models.

In central Canada, 26 of 27 rainfall series of maximum rainfall over durations of 5 minutes to 24 hours for Hamilton, London and Winnipeg stations were stationary, i.e., unchanged. The Great Lakes region represented by London and Hamilton, where no change in annual extreme rainfall was observed, also includes several large urban centres. 
A previous post evaluated Environment and Climate Change Canada annual maximum rainfall trends for 676 climate stations across Canada: https://www.cityfloodmap.com/2021/10/annual-maximum-rainfall-trends-in.html
There were few statistically significant trends, up or down, in the most recent v3.20 datasets, as noted in the following chart:

This summary table below shows that earlier datasets had similar trends with the majority of trends (i.e., over 90% of stations with calculations available showed no significant trend):

Trend in Maximum Rain    v3.20       v3.10       v3.00         v2.30
Significant Increase              4.16%     4.28%       4.18%        4.09%
Significant Decrease             2.25%     2.24%       2.33%        2.30%
No Significant Trend          85.73%    85.80%     85.55%      86.37%
No Calculation                      7.86%      7.68%       7.94%        7.24%

Looking at particular regions such as Southern Ontario and Manitoba where stationary annual maximum rainfall was observed in the paper above, one can see the variability in trends and significant across different stations and durations.

Southern Ontario, including the Hamilton and London stations has more decreasing trends than increasing ones:

In Manitoba, the trends vary by station with some recording increases over all durations with other recording decreases. Winnipeg has a combination of decreases, no change, and an increase for the 9 durations evaluated as shown below:

These trends are as reported in Environment Canada's v3.10 Engineering Climate datasets and will be published for all regions in the upcoming National Research Council of Canada cost benefit guideline for flood control infrastructure in a changing climate.

The tables above suggest that evaluating single stations may not provide a complete picture of overall changes in a region. For example, the paper highlights the non-stationarity in Moncton annual maximum rainfall. Other long term stations in New Brunswick, such as Fredericton have some trends that are opposite to those observed in Moncton (i.e., the Fredericton station has more decreasing trends than increasing ones and a statistically significant decrease), and others do not exhibit as strong increasing trends (e.g., the Charlo Auto station does not have the same number of statistically significant increases as Moncton and its 1-hour rainfall has not increased). Therefore Moncton is not representative of other long-term New Brunswick station trends.

The following charts show the v3.20 annual maximum series trends for the six stations studied in the paper, i.e., Calgary, Hamilton, London, Moncton, Vancouver and Winnipeg.

Only Moncton 6, 12 and 24-hour series have statistically significant increases. As noted above, Fredericton has observed decreasing trends as well, including a statistically significant decrease in 5-minute annual maximum rainfall, and no statistically significant increases:

Ultimately, annual maximum rainfall series are used to derive design rainfall intensities (IDF curves) by fitting a probability distribution to observed annual maxima. A previous post demonstrated how IDF values changed following the addition of recent observations (link:  https://www.cityfloodmap.com/2020/07/how-have-rainfall-intensities-changed.html):

On average, extreme intensities (red dots represent 100-year intensities) have decreased slightly for all durations. Less extreme intensities (green dots represent 2-year intensities) have increased slightly. Regions have different trends, sometimes with short duration intensities increasing and long-duration intensities decreasing, and vise versa as shown in another post: https://www.cityfloodmap.com/2020/07/can-we-use-daily-rainfall-models-to.html


The paper also presents future rainfall intensity projections that will be reviewed in an upcoming post. A review of projected results, included in supplemental material but not the main document shows that under some emissions scenarios (i.e., representative concentration pathways), rainfall intensities are projected to decrease in Ontario. The main document only presents projections for a high emissions scenario (RCP8.5) that has been questioned in terms of its likelihood by the Pacific Climate Impacts Consortium (see Science Brief: https://www.pacificclimate.org/sites/default/files/publications/Science_Brief_39-June_2021-final.pdf)

The Science Brief notes "Given that RCP8.5 is not the most "likely" outcome of emissions following business-as-usual or stated policy intensions, its reasonable to refer to it as a high emissions scenario instead of business-as-usual.

Others have also questioned the validity of RCP8.5 as Roger Pielke Jr. reported in Forbes (https://www.forbes.com/sites/rogerpielke/2019/09/26/its-time-to-get-real-about-the-extreme-scenario-used-to-generate-climate-porn/?sh=23797f704af0) and with Justin Ritchie in Issues in Science and Technology (https://issues.org/climate-change-scenarios-lost-touch-reality-pielke-ritchie/).

Why is understanding emissions scenario relevant to rainfall design intensities? Because temperature-based adjustments are recommended to project future rainfall design intensities (see Climatedata.ca and CSA IDF Guide approach in an upcoming post), and temperature changes depend on the emissions scenario considered. High emissions scenarios can be considered in future projections "if rainfall consequences to infrastructure are severe" as part of risk-based decisions making, according to Climatedata.ca. The ASCE's MOP 140 Climate-Resilient Infrastructure: Adaptive Design and Risk Management, in particular Chapter 7 Adaptive Design and Risk Management, also provides recommended levels of climate analysis as a function of design life and risk category, and the characteristics of various levels of climate analysis.

Adjusting IDF Curves to Account for Climate Change

The following page "IDF Curves and Climate Change" is presented at climatedata.ca and describes a methodology for adjusting rainfall design intensities for future conditions. The need to account for future conditions in long-term planning is noted in Environment and Climate Change Canada's Engineering Climate Datasets IDF Files:

Past changes in IDF values have been reviewed in a previous post: https://www.cityfloodmap.com/2020/07/how-have-rainfall-intensities-changed.html

Note that the ECCC guidance relies on RCP4.5 and RCP8.5 scenarios based on historical and future annual average temperatures for IDF stations from the Climate Atlas. Recent research by Roger Pielke Jr, Matthew G. Burgess and Justin Ritchie suggests those RCPs are not the most plausible scenarios (see: "Plausible 2005-2050 emissions scenarios project between 2 and 3 degrees C of warming by 2100" in Environmental Research Letters - https://iopscience.iop.org/article/10.1088/1748-9326/ac4ebf). Accordingly practitioners involved in robust risk assessments should consider how scenarios that are less plausible are considered in analysis.


Learning Zone
Topic 6: Intensity-Duration-Frequency (IDF) Curves
IDF Curves and Climate Change

It is not appropriate to use IDF curves based on historical information alone for long-term planning. To account for climate change impacts to extreme rainfall, ECCC recommends use of a scaling methodology to adjust IDF curves. Read this article for additional information about integrating climate change into IDF curves, including a practical example.

5 min


IDF curves are an important tool for decision-making about risks of extreme precipitation, but climate change is expected to increase extreme rainfall in Canada. Because of this, IDF curves based on historical observations alone are not appropriate for long-term decision-making. To account for climate change impacts to extreme rainfall and IDF curves, Environment and Climate Change Canada recommends use of a scaling methodology.

Climate change has intensified extreme rainfall events in North America and is projected to do so even further in future. However, projecting future rainfall metrics shown on IDF figures remains challenging due to sparse extreme rainfall observations, challenges in modelling local extreme rain events, and climate variability.

Due to the challenges described in the Primer on Climate Change and Extreme Precipitation, both climate models and statistical tools have limitations in their ability to project future short duration rainfall events. This is described in more detail in CSA PLUS 4013:2019: Technical Guide: Development, Interpretation And Use Of Rainfall Intensity-Duration-Frequency (IDF) Information along with corresponding guidance for practitioners.

However, a relationship between warming temperatures and precipitation extremes provides an alternate means for adjusting historical IDF curves. This ‘temperature scaling’ method is being increasingly used to estimate future Canadian rainfall extremes.  It is described in CSA PLUS 4013 and is being used to develop future rainfall estimates for the National Building Code of Canada and Canadian Highway Bridge Design Code.

Temperature scaling provides a simple and robust way to update IDF curves for climate change.  However, careful consideration of uncertainties in estimates of future extreme rainfall is still required.  Scaling factors may vary between locations and rainfall event types.  Local temperature change projections depend on future emissions, climate model choices, and natural variability.   And the historical IDF curves that underlie any future IDF curves estimates may themselves be less than ideal estimates of past rainfall extremes.

ECCC suggests the following method for estimating future changes to extreme rainfall magnitudes described on IDF curves:

    1. For the location of interest, download historical IDF curve data from ClimateData.ca or develop based on guidance from ECCC and CSA PLUS 4013:2019.  Use this data to determine historical estimated rainfall intensity (RC) for the storm duration and return period of interest.

    2. Determine an appropriate future timeframe and emissions scenario, and using ClimateData.ca, the Climate Atlas of Canada, or Climate Resilient Buildings and Core Public Infrastructure data, find the long-term (30-year mean) annual mean temperature change (ΔT) for your location, timeframe and emission scenario.  Develop this information by using results from an ensemble of climate models.

    3. Determine future estimated rainfall intensity value (RP) according to the equation:

RP = RC x 1.07^ΔT

Integrating Climate Change into IDFs: A Worked Example

This exercise provides an illustrative step-by-step example of how to apply the temperature scaling approach to shift IDF values and estimate future extreme rainfall conditions.

Example goal: Estimate change in intensity of 1-in-100-year rainfall, for a 1-hour storm duration, for design of new a Canadian infrastructure project that is expected to last 50 years.

  1. Estimate observed 1-in-100-year rainfall intensity for a 1-hour storm event.
  2. Estimate change in temperature, 50 years in the future.
  3. Estimate change in extreme rainfall 50 years in the future.

Step 1: Obtain a historical estimate of 1-in-100-year rainfall for 1-hour storms:

Download available ECCC IDF historical baseline information from ClimateData.ca -> Navigate to the ClimateData.ca IDF map, and identify the closest available data to your location, with a long record of rainfall observations.

Identify historical 1-in-100-year 1-hour storm intensity for your location.

Step 2: Estimate change in temperature for your location, for 50 years in the future:

Download historical and future annual average temperatures for the IDF station location from the Climate Atlas (or another suitable resource) for an ensemble of climate models and for RCP4.5 and RCP8.5.  If using the Climate Atlas: obtain a location-relevant climate summary report, and for Variable=‘Mean Temperature’ and Type of display=‘Time Series’, from the ‘Climate model data’ link obtain two CSV format spreadsheets, each containing multi-model RCP 4.5 and RCP 8.5 projection information.

  • For each climate model simulation and RCP scenario within the downloaded ensemble, calculate:
    • 31-year average Historical Temperature that best represents the observational period used to develop historical IDF information:
      • For each RCP scenario-specific CSV file, use a spreadsheet program to determine a 31-year average annual historical temperature for each climate model. Center this 31-year time period in the middle of the observational period used to develop the original historical IDF curves.
    • 31-year average Future Temperature, centered on the final year of the proposed asset lifetime:
      • For each RCP scenario-specific CSV file, use a spreadsheet program to determine the 31-year 2065-2085 average annual future temperature value for each climate model.   This period is used because it brackets the year 2070, which is the estimated end-of-life for the proposed asset, given the 2020 construction year, and a 50 year design lifetime.
    • Change in temperatures over the asset lifetime:
      • For each climate model and RCP scenario, use Microsoft Excel or a similar program to calculate the change in temperatures:
Temperature Change = Future Temperature – Historical Temperature

Step 3: Estimate change in extreme rainfall for your location, for 50 years in the future:

  • Given historical rainfall intensity and the range of climate model and RCP scenario-specific temperature change values, use temperature scaling to calculate range of estimated future 1-in-100-year 1-hour intensities for your location.  For each climate model and RCP scenario, use a spreadsheet program to calculate future 1 hour 1-in-100-year rainfall intensities RP using the equation  (RP=RC x 1.07^ΔT)  and setting RC to the historical rainfall intensity from the historical IDF curve, and ΔT equal to each climate model’s temperature change value, for each RCP scenario.
  • Aggregate future rainfall intensities into summary statistics for use in risk-based decision-making.  For each RCP scenario, calculate summary estimates of future rainfall intensity (for example, 10th, 50th and 90th percentiles).
  • Apply risk-based decision-making to choose the future extreme rainfall value that is most appropriate for asset risk thresholds.  For example, if rainfall consequences to infrastructure are severe, consider applying upper end of projected future RCP 8.5 1-hour 1-in-100-year rainfall intensities to infrastructure design.
Now that you have read IDF Curves and Climate Change, you may wish to review IDF Curves 101 and Best Practices on Using IDF Curves.

National Guidelines on Undertaking a Comprehensive Analysis of Benefits, Costs and Uncertainties of Storm Drainage and Flood Control Infrastructure in a Changing Climate

The following paper was presented at the 2021 WEAO conference. The presentation is included at the bottom of the post. A pdf copy of the paper is available here:  paper

National Guidelines on Undertaking a Comprehensive Analysis of Benefits, Costs and Uncertainties of Storm Drainage and Flood Control Infrastructure in a Changing Climate

Fabian Papa*, M.A.Sc., M.B.A., P.Eng., FP&P HydraTek Inc., Robert J. Muir, M.A.Sc., P.Eng., City of Markham, Yehuda Kleiner, Ph.D., P.Eng., National Research Council of Canada

*FP&P HydraTek Inc., 216 Chrislea Road, Suite 204, Vaughan, Ontario L4L 8S5


      Following more than two years of extensive research and stakeholder engagement, the National Research Council of Canada (NRC) has recently completed the development of a comprehensive resource for practitioners to assist in the development of economic assessments of initiatives aimed at reducing flooding damage to core public infrastructure assets.  The overall guidelines which bear the same title as this paper consists of a “main” guideline document supported by several appendices of foundational research, comprising over 700 pages in total.  

       The guidelines (NRC, 2021) were developed in recognition of the need to harmonize and standardize the assessment of the value of storm drainage and flood control infrastructure initiatives. The benefits provided by these infrastructure initiatives include the value of future avoided damages as well as direct and indirect co-benefits, such as enhanced health, recreational and environmental value.  These benefits are compared to the costs associated with the infrastructure initiatives whilst considering the various uncertainties associated therewith, explicitly including those uncertainties associated with a changing climate.  While such analyses are not uncommon in Canada, they have generally been limited to large-scale projects or other special situations requiring significant levels of investment and sophistication. In this light, these guidelines are intended to help promote such practices for a broader range of projects and a broader range of jurisdictions with varying degrees of sophistication as well as the quantity and quality of available information relating to their assets.

      These guidelines are intended to promote the rational assessment of projects or initiatives, using rigorous analysis through an economic lens such that competing projects or alternatives can be objectively assessed and compared.  Concepts such as the time value of money, benefit estimation, life cycle costs, net present value, net benefits, benefit-cost ratios, cost-effectiveness, sensitivity analyses and probabilistic risk assessments are explicitly considered in the guidelines.  The application of these concepts is demonstrated through five case studies that span a broad spectrum of project or initiative types as well as scales.

      This paper is intended to provide a brief synopsis of the guidelines, and the reader is encouraged to obtain a copy of the complete publicly-available document for additional details.

 Organization of the Guidelines

     The guidelines are organized into two components: (i) a main body referred to as the Guidelines Document; and (ii) nine appendices consisting of a comprehensive bibliography with over 300 entries followed by a glossary and list of acronyms, the foundational research (discussed further below) and case studies.  The Guidelines Document itself provides the reader with brief summaries of the salient findings of the foundational research work, followed by a generalized approach to conducting the economic assessments and relevant information for performing time value of money calculations, estimating benefits and costs as well as assessing uncertainties.  As with any such practice, it is evolving in nature and, while the fundamental concepts generally do not change materially over time, the ability to apply these concepts can change as the degree of available information expands and improves.  To this end, a brief section dealing with considerations for future work concludes the Guidelines Document.

      The extensive foundational research work is summarized as follows (with the relevant appendix titles in bold typeface):

 ·       A Benefit-Cost Analysis Industry Scan was undertaken to assess practices across Canada and internationally to identify the state-of-the-art as well as limitations.  Included with this work was the review and assessment of several relatively recent applications made to Infrastructure Canada’s Disaster Mitigation Adaptation Fund (DMAF) which, in turn, revealed several issues related to the estimation of benefits and application of benefit-cost analyses.

·       A thorough review of Direct & Indirect Long Time Horizon Flood Damages reports and research studies was undertaken in conjunction with a review of available insurance industry data sets for purposes of estimating benefits (i.e., avoided damages) associated with project or initiatives aimed at reducing flooding.  While bottom-up estimation of avoided damages is fairly common, damage estimation considering actual reported losses has not been readily available – insurance industry claim data has been analyzed to support such analysis.

It is not always sensible or appropriate to apply bottom-up techniques when assessing certain project types or scales.  The ability to use insurance industry data allows for top-down assessments and guidance on how this is done is provided in this appendix.  Amongst the concepts covered in this portion of the research is that related to the use of damage-probability relationships to derive the Expected Annual Damages (EAD), also referred to as Annual Average Damages (AAD), being an important value in the estimation of the overall present value of damages. 

Table 1 provides the results of the assessment of available insurance industry data in relation to the value of sewer back-up. Losses per property may be applied to bottom-up analyses., Aggregate EAD values, to be used in top-down analysis are provided for flood-related losses as well as sewer back-up losses.  Additional details are available in the guidelines and its appendices, and it is expected that these values may continue to be refined and updated over time as additional information becomes available. 



Event Average Sewer Back-up Loss

(for bottom-up analysis)

Flood Loss EAD
(for top-down analysis)

Sewer Back-up/Water EAD

(for top-down analysis













British Columbia








New Brunswick




Newfoundland and Labrador




Nova Scotia








Prince Edward Island












The aggregate EAD values may be scaled down to a municipal- or project-level to estimate existing damages that could potentially be avoided in the future with the new infrastructure under consideration. Details are provided in the case studies.

·      The appendix Climate Change & Flood Damage Considerations addresses issues related to meteorological uncertainties. Potential changes in climate and meteorology have the potential to significantly affect the shape of future damage-probability relationship. This component of the research thoroughly reviews the available literature and data to give the reader a complete reference to consult.  One of the important findings of this work was the need to differentiate between short duration meteorological events (typically less than 1 day and often on the order of hours) and long duration climate that ranges from several days to more typically on the order of months, seasons or years.  Urban (pluvial) and sewer surcharge-related flooding, where the majority of damages occur, is typically driven by short-duration rainfall events and therefore, these deserve the appropriate level of focus when considering projects at the more common scales of sewersheds and municipalities.  Environment and Climate Change Canada (ECCC) data relating to short-duration rainfall trends was assessed in detail and found to (i) generally not show strong overall signs of change in any direction (i.e., up or down), and (ii) have a significant variation that is location-dependent.  These observations regarding short duration rainstorms are also corroborated in the literature (Shephard et al., 2014; ECCC, 2020).  Methods for considering future climate conditions are reviewed, albeit with varying degrees of uncertainty, and methods for dealing with such uncertainty are also identified.

·       It is important to recognize that intangible benefits also accrue with any interventions that reduce the likelihood and consequence of flooding.  Accounting for these additional benefits will have the effect of improving the economic assessment of any intervention.  The appendix titled Post-Flood Event Economic, Legal, Social and Indirect Costs addresses matters related to reductions in property values, human health impacts, population displacement, disruption of (and stress on) municipal infrastructure services, and legal costs. The appendix titled Post-Flood Event Environmental Impacts addresses matters related to flood impacts such as erosion, quality of water in the environment, impacts to flora and fauna and greenhouse gas emissions, among others.  It is worth noting that it is often difficult, and sometimes impossible to monetize many of these co-benefits.  Nevertheless, the process of identifying and (non-monetarily) quantifying such benefits is helpful in striving for a comprehensive economic assessment and may be incorporated into multi-criteria and/or triple bottom line analyses that can accompany the monetarily-based economic assessments.

·       The appendix titled Life Cycle Costs of Storm Drainage and Flood Control Infrastructure addresses an area where the industry benefits from a considerable amount of data and experience as such assessments, or at least components thereof, are routinely conducted in relation to project selection, construction cost estimation, construction contracting as well as asset management and financial forecasting.  In addition to basic guidance on developing cost streams for time value of money calculations, an abundance of cost estimating data and relationships is also provided to facilitate this component of any economic assessment.

·       The overall document concludes with an appendix consisting of five Case Studies which demonstrate the application of the various concepts and methods promoted in the guidelines.  The case studies are largely developed from actual projects of various types, scales and locations in Canada in order to give the practitioner a sense of how such economic assessments may be approached and conducted. 

      Although the guidelines are the result of specific, deliberate and thorough research, they are not to be construed as a prescriptive approach.  Each opportunity to apply them needs to be assessed based on its own particular circumstances, including the degree of importance (i.e., value of initiative considered and/or risk associated with infrastructure in question, including its criticality), the quantity and quality of available information as well as the level of effort to acquire any additional information and conduct supporting technical analyses (e.g., hydrologic and hydraulic modelling, depth-damage curve development, etc.), amongst other matters.  To assist the practitioner in identifying how to approach an analysis, a conceptual model is provided in Figure 1.




      As noted earlier, the main benefit of any flood-control measure is the value of the damages this measure is expected to avoid over the duration of its service life.  The high uncertainty that is inherent in estimating future damages necessitates a probabilistic approach, where damage from a flooding event is associated with the probability of occurrence of this event.  This is illustrated graphically in Figure 2, and involves determining the area beneath each of the damage-probability curves (i.e., both the existing curve and the future, after the improvement project, curve) to arrive at the area between these curves.



      While this calculation seems straightforward enough, it could be complicated by the fact that many relevant factors are not necessarily stationary over time.  Matters such as economic growth, representing the real (rather than nominal) value of the properties and assets that are impacted by flooding that can be expected to grow over time as the overall wealth of the society increases.  Further, climate change as well as increased urbanization may potentially change the character of the relationship between damage and probability.  Changes in the value of assets at risk of flooding (i.e., economic growth) will have the effect of shifting the damage-probability curve vertically (i.e., positive growth will result in an upward shift), while changes in climate, assumed to be represented by changes in rainfall intensities for different return periods (or probabilities of occurrence) will result in a horizontal shift (i.e., increasing rainfall intensities will result in a shift to the right).  The combined impact of these changes, as well as how EAD may change over time as a result thereof, is illustrated in Figure 3.




 A good forecaster is not smarter than everyone else,

he merely has his ignorance better organized.

- Anonymous

      It is extremely important to acknowledge, understand and explicitly consider the uncertainties inherent in any analysis, particularly given the scale of investment and potential damage implications associated with storm drainage and flood control infrastructure.  Ignoring these uncertainties may result in significant under- or over-investment, yielding poor returns on investment and depriving society of value by wasting resources that could otherwise be deployed for other, more valuable, infrastructure improvements.  The impact of neglecting to account for uncertainty is magnified by the extremely long service life of these infrastructure assets – typically in the order of 75-100 years.

      Uncertainties exist in relation to the estimation of baseline benefits and costs, as well as in relation to potential changes in the benefits of avoided damages associated with economic growth and potential climate change impacts.  Additionally, the assumptions applied for the time value of money calculations, including the discount rate and time horizon, may play meaningful roles in changing the economic outlook of a project. 

      The guidelines identify various methods for assessing uncertainty, including the relatively simple application of sensitivity analysis and, as a subset thereof, stress tests.  Both of these types of analyses have been adopted by various jurisdictions to help identify vulnerabilities in existing or proposed infrastructure systems and allow for the allocation of additional costs and efforts only where they are most needed.  A more sophisticated method of dealing with uncertainty covered in the guidelines include the application of the probabilistically-based Monte Carlo analysis, where probability distributions for each of the uncertainty-bearing parameters can be developed and applied to produce a probability distribution for the output (e.g., benefit-cost ratio or other outcome sought through the analysis). 

      The guidelines also contain a discussion of Real Options Analysis, which is expected to be particularly relevant to the intended audience given the potential scale of investment required for certain projects aimed at reducing flooding.  This approach focuses on adaptability and incorporates the ability to incorporate information as it becomes available to help decide on the appropriate next step.  It limits possible over-investment that may result from high uncertainty, which in turn leads to over-estimation of the severity of future conditions, whilst not constraining the ability to implement the investment when supported by the then available evidence.  This approach bears a strong resemblance to the Observational Method of the American Society of Civil Engineers (ASCE) in relation to the adaptive design and risk management of infrastructure for climate resiliency (ASCE, 2018).  It is a practical approach and is typically practiced in a less formal manner, although there is merit in formalizing (and documenting) such assessment processes to promote a comprehensive consideration of influencing matters as well as for purposes of communications, both when the analyses are occurring periodically over time, as well as across time periods.  The Canada in a Changing Climate: National Issues report (Government of Canada, 2021) identifies Real Options Analysis as one main approach for accommodating uncertainty in the economic appraisal of adaptation actions.


    The development of a national set of guidelines to undertake comprehensive economic assessments of storm drainage and flood control infrastructure is intended to promote, advance and to some extent harmonize and standardize such practices across Canada and at various levels of implementation.  The guidelines, supported by extensive foundational research, represent a comprehensive reference for practitioners in assessing the value of initiatives that may be considered, including the consideration of uncertainties (including those related to potential climate change impacts), such that competing projects and project alternatives can be objectively and rationally assessed so as to inform decisions and promote the judicious allocation of investment capital.  In many ways, these guidelines represent somewhat of a renaissance of the application of classical engineering economics in relation to matters that are of current relevance and in light of the vast (and growing) amount of information and tools available to inform these assessments.


American Society of Civil Engineers (ASCE) (2018) Climate-Resilient Infrastructure: Adaptive Design and Risk Management. Committee on Adaptation to a Changing Climate.

Environment and Climate Change Canada (ECCC) (2020) Climate-Resilient Buildings and Core Public Infrastructure.

Government of Canada (2021) Canada in a Changing Climate: National Issues.

National Research Council of Canada (NRC) (2021) Guidelines on Undertaking a Comprehensive Analysis of Benefits, Costs and Uncertainties of Storm Drainage Infrastructure and Flood Control Infrastructure in a Changing Climate

Shephard, M.W., Mekis, E., Morris, R.J., Feng, Y., Zhang, X. (2014) Trends in Canadian Short-Duration Extreme Rainfall: Including an Intensity-Duration-Frequency Perspective, Atmosphere-Ocean, 52:5, pp. 398-417


The follow presentation was made at the conference in London, Ontario.