An online article in Canadian Underwriters describes the new flood risk models developed to assess hazards, price flood endorsements and assess portfolio risk in canadianunderwriters.ca. In the comment below, we look beyond the short term insurance risk data needs and toward to holistic approach risk management.
The journey toward a Canada-wide flood risk model shows one thing - a paradigm shift is needed in how the insurance industry, regulatory agencies and municipalities share data on flood risks. Only then will there be data to support fair and accurate insurance products based on risk, data that society can access and use to make important risk management decisions, and data that municipalities/regulatory agencies/ministries can use to set risk avoidance, reduction and remediation policies. The discussion today is just the first step toward that. While a robust 10 m fine grid flood risk screening tool could satisfy the immediate need for price local insurance products and assess portfolio risk, the long term goal has to be a comprehensive risk management strategy built on this type of data. How? Well if "flood is the new fire", consider the fire model where fire underwriters, municipal fire services their consultants, and property owners participate in a system that quantifies and shares risk data and where risk management decisions are made in a coordinated manner.
With immediate product needs, the insurance industry requires a consistent risk model across the country and so has to resort to coarse 30 m topography cell screening to at best identify riverine risks - but can not account for the local factors such as hydraulic relief structures that are important for the higher frequency events (i.e., bridges, culverts and embankment underpasses that are 'under' the 30 m topography model), or the underworkings of sewer infrastructure or surface constraints (building flow obstructions) critical in urban flash flooding beyond river valley systems. Meanwhile, some municipalities are sitting on InfoWorks and EPA SWMM dual-drainage models that predict hydraulic flood levels pipe-by-pipe that characterizes basement flood risk, and predict block by block overland ponding for all storm return periods. Similarly, conservation authorities in Ontario have return period riverine flood levels derived from survey-grade topography and hydraulic structure surveys, considering calibrated flow hydrology. Flood risk data is not new - Toronto East York SWMM models were first developed in the 1970's on punch cards, Toronto North York models in the 1980's on 20MHz 386's - no need for GPU processing really. Today Toronto is covered in InfoWorks models, Hamilton has Mike Urban, Calgary XPSWMM ... and on.
But all this existing data is in silos, each with a single regulatory or management purpose, and never rolled-up, parsed, or aggregated to provide a baseline for insurance risk purposes. You can understand why Carpenter pursues a Canada-wide 30 m grid model for surface flooding or IBC develops MRAT for sanitary back-up risk characterization - its because it is easier to start from scratch with coarse risk assessment than to get down in the weeds of pipe-by-pipe municipal infrastructure flood models (that do vary by neighbourhood to neighbourhood, consultant by consultant, model platform by model platform), or creek-by-creek conservation authority (or other provincial agency) floodplain models (that do vary as well in terms of vintage, accuracy, consistency in hyetographs/design storm drivers). So there has been a deluge of data building for a half century on riverine flood risk, and over decades on urban flood risks - but it has never been approached in a way that it can be leveraged for holistic flood risk management.
Under a new paradigm, with a more holistic risk management end goal in mind, flood risk data can be collected, developed and applied through a partnership approach, without the need to reinvent or duplicate riverine flood risk mapping. Consistent, shared risk data would support alignment between the regulatory aspects of flood risk management, the business decisions related to development, and municipal and government decisions on infrastructure investment and risk reduction programs (flood proofing, emergency preparedness, education). The constraints to getting to there is not GPU computing power for 1 metre-cell 2D urban dual drainage models, but rather it is more fundamental and more challenging, relating to how various private and public organizations cooperatively manage issues of common interest.
In-depth data and analysis on extreme weather and flood risks on www.cityfloodmap.com share engineering insight on complex topics of infrastructure design and performance, urban hydrology, flood risk assessment, and cost-effective risk management. Our goal is to promote critical, evidence-based "Thinking Slow on Floods and Flow" to improve flood and stormwater management policies and achieve effective environmental outcomes. R.J. Muir, Toronto, ON.