Economics of Flood Damage Claims - Large Events Dominate Overall Losses - Should Effective Mitigation Strategies Focus On "The Big Ones"

What type of meteorologic events dominate flood damage claims? Is it from many frequent small storms or a few infrequent black-swan events? Understanding what size of events cause the most losses can help us focus on the most effective flood loss mitigation measures - this is essential for achieving high returns on investment in flood mitigation strategies. By reducing flood losses in an economically efficient manner, high benefit-cost ratios can be achieved.

This post summarizes the distribution of FEMA's flood damage claims and explores what type of storm events - big or small - govern extreme weather losses.

FEMA summarizes the number of payout claims and the total value of payouts for significant flood events, i.e., those with 1500 or more payouts. The total value of payouts, adjusted for inflation to 2018 dollars, is plotted below against the total number of claims in the events between 1978 and 2017:

FEMA Average Claim Amount for Various Event Sizes (Number of Claims) - Small Significant Flood Events with a Minimum of 1500 Claims Per Event

The median number of payouts is 4115 with a median payout amount of $29,700, adjusted to 2018 dollars. This is over a total of 116 flood events from 1978 to 2017.

Larger storm result in more extensive flood damages and numbers of payout claims as shown on the following chart that labels some of the largest tropical storm / hurricane events:

FEMA Average Claim Amount for Various Event Sizes (Number of Claims) - Small and Large Significant Flood Events with a Minimum of 1500 Claims Per Event

How do the larger events affect the flood damage and payout values? The average flood claim payout of $36,200 is above the median value reflecting the skew in catastrophic event distribution - the right tail of rare black-swan events in the probability distribution of events pulls the average above the median.

Five of the 116 event have claim counts that are over ten to forty times the median number of claims. That is, Hurricane Ike and Irene had over 40,000 claims compared to the median count of just over 4000 claims. And Hurricane Harvey had over 160,000 claims. The losses are greater for these larger events with the best-fit line showing average claim values of over $50,000 to over $120,000 for these largest significant events. What effect do these claim counts have on weighted claim amount - they increase the claim-count-weighted average loss to $60,600 - more than double the median claim amount per event that is not weighted by the number of claims in each event.

So when looking at the economic losses associated with a significant flood event, we need to consider the size of the event. And when we develop strategies and best practices for flood resilient communities and flood risk mitigation, striving for significant damage reduction and return on investment in averted flood damage losses, we must also consider what events cause the most damages. Canada's Disaster Mitigation and Adaptation Fund (DMAF), for example, requires return on investment (ROI) evaluations for eligible risk reduction projects. It would appear that to achieve meaningful flood damage reduction ROI we must target solutions toward events leading to the most damages

Looking at FEMA's significant flood events, data show that 3 of 116 events account for 54% of the total inflation-adjusted damages. Those 3 events are Hurricane Harvey, Superstorm Sandy and Hurricane Katrina. And the top 20 events, each with total event claims of over $500M, account for 81% of the total claims. So it is clear that to reduce the bulk of flood damages we have to consider how to increase resiliency in existing communities during the largest storm events. If we target flood risk reduction for the small catastrophic events, the smaller 97 events, we will be addressing only 20% of the total claim value. So the 80/20 rule, the Pareto principle, does apply to flood damage reduction.

FEMA Inflation Adjusted Significant Flood Event Payout Distribution - Pareto Distribution and the 80/20 Rule

The impact on a few recent large events on damages helps show sample-bias in catastrophic event losses as explored in a previous post. That is, up to 2004 prior to Hurricane Katrina, the distribution of losses based on the 1978-2004 sample of events did not consider the true 'population' distribution of flood events that includes very extreme, right-tail events. As Fleming demonstrated in "Yep, We're Skewed", short samples with high skew underestimate losses of the true population of events.

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For statistics geeks:

Could it be that the common chorus of explaining recent floods losses as being due to climate change may in fact be explained simply by statistics and larger sample sizes overcoming short sample biases (underestimation)?

Could it be that growth in high risk areas is driving flood damages higher? AON Benfield's review of Hurricane Harvey suggests that growth in at-risk areas explains some flood impacts:

 "Given the volume of water, local infrastructure across southeast Texas was simply unable to handle such an enormous amount of rainfall in a short amount of time. This led to major water run-off that quickly accumulated across a very large area. With so much residential and commercial growth throughout this part of the state – combined with abundant concrete and poor absorbing clay soil –this only worsened the flood impact."

Solutions to flood risk mitigation therefore cannot only be local infrastructure solutions to convey enormous amounts of water but rather land use planning policies to direct development and redevelopment away from high flood risk areas. As AON Benfield notes " Hurricane Harvey’s rainfall reached the 1,000-year rainfall return period based on many time intervals during the course of a number of hours and days.", and it is not cost effective, or technically feasible, to have local infrastructure convey the runoff from events of this magnitude.

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Canada Connection (for those appreciate tree-sauce, skatey-punchy, and noble antler cows):

CatIQ claim datasets have been used to evaluate flood damages across Canada according to the size of the flood event (i.e., related to the number of claims). A similar pattern of increasing damages with increasing event size and distribution is apparent in the CatIQ datasets. In contrast to the FEMA claims noted above for many hurricane events, the CatIQ data reflect basement flooding claims primarily, as overland flooding has not been insured in the past and is not widely held. What is the magnitude of these Canadian claims? Aviva Canada provided this summary of claim trends and magnitude:

"In 2014, water damage claims accounted for 44% of dollars paid out on all Aviva Canada property damage claims, compared with 39% in 2004. The average cost per residential water damage claim has increased significantly – going from $11,709 in 2004 to $16,070 in 2014, a 37% increase."

So basement flooding damages are significantly less than FEMA's large scale catastrophe claims. CatIQ data shows that for larger events (those with higher claim counts) the average claim amount does increase above the Aviva Canada values noted above. Comprehensive benefit-cost analysis used to develop ROI rankings for flood mitigation projects would apply the lower range of typical damages to frequent to moderate events and the higher damages/claim amounts to the frequent events, factored by their probabilities. The most frequent storms, typically 5 to 10 year return period events as in a recent study by Atkins for the US EPA do not generate damages.

Risks Are Where You Map Them - The Truth in WYSIATI (What You See Is All There Is) When Defining Urban Riverine Flood Plain Risks

"To Map or Not To Map, That Is The Question"

If buildings along a channel are subject to frequent flooding but there is no regulatory mapping, is it really a 'flood risk zone'?

Risks are sometimes equated to the presence of regulatory mapping that defines risk. But risks exist whether you map and manage them or not. This post explores the "Where?" and the "How?" of floodplain mapping to best define risks.

First some background - regulatory mapping, such as under Ontario's Conservation Authorities Act regulations, delineates risk areas where it has been decided to map risks. It is a choice - to map or not to map. Regulation and risk are therefore quite different, as risk can extend upstream of the last flood plain mapping sheet, extending further up the river system, or even up through the urban landscape and infrastructure systems. Obviously, our goal in terms of risk management and urban flood damage mitigation would be to map all the important risks - those contributing to frequent or extensive damages - and to then develop a strategy to address those risks.

While Ontario is quite advanced in terms of the identification and management of river flood risks, there are opportunities for improvement where risks on smaller urban watercourses are defined. Traditionally, a catchment size limit of half a square mile, or about 125 hectares, was used to define rivers reaches where hydrologic and hydraulic modelling would be completed to delineate the extent of the regulatory flood plain. Reaches for smaller reaches were not typically mapped. In new development areas, a smaller threshold is often applied during land use planning and development servicing studies which ensures that local risk are managed. However in historical development areas, it is not uncommon that some river reaches with catchment sizes of several hundred hectares are not mapped, meaning that risks in small flashy systems (those that respond to high intensity rainfall convective summer storms) are not identified, regulated, or mitigated.

Given today's focus on Best Practices to mitigate existing community flood risks, the mapping of riverine flood risks is a subject of attention. The federal government, Natural Resources Canada and Public Safety Canada, have recently published a Federal Floodplain Mapping Framework Version 1.0, 2017 that forms part of the Federal Floodplain Mapping Guidelines Series - a link to that document is here :

http://publications.gc.ca/collections/collection_2017/rncan-nrcan/M113-1-112-eng.pdf

The following figure summarizes the framework steps.

The report notes priority setting including "where to conduct floodplain mapping"  as a future activity:

We encourage that Priority Setting be robust to answer the "where" and "how far" mapping will be pursued. Why? There is a considerable amount of focus on next steps, getting lost in the weeds with LiDAR data acquisition and climate change assessments in the next delineation step in the framework. So the question is "Is there enough prioritization relative to other technical considerations?", as suggested in the follow graphic:

How about an example showing why "Where to Map?" is more important than "How to Map?".

The Don Mills Channel is a small urban drainage channel, with a historically realigned watercourse called Cummer Creek in the Don River Watershed. Floodplan mapping has been pursued since the 1960's in Ontario and a great summary of floodplain mapping history is available here: The State of Floodplain Mapping in Ontario Presented to the Institute for Catastrophic Loss Reduction, June 15, 2007, Don Pearson, General Manager, Conservation Ontario.

The City of Markham is conducting a flood reduction Class Environmental Assessment study to understand the causes of flooding in the Don Mills Channel study area and to develop a range of alternative solutions to reduce flooding and flood damages. The Class EA flood risk analysis modelling (not the regulatory mapping) shows the extent of flooding during a 100-year event:

While the watercourse is an area of focus for flood control, regulatory floodplain mapping was completed for the channel only in 2011. Prior to that, estimation mapping was completed (by this post's author) to support generic regulation updates in 2006.

So how has the characterization of risks changed with this 'new' mapping of the Don Mills Channel?The following figures illustrate how building flood risks in the newly mapped Don Mills Channel compare with city-wide Markham building flood risks identified as part of its Flood Emergency Response Plan.

Extending floodplain mapping a one tributary can dramatically change the characterization of overall riverine flood risk for the 100-year flood event. 

Riverine flood risks defined by depth of flooding at building structures changes significantly with the extension of floodplan mapping to previously unmapped watercourse reaches.

Frequent flooding during low return period events increases significantly with the extension of floodplan mapping to the Don Mills Channel, a tributary of the Don River also called Cummer Creek.

The charts above clearly show that the accounting of at-risk buildings within the extension of regulatory floodplain mapping in a single tributary dramatically changes the characterization of city-wide risks.  For example, the number of high flood depth structures (depth greater than 0.6 metres) during a 100 year event in the new reach is more than double the entire previous city-wide number. For frequent flood events like the 10 year storm in the last chart, the number of high-depth structures increases by 10 times or more - these new, frequent, high-depth structures can be expected to represent a high proportion of average annual flood damages.

While development occurred in the Don Mills Channel area in the 1960's (channelization and realignment was in fact to support development at the time according to the original 1966 design report), floodplain mapping was not initiated until 40 years later with the generic regulation update estimation mapping (i.e., HEC GeoRAS considering only overland components and not culvert enclosures - see this post for our perspective on riverine flood vulnerability methods). Advanced mapping to support regulation was completed later in 2011.

So what was the critical question to defining risk? Was it "How?" the floodplain should be mapped, like using various hydraulic models:

1) basic 1-dimensional HEC-RAS with no culverts (the 2006 HEC-GeoRAS estimation) or
2) more advanced 1-dimensional HEC-RAS with culverts (2011 mapping) or
3) even more advanced 2-dimensional PCSWMM integrated with the municipal storm pipe network (2018 Class EA)?

.. or using various design storms to determine design flows like:

1) TRCA's low-intensity watershed storm, or
2) Markham's high-intensity urban storm

... or considering various climate conditions like:

1) today's climate and IDF curves (which are not reflected in the watershed storms at all) or today's regulatory storm (Hurricane Hazel) or
2) tomorrow's estimated climate and IDF curves (take your pick on methods ... none of which converge) or tomorrow's regulatory storm (Hurricane Hazel ... exactly the same as today's Hurricane Hazel)

.. or refining the digital elevation model using LiDAR to get those flood depths to millimetre accuracy around every metre of he perimeter of each building, instead of typical mapping?

A recent presentation describes the modelling uncertainties in "How" various analysis methods have been applied from the 1960's to today:

MNRF CWRA Technical Workshop March 6 2018 Rob Grech and Robert Muir City of Markham from Robert Muir

Or is the most important question in defining risk the "Where?" Yes, "Where?" is the important part and the other considerations of "How?" are secondary or tertiary at best.

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Nobel laureate Daniel Kahneman, author of Thinking Fast and Slow, referred to WYSIATI, an acronym for "What You See Is All There Is", which is a way of saying that we often miss things by acknowledging only the things we know (the known knowns) while being oblivious to the unknown unknowns. We recognize only what we see - or what we map and acknowledge. In the case of flood plain mapping, the risks we map are often considered to be all there is, since that is all that is being regulated or managed. Obviously then, "Where?" and "If" we map riverine flood risks can be of critical importance. And although our technical methods for delineating flood risks must be carefully considered, "How?" we define risks is relatively less important.