Flooding & Landsliding —How do we define and cope with Risk?

1. Flooding & Landsliding—How do we define and cope with Risk? By Bob Gerber, P.E. & Certified Geologist Ransom Consulting, Inc. Robert.Gerber@RansomEnv.com 207-838-1418

2. Real v. Perceived Risk • Variables that may appear to create differences between perceived risk and real risk: • Number of lives, dollars or environmental damage at stake • Amount of control one has over the risk factors • Whether the risks are static or change with time • Ability to avoid risk or insure against it • How rare the event may be • Whether the individual factors contributing to the risk are independent of each other or are linked or coupled • Whether one is considering the chance of a single occurrence in a year or the chance of at least one occurrence over 100 years • Extent of knowledge or ability to estimate the risk • Most risks can be quantified (e.g., as annual probabilities of occurrence) and compared with other risks, but most people are still uncomfortable with risks defined as probabilities. Expert witnesses are often asked to opine whether an event is more likely than not to occur under a certain set of circumstances (i.e., is the probability of occurrence >50%?)

3. Deterministic v. Probabilistic Modeling • Predictive groundwater modeling and slope stability modeling for many regulatory programs is primarily done from a deterministic point of view. No error bars or confidence intervals are defined. A slope is usually considered “safe” if the Factor of Safety (FS) against failure is >1.5. The physical properties of the slope are treated as if they are fully known with certainty everywhere in the slope. • RCRA closure, from the human health risk assessment perspective, is almost all done using statistics and probabilistic approaches where cancer risks are being evaluated. • Groundwater quality regulatory compliance at a landfill is determined by comparing upgradient vs. downgradient groundwater quality using statistical and probabilistic approaches. • The probability of an earthquake with a magnitude of a certain recurrence interval is usually done using a complex probabilistic approach although some geologic interpretation is embedded in the method.

4. Evaluating risks with large consequences associated with complex technologies • Interesting reference: Charles Perrow, Normal Accidents, Living with High-risk Technologies (1984, reprinted 1999 with some new material) • The complexity issue & coupling • Accident probability goes up with complexity of the system • Linear systems have lower likelihood of major accidents than systems that have tight coupling leading to unforeseen interactions between separate systems • Normal Accident Theory (NAT) implies that accidents are normal or inevitable in highly coupled, complex systems • The size of the potential harm, the number of people potentially affected, and the nature and length of the harm affects the degree of risk that is tolerated by society

5. Perrow (1999), Afterword, p. 385 Perrow unwittingly predicts our 2008 financial meltdown when he looks at financial practices through the lens of accident theory

6. Flood Risk • Coastal Flooding • Flooding caused by storm surge and/or large waves generated and driven primarily by high wind velocities. Because of the spatial variability of where an extreme ocean storm might hit, it is difficult to estimate recurrence intervals at any specific point, particularly with changing storm frequencies and intensities. • Riverine Flooding • Flooding caused by large precipitation and/or snowmelt events that may be exacerbated by debris or ice jams. The statistical approach to estimating flood elevations of specific recurrence intervals is well established using gaging stations with long (>20 years) continuous records. This assumes the risk is relatively constant through time.

7. Components of Risk in Ocean Flooding • Wind (Frequency of extreme winds seem to be increasing in recent times) • The component of water level related to storm surge, which is related to wind, and the component related to tide elevation (i.e., neap or spring tide and height of tide at the height of storm) • Wave Heights—either propagated from large offshore waves or locally wind-generated waves • Wave Setup (momentum transfer, raises water levels 1’ to 5’ at the immediate shoreline) • Wave Runup (deep water and steep slopes at shore create the largest wave runup) • Sea Level Rise (backward looking only and rate of rise has been slow compared with effects of recent increase in storm intensity and frequency) • Loss of land due to wave erosion (assumed with sand dunes, soft soil slopes, and man-made structures as part of runup analysis)

8. The state-of-the-art method of estimating ocean surge from extreme events • Use very advanced coupled ocean surge and wave models that simulate the tracks of all historical storms (~100 years of storm data); only done to date with hurricanes; need to add northeasters • Develop statistics on water elevation at the shore for each point of interest on the shore based on the model simulations of each storm • Can derive the annual probability of occurrence of any given water elevation at each point from the statistics • May need to make adjustments for recent increase in severity and frequency of ocean storms • This method differs from that currently used by FEMA in southern Maine where such variables as peak tide stage and peak storm surge are assumed to occur simultaneously. The joint probability of occurrence of two independent probabilities of 1% each is much less than 1% (actually the product of 1% x 1% where events are not linked in any way).

9. Variable Components of Risk in River Flooding • Precipitation (both precipitation and runoff have been documented to be increasing since 1970) • Land Use changes (e.g., adding impervious area) increases runoff • Joint probability of a melting snowpack in combination with heavy rain • Unpredictable obstructions in the channel (e.g., chance of ice jams or debris jams)

10. Yarmouth Historical Society Risk Evaluation • A building was offered for free for a new historical society repository on edge of Royal River 100-yr floodplain • How do you help the client decide whether the risk is acceptable? Besides the hydraulic modeling involved, it required trying to describe the difference between single event and cumulative probability theory • When I was with Sebago Technics we did the best we could to account for apparent increases in flood flow with time as a function of recurrence interval flooding events

13. Comparison of 100-year rainfall in 24 hours based on data up to 1961, vs current estimate of that value from the Northeast Regional Climate Center at Cornell; 25% increase 1961 TP 40

14. 100-yr flood 64% 500-yr flood

16. April 1996 Rockland Harbor Landslide

17. Landslide risk is usually stated in terms of factor of safety against sliding • Factor of Safety = Ratio of forces resisting failure to forces causing failure • Variables include: • Topography (shore slopes can be over-steepened by wave erosion) • Geology (depth to hard substrate, type of soil and nature of layering) • Groundwater pore pressure distribution • Soil strength spatial variability • Can calculate annual probability of failure if you can gather enough soil strength data so that geostatistics can be applied but this usually would cost too much for a typical landowner • One approach is to monitor slope movement and manage the risk in real time by adjusting a variable. This was done in the Ft. Halifax dam removal on the Sebasticook River in Winslow where reservoir level was the variable that was adjusted because it translated to groundwater pore pressure distribution

18. Horizontal Slope Movements below Dallaire Street Monitored in real time

19. July 2008, just downstream of Dallaire St. houses

20. Summary • To understand risk objectively, try to put it in probabilistic terms that can be compared against other risks you are more familiar with that can be characterized probabilistically • You can make choices that can reduce risk (move away from risk, build protective structures, buy insurance, reduce complexities, etc.) • Short-term risks of high consequences can often be managed in real time through monitoring and adjustment of variables • Learn the difference between annual occurrence probability and cumulative probability over multiple years • In man-made systems, highly coupled systems are more likely to fail than unlinked linear systems