Risk Assessment: Sea Level Rise case study in Foster City, CA

In this study, we perform a flooding hazard risk assessment in Foster City, CA in response to potential sea level rise in the future. Foster City is a city located in San Mateo County, California. The 2020 census put the population at 33,805, an increase of more than 10% over the 2010 census figure of 30,567 (wiki). Foster City was founded in the 1960s, built on the existing Brewer Island in the marshes of the San Francisco Bay on the east edge of San Mateo, enlarged with engineered landfill. Foster City is particularly prone to future sea level events given its geographic location. Luckily, the city is somewhat prepared for its future. A massive steel sea wall along the Beach Park Boulevard in FC is being constructed to protect its residents and industry (Foster City Levee Project). In the following analysis, we focus on how much risk and monetary losses there would be for FC without the ongoing levee construction, who would be impacted majorly, and how much potential losses are being avoided by the levee construction.

1 Hazard

The area of interest, Foster City, is shown here in Figure 1. The green line outlines the city boundary whereas the blue lines indicate census block groups. As shown on the map, the city lies on the inner coastal line of the San Francisco bay, showing high potential of SLR risk.

Figure 1. Map of census block groups in Foster City

The proposed levee project is constructed along the coastal line on Beach Park Boulevard, shown in Figure 2. The height of the levee varies on different part of the construction. From Baywinds Park to the Beach Park Boulevard/Foster City Boulevard intersection, the final height of the wall, including wall cap, will be 3.5 feet (1.07m) above the walking surface. For most of the remaining levee structure, the final height of the wall will be 2.5-to-3.5 feet (0.61 - 1.07m) or less above the walking surface (Foster City Levee). For the simplicity of this analysis, we just assume the wall is 1m on average.

Given the granular hazard data from Our Coastal Our Future (OCOF), in form of flooded maps, nine hazard scenarios are considered in this study, with sea level rise level (SLR) of 0m, 25m, 50m, and flood return periods (RP) of 1 year, 20 years, and 100 years. The “return period” of 20 years, for example, means there would be a 20% change of a hazard event of the given intensity or greater happens, or in other words, 1 in 20 years. The map data from OCOF tells us in granular details what locations are flooded in what depth given the hazard scenario. We will use the flooded depth to estimate the associated monetary damages.

2 Exposure related data processing

With the hazard data from OCOF, we want to associate specific locations with buildings, vehicles, and population data to further quantify flood hazard exposure, in terms of percent damage per building, damaged vehicles per building, and $ losses per household or per building.

Block-level population data in Foster City is accessible from census decennial data in year 2020. Census block group-level vehicle ownership data, in terms of number of owned vehicle per household, is accessible from census ACS5. Building geographic data can be accessed from OpenStreetMap, and from here constructed our exposure analysis, explained below in further details.

2.1 Vehicle count projection in 2020-2050

Since our proposed flood event happens in 20 or 100 years in the future, where the vehicle counts and population would progress accordingly. Luckily, the EMFAC database by California Air Resources Board provided previous and projected future vehicle miles traveled (VMTs) in regions in California, in 2020-2050. We use the ratios of the projected VMTs in future years to VMTs in 2020 to estimate the ratio of future vehicle counts to vehicle counts in 2020, in Foster City.

This, however, contains high uncertainty. For example, such projection assumes the vehicle ownership percentage as constant in the next 30 years, where people may own more cars with economic growth, or less if more public transportation infrastructure is set in place. Readers should keep this uncertainty in mind while evaluating the risk assessment results.

The full projected rate is shown in Table 1. The total vehicle counts in Foster City in 2030 would be 92% of current numbers in 2020, estimated by the ratios of corresponding VMTs from EMFAC.

Table 1. Vehicle count projection rates in Foster City in 2020-2050, base case = 2020 (source: EMFAC)
Calendar Year	Total VMT	Projected Rate
2020	2972498142	1.0000000
2030	2738606168	0.9213147
2040	2581957081	0.8686152
2050	2549848467	0.8578133

2.2 Vehicle ownership from ACS5

The vehicle ownership status (vehicle counts owned per household) is retrieved from census ACS5, therefore in census block group granularity. The block information in shown in Figure 3.

Figure 3. Block maps of Foster City

2.3 Building Footprint

The building data in Foster City is retrieved from OSM. The dataset contains building unique code (osm_id) and building types (“residential”, “commercial”, and etc.). There are 6,839 building entries in Foster City. Specs of building types in FC are shown in Table 2.

For vehicle damages, we only consider residential buildings in the areas since they are associated with households in ACS5. There are 4,329 buildings in Foster City who have no building type specification. Here we assume they are all residential. Therefore, “apartments”, “detached”, “house”, “residential”, and NAs are considered as residential housing in the OSM data, 6,621 buildings in total. The building dataset is later joined with block-level population data. Entries with 0 population (therefore non-residential) are excluded from further calculation. 35 buildings are excluded. The specs of analyzed buildings are listed in Table 3.

Table 2. Building types and counts in Foster City (source: OSM)
Building Type	Count
apartments	114
carport	56
church	2
cistern	4
commercial	12
detached	1
garage	36
hotel	2
house	1939
office	11
parking	9
residential	238
retail	9
roof	4
school	17
shed	34
terrace	22

Table 3. Types and counts of buildings of interest in the following analysis (source: OSM)
Building Type	Count
apartments	114
assumed residential	4329
detached	1
house	1939
residential	238

3 Exposure

3.1 Building exposure intensity

Among our nine proposed flood scenarios, the most severe situation is a 100yr return period flood with a 50m sea level rise. In Figure 4, the impacted buildings under such scenarios are shown in red outlines, where the blue color indicates the amount of flooding. Please keep in mind areas without red outlines are dense with non-residential buildings, also heavily impacted by the flooding, only outside of the scope of current analysis.

Figure 4. Map showing influenced residential buildings under a 100yr return flood scenario with 50m of sea level rise

The flood depth is shown in Figure 5.

Figure 5. Map showing flood depth in a 100yr-return flood with 50m SLR

3.2 Exposure in monetary values

As shown in Figure 4, we know how many buildings are impacted, or exposed, to each of our proposed flooding hazard. The percentage of damage to each building as well as its residing vehicles is different according to its flooding depth. This damage percentage can be estimated by the structural damage percentage and content damage percentage in Economic Guidance Memoranda proposed by the U.S. Army Corps of Engineers. We used the structural and content depth-damage parameters for “one story, no basement” from ERDC.

In our comparison scenarios for the levee project, we calculate two sets of damage values based on the availability of the levee. The height of the levee tis set to 1m throughout the analysis.

3.3 Building damage

Comparing the depth-damage curve for residential buildings in Foster City in Figure 6 and 7, we can clearly see the percent damages drop significantly in response to the levee construction.

Figure 6. Building Depth-Damage Curve in Foster City, without levee protection.

Figure 7. Building Depth-Damage Curve in Foster City, with levee protection.

3.4 Vehicle Damages

The vehicle damages show similar results with buildings, in Figure 8 and 9.

Figure 8. Vehicle Depth-Damage Curve in Foster City, without levee protection.

Figure 9. Vehicle Depth-Damage Curve in Foster City, with levee protection.

4 Averaged Annual Loss

Finally, in estimates of monetary losses, we calculate Average Annualized Losses for vehicles. We choose Representative Concentration Pathway 4.5(RCP) as the climate model from which we will gather the distribution of probabilities for sea level rise in the time period of 2020 to 2050. RCP is a greenhouse gas concentration trajectory adopted by the Intergovernmental Panel on Climate Change (IPCC). We’ll use the RCP4.5 data as the likelihood for our sea level rise scenarios in 2020 to 2050, in order to annualize our projected damages in 2020 and 2050 to each year in between. This would serve as the exceedance rates, where an event greater or equal to the described scenario would happen.

Given the above calculation, the averaged annualized losses associated with vehicle damages in Foster City are shown in Figure 5. While almost all of the residential buildings in Foster City are impacted by the flooding risk, two communities are severely impacted as in dollar amount due to such risks, shown in dark red under 2050 damge without the levee construction in Figure 5. This is due to its high vehicle and population density within a single building as well as its proximity to water body. With the levee construction, the damage is most significantly lessened in these communities. However it still appears as significant losses.

Figure 10. Average Annualized Losses associated with vehicle damages in Foster City in 2020 to 2050, with or without the levee construction

Figure 11. AAL associated with vehicle damages in Foster City in Census Block Group leve

In total, the construction of the levee project would save $21.3 million in vehicle damages in Foster City per year in response to flooding under sea level rise, or an AAL of $4,782 per vehicle.