In metropolitan regions made up of multiple independent jurisdictions, adaptation to increased coastal flooding due to sea level rise requires coordinated strategic planning of physical and organizational approaches. To better understand specific choices for sea level rise adaptation we examined potential costs to raise current protective infrastructure to future water levels.

Our analysis is based on four primary steps.

First we reclassified the shoreline infrastructure data from San Francisco Estuary Institute (SFEI). We used the following dictionary to reclassify the data in terms of the Landform / Wall value: {'Berm': 'Landform', 'Channel or Opening': 'Landform', 'Shoreline Protection Structure': 'Landform', 'Embankment': 'Landform', 'Engineered Levee': 'Landform', 'Floodwall': 'Wall', 'Natural Shoreline': 'Landform', 'Transportation Structure': 'Wall', 'Water Control Structure': 'Wall', 'Wetland': 'Landform'}. We used the following dictionary to reclassify the data in terms of the Dynamic / Static value {'Berm': 'Static', 'Channel or Opening': 'Static', 'Shoreline Protection Structure': 'Static’, ‘Embankment': 'Static', 'Engineered Levee': 'Static', 'Floodwall': 'Static', 'Natural Shoreline': 'Dynamic’, ‘Transportation Structure': 'Static', 'Water Control Structure': 'Dynamic', 'Wetland': 'Dynamic'}. Additionally, for some of the shoreline protection structure sites we used Google Earth and site visits to shift their categorization from landform to wall.

Second we conducted a rapid assessment of water exceedance levels by calculating the difference in height between the projected floodwater and the structure. We subtracted the height of every shoreline segment in the SFEI data from the USGS CoSMoS model’s projected future water levels.

Third we generated three potential shorelines for cost comparison. The most bayward line, referred to here as “Shoreline A”, was mapped just using SFEI’s shoreline infrastructure data. We used the “Bayshore_Defense” category, with the values “First line of shoreline defense” or “Wetland on Bay shore” to designate “Shoreline A.” We designated the other two shorelines using an intersection of SFEI’s shoreline infrastructure data and the BAARI data to distinguish the saltwater and freshwater habitat zones. The shoreline referred to as “Shoreline B” uses SFEI’s mapping of saltwater habitat. The shoreline referred to as “Shoreline C” is the most landward of the three we designated, and is based on SFEI’s mapping of freshwater habitat.

Finally, we calculated potential costs based on our review of costs specific to projects in the San Francisco Bay Area, and supplemented these data with cost calculations from the literature where needed. For walls we used $218.0 (2016 USD$) as the middle value for each linear kilometer, and for each meter of raised infrastructure height. For walls we used a high and low value based on + or – $75.0 from our middle value. For landforms we used $8.0 (2016 USD$) as the middle value for each linear kilometer, and for each meter of raised infrastructure height. For landforms we used a high and low value based on + or – $4.0 from our middle value.

We compared 4 different approaches to calculating an approximate cost of raising existing coastal structures: 1) simple without parcel costs, 2) simple with parcel costs, 3) complex without parcel costs, and 4) complex with parcel costs. The “simple” approaches (#1 and #2) used a linear relationship when calculating the cost of raising the height of a levee or a wall. In our “complex” cost estimation approaches (#3 and #4), we applied a levee-growth cost factor that incorporates greater nuances to cost estimation. We also recognized that land costs will be a major factor in the cost of higher levees. Therefore at the county scale we added an additional parcel cost. This parcel calculation was applied to both the simple and complex levee approaches resulting in approaches #2 and #4. The data for this parcel cost is in our county data. Our file called “ModelCode_4Approaches-NoStorm” provides the code for these four different approaches.

The first 22 columns ending with “Comments_” are based on the original SFEI data. We added the data in the rest of the columns. In columns 25 to 28 we present the reclassified data. In columns 29 – 51 we present the exceedance numbers in meters. The first three numbers indicate the sea level rise amount in centimeters. The second three numbers indicate the storm conditions as developed by USGS in the CoSMoS model (000 is mean, 001 is annual, 020 is 20 year storm and 100 is 100 year storm). In columns 52 – 54 we provide the unit cost. In columns 55 – 65 we provide the amount a shoreline segment would be raised under specific scenarios. We use “ns” to refer to a no storm even and “ys” to refer to a 100-year storm event. We use the numbers on the end to refer to the amount of sea level rise in centimeters. In columns 67 – 132 we present each segment’s cost. We use “A1” and “A3” to refer to approach 1 or approach 3 for cost calculations. We again use “ns” to refer to a no storm even and “ys” to refer to a 100-year storm event. We use “l” to refer to low-end costs, “m” to refer to middle costs, and “h” to refer to high-end costs. We use 0 – 5 to refer to sea level rise scenarios as follows: 0 – no sea level rise, 1 – 50 cm of sea level rise, 2 – 100 cm of sea level rise, 3 – 150 cm of sea level rise, 4 – 200 cm of sea level rise, and 5 – 500 cm of sea level rise. Finally, there are a number of null values many of our added columns. These reflect the fact that certain shorelines are not exceeded by future water levels and therefore do not have an associated raise factor or cost.