SanFranciscoBay_Adapt2SeaLevelRise_CostData
Creators: name: Hirschfeld, Daniella
name: Hill, Kristina
name: Plane, Ellen
Publisher: name: Dryad
publisherIdentifier: https://ror.org/00x6h5n95
publisherIdentifierScheme: ROR
Year: 2017
Subjects: coastal flooding
coastal management
Coastal planning
Regional strategies
Storm Surge

description: 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.
description: 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.
description: 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.