Agenda packet — Newark City Council, July 24, 2025 (part 13 of 13)

The compound flooding hazard model for Newark and the adjacent areas of the Mowry OLU utilizes a scenariobased approach to assess both present and future flood risks. This model is driven by water level boundary conditions in the San Francisco Bay, which incorporate tides and storm surges. These conditions are derived from high-resolution, regionally accurate modeling efforts conducted by the USGS, Deltares, and ACFCD (Figure 12). These regional models form part of the Delft3D San Francisco Bay Community Model (Nederhoff et al., 2021), which provides 70 years of continuous data (1950–2019).

City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 18 For this study, several five-day periods representing MHHW as well as 10-year and 100-year coastal events were selected (Table 4 and Figure 13). By using the recorded data from these periods, it is ensured that the model simulates realistic conditions that have occurred in the past (Table 4). This approach enhances the reliability of the predictions by grounding them in observed events. ACFCD also utilizes this approach.

Table 4 Five-day coastal periods for model simulations
Event Peak Value (ft) in NAVD88 Historical Date of Peak Value 100-year 10.2 January 27, 1983
10-year 9.5 February 06, 1998
MHHW 7.0 March 07 2004
Figure 12 Values computed by Delft3D near SFINCS boundary Figure 13 Coastal water levels imposed at compound flood model City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 19

2.4.3 Subsidence
There has been a history of groundwater pumping related subsidence in the Bay Area. For example, subsidence due to over pumping of groundwater is well documented in the Santa Clara Valley (located south of Newark and Alameda County) due to widespread agricultural land use. Measures to manage the groundwater resource in the Valley began in the 1930s. However agricultural expansion continued to result in land subsidence. By the late 1990’s, subsidence in the Valley had been resolved (USGS, 2018). Figure 14 shows ground level reductions and subsidence rates for one location in the Central Valley for context.

Figure 14 Ground subsidence at USGS Index Well 7R99 (located in Santa Clara Valley) between 1900 and 2010 Future groundwater levels will be influenced by both SLR and varying rainfall behavior. During periods of higher rainfall, groundwater levels are expected to rise along with SLR. Drought typically reduces groundwater levels. However, with the contribution of SLR, drought periods will have less of an impact on groundwater levels. For these reasons, and in light of the impact of SLR, land subsidence should be expected to be less than any historical subsidence (assuming that future groundwater pumping remains at sustainable rates).

When considering the 2050 SLR scenario of 0.8ft, and 2100 SLR scenarios of 3.1ft to 6.6ft, the groundwater levels are expected likely to rise with the rising sea levels (refer to Section 2.4.2). Therefore, long-term landsurface-elevation changes from groundwater pumping-induced subsidence is not anticipated to occur within the study area. If later research indicates subsidence has a larger impact, subsidence rates could be accounted for in the model by adjusting topography heights with the expected values.

2.4.4 Drainage Infrastructure
The culvert physical parameters, such as location and size, were provided by ACFCD, are included in the model, and are depicted in Figure 15. The model does not include other urban drainage systems (i.e., storm drain network) because the most conservative scenario assumes that the drainage infrastructure is at capacity and not accepting additional runoff. Nonetheless, the potential reduction in flooding from green infrastructure can still be assessed. There are no pump stations within the study area.

City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 20 Figure 15 Culverts and levees included in the model

2.4.5 Flood Management Structures
There are levees around the existing salt ponds on the Newark shoreline (Figure 15). The levees were modeled as weirs, to simulate the effects of constrained flow. No information is available on levee condition. It is assumed that the levees are stable and do not fail. This allows the analysis to represent the expected conditions and focuses on the behavior of water flow as opposed to structural integrity.

The model also includes levees/berms along the Alameda Creek Flood Control Channel to model the effect of this infrastructure. The median levee elevation is approximately 12.3ft in the model extents.

2.5 Sensitivity Analysis
A sensitivity analysis of peak rainfall timing was conducted to confirm the worst-case flooding scenario relative to tidal and rainfall peak alignment. Three simulations were tested to evaluate scenarios where peak rainfall occurred at the same time, 30 minutes prior, and 1 hour prior to the peak tidal water level during a 24hour storm (Figure 16). The maximum inundation extents were observed when the peak rainfall and peak tidal water level were aligned; therefore, this alignment was applied for all other model scenarios to represent the conservative, worst-case flood conditions.

City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 21 Figure 16 Sensitivity analysis of peak rainfall and tidal water level

2.6 Assumptions and Limitations
This analysis assumes that:
• Publicly available data and data provided by the City and ACFCD is correct. • The FEMA hazard maps effective in 2009 are correct for the present-day 100-year rainfall event. • The existing levees are stable and do not fail.
• Drainage infrastructure is at full capacity during storm conditions.

Limitations include:
• The model accuracy is dependent on the quality and resolution of the input data, such as topography, bathymetry and rainfall.
• There is inherent uncertainty in model predictions. The model assumptions and inputs may not fully capture real-world complexities and variability in natural systems, which can affect the accuracy of the results. For instance, water levels in San Francisco Bay were reproduced with an error of several inches (see to Section

3.2) and therefore do not perfectly align with historical observations. • There are no stream gauges within the study area, therefore no stream gauge data was available to calibrate the riverine flow rates.

City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 22

3. Model Results
The scenarios from Section 2.2 were modeled to represent the flood extents and depths for the selected present day, 2050, and 2100 conditions.

3.1 Outputs and Analysis
The ten scenarios from Section 2.2 for present day, mid-century, and end-of-century were modeled, and flood depths at several locations are compared in Figure 17 and Table 5. Results are included in this section with additional higher resolution maps included in Appendix C.

Figure 17 Model result locations associated with flood depths in Table 5 Table 5 Model result flood depths at locations depicted in Figure 17 Time Storm/ Quasi-permanent
Inundation
SLR
(ft)
Location ID
1 2 3 4 5 6 7 8
Water Depth (ft)
Present
Coastal Storm 0 6.3 1.9 1.9 6.8 0.0 0.7 0.0 0.5
Inland Storm 0 6.5 3.2 1.4 7.5 0.6 0.9 0.0 0.7
2050
Future Storm (Coastal) 0.8 6.3 2.2 2.7 6.9 0.1 0.7 0.0 0.6 Quasi-permanent Inundation 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2100
Future Storm (Coastal)

3.1 6.4 4.9 6.5 8.5 1.8 0.7 0.0 4.4

4.9 6.4 8.2 9.0 10.8 4.9 0.7 0.0 7.3

6.6 7.1 10.0 10.8 12.6 6.7 0.9 0.0 9.1
Quasi-permanent Inundation

3.1 0.0 0.0 2.5 0.0 0.0 0.0 0.0 0.0

4.9 0.0 0.0 4.3 6.6 0.0 0.0 0.0 2.9

6.6 0.0 6.3 7.4 9.2 3.1 0.0 0.0 5.4
City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 23 The model is dynamic and simulates a period of five days; an example of the results at different time steps is depicted in Figure 18.

Figure 18 End-of-century Storm Scenario (coastal) flood hazard results with 3.1ft of SLR (where t is the time) City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 24

3.1.1 Present Day
The Coastal Storm Scenario (100-year coastal + 10-year inland) and Inland Storm Scenario (100-year inland + 10-year coastal) maximum flood depth results are depicted in Figure 19 and Figure 20.

Figure 19 Present day Coastal Storm Scenario flood hazard results Figure 20 Present day Inland Storm Scenario flood hazard results City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 25 The Inland Storm Scenario has wider flood inundation extents, as depicted in Figure 21 which compares the Coastal and Inland Storm Scenario maximum flood depths. The green areas indicate a higher inland flood depth and blue areas indicates higher coastal flood depth. Under present day conditions, the flooding from the Inland Storm has a greater impact in residential and commercial areas, particularly within the City of Newark boundary.

The berms around the salt farms provide a level of protection against coastal flooding and the berms are not overtopped in either of the present-day scenarios.

Figure 21 Comparison of the maximum flood depths between the Coastal and Inland Storm Scenarios City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 26

3.1.2 Mid-Century (2050)
The mid-century scenarios include 0.8ft of SLR with the quasi-permanent inundation and Storm Scenario. The respective maximum flood depth results are depicted in Figure 22 and Figure 23. The quasi-permanent inundation map depicts typical day-to-day conditions.

Figure 22 Mid-century quasi-permanent inundation scenario flood hazard results Figure 23 Mid-century Storm Scenario flood hazard results City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 27 The quasi-permanent inundation results depict limited areas of impact, with localized parts flooding in the northwest and southeast of the City. Initial mitigation efforts could be focused on these locations. When considering the Storm Scenario in addition to the Quasi-permanent conditions, the flooding becomes more widespread, particularly in the salt farms.

3.1.3 End-of-Century (2100)
The end-of-century scenarios include 3.1ft, 4.9ft, and 6.6ft of SLR with the quasi-permanent inundation and Storm Scenarios. The quasi-permanent inundation results under the three SLR scenarios, respectively, are depicted in Figure 24 through Figure 28. The quasi-permanent inundation map depicts typical day-to-day conditions. The Storm Scenario maximum flood depth results under the three SLR scenarios, respectively, are depicted in Figure 25 through Figure 29.

Figure 24 End-of-century Quasi-permanent Inundation
Scenario under 3.1ft of SLR flood hazard results
Figure 25 End-of-century Storm Scenario under 3.1ft of
SLR flood hazard results
Figure 26 End-of-century Quasi-permanent Inundation
Scenario under 4.9ft of SLR flood hazard results
Figure 27 End-of-century Storm Scenario under 4.9ft of
SLR flood hazard results
City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 28 Figure 28 End-of-century Quasi-permanent Inundation
Scenario under 6.6ft of SLR flood hazard results
Figure 29 End-of-century Storm Scenario under 6.6ft of
SLR flood hazard results
The quasi-permanent inundation results considering 3.1ft of SLR depict limited areas of impact similar to the mid-century results, with localized areas in the northwest and southeast of the city becoming inundated. Quasipermanent inundation from 4.9ft of SLR impacts the southern section of the salt farms and a greater extent of the area in the northwest of the city. The tipping point where day-to-day impacts from quasi-permanent inundation become significant occur when SLR increases from 4.9ft to 6.6ft of SLR, visualized in Figure 30, which depicts the MHHW level relative to the median weir elevation.

Figure 30 Visualization of MHHW elevation and weir elevation under SLR scenarios with tipping point depicted The areas impacted by quasi-permanent inundation with 4.9ft of SLR are similar to those impacted by 3.1ft of SLR, but the maximum flood depths are greater. In the 6.6ft of SLR scenario, a significantly larger portion of developed areas are impacted, and widespread mitigation would be required. Figure 31 depicts the change in inundation from 4.9ft to 6.6ft SLR, where the darker the color indicates how much more flooding there is in

6.6ft SLR than 4.9ft SLR scenarios (MHHW).

City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 29 When considering the Storm Scenario in addition to the quasi-permanent conditions, the tipping point for widespread flooding occurs with 3.1ft of SLR, which could occur in a nearer timeframe than the quasipermanent inundation tipping point. In particular, the salt farms and in the developed areas in the northwest of the city experience the most flooding. Inland flooding also occurs in pockets throughout the residential neighborhoods in this scenario.

Figure 31 Difference in flood depths from quasi-permanent inundation due to 4.9ft versus 6.6ft of SLR

3.2 Validation
The Delft3D San Francisco Bay Community Model (Nederhoff et al. (2021)), from which the coastal boundary conditions were derived, is calibrated against tide gauge data. For this regional Newark model, the model results water levels were validated against the Coyote Creek tide gauge water levels in Figure 32. The modeled water levels (“SFINCS model”) align with the observed values (“observed (hourly)”), as seen visually for the time series below during winter 1983.

City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 30 Figure 32 Validation Coyote Creek – RMSE 15cm, MAE 11cm The model results verification compared to FEMA indicates there is some overestimation of flooding mainly on land driven by rainfall. This is likely because of two reasons: 1) urban drainage systems are not included in the SFINCS model because they are assumed to be at full capacity which results in ponding water in the streets, and 2) The FEMA model does not include local storm drain systems and is not a 2D model, therefore flooding will not show in the streets unless it is specifically around creeks or channels which are overtopped. Therefore, it is expected that there will be some misalignment between the results from inland flooding. There is also some underestimation in the salt ponds, which may be driven by overestimation of the weir height, or potential inaccuracies or assumptions in the FEMA results.

Despite these limitations, the results include an 88% hit rate, which means that the SFINCS model flooding aligned with 88% of the FEMA flood area, which gives confidence that the model is capturing the main flood patterns as depicted in the FEMA benchmark.

It is estimated that biases are likely consistent across different return periods, meaning it does not vary significantly with event magnitude. However, the relative patterns of increasing flooding driven by climate change factors, such as sea level rise and heightened precipitation, are still well captured. While the absolute flood extents may carry systematic biases, the relative trends remain reliable for assessing future risks. For projections at specific time horizons, the overestimation may slightly inflate the total flooded area but is unlikely to significantly alter the trends in increased flood hazards under climate change scenarios. These trends are critical for planning purposes, as they provide insight into the relative changes in risk and the areas requiring priority action.

City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 31

4. Conclusions and Next Steps
The findings from this compound flood hazard modeling highlight the significant hazards posed by rising sea levels, increased storm intensity, and groundwater emergence to the City of Newark. The flood hazard model developed for this study provides a comprehensive understanding of current and future flood hazards, demonstrating that both coastal and inland storm scenarios could increasingly impact residential, commercial, and green spaces. Limitations include the quality and resolution of input data (i.e., topography, bathymetry, rainfall), inherent uncertainty in model predictions, and absence of available stream gauge data for calibration.

The model results underscore the urgency of implementing adaptive measures to mitigate associated risks, particularly in vulnerable areas such as in the northwest of the city which is exposed in the present-day coastal storm scenario. The alignment of peak rainfall and tidal events further emphasizes the need for robust flood management strategies to protect the community and infrastructure.

The next phase of work includes evaluation of the impact of the flooding on communities and infrastructure using Delft FIAT. The flood hazard results from this modeling effort will be utilized as the baseline for this assessment. The vulnerability assessment will identify assets that are exposed to flooding in the various future scenarios, considering the flood depth and potential damage. Risk modeling will then be performed in Flood Adapt and will support the implementation of a multi-criteria approach to identify key flood risk areas, considering severity of flood risk, potential impact on vulnerable communities, and criticality of impacted assets.

Financial losses will also be estimated.

Concept-level adaptation solutions will be developed to address key areas in the city which are exposed to significant flood risk. The proposed adaptation solutions will be evaluated through a simple benefit-cost analysis and potential funding sources will be identified. Arup led a community engagement meeting at the project onset, to inform the public and solicit input, and a second meeting will review the results and present proposed conceptual adaptation measures.

City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 32 References
[1] Alameda County Flood Control and Water Conservation District. 2018. 2018 Hydrology & Hydraulics Manual. Accessed October 2024 from https://acfloodcontrol.org/the-work-we-do/the-work-we-dohydrology-manual/ [2] Alameda County Water District. February 2023. Survey Report on Groundwater Conditions. Accessed November 2024 from: https://www.acwd.org/DocumentCenter/View/4831/Groundwater-Survey-Report2023 [3] Alameda County Water District. February 2024. Survey Report on Groundwater Conditions. Accessed November 2024 from: https://acwd.org/DocumentCenter/View/6587/Survey-Report-on-GroundwaterConditions-February-2024 [4] California Energy Commission. 2025. “Cal-Adapt: Explore and analyze climate data from California’s Climate Change Assessments.” Accessed January 2025: https://cal-adapt.org/ [5] City of Newark. March 2024. 2024 Tri-City Local Hazard Mitigation Plan Update. Prepared by Foster Morrison Consulting. Accessed September 2024 from: https://www.newark.org/residents/emergencypreparedness/local-hazard-mitigation-plan-lhmp [6] California Ocean Protection Council. 2024. State of California Sea Level Rise Guidance: 2024 Science & Policy Update. Accessed November 2024 from: https://opc.ca.gov/wpcontent/uploads/2024/05/California-Sea-Level-Rise-Guidance-2024-508.pdf [7] Federal Emergency Management Agency (FEMA). June 2024. National Flood Hazard Layer Viewer.

Accessed November 2024 from https://hazardsfema.maps.arcgis.com/apps/webappviewer/index.html?id=8b0adb51996444d4879338b5529aa9cd&extent =-122.11283061997598,37.489732629187024,-121.9466624070854,37.55780500222925 [8] Leijnse, T., van Ormondt, M., Nederhoff, K., van Dongeren, A. 2021. Modeling compound flooding in coastal systems using a computationally efficient reduced-physics solver: Including fluvial, pluvial, tidal, wind- and wave-driven processes, Coastal Engineering, Volume 163, 103796, ISSN 0378-3839, https://doi.org/10.1016/j.coastaleng.2020.103796
[9] National Weather Service. 1982. Report on the San Francisco Bay Area Storm January 3-5, 1982. Western Region Headquarters. Accessed November 2024 from:
https://www.weather.gov/media/publications/assessments/San%20Francisco%20Bay%20Area%20Storm %20January%201982.pdf
[10] Nederhoff, K., Saleh, R., Tehranirad, B., Herdman, L., Erikson, L. H., Barnard, P. L., & van der Wegen, M. 2021. A New Way to Model the Bay. Accessed September 2024 from www.d3d-baydelta.org [11] Nederhoff, K., Leijnse, T. W. B., Parker, K., Thomas, J., O’Neill, A., van Ormondt, M., McCall, R., Erikson, L., Barnard, P. L., Foxgrover, A., Klessens, W., Nadal-Caraballo, N. C., & Massey, T. C. (2024).

Tropical or extratropical cyclones: what drives the compound flood hazard, impact, and risk for the United States Southeast Atlantic coast? Natural Hazards. https://doi.org/10.1007/s11069-024-06552-x [12] Pierce, D. W., D. R. Cayan, D. R. Feldman, and M. D. Risser, 2023: Future Increases in North American Extreme Precipitation in CMIP6 downscaled with LOCA. J. Hydrometeor., https://doi.org/10.1175/JHMD-22-0194.1, in press. [13] San Francisco Estuary Institute (SFEI). December 16, 2022. Shallow Groundwater Mapping: Alameda, Marin, San Francisco, and San Mateo Counties. Accessed November 2024 from:
https://www.sfei.org/data/shallow-groundwater-mapping#sthash.4rH9IE3Y.dpbs [14] San Francisco Bay Conservation and Development Commission (BCDC). September 2024. September 2024 Draft Regional Shoreline Adaptation Plan (RSAP). Accessed September 2024 from https://bcdc.ca.gov/wp-content/uploads/sites/354/2024/09/Appendix-A-Regional-Shoreline-AdaptationPlan.pdf City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | January 22, 2025 | Arup US, Inc. Flood Modeling Report Page 33 [15] U.S. Geological Survey (USGS). December 6, 2018. Land Subsidence in the Santa Clara Valley.

Accessed November 2024 from https://www.usgs.gov/centers/land-subsidence-in-california/science/landsubsidence-santa-clara-valley [16] U.S. Geological Survey (USGS). 2019a. National Land Cover Database. Accessed September 2024 from https://www.usgs.gov/centers/eros/science/national-land-cover-database [17] U.S. Geological Survey (USGS). 2019b. Web Soil Survey. Accessed November 2024 from https://websoilsurvey.sc.egov.usda.gov/app/WebSoilSurvey.aspx [18] U.S. Geological Survey (USGS). N.d. Areas of Land Subsidence in California. Accessed November 2024 from https://ca.water.usgs.gov/land_subsidence/california-subsidence-areas.html [19] United States Department of Agriculture. 1986. Urban Hydrology for Small Watersheds: Technical Release 55. Natural Resources Conservation Service. Accessed November 2024 from:
https://www.ars.usda.gov/research/software/download/?softwareid=8&modecode=80-42-05-10 [20] United States Department of Agriculture. 2020. Download Soils Data. Natural Resources Conservation Service. Accessed November 2024 from: https://websoilsurvey.nrcs.usda.gov/app/WebSoilSurvey.aspx [21] The Water Institute. 2024. Compound Flooding. Accessed November 2024 from:
https://thewaterinstitute.org/projects/compound-flooding City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | November 22, 2024 | Arup US, Inc. Flood Modeling Report Appendix A
FEMA Map with Base Flood Elevations

City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | November 22, 2024 | Arup US, Inc. Flood Modeling Report Appendix B
SFEI Groundwater Maps

City of Newark Sea Level Rise Vulnerability Assessment and Adaptation Strategy 304252-00 | Draft 1 | November 22, 2024 | Arup US, Inc. Flood Modeling Report Appendix C
Model Results
County of Santa Clara, Maxar
Coastal Storm
Scenario - Present
(ft)
Value
0 - 0.5

0.5 -1
1- 2
3 - 4
5 - 8
9 - 16
17 - 32
33 - 64
City of Newark
0 0.5 1 2 Miles Mowry OLU
County of Santa Clara, Maxar
Inland Storm
Scenario - Present
(ft)
Value
0 - 0.5

0.5 -1
1- 2
3 - 4
5 - 8
9 - 16
17 - 32
33 - 64
City of Newark
0 0.5 1 2 Miles Mowry OLU
County of Santa Clara, Maxar
2050 Inland Storm
Maximum Flood
Depth (ft)
Value
0 - 0.5

0.5 -1
1- 2
3 - 4
5 - 8
9 - 16
17 - 32
33 - 64
City of Newark
0 0.5 1 2 Miles Mowry OLU
County of Santa Clara, Maxar
2050 Coastal Storm
Maximum Flood
Depth (ft)
Value
0 - 0.5

0.5 -1
1- 2
3 - 4
5 - 8
9 - 16
17 - 32
33 - 64
Mowry OLU
0 0.5 1 2 Miles City of Newark
County of Santa Clara, Maxar
2050 Inland Storm
Maximum Flood
Depth (ft)
Value
0 - 0.5

0.5 -1
1- 2
3 - 4
5 - 8
9 - 16
17 - 32
33 - 64
Mowry OLU
0 0.5 1 2 Miles City of Newark
County of Santa Clara, Maxar
2100 SLR 3.1 ft:

Permanent
Inundation (ft)
Value
0 - 0.5

0.5 -1
1- 2
3 - 4
5 - 8
9 - 16
17 - 32
33 - 64
City of Newark
0 0.5 1 2 Miles Mowry OLU
County of Santa Clara, Maxar
2100 Coastal Storm,

3.1 ft SLR,
Maximum Flood
Depth (ft)
Value
0 - 0.5

0.5 -1
1- 2
3 - 4
5 - 8
9 - 16
17 - 32
33 - 64
Mowry OLU
City of Newark
0 0.5 1 2 Miles
County of Santa Clara, Maxar
2100 SLR 4.9 ft:

Permanent
Inundation (ft)
Value
0 - 0.5

0.5 -1
1- 2
3 - 4
5 - 8
9 - 16
17 - 32
33 - 64
City of Newark
0 0.5 1 2 Miles Mowry OLU
County of Santa Clara, Maxar
2100 Coastal Storm,

4.9 ft SLR,
Maximum Flood
Depth (ft)
Value
0 - 0.5

0.5 -1
1- 2
3 - 4
5 - 8
9 - 16
17 - 32
33 - 64
Mowry OLU
City of Newark
0 0.5 1 2 Miles
County of Santa Clara, Maxar
2100 SLR 6.6 ft:

Permanent
Inundation (ft)
Value
0 - 0.5

0.5 -1
1- 2
3 - 4
5 - 8
9 - 16
17 - 32
33 - 64
City of Newark
0 0.5 1 2 Miles Mowry OLU
County of Santa Clara, Maxar
2100 Coastal Storm,

6.6 ft SLR,
Maximum Flood
Depth (ft)
Value
0 - 0.5

0.5 -1
1- 2
3 - 4
5 - 8
9 - 16
17 - 32
33 - 64
Mowry OLU
City of Newark
0 0.5 1 2 Miles
City of Newark
Sea Level Rise Vulnerability Assessment
Vulnerability and Risk Assessment Report
Draft | April 29, 2025
© Esri, NASA, NGA, USGS | NOAA Office for Coastal Management | Arup This report takes into account the particular instructions and requirements of our client. It is not intended for and should not be relied upon by any third party and no responsibility is undertaken to any third party.

Job number 304252-00
Arup US, Inc.
560mission Street, Suite 700
San Francisco, CA 94105
USA
arup.com
304252-00 | Draft 1 | April 29, 2025 | Arup US, Inc.

Contents
Executive Summary 4

1. Introduction 6

2. Vulnerability and Risk Model Development 8

3. Vulnerability and Risk Model Results 14

4. Conclusions and Next Steps 33
References 34

1. Introduction 6

2. Vulnerability and Risk Model Development 8

3. Vulnerability and Risk Model Results 14

4. Conclusions and Next Steps 33
References 34
Appendices
Appendix A
Zoning in Fremont
Zoning in Newark
Appendix B
EPA Queried Facility Registry Sites (FRS Sites) in Newark and Fremont Water Board Sites
Appendix C
FloodAdapt Output Maps
City of Newark
304252-00 | Draft 1 | April 29, 2025 | Arup US, Inc.

Sea Level Rise Vulnerability Assessment and Adaptation Strategy Vulnerability and Risk Assessment Report Page 3
Key Terms & Acronyms
Acronyms Full Form
ac acres ACWD Alameda County Water District
BCDC San Francisco Bay Conservation Development Commission CEC California Energy Commission
CI CalEnviroScreen 4.0 Indicator
DEM digital elevation model
EPA US Environmental Protection Agency
FFE finished floor elevation
FRS Facility Registry Service
MHHW Mean Higher High Water
mi miles
MTC Metropolitan Transportation Commission
NAVD88 North American Vertical Datum of 1988
NSI National Structure Inventory
OEHHA California Office of Environmental Health Hazard Assessment OLU Operational Landscape Unit
SFEI San Francisco Estuary Institute
SLR sea level rise
SVI social vulnerability index
the City the City of Newark
USACE U.S. Army Corps of Engineers
Water Board San Francisco Bay Regional Water Quality Control Board City of Newark
304252-00 | Draft 1 | April 29, 2025 | Arup US, Inc.

Sea Level Rise Vulnerability Assessment and Adaptation Strategy Vulnerability and Risk Assessment Report Page 4
Executive Summary
Flooding, sea level rise (SLR), and strong storms are growing threats for the City of Newark (the City). This study analyzes how these risks could affect the City’s infrastructure, communities, and natural areas. This analysis focuses on identifying what is at risk, like homes, roads, and wetlands, and estimating the potential damage.

Detailed flood maps show which areas might be permanently or regularly inundated in the future if no action is taken. These maps, described in the Flood Modeling Report, provided the foundation for the vulnerability and risk assessment presented here.

To better understand flood impacts, this study applied a planning tool called FloodAdapt, which brings together flood maps, infrastructure and building data, and information on potential damage and consequences. For analyzing SLR scenarios, any asset located below the future projected daily high tide line was assumed to be regularly flooded and treated as a total loss. To consider storm scenarios, damages based on modeled flood depths were estimated using industry-standard “depth-damage curves,” which relate water depth to the expected cost of damage.

This process helped estimate not only potential financial losses, but also identify which neighborhoods, facilities, and ecosystems are most at risk. The results of this risk analysis describe the cost of no action and help lay the groundwork for future adaptation planning.

Key Findings
This analysis provides a clear picture of what is at stake for the City—today, mid-century, and by the end-ofcentury. The findings below highlight the scale of potential impacts, which grow significantly over time and underscore the urgency of proactive planning.

Four SLR scenarios were applied: one representing mid-century conditions (0.8ft) and three representing end-ofcentury conditions (3.1ft, 4.9ft, 6.6ft). This approach captures the range of reasonable uncertainty by 2100 and aligns with state and regional standards for this type of analysis, including guidance from BCDC.

Table 1 summarizes the assets exposed to SLR for each of the four scenarios. The listed assets would be flooded under daily high tides, which the report also calls quasi-permanent inundation, as assets in the tidal zone would be inundated only part of the time. The results significantly increase from the 2050 scenario to the end-ofcentury scenarios, described more following the tables.

Table 1 Summary of quasi-permanent flood impacts from future SLR scenarios Asset Type (units) Mid-century (2050) End-of-century (2100)

0.8ft SLR 3.1ft SLR 4.9ft SLR 6.6ft SLR
Buildings (count) 10 50 490 2,200
Roads and trails (mi) 10 20 50 60
Rail lines (mi) 2 3 5 6
Sewer lines (mi) 1 4 11 17
Sewer system (count) 0 manholes
0 pump/lift station
130 manholes
1 pump/lift station
650 manholes
2 pump/lift stations
980 manholes
2 pump/lift stations
Electrical substations (count) 0 1 1 1
Transmission lines (mi) 4 20 30 40
Population in impacted census
blocks (count) 23,000 23,000 23,000 29,000
Contamination sites (count) 1 1 1 20
Wetland area (ac) 8,000 8,500 8,600 8,900
Total zoning area (ac) 4,100 4,700 7,900 12,000
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The estimated losses from quasi-permanent inundation are tabulated in Table 2. These values assume that the exposed assets, which would experience flooding under daily high tides, are a total loss, which is a conservative assumption as some amount of partial loss is plausible.

The sum shows $71M of impacted assets by 2050. The value increases by a factor of six by end-of-century under 3.1ft SLR and may be as much as $3.8B with 6.6ft SLR. These values assume all assets exposed, including those exposed to daily high tides under future SLR, are a total loss, which may conservatively overestimate impacts. This analysis forms a foundation upon which to evaluate cost-related benefits of adaptation strategies.

Table 2 Total estimated cost of SLR, in millions of dollars, given exposed assets are considered a total loss Asset Type
Mid-century
(2050)
End-of-century
(2100)

0.8ft SLR 3.1ft SLR 4.9ft SLR 6.6ft SLR
Buildings $45 $200 $1,500 $3,100
Roads $0 $70 $360 $490
Rail $4.5 $7.5 $14 $17
Sewer $1.7 $5.7 $22 $32
Power $20 $115 $160 $180
Total Loss $71 $398 $2,056 $3,819
Between now and 2050, the City faces limited but important early-stage risks from SLR, mostly affecting utilities and industrial infrastructure. The risks include:

Buildings: Approximately 10 buildings are at risk of daily flooding, primarily industrial and public buildings.

Roads and Trails: No permanent loss identified, but storm scenarios indicate significant flooding.

Rail Lines: About 1.5mi of rail lines are expected to be quasi-permanently inundated.

Sewer System: 1mi of active sewer lines and 5 sewer manholes would be flooded under high tides.

Power System: 4mi of transmission lines are within flooded areas.

Between 2050 and 2100, the scale of risk increases dramatically across all sectors. The risks include:

Buildings: By 2100, estimates range from about 50 to over 2,000 buildings impacted by daily flooding, depending on SLR ranging from 3.1ft to 6.6ft. There is a significant increase in residential and commercial buildings exposed.

Roads and Trails: Approximately 5mi of roads and 15mi of trails could experience quasi-permanent inundation by 3.3ft SLR, increasing to 37mi and 23mi, respectively, by 6.6ft SLR.

Rail Lines: Permanent inundation could affect 3mi to 6mi of rail lines.

Sewer System: 4-17mi of active sewer lines and up to 1,000 sewer manholes could be exposed to permanent inundation from SLR or daily flooding in the tidal zone.

Power System: 20mi to 40mi of transmission lines and one electrical substation could be quasi-permanently inundated.

Next Steps
The upcoming phase will focus on developing adaptation measures for key areas at risk, engaging the public, and incorporating feedback to prioritize actions and develop an adaptation strategy for the City.

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1. Introduction
The City of Newark has initiated a comprehensive Sea Level Rise Vulnerability Assessment and Adaptation Strategy to address the challenges posed by rising sea levels and associated flooding risks. This project aims to develop a robust understanding of the City’s flood risks and to formulate effective adaptation strategies. The study area encompasses the Mowry Operational Landscape Unit (OLU) which includes the entire City of Newark and portions of Fremont. Refer to the Flood Modeling Report for additional details on the flood hazard modeling approach and results. This report documents the approach and initial findings from the vulnerability and risk assessment. The upcoming phase will focus on adaptation strategies for key areas at risk.

Prior to this effort, the City conducted a Local Hazard Mitigation Plan effort with Union City and the City of Fremont which highlighted the need for this project. This project represents the first critical step in the adaptation planning process for the City by establishing a baseline understanding of pertinent flooding risks using industry best practices and methods. This understanding is essential for the second step, which involves developing risk-informed adaptation strategies and identifying potential partners for implementation.

This report summarizes the vulnerability and risk assessment model development, results, and conclusions. The assessment includes impacts on infrastructure, residents, business and the environment from flood hazards, including quantification of the number of assets at risk and estimated costs.

1.1 Study Area
The study area covers the Mowry OLU, which includes the entire City of Newark as well as portions of Fremont (Figure 1). The study area includes approximately 15mi of shoreline along the San Francisco Bay. The model extent is slightly larger than the Mowry OLU to ensure full coverage of Newark’s infrastructure and flood pathways, including areas just beyond the OLU boundary that influence local flood dynamics.

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Figure 1 Study area, model extents, and jurisdictions
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1.2 Vulnerability and Risk Assessment Approach
A flood hazard model of the Mowry OLU, which includes the City of Newark, was developed for both present and future SLR and storm scenarios. Four main types of flood scenarios were modeled for this project:

Present Coastal Storm Scenario: This scenario is defined in this study as the 100-year coastal event which considers tides and storm surges occurring simultaneously with a 10-year inland event which considers rainfall.

Present Inland Storm Scenario: This scenario is defined in this study as the 100-year inland event which considers rainfall occurring simultaneously with a 10-year coastal event which considers tides and storm surges.

Tidal (Quasi-Permanent) Inundation: These scenarios are defined by MHHW, which represents a typical high tide that serves as a proxy for everyday flooding. When modeling future MHHW with different SLR scenarios, the resultant maps provide useful tools for planning.

Future Coastal Storm Scenario: The future Storm Scenarios evaluate the maximum of the coastal storm scenario and the inland storm scenario to represent extreme but plausible combined storm scenarios. Rainfall for the future events comes from future climate projections of precipitation.

These scenarios are summarized in Table 3. The scenario development and hazard outputs are detailed in the Flood Modeling Report. Table 3 Summary of flood hazard scenarios run through the model Time Horizon Scenarios
Present Coastal Storm Scenario: 100-year coastal + 10-year inland Inland Storm Scenario: 100-year inland + 10-year coastal Mid-century (2050)

0.8ft SLR
Qua si-permanent Inundation
Future Coastal Storm
End-of-century (2100)

3.1ft SLR (Intermediate Scenario)
Qua si-permanent Inundation
Future Coastal Storm

4.9ft SLR (Intermediate-High Scenario)
Qua si-permanent Inundation
Future Coastal Storm

6.6ft SLR (High Scenario)
Qua si-permanent Inundation
Future Coastal Storm
The exposure of infrastructure, communities, and the environment to flooding was evaluated by intersecting their locations with the flood inundation extents using GIS. The vulnerability and risk assessment identified assets that are exposed to flooding in the storm and SLR scenarios, considering flood depth and potential damage. For building assets, damage was estimated using a depth-damage curve assigned to each asset, like apartment buildings or commercial businesses. As pictured in the center of Figure 2 and defined further in Section 2.4.2, depth-damage curves map the percentage of damage to the inundation depth for these assets.

Percent damage was directly related to financial loss for each asset for the storm scenarios, also shown in Figure 2. For SLR scenarios without storm, 100% damage was assumed.

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Figure 2 Overview of the calculation framework in Delft-FIAT, depicting the input of damage curves and asset data Risk was assessed using a scenario-based approach to evaluate the impact of flooding under each SLR and storm scenario. The financial losses of damage to physical infrastructure and buildings were estimated within FloodAdapt for the SLR scenarios, building on the assessment of exposure, damage, and vulnerability.

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2. Vulnerability and Risk Model Development
This section describes the development of the vulnerability and risk model using FloodAdapt. The sections capture:

Software and tools used to conduct the assessment
Scenarios modeled
Key model inputs collected from best available public datasets and incorporated into the modeling Assumptions and limitations made to develop these models

2.1 Software and Tools
Delft-FIAT is a Python-based tool developed to rapidly assess direct economic impacts to buildings, utilities, and roads for user-input flood maps. Delft-FIAT utilizes a unit-loss method similar to the Hazus tool by the Federal Emergency Management Agency. This report is focused on the inputs and outputs of the Delft-FIAT model that supported the vulnerability and risk assessment.

FloodAdapt is a decision-support tool that seeks to advance and accelerate flooding-related adaptation planning.

A FloodAdapt model was configured with flood hazard, vulnerability, and risk results (Figure 3). It will be used to model adaptation strategies.

Figure 3 Interaction between models and tools
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2.2 Scenarios Modeled
Ten flood scenarios were modeled as summarized in the Flood Hazard Report, encompassing the study area and evaluating timeframes for present-day, mid-century, and end-of-century conditions. The models cover four SLR scenarios and two storm scenarios, summarized in Table 3. Quasi-permanent inundation maps refer to areas inundated under Mean Higher High Water (MHHW) for that SLR scenario. For more detail on the flood hazard scenarios please review the Flood Hazard Report. 2.3 Data Collection and Sources Existing data and models were collected and developed to provide a tailored analysis for the City. Data was provided by the City as well as from local agencies, such as the Alameda County Flood Control District, San Francisco Bay Regional Water Quality Control Board (Water Board), Metropolitan Transportation Commission (MTC), and San Francisco Estuary Institute (SFEI). Datasets from state and national sources were also used, such as U.S. Army Corps of Engineers (USACE) National Structure Inventory (NSI), California Energy Commission (CEC), U.S. Environmental Protection Agency (EPA), and the California Office of Environmental Health Hazard Assessment (OEHHA). The sources are detailed in Table 5. Publicly available data was also collected and reviewed. Table 4 summarizes the data requests, data sources, and the availability of the data.

Unavailable data is defined as data not received from the City of Newark and not readily available online.

Table 4 Data and data sources
Available Data Unavailable Data
Building Data
Population Data
Land Use Data
Zoning Data
Roadway Data
Rail Line Data
Power System Data
Sanitary System Data
Emergency Facility Data
Landfill Data / Contaminated Sites
Trail Data
Community and Public Health Data
Community Facilities
Wetland Data
Vulnerable Communities Data
Transit System: Bus lines, yards, transit hubs
Water System: Water distribution system and pumps and treatment plants Economic Impact Data: Economic activities, property values, and potential economic loss information
Infrastructure Improvements: Planned infrastructure improvement projects O&M: Ongoing maintenance/replacement schedules, e.g. road repaving projects or culvert/bridge replacement.

Existing Cost-Benefit Analysis: Economic evaluation of proposed/existing adaptation measures. Feasibility Assessment: Technical and logistical feasibility of proposed/existing adaptation measures.

Proposed Adaptation Measures: Potential strategies for mitigating risks and adapting to SLR.

Planning Documents: Current comprehensive plans, hazard mitigation plans, and climate adaptation plans

2.4 Vulnerability and Risk Assessment Key Model Inputs
The FloodAdapt software was used for the vulnerability and risk assessment using inputs collected primarily from publicly available sources. The inputs and their sources are discussed in this section.

2.4.1 Flood Hazard Data
The results presented in the Flood Hazard Report were used to feed into the vulnerability and risk assessment.

Delft-FIAT overlays spatial data on flooding and exposed assets to calculate flood damages, as depicted in Table 5. The results from the Flood Modeling Report are summarized below. Details from these results and high-resolution flood maps can be referenced there.

Present Day
The berms around the salt farms provide a level of protection against coastal flooding and the berms are not overtopped in either of the present-day scenarios.

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The Inland Storm Scenario has wider flood inundation extents and has a greater impact in residential and commercial areas, particularly within the City of Newark boundary, compared to the Coastal Storm Scenario which is concentrated in areas closer to the bay.

Mid-century (2050)
Quasi-permanent Inundation:

The quasi-permanent inundation results depict limited areas of impact, with localized parts flooding in the northwest and southeast of the City.

Storm Scenario:

When considering the Storm Scenario in addition to the quasi-permanent conditions, the flooding becomes more widespread, particularly in the salt farms.

End-of-century (2100)
Quasi-permanent Inundation:

3.1ft SLR to 4.9ft SLR: Similar flood extents with limited areas of impact similar to mid-century, localized flooding in the northwest and southeast of the City. Maximum flood depth increases at 4.9ft SLR.

Tipping point (4.9ft to 6.6ft SLR): The flood hazard report identified a “tipping point” in the results where the increase in sea level result in disproportionately large and often irreversible impacts. At this stage, significant day-to-day impacts from quasi-permanent inundation begin, with berms overtopped.

6.6ft SLR: Significantly larger portion of developed areas impacted, requiring widespread mitigation.

Storm Scenario:

When considering the Storm Scenario in addition to the quasi-permanent conditions, the tipping point for widespread flooding occurs with 3.1ft SLR, which could occur in a nearer timeframe than the quasipermanent inundation tipping point.

In particular, the salt farms and in the developed areas in the northwest of the City experience the most flooding. Inland flooding also occurs in pockets throughout the residential neighborhoods in this scenario.

2.4.2 Asset Data
The vulnerability model assesses the exposure of different asset types to flood inundation, and it considers how those assets may be damaged. Assets in this assessment include buildings (residential, commercial, industrial, and public), roads, utility infrastructure (power and sewer), landfills, and wetlands. Data was collected where available about their location and characteristics (e.g., building use type) to inform the vulnerability and risk assessment. This information is summarized in Table 5.

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Table 5 Summary of key model inputs for the assets
Asset Type Asset Name (Subtype) Data Source Data Type Vulnerability Curve Cost Data
Building Data Building centroids (points) NSI (USACE) Point Arup NSI (USACE) Population Data Equity Priority
Communities (areas) MTC Polygon N/A N/A
Zoning Data Zoning (areas) City of Newark and
City of Fremont Polygon N/A N/A
Roadway Data Roadways (lines) City of Newark and
OSM Polyline Arup N/A
Rail Line Data Rail lines (lines) City of Newark Polyline Arup Arup Sanitary System Data
Manholes (points)
Power/Lift Stations
(points)
Easements (points)
Mains (lines)
Union Sanitary
District
Points and
Polylines Arup, HAZUS Arup
Power System Data
Electrical substations
(points) CEC Points Arup, HAZUS PG&E
Transmission Lines (lines) CEC Lines Arup, HAZUS PG&E
Emergency Facility
Data
Police stations (points)
Fire stations (points)
City of Newark and
City of Fremont Point Arup Arup, NSI (USACE)
Landfill Data /
Contaminated Sites
Facility Registry Service
Sites (points)
Water Board sites (points)
EPA and Water
Board Point N/A N/A
Trail Data Bike trails (lines)
Pedestrian trails (lines) MTC Line Arup N/A
Public Health Facilities Hospitals (points)
Care centers (points)
City of Newark and
City of Fremont Point Arup Arup, NSI (USACE)
Community Facilities
Libraries (points)
Schools (points)
Community/civic centers
(points)
Other public use buildings
(points)
City of Newark and
City of Fremont Point Arup Arup, NSI (USACE)
Wetland Data Wetlands (areas) SFEI Polygon N/A N/A
Vulnerable
Communities Data
Vulnerable communities
(areas) CA OEHHA Polygon N/A N/A
Point and linear assets were assessed quantitatively via FloodAdapt. Point assets are combined as an input “Buildings” dataset, while linear assets were combined as an input “Roads” dataset to be used in FloodAdapt.

These datasets went through a pre-processing stage to combine all point assets together and all linear assets together. Preprocessing included the following:

There was overlap in the NSI dataset and other provided buildings above, a pre-processing step was done to filter buildings that overlapped one another within a 30ft radius.

Linear assets were segmented into 500ft increments to provide more granularity to results as the centroid digital elevation model (DEM) value is assigned to each feature.

The unavailable assets listed in Table 3 were excluded from this analysis. Should datasets become available in the future, they can be uploaded to the model via the FloodAdapt interface after preprocessing the data into exposure and vulnerability datasets.

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Area features were assessed qualitatively through a geospatial analysis. To do this assessment, the flood maps were turned into polygons and overlaid with areas to determine percent flooding and exposure to land and people.

Asset Vulnerability Data
Depth-damage curves are used to estimate the damage to assets based on the depth of flooding, as shown in Figure 4. These curves relate the depth of water to the percentage of damage, also used to estimate percentage of financial loss, for different asset types. The curves are derived from empirical studies (such as HAZUS) and detailed component-based models (such as Arup). Data sources for the vulnerability curves for each asset are listed by type in Table 5.

Figure 4 Example vulnerability curves used in FloodAdapt showing a set of depth-damage curves (Arup) The implementation of vulnerability curves required several assumptions. These details are summarized in Table 6.

Table 6 Asset types and vulnerability curve implementation Asset Type Vulnerability Curve Implementation
Points The finished floor elevation (FFE) for buildings was used from the USACE NSI database. Where FFE was not available, it was assumed to be 0.5ft above the ground. All other point assets were assumed at-grade (0ft above the ground).

Lines All linear assets were assumed to be at-grade (0ft above the ground).

Areas All area assets were assumed to be at-grade (0ft above the ground).

Asset Cost Estimate Data
As shown in Table 5, values of each asset used cost data from several sources, including the NSI database (USACE, 2022) for most buildings, PG&E data for power system infrastructure, and Arup-developed cost data for the remainder of assets whose costs were assessed. These cost estimates should be considered as rough order of magnitude values to present a high-level estimate of potential financial losses under each scenario. The costs do not consider broader economic impacts.

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2.5 Assumptions and Limitations
This analysis assumes that publicly available data and data provided by the City and sources listed below accurately represent existing conditions and infrastructure. Limitations include:

The hazard model accuracy is dependent on the quality and resolution of the input data, such as topography, bathymetry, and rainfall.

Damage values for buildings are based on depth-damage curves assigned based on the use type in the NSI dataset or overridden by a City-provided dataset if provided.

Maximum damage values of assets are based on average values from previous studies or published reports for non-building assets.

Flooding depth of linear assets are based on a DEM at a 500-meter resolution.

The data may not account for recent changes or developments in the area, such as new construction or infrastructure changes.

Results presented are based on the inputs discussed herein. There may be gaps in the data that could lead to incomplete analysis or conclusions.

Results were rounded to two significant figures before summation.

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3. Vulnerability and Risk Model Results
Vulnerability is defined as the combination of exposure and potential damage. Exposure refers to the extent to which various types of assets, such as physical structures, human populations, environmental resources, and economic entities, are subject to potential harm. Potential damage describes the possible extent of harm or loss that could occur if these exposed assets are affected, including physical destruction, human health impacts, environmental degradation, and economic losses. Risk focuses on these consequences for potential events, for this assessment in terms of cost information. Risk assessment involves evaluating the likelihood of an event occurring and the severity of its impact, here quantified in financial terms. Together, these concepts help in understanding and mitigating the potential adverse effects on assets and resources (Figure 5).

Figure 5 Vulnerability and risk relationship (Arup)
The results from the vulnerability and risk model results are presented in this section, first with a summary of results, followed by details of the qualitative and quantitative assessment performed.

3.1 Vulnerability Summary
Table 7 summarizes exposed assets for each SLR scenario, where the listed assets would be flooded under daily high tides (i.e., MHHW) at a minimum. The results significantly increase from the mid-century scenario to the end-of-century scenarios.

Table 7 Summary of vulnerable assets exposed under quasi-permanent inundation in each SLR scenario Asset Type (units)
Mid-century
(2050)
End-of-century
(2100)

0.8ft SLR 3.1ft SLR 4.9ft SLR 6.6ft SLR
Buildings (count) 10 50 490 2,200
Roads and trails (mi) 10 20 50 60
Rail lines (mi) 2 3 5 6
Sewer system (mi) 1 4 11 17
Sewer system (count) 0 manholes
0 pump/lift station
130 manholes
1 pump/lift station
650 manholes
2 pump/lift station
980 manholes
2 pump/lift station
Electrical substations (count) 0 1 1 1
Transmission lines (mi) 4 20 30 40
Socially vulnerable
households 0 0 0 10
Contamination sites**
(count) 1 1 1 20
Wetland area (ac) 8,000 8,500 8,600 8,900
Total zoning area (ac)*** 4,100 4,700 7,900 12,000
**Contamination sites include those queried from the EPA Facility Registry Service Sites that fall under the Hazardous Waste Program, Superfund/Superfund National Priorities List, and Toxic Release Inventory Reporter within Fremont and Newark, along with sites provided by the Water Board.
***Total zoning area is defined as the land that is zoned per the cities of Newark and Fremont within the OLU City of Newark
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Under the coastal storm scenario, the number of exposed assets is much higher than considering SLR alone.

Table 8 includes a high-level summary by SLR scenario with coastal storm for present and future time horizons resulting from the quantitative assessment.

Table 8 Summary of vulnerable assets exposed in present and future storm scenarios Asset Type Present-day
(2025)
Mid-century
(2050)
End-of-century*
(2100)
Buildings (count) 180 200 1,900 to 4,600
Roads and trails (mi) 50 50 70-80
Rail lines (mi) 3 4 5 to 8
Sewer system (mi) 30 120 120 to 130
Sewer system (count) 600 manholes**
0 pump/lift station
500 manholes**
1 pump/lift station
1,120 to 1,370 manholes
2 to 3 pump/lift station
Electrical substations (count) 0 0 1
Transmission lines (mi) 20 30 35 to 40
*Range from multiple SLR scenarios modelled for end-of-century (3.1ft, 4.9ft, and 6.6ft). **Reduction in flooding from present to 2050 is due to ponding in the model, where depths are below 4in. This applies to approximately 200 manholes in 2025 and 100 manholes in 2050.

3.2 Qualitative Results
The qualitative results in this section focus on people, contamination sites, habitats, and land exposed to daily high tides, a state referred to as quasi-permanent inundation, for each of the four SLR scenarios evaluated.

3.2.1 Population
The population density of census blocks in the Mowry OLU affected by each of the future SLR inundation scenarios is shown in Figure 6. This bivariate mapping conveys the population density of each census block and the percent area of each census block that is inundated. In a bivariate map, two variables are shown simultaneously using a combined color scale—here, population density and flood extent. Yellow areas are relatively more populated, blue areas have higher relative flooding, and the increasingly red values have both relatively more flooding and denser population. The census block data is from 2020.

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Figure 6 Census blocks affected by quasi-permanent flood levels with rising SLR The most vulnerable census block is in the northwest portion of the study area in all future SLR scenarios. The tipping point from 4.9ft to 6.6ft inundation reveals that the most populous blocks within the City on the western side, consisting of approximately 5,800 people, are flooded daily by 6.6ft SLR and can be expected to be vulnerable during coastal storms earlier than 2100.

In addition to census population, flood extents were overlayed with regions of unique CalEnviroScreen 4.0 Indicator (CI) scores. This is a science-based mapping tool developed by the California EPA and the Office of Environmental Health Hazard Assessment. The map of the surrounding area and their CI scores is depicted in Figure 7. The CI scores incorporates various socioeconomic indicators, such as income, education, and housing conditions, to evaluate how these factors contribute to a community's susceptibility to pollution. Communities with higher social vulnerability often face greater health risks from environmental hazards due to limited resources and resilience.

Within FloodAdapt, a high social vulnerability is listed as social vulnerability index (SVI) > 0.6, and displacement is expected where inundation of homes exceeds 6ft. By 2050, approximately 40 homes with a high SVI score are expected to experience moderate flooding during the storm scenario, and displacement is not expected. For the 2100 storm, between 50 to 400 homes with a high SVI score are expected to experience moderate flooding, and displacement is expected for 50 homes. Less than 10 socially vulnerable homes are expected to be impacted by quasi-permanent inundation at 6.6ft SLR.

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Figure 7 CI scores for the City and the surrounding area The social and economic vulnerability to environmental factors as determined by the CI scores is presented in the Figure 8 with description of flood extents from the quasi-permanent inundation.

Figure 8 Bivariate map with flood extent and CI score (the CI score is the same for each image) City of Newark
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Figure 8 depicts census tracts with some inundation and presents their CI scores, which range from 21.8 to 48.3 out of 100 which is moderate compared to the surrounding region. The flood extents vary based on the SLR scenario and the CI score is consistent across all scenarios. The extent of vulnerable groups impacted across scenarios is similar until 6.6ft SLR when an additional population block is impacted in the northern zone of the City (population 5,500). The highest CI scored zone is 48.3 which is characterized by 35% of the population living below two times the federal poverty level, 55% linguistic isolation, 12% unemployment, and 40% of residents with a housing burden.

3.2.2 Contamination Sites
Figure 9 depicts the locations of EPA Facility Registry Service (FRS) Sites in Newark and Fremont that fall under the EPA Hazardous Waste Program, Superfund/Superfund National Priorities List, and Toxic Release Inventory Reporter within Fremont and Newark, and contamination sites provided by the Water Board within the OLU. There are 251 total sites identified in Mowry OLU between these two datasets. Refer to Appendix B for a full list of Facility Registry Sites and Water Board sites in Newark and Fremont.

In Figure 9, the lefthand side depicts the quasi-permanent flood extents in reference to potentially contaminated sites, and the righthand side depicts the site locations in reference to groundwater.

Figure 9 Contaminated sites and flooding (left) and contaminated sites and emergent groundwater from SFEI (right) When considering flooding of the FRS sites, 11 are impacted under 6.6ftSLR and there are no impacted sites under the lower SLR scenarios evaluated. Only one Water Board site is impacted at all quasi-permanent inundation states. Eight (8) Water Board sites are impacted under 6.6ft. The type and count of sites impacted under the SLR scenarios are listed in Table 9.

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Table 9 Count of contamination sites exposed to quasi-permanent inundation Contaminated Sites Source
Mid-century
(2050)
End-of-century
(2100)

0.8ft SLR 3.1ft SLR 4.9ft SLR 6.6ft SLR
Land Disposal Site Water Board 0 0 0 2
Water Board - Cleanup Program Site Water Board 0 0 0 3
Non-case Information Water Board 0 0 0 1
LUST Cleanup Site Water Board 1 1 1 2
FRS Sites EPA 0 0 0 11
Total 1 1 1 19
The potential for environmental contamination via groundwater presents a potential hazard shown on the right in Figure 9 due to the rising groundwater levels (SFEI, n.d) with overlay to approximately 50% of the total contaminated sites by 6.6ft SLR presents concern for environmental contamination. Rising groundwater levels can damage infrastructure designed to contain hazardous materials. This includes underground storage tanks and waste containment systems, which may fail and release contaminants. The increased pressure from groundwater can also compromise the integrity of these structures. Contaminated groundwater can lead to significant environmental and health hazards. Toxic substances such as heavy metals, pesticides, and industrial chemicals can be released into the environment, posing risks to human health and ecosystems.

3.2.3 Wetlands
Wetlands are natural transition zones between the sea and land and consist of valuable ecosystem elements such as coastal vegetation and unvegetated mudflats. They are a vulnerable land type as they can be lost due to SLR if their rate of landward migration is lower than seaward erosion (Chen et al., 2024).

The total wetland area in the Mowry OLU is 9,000ac. The two main habitat types are Freshwater Emergent and Estuarine/Marine according to U.S. Fish and Wildlife designations. The wetland area by type with overlaid outlines of quasi-permanent inundation is shown in Figure 10. The area designated as Lake was excluded from the quantification, as it is representative of the industrial salt flats in the OLU and discussed in Section 3.2.4.

A full-page version of this map is available in Appendix D.

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Figure 10 Wetlands areas from the U.S. Fish and Wildlife Service Of this dataset, the two types of wetland areas (Estuarine & Marine Wetland and Freshwater Emergent Wetland) total area impacted for each SLR scenario is shown in Table 10.

Table 10 Wetland area impacted in each SLR scenario
Wetland Areas
Mid-century
(2050)
End-of-century
(2100)

0.8ft SLR 3.1ft SLR 4.9ft SLR 6.6ft SLR
Estuarine and Marine Wetland 8,000 8,500 8,500 8,700
Freshwater Emergent Wetland 20 20 100 180
Total Area (ac) 8,020 8,520 8,600 8,880
Present-day (2025)
Healthy wetland habitats exist in the present-day tidal zone. These areas support diverse vegetation and wildlife, contributing to the overall ecological health of the region. The salt farms provide habitat for over 70 bird species.

Mid-century (2050)
By mid-century, some wetland areas that were previously inundated only during high tides will experience permanent inundation. This change will impact the health of existing vegetation and inhabitants, potentially leading to shifts in species composition and ecosystem functions. Most of the marine wetland is inundated by

0.8ft SLR (90%) and a small portion of the freshwater emergent wetland is inundated daily.

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End-of-century (2100)
A notable shift in freshwater emergent wetland occurs between 3.1ft to 4.9ft SLR, where percent inundation increases five times (from 20 to 100 ac). By 6.6ft SLR, most of the salt ponds are expected to be quasi-permanently inundated. This represents a substantial increase in inundation, affecting the stability and health of these wetland ecosystems.

3.2.4 Land Use
The types of zoned areas in the City include five main uses: Industrial, Parks and Open Space, Residential, Commercial, and Public. The zoning in the Mowry OLU is shown in Figure 11 and the impacted areas are summarized in Table 11. Refer to Appendix A for the full list of zones. A full-page version of this map is available in Appendix D.

Figure 11 Zoning in Mowry OLU
Table 11 Impacted areas (ac) by zone type
Zone
Total Zone
Area
(ac)
Mid-century
(2050)
End-of-century
(2100)

0.8ft SLR 3.1ft SLR 4.9ft SLR 6.6ft SLR
Industrial 7,400 50 90 1,070 2,600
Parks and Open Space 36,300 3,800 4,400 6,600 8,500
Residential 13,500 200 200 200 300
Commercial 700 2 10 30 150
Public 1,800 10 20 20 50
Total Impacted Zoned Area – 4,062 4,720 6,850 9,000
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Present-day (2025)
Currently, the areas designated for industrial, residential, commercial, public, and parks and open spaces are largely unaffected by SLR. These zones support various activities and infrastructure, contributing to the economic and social fabric of the region. The wetlands and salt farms in Newark and Fremont, continue to provide critical habitats for wildlife and support biodiversity.

Mid-century (2050)
By mid-century, the impact SLR begins to manifest noticeably. The impacts include:

Parks and Open Space: 3,800ac are affected, potentially disrupting recreational areas and natural habitats.

Residential Areas: 200ac are impacted, posing risks to homes and communities.

Industrial Areas: 50ac are impacted, indicating initial encroachment of rising waters into industrial zones; most of this area is zoned within the salt flats.

Public Areas: 10ac are impacted, indicating some early effects on public infrastructure and services.

Commercial Areas: <5ac are affected, suggesting minimal early impact on commercial zones.

End-of-century (2100)
By the end-of-century, the impact of SLR varies significantly across the different scenarios, from Intermediate SLR (3.1ft) to High SLR (6.6ft). The impacts include:

Parks and Open Space: The affected area ranges from 4,400ac (Intermediate) to 8,500ac (High), threatening recreational spaces and natural habitats.

Industrial Areas: The impacted area ranges from 90ac (Intermediate) to 2,600ac (High), indicating substantial risk to industrial infrastructure and operations.

Residential Areas: The impacted area ranges from 200ac (Intermediate) to 300ac (High), posing significant risks to housing and communities.

Commercial Areas: The affected area ranges from 10c (Intermediate) to 150ac (High), indicating increasing a large range of risk to commercial properties.

Public Areas: The impacted area ranges from 20ac (Intermediate) to 50ac (High), suggesting growing threats to public infrastructure and services.

3.3 Quantitative Results
This section details the quantitative risk results, which show the counts of assets and estimated dollar loss from impacted assets within the Mowry OLU. Results are presented for buildings, roads, trails, rail lines, sewer system, and power system. For each SLR scenario, there is a summary of results for both the assets exposed to quasi-permanent flooding (e.g., inundated by high tides and/or SLR in a given scenario) and to coastal storms (i.e., the 100-year storm surge).

The severity of flooding is also presented, where flood depths range from slight to severe flooding depending on the asset type. This provides more detailed description and insight to the consequences at different levels of flooding.

Figure 12 depicts the flood maps for the quasi-permanent SLR scenarios, showing concentration of exposed assets in red. Notably, the northwest corner of Newark has a high concentration of exposed assets. Higher resolution maps can be found in Appendix C.

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The estimated losses (in dollars) are tabulated in Table 12, showing $71M of impacted assets by 2050. The value increases nearly six-fold to $398M by end-of-century under 3.1ft SLR and may be as much as $3.8B with 6.6ft SLR. These values assume all assets exposed, including those exposed to daily high tides under future SLR, are a total loss, which may conservatively overestimate impacts.

Table 12 Total estimated cost of SLR, given exposed assets are considered a total loss Asset Type
Mid-century
(2050)
End-of-century
(2100)

3.3.1 Buildings
The count of buildings exposed to SLR is tallied in Table 13 and presented by building type. Buildings located in the tidal zone are exposed to quasi-permanent flooding, and these buildings are considered a total loss. By mid-century, twelve buildings were identified as exposed, including 10 public buildings and 2 industrial buildings, whose loss values were estimated at a total of $45M.

Table 13 Count of flooded buildings by type under quasi-permanent inundation Building Type
Mid-century
(2050)
End-of-century
(2100)

0.8ft SLR 3.1ft SLR 4.9ft SLR 6.6ft SLR
Public Buildings 10 30 70 100
Industrial Buildings 2 15 70 110
Commercial Buildings 0 2 70 100
Residential Buildings 0 5 280 1,800
Emergency Facility 0 0 0 3
Hospitals and Care Centers 0 0 2 4
Schools 0 0 0 3
Total Count 12 52 492 2,120
Total Loss ($millions USD) $45 $200 $1,500 $3,100
The values of building counts affected by quasi-permanent inundation are visualized in Figure 13. The shaded area shows the range based on SLR scenario, from Intermediate (3.1ft) to High (6.6ft).

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Figure 13 Number of impacted buildings by type in each time horizon on a log-normal scale The results from storm scenarios are depicted in Table 14 and Table 15 based on estimated building repair costs and the level of flooding at each building in each storm scenario.

Table 14 Building types and damage value under storm scenarios Building Type
Estimated Cost (million $ USD)
Present-day (2025) Mid-century (2050) End-of-century* (2100) Public Buildings $40 $40 $100–200
Industrial Buildings $15 $35 $200–450
Commercial Buildings $50 $55 $220–680
Residential Buildings $10 $10 $100–470
Emergency Facility $ – $ – $<1–3
Hospitals and Care Centers $1 $1 $2–12
Schools $ – $ – $2–10
Total Cost $116 $141 $625–1,825
*Range for 2100 represents 3.1ft to 6.6ft SLR.

Table 15 Severity of building flooding under storm scenarios Time Horizon Minor Flooding Major Flooding Destroyed Buildings Count of Buildings Present 54% 40% 6% 180
2050 48% 44% 8% 200
2100* 57% (3.1ft SLR)
15% (6.6ft SLR)
40% (3.1ft SLR)
80% (6.6ft SLR)
3% (3.1ft SLR)
5% (6.6ft SLR)
1,900 (3.1ft SLR)
4,600 (6.6ft SLR)
*Minor flooding for buildings is defined as inundation depths < 1ft **Major flooding for buildings is defined as inundation depths 1ft to 6ft ***Destroyed buildings are defined as those with > 6ft inundation City of Newark
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Present-day (2025)
Under a 100-year storm surge event, the following impacts were identified through 2050:

Total damage is approximately $116M for buildings.

Approximately 180 buildings are affected, where most of the sustained damage is minor (54%).

Mid-century (2050)
Assets at stake under SLR include:

Very minimal exposure of buildings (approximately 10) to daily flooding, composed of industrial and public buildings.

Temporary loss over storm scenarios includes:

Approximately 200 buildings are impacted with a rise in major flooding and destroyed buildings, adding an additional $25M in cost from today’s 100-year storm surge event.

End-of-century (2100)
Assets at stake under SLR include:

By 2100 with 3.1ft SLR, the number of buildings impacted by quasi-permanent inundation increases by a factor of 5 (50 buildings). Commercial buildings begin to be impacted.

By 4.9ft SLR, the count of impacted buildings increases by a factor of 10 to 490 buildings.

By 6.6ft SLR, up to 2,160 buildings are impacted on a daily basis. Hospitals and care centers are impacted.

The majority of buildings impacted by the end-of-century are residential.

Temporary loss of assets over storm scenarios include:

In an end-of-century storm scenario, there are up to 4,600 flooded buildings, most of which are impacted by severe flooding. The cost of a storm event will be between $600M to $900M, around 1.5 to 5 times greater cost than a 2050 storm event.

3.3.2 Roads and Trails
Table 16 and Table 17 summarize impacts to roads and trails under future SLR scenarios (considered a total loss) and in the storm scenarios. Table 16 summarizes the quasi-permanent inundation scenarios, summing assets located in the tidal zone (below high tide).

Figure 14 displays the results of the storm scenarios, in which inundation is considered temporary. These results were summarized as a dollar value, where costs to repair assets were used.

Overall, most roads in Mowry OLU are residential and major roads, and both experience up to 50% extent inundation by the end-of-century. There is a very small extent of arterial roads within the OLU, and freeways experience up to 30% inundation extent by end-of-century.

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Table 16 Miles of flooded roads under quasi-permanent inundation Type of Road Total Length (mi)
Mid-century
(2050)
End-of-century
(2100)

0.8ft SLR 3.1ft SLR 4.9ft SLR 6.6ft SLR
Arterial 1 0 0 0.4 0.4
Residential 90 0 3.2 18 26
Major Road 40 0 2.4 11 13
Freeway 15 0 0 1.3 2.2
Trails 75 10 15 20 23
Total Roads (mi) 221 10 20.6 50.7 64.6
Total Cost*
(Millions USD) $0 $70 $360 $490
*Total cost does not include the cost of trail replacement.

Table 17 Average severity of roadway flooding in each storm scenario Time Horizon Total Flooding
(mi)
Slight Flooding
(%)
Minor Flooding
(%)
Major Flooding
(%)
Fully Flooded
(%)
Present (2025) 50 28% 18% 48% 6%
Mid-century (2050) 50 28% 15% 48% 9%
End-of-century (2100) 70-80 17% (3.1ft SLR)
12% (6.6ft SLR)
7% (3.1ft SLR)
5% (6.6ft SLR)
31% (3.1ft SLR)
19% (6.6ft SLR)
45% (3.1ft SLR)
64% (6.6ft SLR)
Note: Values above are not inclusive of trail flooding during storm Figure 14 Percent of road system by degree of flooding (2100 is reported as an average value of 3.1, 4.9 and 6.6ft SLR) Present-day (2025)
Under a 100-year storm surge event, 50mi of roadways (non-inclusive of trails) are expected to be impacted, to varying degrees listed in Table 17.

Slight flooding: 14mi of road are expected to experience at least slight flooding (<0.3ft). This flooding is expected to affect pedestrians through ponding but no vehicles.

Minor flooding: 9mi of roadway experience >0.5ft flooding and may experience damage, or at the very least be closed for several hours to several days and disrupt cars.

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Major Flooding: 27mi of roadway experience >1ft flooding. This level of inundation can significantly disrupt traffic flow, cause extensive damage to road surfaces, and potentially undermine the structural integrity of the roads, leading to prolonged closures and costly repairs.

Fully Flooded Roads: 3mi of roads experience > 2ft flooding. Major flooding can render roads completely impassable, isolate communities, hinder emergency response efforts, and result in substantial long-term damage to the infrastructure, necessitating major reconstruction efforts.

Mid-century (2050)
No permanent loss was identified at 0.8ft SLR of roadways was identified. Ten (10) miles of trails were found to experience daily flooding and could impact use.

Temporary loss of assets over storm scenarios include:

Flooding extents are expected to be the same in this storm scenario as present day, with marginal differences in the overall road system.

End-of-century (2100)
Assets at stake under SLR include:

No permanent loss of roads was identified at 3.1ft SLR, but 15 miles of trails are identified as impacted. At

4.9ft SLR, roughly 6mi of roads and 20mi trails experience quasi-permanent inundation, which increases to 23mi of trails and 41mi of roads at 6.6ft SLR. The impacts from 4.9 and 6.6ft SLR includes 0.4mi of arterial roads, 18mi to 26mi of residential roads, 11mi to 13mi of major roads, 1.3mi to 2.2mi of freeways, and 20-23mi of trails.

Temporary loss of assets over storm scenarios include:

By the end of the century, storms are expected to impact 70-80mi of roadways, with most of this (76-83%) consisting of major flooding (>1ft inundation).

3.3.3 Rail lines
There are 13mi of railroad within the site boundary and their impacts within the different storm scenarios are listed in Table 18. The severity of rail system flooding under storm scenarios is included in Table 19 and displayed in Figure 15.

Table 18 Extent of flooded rail lines under quasi-permanent inundation Type
Mid-century
(2050)
End-of-century
(2100)

0.8ft SLR 3.1ft SLR 4.9ft SLR 6.6ft SLR
Railroad (mi) 1.5 2.5 4.5 5.5
Total Loss (millions $) $4.5 $7.5 $14 $17
Table 19 Severity of rail system flooding under storm scenarios Time Horizon Total Flooding*
(mi)
Slight Flooding
(%)
Minor Flooding
(%)
Major Flooding
(%)
Severe Flooding
(%)
Present 3 (2) 10 10 16 64
Mid-century 4 (3) 6 6 10 78
End-of-century* (2100) 5-8 (5-8) 8% (3.1ft SLR)
6% (6.6ft SLR)
0% (3.1ft SLR)
3% (6.6ft SLR)
18% (3.1ft SLR)
7% (6.6ft SLR)
74% (3.1ft SLR)
84% (6.6ft SLR)
*The length of railway that is anticipated to impact a train (inundation > 0.5ft) is reported in parentheses City of Newark
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Figure 15 Percent of rail system flooding by flood level (2100 is reported as an average value) Present-day (2025)
Under a 100-year storm surge event, the following impacts were identified through 2050:

Flooding Extent: Coastal storms are expected to flood approximately 3mi of railway, 2 of which are expected to impact railway travel.

Flooding Severity: 15% of this flooding is severe (1ft to 2ft inundation).

Implications: The current flooding poses operational challenges and potential disruptions to rail services, requiring immediate mitigation measures to ensure safety and continuity.

Mid-century (2050)
Assets at stake under SLR include:

Permanent Inundation: By 2050, approximately 1.5mi of railroad lines are expected to be quasi-permanently inundated.

Implications: Permanent inundation will require long-term planning and investment in adaptive measures, such as elevating tracks or relocating vulnerable sections, to maintain rail connectivity and protect critical transportation assets.

For a storm in 2050, temporary impacts to assets include:

Flooding Extent: The extent of flooding on railroad lines is projected to increase by 50% (up to 4mi).

Flooding Severity: Moderate to severe flooding is expected to double up to 25% being at least a foot inundated, while slight and minor flooding will be reduced by half.

Implications: The increased flooding severity will necessitate significant infrastructure upgrades and enhanced flood management strategies to prevent prolonged service interruptions and ensure resilience against future storms.

End-of-century (2100)
Assets at stake under SLR include:

Permanent Inundation: By 2100, the railroad lines are expected to experience significant permanent inundation, with estimates ranging from 6mi to 9mi of railroad being affected.

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Implications: The permanent loss of railroad infrastructure will necessitate extensive long-term planning and investment in adaptive measures. This may include elevating tracks, constructing protective barriers, or relocating vulnerable sections to ensure rail connectivity and protect critical transportation assets.

Temporary loss of assets over storm scenarios include:

Flooding Extent: Coastal storms in 2100 are projected to flood approximately 6mi to 9mi of railroad.

Flooding Severity: The severity of flooding is expected to increase, with moderate to severe flooding becoming more prevalent. This will require substantial infrastructure upgrades and enhanced flood management strategies to prevent prolonged service interruptions and ensure resilience against future storms.

Implications: The increased flooding extent and severity will pose significant operational challenges, necessitating robust mitigation measures and emergency response plans to ensure the safety and continuity of rail services.

3.3.4 Sewer System
The number of sewer system assets exposed to SLR is tallied in Table 20. Sewer system assets located in the tidal zone are exposed to quasi-permanent flooding, and these assets are considered a total loss. The total estimated loss ranges from $11M by 2050 to approximately $200M by the end of the century.

Table 20 Extent of sewer system flooding by type under quasi-permanent inundation Type
Mid-century
(2050)
End-of-century
(2100)

0.8ft SLR 3.1ft SLR 4.9ft SLR 6.6ft SLR
Sewer line (active) (mi) 1.0 3.6 11 17
Sewer line (abandoned) (mi) 0 0.07 0.16 0.16
Sewer Manhole 5 130 650 980
Abandoned Sewer Manhole 0 7 10 10
Sewer Pump/Lift Station 0 1 2 2
Total Loss ($ million USD) $1.7 $5.7 $22 $32
During a coastal storm the count of impacted assets is much higher, as seen in Table 21.

Table 21 Sewer system flooding under storm scenarios
Time Horizon Miles of Flooded – Mains* Count of Flooded Manholes**
Count of Sewer Pump/
Lift Station
Present 30 600 0
2050 120 500# 1
2100+ 120–130 1,100–1,400 2–3
*Flooding for hydraulic structures is defined as inundation depths >= 1ft. **Flooding for manholes is defined as inundation depths < 0.1ft #Reduction in flooding from present to 2050 is likely due to ponding in the model, in isolated areas with depths less than four inches (<0.3ft). +Range for 2100 represents the lower and upper bounds of anticipated SLR (3.1ft to 6.6ft).

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Present-day (2025)
Under a 100-year storm surge event, the following impacts were identified through 2050:
30mi of sewer mains: These are critical for wastewater transport and are at risk of flooding, which could lead to service disruptions and potential contamination.
600 sewer manholes: Vulnerable to inundation, which can cause blockages and overflow. These include 20 abandoned sewer manholes.

Mid-century (2050)
Assets at stake under SLR include:
1mi of active sewer lines

2.2mi of abandoned sewer lines
130 sewer manholes
7 abandoned sewer manholes
1 sewer pump/lift station
Temporary loss of assets over storm scenarios include:
120mi of flooded mains
500 flooded manholes
1 sewer pump/lift station
End-of-century (2100)
Assets at stake under SLR include:
11-17mi of active sewer lines: Significant increase in risk of flooding and service disruptions. 650 to 1,000 sewer manholes, and 10 abandoned sewer manholes: Consistent potential overflow points. 2 sewer pump/lift stations
Temporary loss of assets over storm scenarios include:
120mi to 130mi of flooded mains
1,100 to 1,400 flooded manholes
2 to 3 sewer pump/lift stations
These updates reflect the severity and extent of sewer system flooding under different scenarios, highlighting the increasing risks and potential impacts over time.

3.3.5 Power System
There are three electrical substations and 45mi of transmission lines included in the study area for this assessment. The number of power system assets exposed to SLR is tallied in Table 22. Power system assets located in the tidal zone are exposed to quasi-permanent flooding, and these assets are considered a total loss.

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Table 22 Extent of flooded power system by type under quasi-permanent inundation Type
Mid-century
(2050)
End-of-century
(2100)

0.8ft SLR 3.1ft SLR 4.9ft SLR 6.6ft SLR
Electrical substations (count) 0 1 1 1
Transmission lines (mi) 4 20 30 35
Total Loss ($ million USD) $20 $120 $160 $180
Power transmission lines may be elevated out of inundated areas, but their accessibility may be limited. Notably, some transmission lines are currently located in the San Francisco Bay. The results for the coastal storm scenario are presented in Table 23.

Table 23 Severity of power system flooding under storm scenarios Time Horizon
Miles of Flooded
Transmission
Line
Slight Flooding
(%)
Minor Flooding
(%)
Major Flooding
(%)
Fully Flooded
(%)
Present 25 24% 28% 14% 34%
Mid-century 30 9% 5% 7% 79%
End-of-century* (2100) 35-40 4% (3.1ft SLR)
2% (6.6ft SLR)
5% (3.1ft SLR)
4% (6.6ft SLR)
10% (3.1ft SLR)
4% (6.6ft SLR)
81% (3.1ft SLR)
90% (6.6ft SLR)
*Range for 2100 represents the lower and upper bounds of anticipated SLR (3.1ft to 6.6ft).

Present-day (2025)
Under a 100-year storm surge event, the following impacts were identified through 2050:
25mi of transmission lines. 10mi of these assets would experience over 1ft inundation Mid-century (2050)
Assets at stake under SLR include:
4mi of transmission lines are expected to be inundated and were considered permanently lost Temporary loss of assets over storm scenarios include:
30mi of transmission line flooding, with 25mi over 1ft inundated End-of-century (2100)
Assets at stake under SLR include:
20mi to 35mi of transmission lines: Significant increase in risk of permanent inundation. 1 electrical substation: Identified as vulnerable to permanent flooding.

Temporary loss of assets over storm scenarios include:

Transmission lines: Increase from 20mi to a range of 30mi to 35mi, indicating further expansion of the flood-prone area.

Electrical substations: Consistent vulnerability with 1 substation at risk.

These updates reflect the severity and extent of power system flooding under different scenarios, highlighting the increasing risks and potential impacts over time.

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4. Conclusions and Next Steps
The findings from the Sea Level Rise Vulnerability Assessment and Adaptation Strategy highlight the increasing vulnerability of assets within the study extent to SLR scenarios. The vulnerability and risk assessment developed for this study provides a comprehensive understanding of current and future flood risks, demonstrating that both coastal and inland storm scenarios could increasingly impact residential, commercial, and green spaces.

Limitations include the quality and resolution of input data and inherent uncertainty in model predictions.

The model results underscore the urgency of implementing adaptive measures to mitigate associated risks, particularly in vulnerable areas such as the northwest of the City, which is exposed in the present-day coastal storm scenario. Qualitative results indicate that the most vulnerable census block is in the northwest portion of Mowry OLU, with significant impacts on residential areas, especially under higher SLR scenarios. Additionally, contamination sites, wetlands, and land use areas such as parks and open spaces are highly susceptible to flooding, with potential environmental and health hazards due to rising groundwater levels and inundation.

Between now and 2050, the City faces limited but important early-stage risks from SLR, mostly affecting utilities and industrial infrastructure. The risks include: