The causes and consequences of high uncertainty in global sea level rise : from subglacial dynamics to vulnerabilities within our urban systems
Abstract/Contents
- Abstract
- Global sea level rise is increasing the frequency and spatial extent of coastal flooding. Population growth and urbanization are concentrating flood risk. Coastal communities around the world are developing adaptation plans, but the uncertainties associated with sea level rise present challenges. Part one of this thesis highlights one of the major causes of uncertainty in sea level rise, namely, the subglacial dynamics that facilitate rapid ice loss in ice sheets. Part two of the thesis quantifies the cascading consequences of the flood-related disruption of urban transportation systems, thus providing an actionable framework for adaptation planning in light of the uncertainty in sea level rise. Rapid ice loss in West Antarctica is sensitively affected by meltwater drainage at the bottom boundary of the ice sheet, where ice meets a soft, deformable sediment bed. First, we show that a thin meltwater film between the ice and the sediment bed grows unstably into a spatially heterogenous drainage system by eroding the bed. We model the film with the Navier Stokes equations and the Exner equation and use a spectral Galerkin method to solve the linearized system. Second, using a discrete element model, we show that the shearing of the sediment bed by the motion of the ice elevates porosities and increases meltwater flux at the bed. Improving our understanding of the drainage system reduces the uncertainty in sea level rise projections for the coming decades. A rising sea level can severely impact coastal communities by disrupting urban systems such as transportation. We quantify the impacts of flood-related traffic disruption in the San Francisco Bay Area over the 2020--2040 period by integrating an incremental traffic assignment model with coastal flood maps. Using graph-theoretic tools, we show that communities with sparse road networks are highly vulnerable to flood-related travel time delays, irrespective of their proximity to the flooded areas. Furthermore, by developing statistical models of historical car accident data, we show how the flooding of major traffic corridors such as the US-101 can substantially alter the spatial distribution of car accidents by rerouting traffic onto local streets passing through urban and suburban communities.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2020; ©2020 |
| Publication date | 2020; 2020 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Kasmalkar, Indraneel Gireendra |
|---|---|
| Degree supervisor | Suckale, Jenny |
| Thesis advisor | Suckale, Jenny |
| Thesis advisor | Baker, Jack W |
| Thesis advisor | Dunham, Eric |
| Degree committee member | Baker, Jack W |
| Degree committee member | Dunham, Eric |
| Associated with | Stanford University, Institute for Computational and Mathematical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Indraneel Kasmalkar. |
|---|---|
| Note | Submitted to the Institute for Computational and Mathematical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2020. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2020 by Indraneel Gireendra Kasmalkar
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...