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Geology topics

Michelle Hummel

Publications and source records attributed to Michelle Hummel.

2 recordsLinked to original sources

Interactions of estuarine shoreline infrastructure with multiscale sea level variability

Sea level rise increases the risk of storms and other short‐term water‐rise events, because it sets a higher water level such that coastal surges become more likely to overtop protections and cause floods. To protect coastal communities, it is necessary to understand the interaction among multiday and tidal sea level variabilities, coastal infrastructure, and sea level rise. We performed a series of numerical simulations for San Francisco Bay to examine two shoreline scenarios and a series of short‐term and long‐term sea level variations. The two shoreline configurations include the existing topography and a coherent full‐bay containment that follows the existing land boundary with an impermeable wall. The sea level variability consists of a half‐meter perturbation, with duration ranging from 2 days to permanent (i.e., sea level rise). The extent of coastal flooding was found to increase with the duration of the high‐water‐level event. The nonlinear interaction between these intermediate scale events and astronomical tidal forcing only contributes ∼1% of the tidal heights; at the same time, the tides are found to be a dominant factor in establishing the evolution and diffusion of multiday high water events. Establishing containment at existing shorelines can change the tidal height spectrum up to 5%, and the impact of this shoreline structure appears stronger in the low‐frequency range. To interpret the spatial and temporal variability at a wide range of frequencies, Optimal Dynamic Mode Decomposition is introduced to analyze the coastal processes and an inverse method is applied to determine the coefficients of a 1‐D diffusion wave model that quantify the impact of bottom roughness, tidal basin geometry, and shoreline configuration on the high water events

Journal of Geophysical Research: Oceans

Clusters of community exposure to coastal flooding hazards based on storm and sea level rise scenarios—implications for adaptation networks in the San Francisco Bay region

Sea level is projected to rise over the coming decades, further increasing the extent of flooding hazards in coastal communities. Efforts to address potential impacts from climate-driven coastal hazards have called for collaboration among communities to strengthen the application of best practices. However, communities currently lack practical tools for identifying potential partner communities based on similar hazard exposure characteristics. This study uses statistical cluster analysis to identify similarities in community exposure to flooding hazards for a suite of sea level rise and storm scenarios. We demonstrate this approach using 63 jurisdictions in the San Francisco Bay region of California (USA) and compare 21 distinct exposure variables related to residents, employees, and structures for six hazard scenario combinations of sea level rise and storms. Results indicate that cluster analysis can provide an effective mechanism for identifying community groupings. Cluster compositions changed based on the selected societal variables and sea level rise scenarios, suggesting that a community could participate in multiple networks to target specific issues or policy interventions. The proposed clustering approach can serve as a data-driven foundation to help communities identify other communities with similar adaptation challenges and to enhance regional efforts that aim to facilitate adaptation planning and investment prioritization.

California