Long-term coastal evolution is difficult to understand let alone predict, owing to the complexity of the underlying physical processes, the sparsity of observations, and the deficiencies of models. Nevertheless, reliable, quantitative predictions of coastal change are increasingly sought because beaches represent a first line of defense against extreme coastal storms. Recent advances in remote sensing show promise to transform the field of coastal science from a ‘data-poor’ field to a ‘data-rich’ field with the proliferation of remotely-sensed coastal change data. Notable advances include (1) the application of airborne Structure-from-Motion photogrammetry to observe coastal change (Warrick et al., 2016) as an affordable alternative to LIDAR and (2) satellite-derived shoreline observations (Luijendijk et al., 2018), with global-scale, repeat coverage from 1-14 days and spatial accuracy on the order of 5-15 meters.
Advancing and synthesizing large-scale, remotely-sensed coastal observations with state-of-the-art, data-assimilated models of coastal change (e.g., Vitousek et al., 2017) is the primary goal of the proposed Research Opportunity (RO). This RO seeks proposals that address the research challenges on the path towards the realization of an operational, national-scale, data-integrated coastal change model system that intelligently synthesizes observations and simulations. Proposals are expected to make fundamental research contributions in the areas of remote sensing and/or numerical modeling of coastal change. Strong candidates are expected to possess demonstrated knowledge of coastal systems via the application of remote sensing technologies and/or numerical models to research problems.
Possible remote sensing topics of research include (but are not limited to):
- Advancing algorithms for satellite-derived shoreline extraction
- Evaluating and improving the accuracy of satellite-derived shoreline positions
- Integrating machine learning / deep learning with remotely sensed data
- Satellite-based Structure-from-Motion
- Crowd-sourced shoreline data
- Sensor development for remote-sensing platforms (e.g., drones, aircraft, satellites)
Possible modeling topics of research include (but are not limited to):
- Programmatically integrating data-assimilated coastal change models with remote sensing
- Improving interactions of shoreline change models with cliffs, dunes, barrier islands, etc.
- Applying advanced methods for data assimilation (Kalman filter variants or 4D-Var)
- Novel formulations for coastal change processes and models
- Uncertainty quantification due to climate variability (e.g., waves, sea-level rise, fluvial processes) and management scenarios (e.g., armoring, nourishment, dam removal)
- Coupling of 1-D hybrid shoreline change models with traditional 2D/3D physics-based models
Interested applicants are strongly encouraged to contact the Research Advisor(s) early in the application process to discuss project ideas.
Proposed Duty Station: Santa Cruz, CA
Areas of PhD: Oceanography, civil & environmental engineering, coastal engineering, geology, geography, applied mathematics, atmospheric science, computer science, data science, or related fields (candidates holding a Ph.D. in other disciplines, but with extensive knowledge and skills relevant to the Research Opportunity may be considered).
Qualifications: Applicants must meet the qualifications for: Research Geologist, Research Oceanographer
(This type of research is performed by those who have backgrounds for the occupations stated above. However, other titles may be applicable depending on the applicant's background, education, and research proposal. The final classification of the position will be made by the Human Resources specialist.)
Human Resources Office Contact: Audrey Tsujita, 916-278-9395, atsujita@usgs.gov
