River deltas are complex landforms which transport water and sediment from continents to oceans. They are extremely sensitive to environmental changes, e.g. sea-level rise, sediment and water supply, and therefore communities that rely on the resources of these dynamic and sensitive landscapes are at risk. The past dynamics of deltas are partially preserved in their sedimentary records, and these records represent valuable templates for testing predictive models of future change. To understand these systems, the researchers propose to create a predictive framework that enables them to relate the arrangement of channels and floodplains on the surface of deltas to the record of past dynamics preserved in their sediments. Much like river deltas, the earth science field also needs to be responsive to changing demographics in the scientific community through strategic distribution of resources and opportunities. This project provides support for underrepresented minority lead scientists, early career investigators, and inclusive research experiences for students, allowing the researchers to leverage the knowledge and experience that comes from a diverse research team. The framework of support proposed here could be a valuable template for creating a more diverse and inclusive scientific community, particularly in earth science, which continues to have the lowest (9%) rates of ethnic and racial diversity of all other STEM fields.
Records of past environmental states contained within the sedimentary deposits of river deltas, while amongst the most complete on Earth, are extremely challenging to decipher. The premise of the proposed research is that the sedimentary record of deltaic systems is mediated by a combination of their autogenic dynamics (e.g. avulsion and lateral migration rates) and allogenic forcings (e.g. climate, tectonics, sea level). The researchers propose to develop an integrated statistical framework to characterize deltaic transport systems and their sedimentary records across a range of spatial and temporal scales. To construct this framework, they will iterate between data from physical and numerical experiments, and field data-sets, providing quantitative constraints on scale-dependent dynamics and their contribution to filtering signals stored in the subsurface sedimentary record. This information is crucial for (1) developing and constraining delta evolution models, (2) inferring paleo-environmental conditions from the stratigraphic record, and (3) aiding the management of natural resources (e.g. coastal aquifers, hydrocarbon reservoirs, etc.) by improving predictions of subsurface reservoir properties over a range of scales. This project is jointly funded by the Geomorphology and Land-Use Dynamics Program and the Established Program to Stimulate Competitive Research (EPSCoR).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|Effective start/end date||15/07/19 → 30/06/23|
- National Science Foundation: $135,322.00