Information on river shape, bed morphology and sediment load are critical to help inform research and management issues related to river channels. However, such information is not easily accessible or available in the public domain. This project will create a web platform, entitled RiverMorph, to aggregate, store, share, and analyze river-related scientific data. RiverMorph will also support management of current and future issues related to the nation’s water resources. The data and tools developed for RiverMorph will create digital representations of three-dimensional river morphological structures of most U.S. rivers, which can support fundamental research and practical needs related to stream rehabilitation, infrastructure design, and food risk mitigation. This project will demonstrate how the RiverMorph platform can improve river flow forecasts and produce accurate flood inundation maps that subsequently can help save lives and expense related to flood damages.
The RiverMorph web platform will be designed and developed through collaborations with an extended team of community partners, including state and federal agencies, who are responsible for managing U.S. water resources. RiverMorph will be: 1) open, integrated and platform independent; 2) flexible and adaptable to new types of data and operational capabilities; 3) easy to use in order to encourage contributions from a wide variety of stakeholders; 4) responsive to the needs of multiple end users with diverse technical backgrounds; and 5) interoperable and scalable for sustainability beyond the project duration. The prototype RiverMorph resource will be developed by carefully assessing the availability and accessibility of river data and the needs of potential stakeholders. The usability and adaptability of RiverMorph will be demonstrated through specific science test cases that will address the following research questions: 1) How does channel morphology change over decadal time scales, and how can the underlying processes be modeled to assist with water resources engineering and management decisions? 2) How can river geometry be best described across spatial scales ranging from low order single streams to large stream networks for accurately simulating river hydrodynamics and flooding? 3) How can data-driven approaches improve the understanding of streamwise and river-floodplain-watershed connectivity for supporting modeling approaches over large spatio-temporal scales? Implementation and adoption of RiverMorph will be facilitated by engaging with stakeholders and the broader earth sciences community over the course of the project.
This project is jointly funded by the Geoinformatics, the Hydrologic Sciences, and the Geomorphology and Land Use Dynamics programs in the Division of Earth Sciences.
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.
