Project Grant SVM70024GR0013

This $550,000 National Science Foundation Project Grant under the Geosciences program (CFDA 47.050) will support the development of data-driven physics-informed machine learning models to predict flood-induced flow and sediment dynamics. Over a four-year period ending June 2027, the grantee will improve existing high-fidelity numerical modeling tools and apply them to evaluate flood impacts on infrastructure stability in large waterways. They will then use simulation results to inform and...

The U.S. Geological Survey (USGS) awarded a $338,378 Cooperative Agreement to the Virginia Institute of Marine Science (VIMS) under the USGS Research and Data Collection program (CFDA 15.808). The funding will support a 3-phase project to expand the implementation of a machine learning algorithm approach for near-real time river stage detection using oblique imagery from web cameras. Key objectives include integrating the algorithm with 10 existing USGS web cameras, evaluating the accuracy of...

This Project Grant award of $199,316.00 from the National Science Foundation's (NSF) Geosciences Program (CFDA 47.050) aims to advance the understanding of how extreme weather events, such as heavy rainfall and flooding, may change in response to future climate scenarios. The project, titled "EMBRACE-AGS-SEED: Harnessing the Power of Machine Learning to Generate Ensembles of Regional Climate Projections," will evaluate whether artificial intelligence and machine learning can provide...

The U.S. Geological Survey (USGS) awarded a $300,024 Cooperative Agreement grant under the USGS Research and Data Collection program (CFDA 15.808) to The Pennsylvania State University (Penn State) for the project "Harnessing Physics-Informed Machine Learning to Improve Image-Based Streamflow Measurements". The 3-year project aims to leverage machine learning and artificial intelligence to enhance two image-based flow measurement techniques - space-time image velocimetry (STIV) and...

This Project Grant award, funded by the National Science Foundation (NSF) under the Geosciences program (CFDA 47.050), supports research to develop new technologies that integrate advanced artificial intelligence (AI) and machine learning (ML) with established geoscientific domain knowledge to enhance understanding of landslide causality. The $674,291 award, effective October 1, 2024 through September 30, 2027, will enable the Research Foundation of the City University of New York (RFCUNY) to:...

This $138,559 National Science Foundation Project Grant supports the development of machine learning methods to automatically detect archaeological features of varying sizes as well as anthropogenic landscape modifications in light detection and ranging (LIDAR) data from tropical regions. Awarded on August 1, 2022 to the University of Nebraska with a completion date of July 31, 2024, this grant falls under the NSF's Social, Behavioral, and Economic Sciences program (CFDA 47.075). An...

The University of Illinois was awarded a $249,987 Project Grant from the National Science Foundation Division of Earth Sciences. The grant supports the collaborative research project "Informing River Corridor Transport Modeling by Harnessing Community Data and Physics-Aware Machine Learning." The goal of the research is to strengthen understanding of integrated Earth systems through basic research in atmospheric, Earth, and ocean sciences. Specifically, this Project Grant will fund the...

This National Science Foundation Project Grant of $547,101 will fund research at The University of Iowa from January 2023 through December 2025 to develop an artificial intelligence-powered control framework for optimally regulating streamflow during flood mitigation efforts. The research aims to advance methods for combining physics-informed and recurrent neural networks to predict dynamic system evolution and quantify uncertainty, as well as construct learning-based control synthesis...

This $1,324,092 project grant, awarded by the National Science Foundation's Geosciences program (CFDA 47.050) to Florida International University (FIU), establishes the South Florida Coastal Environmental Data and Modeling Center. The center will focus on developing AI/ML techniques for understanding and predicting key processes affecting coastal environments in Southeast Florida, with an emphasis on addressing challenges like flood damage, sea-level rise, urban flooding, water quality, and...

This five-year, $460,399 project grant from the National Science Foundation's Geosciences program (CFDA 47.050) will fund research and education initiatives focused on improving flood hazard assessments. The principal investigator at Northeastern University will establish a long-term floodplain sedimentation observatory and develop hydraulic models to better understand landscape controls on alluvial sedimentation patterns. This work will help constrain flood hazard estimates through...