NSF AI Disclosure Required
NSF requires disclosure of AI tool usage in proposal preparation. Ensure you disclose the use of FindGrants' AI drafting in your application.
Center Operations: Center for Land Surface Hazards (CLaSH)
NSF
About This Grant
The Center for Land Surface Hazards (CLaSH) has the mission to advance understanding of land surface hazards and to change how people understand and prepare for disasters. Sudden movement of large amounts of rock and soil across the land surface cause losses in every U.S. state and territory, resulting in damage to places where people live and work that make these natural hazards among the most costly in the U.S.. Landslides, debris flows, river erosion, and flash flooding are examples of events that scientists expect to happen with more frequency—possibly three times as often—in the next 50 years. CLaSH will improve understanding and forecasting of these hazards through supporting a team of scientists from different areas who study how hazards start and spread, focusing particularly on how different natural events work together to make disasters worse and last longer. The Center will create a new scientific approach to understand today’s land surface hazards and forecast future ones, with the goal of helping communities to recover faster and lower the costs of these types of disasters. CLaSH partners with government groups, local community organizations, and the public to share information and tools to help people prepare for hazard events and learn skills for future jobs in safety and disaster response. The Center’s education program will create new ways for teachers and students to learn about land surface hazards using the latest technology, hands-on training, and guidance for working with communities affected by these hazards. This award contributes to the U.S. National Science Foundation (NSF) role in the National Landslide Preparedness Act (P.L. 116-323). While most research focuses on individual land surface hazards, these processes often interact with each other, producing cascading hazards that are more severe or last longer—sometimes persisting for years or decades. Forecasting the impact of cascading land surface hazards requires integrating and modeling geomorphic processes to predict interactions that amplify hazardous conditions, such as landslides that dam rivers and sediment aggradation that promotes flooding. Given the lack of critical knowledge of how processes interact along the hazard cascade, it is not yet possible to reliably forecast when cascades will emerge, or how far-reaching and long-lasting their impacts will be. CLaSH aims to (1) develop a novel scientific framework that characterizes land surface hazards today and anticipates how they will change in the future, (2) train a future workforce capable of addressing the impacts of these hazards, and (3) broaden participation in geosciences. The Center’s interdisciplinary team— spanning geomorphology, geotechnical engineering, and atmospheric science—will build an observational network and modeling collaboratory that leverages partners from existing NSF centers and facilities, and government agencies charged with frontline response to national natural disaster events. CLaSH research will generate datasets and analysis tools that capture the full chain of hazard interactions, from landslide initiation through far-reaching downstream effects. This framework will support nationwide assessment of cascading land surface hazards by combining new Earth surface datasets (e.g., national lidar data coverage) with process-based and data-driven models. CLaSH will serve as a hub for advancing and sharing knowledge about land surface hazards across research disciplines and with the public. Its work will enable more accurate hazard forecasts nationwide, helping communities and responders improve preparedness and resilience, while reducing the economic losses associated with these events. 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.
Focus Areas
Eligibility
How to Apply
Up to $6M
2030-09-30
One-time $749 fee · Includes AI drafting + templates + PDF export
AI Requirement Analysis
Detailed requirements not yet analyzed
Have the NOFO? Paste it below for AI-powered requirement analysis.