CLaSH Small Grant Program 2025-2026
Program Overview
The CLaSH Small Grant Program is open to the wider community and provides flexible, seed-level funding to catalyze bold ideas, interdisciplinary collaborations, and measurable impact on hazard cascade science.
- Support creative, high-risk/high-reward projects that broaden participation by bringing new investigators and expertise into the Center
- Advance understanding of interacting land-surface hazards, complementing the scope of current Center activities
- Foster cross-cutting science that connects observations, modeling, and societal relevance
- Open the door to new approaches to land surface hazard cascade research through pilot studies, new field sites, and novel modeling frameworks
- Contribute to the Center's goals of education, workforce development, and community engagement
Priority Areas
The 2025–2026 Request for Proposals seeks integrative studies that couple new data acquisition, process-based modeling, or AI-driven analysis to predict how multi-hazard cascades evolve. Proposals that advance hazard cascade science, community engagement, and workforce development are strongly encouraged.
1. Site-Specific Investigations at CLaSH's Hazard Observatories
Located in Alaska, Appalachia, Puerto Rico, and Southern California.
- Apply geophysical, geochemical, or remote-sensing approaches to investigate site-specific hazard processes
- Integrate new tools and datasets across CLaSH Hazard Observatories
- Extend ongoing or post-event data collection in fire, landslide, or flood-impacted sites
2. Modeling of Weather-Related Forcing and Phenomena
Relevant to CLaSH's current Hazard Observatories.
- Quantify how storms, rainfall, winds, or wildfire alter hazard frequency and magnitude
- Investigate novel couplings of meteorological, hydrological, geomorphic, and hazard models
- Produce datasets and frameworks for scalable hazard prediction
3. Applications of Machine Learning and Development of AI-Ready Datasets
To increase understanding of land surface hazards.
- Build FAIR-compliant, AI-ready datasets to enable model training, validation, and cross-hazard benchmarking
- Develop novel AI algorithms for event detection, forecasting, and early warning of geomorphic hazards
- Apply and optimize machine learning models to simulate cascading hazard sequences linking landslides, erosion, and sediment transport dynamics
Funding Scope
Anticipated Awards: 5 – 9 annually
Award Size: $20,000 - $40,000, including indirect costs
Indirect Costs: In accordance with NSF and institutional federally negotiated rates
Project Duration: Up to 12 months
Projected Start Date: May 1, 2026
Final Report Due: 30 days after project end date
Key Dates
- RFP ReleasedDecember 8, 2025
- Proposal DeadlineFebruary 4, 2026 (11:59 PM PST)
- Award NotificationsApril 6, 2026
- Project StartMay 1, 2026
- Project EndApril 30, 2027
- Final Report DueMay 30, 2027
Contact
Program Contact: contact@geoclash.org