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Active STANDARD GRANT National Science Foundation (US)

EAGER: CHIRRP: Community-driven Tools for Monitoring Flash Droughts to Bolster Resilience in the Agricultural Sector

$3M USD

Funder National Science Foundation (US)
Recipient Organization Texas A&M Engineering Experiment Station
Country United States
Start Date Sep 01, 2024
End Date Aug 31, 2026
Duration 729 days
Number of Grantees 2
Roles Principal Investigator; Co-Principal Investigator
Data Source National Science Foundation (US)
Grant ID 2435046
Grant Description

Flash drought events, characterized by rapid intensification over a short period, lead to significant socio-economic impacts. These episodes are triggered by complex interactions among multiple factors, including climate and land processes. Recent notable flash droughts have resulted in considerable interest among researchers, state and federal agencies, and various stakeholders.

This study aims to engage community members—such as farmers, industry representatives, and county extension agents—who have firsthand experience with the direct impact of flash droughts on agricultural crop yields. Collaboration among researchers, academics, and community leaders is central to this study, which seeks to develop science-based solutions to improve resilience and forecasting, thereby reducing the socio-economic losses faced by farmers, ranchers, and stakeholders due to flash droughts.

The outcomes will advance flash drought monitoring and prediction tools, enhancing crop resilience to rapid climate fluctuations. By engaging a wider network of producers, the project aims to deploy effective risk reduction strategies and enhance crop resilience, especially for marginal farmers. These efforts benefit agriculture and food industries by managing the potential impact of flash droughts and fostering regional economic growth.

The project advances the monitoring and forecasting of flash droughts and provides an opportunity to mitigate their impacts by developing a robust flash drought indicator for better monitoring and prediction across various agricultural crops. It quantifies the drivers that trigger flash droughts using a cascade modeling framework to improve seasonal to sub-seasonal predictions.

Additionally, it fosters equitable community partnerships to quantify flash drought risks and create actionable solutions to enhance the resilience of the agriculture sector. The results are used to create agricultural extension materials, educational content, and training resources for farmers, aiming to deepen scientific understanding of flash drought risks within the agricultural sector.

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.

All Grantees

Texas A&M Engineering Experiment Station

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