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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Ohio State University |
| Country | United States |
| Start Date | Sep 01, 2021 |
| End Date | Sep 30, 2025 |
| Duration | 1,490 days |
| Number of Grantees | 2 |
| Roles | Principal Investigator; Co-Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2117433 |
This project develops improved methods for classifying drought severity in ways that improve comparative understandings of the effects of droughts in different regions. A primary objective of the research is to identify and quantify sources of uncertainty that can affect the accuracy of drought classification. This information is beneficial for determining how the use of different datasets and indices can influence the accuracy of drought assessment.
The results of this project have the potential to help to inform drought monitoring and mitigation activities that are undertaken by local, state, and federal agencies. Aided by a steering committee of drought experts from diverse agencies, the study facilitates improved drought monitoring. In addition, the project provides training opportunities for undergraduate students through summer research internships and courses.
This project develops refined methods for assessing drought severity in diverse regional settings. The researchers have multiple objectives. First, using archival data, the researchers develop objective drought thresholds that can be used for accurate assessments across temporal, seasonal, and spatial contexts.
These thresholds rely on multiple sources of data, including precipitation, temperature, soil moisture, stream flow, and groundwater. Second, using related approaches and data, the researchers quantify the uncertainty and bias in prevailing methods for characterizing drought frequency and severity. Estimating these biases allows for improved projections of future droughts.
Third, the researchers compare their thresholds to historical data on observed impacts of droughts, which provides insight into the validity and utility of the derived thresholds. Overall, the results of this study contribute to efforts to characterize and assess the effects of past droughts while providing enhanced forecasting of future drought severity and impacts.
The methods developed in this study are potentially transferable to global analyses of drought severity and trends.
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.
Ohio State University
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