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Minimize RSR Award Detail

Research Spending & Results

Award Detail

Awardee:UNIVERSITY OF TENNESSEE
Doing Business As Name:University of Tennessee Knoxville
PD/PI:
  • Michela Taufer
  • (302) 690-7845
  • taufer@utk.edu
Award Date:05/05/2021
Estimated Total Award Amount: $ 349,998
Funds Obligated to Date: $ 349,998
  • FY 2021=$349,998
Start Date:06/01/2021
End Date:05/31/2024
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:Collaborative Research: Elements: SENSORY: Software Ecosystem for kNowledge diScOveRY - a data-driven framework for soil moisture applications
Federal Award ID Number:2103845
DUNS ID:003387891
Parent DUNS ID:003387891
Program:Software Institutes
Program Officer:
  • Amy Walton
  • (703) 292-4538
  • awalton@nsf.gov

Awardee Location

Street:1331 CIR PARK DR
City:Knoxville
State:TN
ZIP:37916-3801
County:Knoxville
Country:US
Awardee Cong. District:02

Primary Place of Performance

Organization Name:The University of Tennessee
Street:401 Min H. Kao Bldg, 1520 Middle
City:Knoxville,
State:TN
ZIP:37996-0003
County:Knoxville
Country:US
Cong. District:02

Abstract at Time of Award

Tools for gathering soil moisture data (such as in situ soil sensors and satellites) have differing capabilities. In situ soil moisture data has fine-grained spatial and high temporal resolution, but is only available in limited areas; satellite data is available globally, but is more coarse in resolution. Existing software tools for studying the dynamic characteristics of soil moisture data are limited in their ability to model soil moisture at multiple spatial and temporal scales, and these limitations hamper scientists’ ability to address urgent practical problems such as wildfire management and food and water security. Accurate gathering and effective modeling of soil moisture data are essential to address pressing environmental challenges. This interdisciplinary project designs, builds, and shares a data-driven software ecosystem for soil moisture applications. This software ecosystem models and predicts soil moisture at scales suitable to support studies in forestry, precision agriculture, and earth surface hydrology. This project connects multi-disciplinary advances across the scientific community (such as generating datasets at scale and supporting cloud-based cyberinfrastructures) to develop a data-driven software ecosystem for analyzing, visualizing, and extracting knowledge from the growing data collections (from fine-grained, in situ soil sensor information to coarse-grained, global satellite measurements) and releasing this knowledge to applications in environmental sciences. Specifically, this project (a) develops scalable methodologies to integrate and analyze soil moisture data at multiple spatial and temporal scales; (b) implements a data-driven software ecosystem to access complex information and provide basic and applied knowledge to inform researchers and stakeholders interested in soil moisture dynamics (scientists, educators, government agencies, policy makers); and (c) builds cyberinfrastructures to support discovery on cloud platforms, lowering resource barriers to improve accessibility and interoperability. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Hydrologic Sciences Program, the Division of Earth Sciences, and the Division of Integrative and Collaborative Education and Research within the NSF Directorate for Geosciences. 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.

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