| NSF Org: |
OAC Office of Advanced Cyberinfrastructure (OAC) |
| Recipient: |
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| Initial Amendment Date: | May 5, 2021 |
| Latest Amendment Date: | May 5, 2021 |
| Award Number: | 2103845 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Varun Chandola
OAC Office of Advanced Cyberinfrastructure (OAC) CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | June 1, 2021 |
| End Date: | May 31, 2026 (Estimated) |
| Total Intended Award Amount: | $349,998.00 |
| Total Awarded Amount to Date: | $349,998.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
201 ANDY HOLT TOWER KNOXVILLE TN US 37996-0001 (865)974-3466 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
401 Min H. Kao Bldg, 1520 Middle Knoxville, TN US 37996-0003 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
Hydrologic Sciences, XC-Crosscutting Activities Pro, Software Institutes, EarthCube |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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