| NSF Org: |
OAC Office of Advanced Cyberinfrastructure (OAC) |
| Recipient: |
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| Initial Amendment Date: | July 29, 2018 |
| Latest Amendment Date: | March 30, 2022 |
| Award Number: | 1761887 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Martin Halbert
OAC Office of Advanced Cyberinfrastructure (OAC) CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | August 1, 2018 |
| End Date: | July 31, 2022 (Estimated) |
| Total Intended Award Amount: | $599,999.00 |
| Total Awarded Amount to Date: | $599,999.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
105 JESSUP HALL IOWA CITY IA US 52242-1316 (319)335-2123 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
2 Gilmore Hall Iowa City IA US 52242-1320 |
| 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): | BD Spokes -Big Data Regional I |
| 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
This project will develop a cyberinfrastructure framework to facilitate research on the efficient management of agricultural practices and their impact on water resources in the Upper Mississippi River Basin (UMRB). Large-scale data acquisition, integration, analysis, and visualization using data-enabled information technologies will accelerate the dissemination of knowledge, experience, and shared resources (e.g., technology, equipment, and people) among communities and partners. The key element of the project is a new cyber platform, the Upper Mississippi Information System (UMIS), which will provide water quality data within a rich spatio-temporal hydrologic context. The UMIS directly addresses three of the Grand Challenges for Engineering identified by the National Academy of Engineering: i) provide access to clean drinking water; ii) manage the nitrogen cycle; and iii) engineer the tools of scientific discovery. The UMIS will immediately begin facilitating data access, integration, and scientific discovery for water quality challenges in the UMRB.
UMIS will offer internet-based open access to water quality information in its meteorological, hydrological, and geographical context, providing almost endless potential benefits for stakeholders. For example, the experimental design of the UMIS will enable researchers to study spatial scaling, efficiency of various land use and agricultural practices to improve water quality, and the impact of climate change on land management and water quality. Decision-makers, producers, and extension staff will be able to assess the relative efficacy of local (e.g., best management practices) versus system-level (e.g., state programs) solutions designed to reduce pollution, optimize the use of resources, and evaluate tradeoffs among competing objectives. For all stakeholders, the UMIS will support partnerships and collaborations, increase dissemination of information about a critical natural resource to empower stakeholders at all levels, and set new standards in the communication of scientific data.
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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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This project presents an integrated big data cyberinfrastructure (CI) to support large-scale water-quality data integration, analyses, and visualization in the Upper Mississippi River Basin (UMRB) in real time using data-enabled information technologies. Seamless integration of existing real-time and ad-hoc water quality data streams with continuous modeling in the context of relevant data resources is a major challenge in the big data domain. The project addresses the Grand Challenges issued by the National Academy of Engineering by: 1) illuminating clean drinking water disparities; 2) focusing on the role of nitrogen in water quality issues; and 3) providing ways for laypeople and experts to create knowledge about water quality issues.
Project partners include researchers at the University of Iowa (IIHR - Hydroscience & Engineering), the University of Illinois at Urbana-Champaign (Great Lakes to Gulf Virtual Observatory - GLTG, National Center for Supercomputing Applications - NCSA), Iowa State University, and Lewis and Clark Community College (National Great Rivers Research and Education Center).
Specific impacts of UMIS on potential users and stakeholders can be characterized as immediate and long-term. The immediate impacts include facilitation of a centralized platform for data access, integration, and scientific discovery for water-quality challenges in the UMRB. The long-term implications for this project are the broader scientific community?s potential adoption of data-enabled CI tools and services through the Midwest Big Data Hub to expand its reach to the UMRB and ultimately to the entire Mississippi River and the nation.
The platform is called the Upper Mississippi Information System (UMIS) and provides data (over 1.5 billion records) and real-time model (i.e., daily SWAT runs) results for 8 states in the Upper Mississippi River Basin (UMRB), including parts of Illinois, Indiana, Iowa, Minnesota, Missouri, North Dakota, South Dakota, and Wisconsin. The UMRB has over 20 million residents, or about 6% of all US citizens. Data from all of these states is available in UMIS for exploration and analysis in map form or through statistical plots. To access and view data, users only need basic computer skills.
As part of the UMIS framework, a comprehensive web-based cyberinfrastructure is designed with an emphasis on efficient data consumption, high-dimensional spatiotemporal water quality-related data consumption, and effective resource utilization. Intuitive user interaction and visualizations have been developed to provide a uniform experience to access and analyze a wide variety of water quality data, in terms of content, format, frequency, and purpose, on the web and on demand. Such capabilities are served via a map-oriented interface for interactive raster, polygon, and point data with geospatial filtering as well as dynamic plotting for comparative sensor exploration for multivariate temporal analysis. The UMIS platform also has information layers in raster format that help show the spatial and temporal relationships and correlations.
Since anyone connected to the internet will have access to water-quality information within meteorological and hydrological contexts, the potential broader impacts of this project on different stakeholders are boundless. The integrated design of UMIS enables researchers to study, for example, spatial scaling, the efficiency of various land use and agricultural practices to improve water quality, and the impact of climate change on land management practices and water quality. Decisionmakers, producers, and extension staff can assess the relative efficacy of local (e.g., best management practices) versus system-level (e.g., state strategies) solutions to reduce pollution, optimize the use of resources, establish tradeoffs among competing objectives, and assess the effectiveness of states' nutrient reduction strategies. For all stakeholders, UMIS will drive partnerships and collaborations, increase the dissemination of information about a critical natural resource to empower stakeholders at all levels, and set new standards for the communication of scientific data.
The UMIS will allow the development of new cross-domain collaborations while also strengthening existing partnerships related to water-quality big data among researchers at the University of Iowa, University of Illinois, the National Great Rivers Research and Education Center, Iowa State University, and many other participating institutions. We plan to keep working with our partners and keeping up the platform to help research and educational activities in the UMRB about water quality.
Last Modified: 11/29/2022
Modified by: Ibrahim Demir
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