Project Grant 2144332
- This $250,000 Project Grant award from the National Science Foundation's Office of International Science and Engineering (CFDA 47.079) will establish the groundwork for developing a Global Center to provide real-time water quality forecasts and decision support tools for lakes and reservoirs in the U.S. and Australia facing climate change impacts. The key products to be delivered under this 2-year award include: 1) an American-Australian community of water researchers, managers, industry, and...
- This $499,942 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports research investigating the impacts of climate change on coastal communities in an urban environment. The key products and services to be delivered under this 3-year award (August 2024 - July 2027) include: Analysis of the alignment between water infrastructure, policies, and practices with emerging climate and environmental challenges such as...
- This Project Grant award of $700,000 from the National Science Foundation's Geosciences Program (CFDA 47.050) is focused on improving computational models that describe the relationship between climate and streamflow. The project aims to address uncertainty in these models caused by the influence of human actions on the water cycle, with a specific focus on representing the impacts of dams, which control about 75% of annual runoff in the continental United States. The project will develop a...
- This Project Grant award of $4,170,230 from the National Science Foundation (NSF) under the Office of International Science and Engineering (OISE) program funds research at the University of Michigan to study the impacts of climate change on transboundary water resources in North America. The award supports the establishment of the Global Center for Climate Change Impacts on Transboundary Waters, which conducts research and develops solutions to address water crises resulting from intensifying...
- This Project Grant award of $119,770, provided by the National Science Foundation (NSF) Geosciences Program (CFDA 47.050), aims to enhance the resilience of Great Lakes coastal cities to flooding risks driven by climate change. The project will create an online "Participatory Urban Modeling and Climate Projections for Community-Driven Flooding Resilience" (PUMP-COR) decision support tool that integrates climate, hydrological, and spatial data. This tool will be developed in partnership...
- This Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) provides $199,885 to the Rochester Institute of Technology (RIT) to develop a network science-based framework for analyzing and modeling complex climate systems. The key objectives of this 2-year project are: 1) to synthesize large-scale climate records to investigate the stability of network patterns associated with climate tipping elements, with a focus on the Atlantic Basin; and 2) to develop...
- This Project Grant from the National Science Foundation Division of Earth Sciences, under the Geosciences program (CFDA 47.050), provides $675,290 to Cornell University to estimate the emergence of anthropogenic warming signals in snow water resource metrics in mountainous regions. Working in the headwaters of the Upper Colorado River Basin, the grantee will use an innovative modeling framework with a large ensemble climate model and process-based hydrological modeling to assess the...
- This Project Grant award from the National Science Foundation's Division of Information and Intelligent Systems (CFDA 47.070 - Computer and Information Science and Engineering) provides $349,993 to the University of Pittsburgh to develop new physics-guided graph network models for improved modeling of water dynamics in freshwater ecosystems. The project aims to: 1) create new graph-based architectures to model the complex nature of physical objects and dynamic interactions between physical...
- This $757,974 Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research by The Pennsylvania State University, doing business as Penn State, to develop a systems modeling framework for designing climate-resilient levee infrastructure that supports equitable, resilient, and sustainable floodplain communities. The project aims to address interactions between levee network performance, future climates, natural infrastructure, and behavioral...
- This Project Grant award from the National Science Foundation (NSF) Office of Integrative Activities under the NSF Geosciences program (CFDA 47.050) provides $145,352 to the University Enterprises, Inc. at Sacramento State University to develop a diverse hydrology workforce through an undergraduate hydrological research experience in a coastal California watershed. The project will engage sophomore and transfer students across three California State University campuses in a year-long learning...
CAREER: CAS- CLIMATE: CLIMATE ADAPTATION PATHWAYS IN ECO-HYDROLOGIC SYSTEMS WITH PHYSICS-INFORMED MACHINE LEARNING -SUSTAINABLE WATER RESOURCES PLANNING AND MANAGEMENT IN THE 21ST CENTURY REQUIRES ADAPTATION STRATEGIES THAT ARE ROBUST TO DEEP UNCERTAINTIES IN FUTURE CLIMATE AND ENVIRONMENTAL CHANGE. TO MANAGE THIS UNCERTAINTY, RECENT DECISION-MAKING FRAMEWORKS HAVE PROMOTED FLEXIBLE ADAPTATION PATHWAYS THAT RESPOND DYNAMICALLY TO THE TRAJECTORY OF CLIMATE AS IT UNFOLDS. THIS PROJECT WILL EXPLORE THE HYPOTHESIS THAT THE OPTIMAL DESIGN OF FLEXIBLE ADAPTATION PATHWAYS ? INCLUDING THE SEQUENCE, TIMING, AND PERMANENCE OF ADAPTATION ACTIONS - DEPENDS ON THE MECHANISMS OF DYNAMIC AND THERMODYNAMIC CLIMATE CHANGE INFLUENCING THE WATER SYSTEM, AND THE DEGREE OF NATURAL CLIMATE VARIABILITY AND PREDICTABILITY ACROSS TIME SCALES. TO TEST THIS HYPOTHESIS, THIS WORK WILL DEVELOP INNOVATIONS IN PHYSICS-INFORMED MACHINE LEARNING THAT WILL ENABLE PROCESS-GUIDED CLIMATE SIMULATION, HYDROLOGIC PREDICTION, AND SUB-SEASONAL-TO-SEASONAL FORECASTING THAT SUPPORT RISK-BASED ADAPTATION PLANNING. THESE APPROACHES WILL BE APPLIED IN THE LAKE ONTARIO ECO-HYDROLOGIC SYSTEM TO EXAMINE THREE FUNDAMENTAL QUESTIONS: 1) WHAT ARE THE PRIMARY PATTERNS OF DYNAMIC AND THERMODYNAMIC CLIMATE CHANGE OVER THE GREAT LAKES, AND HOW CAN THEY BE INTEGRATED INTO RISK-BASED SIMULATION FRAMEWORKS? 2) HOW DO THESE CLIMATE MECHANISMS INFLUENCE THE HYDROLOGIC AND ECOLOGICAL RESPONSE OF THE LAKE ONTARIO SYSTEM AND THE DIVERSE INTERESTS OF STAKEHOLDERS, AND HOW PREDICTABLE ARE THESE IMPACTS AT SUB-SEASONAL TO DECADAL TIMESCALES? AND 3) HOW SHOULD ADAPTATION PATHWAYS FOR LAKE LEVEL MANAGEMENT AND COASTAL RESILIENCE BE DESIGNED TO COPE WITH THESE MECHANISMS OF CLIMATE CHANGE? THESE QUESTIONS WILL BE ADDRESSED ALONGSIDE A CO-PRODUCTION MODEL OF COMMUNITY ENGAGEMENT AND KNOWLEDGE SHARING WITH GREAT LAKES COMMUNITIES, STUDENTS, AND OTHER STAKEHOLDERS. THIS WORK WILL IMPACT HYDROCLIMATIC MODELING FOR ECO-HYDROLOGIC SYSTEMS BY DEVELOPING PHYSICS-INFORMED MACHINE LEARNING TECHNIQUES FOR FEATURE IDENTIFICATION, SPATIOTEMPORAL MODELING, EMULATION, FUNCTIONAL DEPENDENCE, AND SYNTHETIC DATA GENERATION, WITH THE ABILITY TO PROPAGATE PHYSICALLY MEANINGFUL FEATURES THROUGH SEQUENTIALLY LINKED SYSTEMS WHILE ACCOUNTING FOR UNCERTAINTY. THE GOAL IS TO DEVELOP A COMPUTATIONALLY EFFICIENT AND PROBABILISTIC MODELLING FRAMEWORK FOR RISK-BASED SIMULATION AND FORECASTING NEEDED TO DEVELOP ROBUST CLIMATE ADAPTATION PATHWAYS. EXPECTED OUTCOMES INCLUDE SIX MAJOR SCIENTIFIC ADVANCEMENTS: 1) A DIAGNOSTIC UNDERSTANDING OF HISTORICAL AND PROJECTED FUTURE THERMODYNAMIC AND DYNAMIC CLIMATE PROCESSES RELEVANT TO ECO-HYDROLOGIC SYSTEMS; 2) THE DEVELOPMENT OF STOCHASTIC MODELS THAT CAN REVEAL HOW THOSE PHYSICAL PROCESSES SHAPE FUTURE CLIMATE RISK TO WATER INFRASTRUCTURE; 3) ENHANCED PREDICTABILITY OF ECO-HYDROLOGIC RESPONSE TO CLIMATE ACROSS SUB-SEASONAL TO DECADAL TIME SCALES; 4) CREDIBLE EMULATION OF SYSTEM OBJECTIVES TO SUPPORT UNCERTAINTY PROPAGATION IN ADAPTATION PLANNING; 5) ENDOGENOUS LEARNING STRATEGIES TO DETECT MECHANISMS OF CLIMATE CHANGE FROM PROJECTIONS AND NOISY OBSERVATIONS; AND 6) THE IDENTIFICATION OF GENERAL PRINCIPLES FOR HOW TO DEVELOP ADAPTATION PATHWAYS IN WATER SYSTEMS EXPOSED TO MULTI-SCALE CLIMATE VARIABILITY AND DIFFERENT MECHANISMS OF CLIMATE CHANGE. THIS PROJECT WILL INTEGRATE RESEARCH, TEACHING, AND SERVICE MISSIONS THROUGH A PEDAGOGIC AND SCHOLARLY MODEL OF COMMUNITY ENGAGEMENT THAT PROMOTES KNOWLEDGE CO-PRODUCTION AND TRANSLATION BETWEEN STUDENTS, ACADEMICS, EXTENSION AND EDUCATION SPECIALISTS, GREAT LAKES COMMUNITIES, AND AN INTERNATIONAL BOARD OF WATER MANAGERS. UNDERGRADUATE AND GRADUATE EDUCATION: MODELS AND PARTNERSHIPS DEVELOPED THROUGH THIS WORK WILL ENHANCE COMMUNITY-ENGAGED PROJECT EXPERIENCES FOR UNDERGRADUATE AND GRADUATE STUDENTS IN COURSES ON HYDROLOGIC ENGINEERING, CLIMATE CHANGE, AND MACHINE LEARNING. ACTIVE LEARNING MODULES WILL EMBED DATA SCIENCE LITERACY DIRECTLY INTO THESE EDUCATIONAL EXPERIENCES. STUDENT TRAINING: THIS PROJECT WILL PROVIDE AN INTERDISCIPLINARY TRAINING EXPERIENCE FOR 1 PHD STUDENT, AND UNDERGRADUATES WILL ALSO BE RECRUITED TO PARTICIPATE THROUGH COURSE-BASED RESEARCH. PUBLIC FORUMS AND K-12 EDUCATION: THROUGH COLLABORATIONS WITH THE SCIENCENTER OF ITHACA NY AND NEW YORK SEA GRANT, THIS WORK WILL DEVELOP PUBLIC FORUMS TO EDUCATE AND LEARN FROM LAKE ONTARIO COMMUNITIES, PARTICULARLY THOSE IN RURAL, LOW-INCOME AREAS, ABOUT WATER LEVEL VARIABILITY, MANAGEMENT, AND IMPACTS ON COMMUNITY RESILIENCE. THESE COLLABORATIONS WILL ALSO SUPPORT MIDDLE SCHOOL CURRICULUM DEVELOPMENT, DISSEMINATED WIDELY ACROSS THE GREAT LAKES SHORELINE. REAL-WORLD DECISION-MAKING: BY COLLABORATING WITH THE INTERNATIONAL JOINT COMMISSION, THIS WORK WILL ENHANCE THE ADAPTIVE MANAGEMENT PLAN OF ONE OF THE LARGEST MANAGED, FRESHWATER LAKES IN THE WORLD THAT IS UNDERTAKING ONE OF THE LARGEST WETLAND RESTORATION EFFORTS IN NORTH AMERICA. 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.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $97.5k | 9/3/25 | ||
| Not listed | $409.1k | 1/19/22 |
GrantNumber | Description | Subgrantee | Prime Award | Dollars Obligated | Updated At |
|---|---|---|---|---|---|
141146214752S | Sciencenter Discovery Museum | Project Grant 2144332 | $2.0k | 12/5/25 |