Groundwater Resilience Assessment through iNtegrated Data Exploration for Ukraine (GRANDE-U)

Jointly funded by the U.S. National Science Foundation (NSF), Estonian Research Council (ETAG), Latvian Council of Science (LCS), Research Council of Lithuania (LMT), National Science Center of Poland (NCN), Polish National Agency for Academic Exchange (NAWA), National Research Foundation of Ukraine (NRFU), U.S. National Academy of Sciences (NAS) and Office of Naval Research Global (ONRG)

Spatiotemporal Database

GRACE-FO Algorithms

AI/ML
Modeling

Participatory Modeling

Workforce Development

Project Goal

 This project aims to develop solutions to the persistent problem of accurately assessing groundwater (GW), which is the main source of drinking water for over 2 billion people globally. Understanding GW dynamics and resilience and achieving integrated water balance parameterization in transboundary regions at finer spatial and temporal scales is a key component of the challenge. Our hypothesis is that integrating hydrogeologic models with satellite and ground-based data to increase the resolution of remote sensing information will allow us to create highly detailed predictions of changes in GW storage and flows across borders. The results will be especially useful to Ukraine, where limitations of the ground observation network require more efficient assessment techniques based on remote sensing. The project’s research design and the robust international collaboration will create a foundation fostering an internationally-engaged workforce and enabling state-of-the-art innovation infrastructure in Ukraine, which is critical to withstand challenges of the current period and the post-war reconstruction.

To accomplish this goal, this project will bring together researchers from six countries: the United States (US), Ukraine (UA), Poland (PL), Latvia (LV), Lithuania (LT), and Estonia (EE). The researchers represent several domains including hydrology and hydrogeology, data science and artificial intelligence, and participatory simulation modeling. Our convergence approach will integrate cutting-edge, data-intensive capabilities in completely new ways to advance the assessment of GW resilience and contextualize findings to facilitate informed water resource management. The international collaboration at the core of this effort, bridging distinct transboundary human systems and connected natural aquifer systems, will accelerate progress that no single discipline or nation could achieve alone. Simultaneously, this project will foster the next generation of leaders and support the development of a modern innovation ecosystem in Ukraine. Through participation in this project, Ukraine will be poised as an international leader in harnessing data-, AI-, and hydrology-specific capabilities to advance groundwater assessment.

Tasks and Objectives

The five major tasks that will aid us in accomplishing our goal are:

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