NSF Org:	EAR Division Of Earth Sciences
Recipient:	MICHIGAN TECHNOLOGICAL UNIVERSITY
Initial Amendment Date:	July 28, 2022
Latest Amendment Date:	July 28, 2022
Award Number:	2218518
Award Instrument:	Standard Grant
Program Manager:	Richard Yuretich ryuretic@nsf.gov  (703)292-4744 EAR  Division Of Earth Sciences GEO  Directorate for Geosciences
Start Date:	September 1, 2022
End Date:	August 31, 2027 (Estimated)
Total Intended Award Amount:	$800,071.00
Total Awarded Amount to Date:	$800,071.00
Funds Obligated to Date:	FY 2022 = $800,071.00
History of Investigator:	Laura Bourgeau-Chavez (Principal Investigator) lchavez@mtu.edu Michael Battaglia (Co-Principal Investigator)
Recipient Sponsored Research Office:	Michigan Technological University 1400 TOWNSEND DR HOUGHTON MI  US  49931-1200 (906)487-1885
Sponsor Congressional District:	01
Primary Place of Performance:	Michigan Technological University 3600 Green Court, Suite 100 Ann Arbor MI  US  48105-1570
Primary Place of Performance Congressional District:	06
Unique Entity Identifier (UEI):	GKMSN3DA6P91
Parent UEI:	GKMSN3DA6P91
NSF Program(s):	FRES-Frontier Rsrch Earth Sci
Primary Program Source:	01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):
Program Element Code(s):	111Y00
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.050

ABSTRACT

Understanding the complex and interwoven effects of changing climate and land use on hydrology is necessary to manage water resources. The Great Lakes Basin (GLB), the world?s largest surface freshwater resource, has experienced dramatic shifts in lake levels from record lows to record highs over the last decade. Despite over a century of lake level measurements, we do not fully understand what drives such fluctuations in Great Lakes levels. One reason is that the basin?s extensive groundwater resources are poorly monitored, and often ignored in models. Here, we propose to develop a hydrologic model that more accurately simulates both surface and groundwater flows, driven by and validated using data from both ground GPS instruments and satellites. This model will provide an unprecedented view of how groundwater, the ?sixth Great Lake?, affects lake levels across the GLB.

We propose a fusion of hydrologic modeling with GPS, InSAR, satellite imagery, and GRACE data to more accurately simulate surface and subsurface flows in the GLB. This will be the first such integration of geodesy (deformation and gravity change), measurements of groundwater-coupled surface water extent from remote sensing, and integrated hydrologic modeling. Through data assimilation, we will produce both historical and nowcast groundwater flow and storage reanalysis products to reveal the spatio-temporal distribution of groundwater across the basin, and relate this to fluctuating lake levels. This will provide reliable information about surface and groundwater storage, lake levels, and flow rates that are needed for water resource management.

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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