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Comparison of groundwater storage changes from GRACE satellites with monitoring and modeling of major U.S. aquifers

November 5, 2020

GRACE satellite data are widely used to estimate groundwater storage (GWS) changes in aquifers globally; however, comparisons with GW monitoring and modeling data are limited. Here we compared GWS changes from GRACE over 15 yr (2002–2017) in 14 major U.S. aquifers with groundwater-level (GWL) monitoring data in ~23,000 wells and with regional and global hydrologic and land surface models. Results show declining GWS trends from GRACE data in the six southwestern and south-central U.S. aquifers, totaling −90 km3 over 15 yr, related to long-term (5–15 yr) droughts, and exceeding Lake Mead volume by ~2.5×. GWS trends in most remaining aquifers were stable or slightly rising. GRACE-derived GWS changes agree with GWL monitoring data in most aquifers (correlation coefficients, R = 0.52–0.95), showing that GRACE satellites capture groundwater (GW) dynamics. Regional GW models (eight models) generally show similar or greater GWS trends than those from GRACE. Large discrepancies in the Mississippi Embayment aquifer, with modeled GWS decline approximately four times that of GRACE, may reflect uncertainties in model storage parameters, stream capture, pumpage, and/or recharge rates. Global hydrologic models (2003–2014), which include GW pumping, generally overestimate GRACE GWS depletion (total: approximately −172 to −186 km3) in heavily exploited aquifers in southwestern and south-central U.S. by ~2.4× (GRACE: −74 km3), underscoring needed modeling improvements relative to anthropogenic impacts. Global land surface models tend to track GRACE GWS dynamics better than global hydrologic models. Intercomparing remote sensing, monitoring, and modeling data underscores the importance of considering all data sources to constrain GWS uncertainties.

Publication Year 2020
Title Comparison of groundwater storage changes from GRACE satellites with monitoring and modeling of major U.S. aquifers
DOI 10.1029/2020WR027556
Authors Ashraf Rateb, Bridget R. Scanlon, Donald R. Pool, Alexander Y. Sun, Zizhan Zhang, Jianli Chen, Brian R. Clark, Dianna M. Crilley, Connor J. Haugh, Christopher M. Hobza, Mary C Hill, Virginia L. McGuire, Meredith Reitz, Hannes Muller Schmied Schmied, Edwin H. Sutanudjaja, Sean Swenson, David Wiese, Youlong Xia, Wesley O. Zell
Publication Type Article
Publication Subtype Journal Article
Series Title Water Resources Research
Index ID 70255619
Record Source USGS Publications Warehouse
USGS Organization WMA - Integrated Modeling and Prediction Division