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Long-term, non-anthropogenic groundwater storage changes simulated by three global-scale hydrological models.
Li, Bailing; Rodell, Matthew; Sheffield, Justin; Wood, Eric; Sutanudjaja, Edwin.
Afiliación
  • Li B; ESSIC University of Maryland, Maryland, USA. bailing.li@nasa.gov.
  • Rodell M; NASA Goddard Space Flight Center, Greenbelt, USA. bailing.li@nasa.gov.
  • Sheffield J; NASA Goddard Space Flight Center, Greenbelt, USA.
  • Wood E; Princeton University, Princeton, USA.
  • Sutanudjaja E; University of Southampton, Southampton, England.
Sci Rep ; 9(1): 10746, 2019 07 24.
Article en En | MEDLINE | ID: mdl-31341252
ABSTRACT
This study examined long-term, natural (i.e., excluding anthropogenic impacts) variability of groundwater storage worldwide. Groundwater storage changes were estimated by forcing three global-scale hydrological models with three 50+ year meteorological datasets. Evaluation using in situ groundwater observations from the U.S. and terrestrial water storage derived from the Gravity Recovery and Climate Experiment (GRACE) satellites showed that these models reasonably represented inter-annual variability of water storage, as indicated by correlations greater than 0.5 in most regions. Empirical orthogonal function analysis revealed influences of the El Niño Southern Oscillation (ENSO) on global groundwater storage. Simulated groundwater storage, including its global average, exhibited trends generally consistent with that of precipitation. Global total (natural) groundwater storage decreased over the past 5-7 decades with modeled rates ranging from 0.01 to 2.18 mm year-1. This large range can be attributed in part to groundwater's low frequency (inter-decadal) variability, which complicates identification of real long-term trends even within a 50+ year time series. Results indicate that non-anthropogenic variability in groundwater storage is substantial, making knowledge of it fundamental to quantifying direct human impacts on groundwater storage.

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Sci Rep Año: 2019 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Sci Rep Año: 2019 Tipo del documento: Article