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Influence of global climate signals on groundwater anomalies in High Plains aquifer
  • Juan Barrera,
  • Manuela Girotto,
  • Janet Barco
Juan Barrera
Facultad de Ingeniería, Ingeniería Ambiental, Universidad de Medellín, Colombia

Corresponding Author:[email protected]

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Manuela Girotto
Dept of Environmental Science, Policy & Management, University of California, Berkeley
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Janet Barco
Facultad de Ingeniería, Ingeniería Ambiental, Universidad de Medellín, Colombia.
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The Gravity Recovery and Climate Experiment (GRACE) mission and the Follow-On mission (GRACE-FO) have been widely used to estimate Groundwater (GW) at different scales. With improved releases and data longevity of these missions it becomes possible to analyze changes on GW and its link with global climate patterns such as El Niño-Southern Oscillation (ENSO), which can contribute to better management of this resource, especially in zones where it is crucial for the livelihoods and food security of the community. In the current study, TWS-derived from GRACE, Soil Moisture and Snow simulated by the Global Land Data Assimilation System (GLDAS) were used in the period 2002-2020 to estimate fluctuations in High Plains Aquifer (HPA). Trend and annual cycle were analyzed, and then Principal Component Analysis (PCA) was carry out to observe spatio-temporal oscillation modes and its relationship with Oceanic Niño Index (ONI) through Spectral Analysis. Furthermore, to validate GRACE-derived GW and evaluate a larger period pattern such as Pacific Decadal Oscillation (PDO), Depth to Water data from United States Geological Survey (USGS) wells distributed in the aquifer were selected with a longer period looking for teleconnections. Results shows increasing trend in Northern High Plains while a decreasing in the central and southern part of it. GW peak occurs in August in most of HPA, three month later than rainfall peak. First four components explain 77% of total variance. GW derived from GRACE and GRACE-FO as well as GW from wells could detect periodicities that suggest connections of GW variability with PDO more than with ENSO in HPA.