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GRACE improves seasonal groundwater forecast initialization over the U.S.

Augusto GetiranaMatthew RodellSujay KumarHiroko Kato BeaudoingKristi ArsenaultBenjamin ZaitchikHimanshu SaveSrinivas Bettadpur
Published in: Journal of hydrometeorology (2020)
We evaluate the impact of Gravity Recovery and Climate Experiment data assimilation (GRACE-DA) on seasonal hydrological forecast initialization over the U.S., focusing on groundwater storage. GRACE-based terrestrial water storage (TWS) estimates are assimilated into a land surface model for the 2003-2016 period. Three-month hindcast (i.e., forecast of past events) simulations are initialized using states from the reference (no data assimilation) and GRACE-DA runs. Differences between the two initial hydrological condition (IHC) sets are evaluated for two forecast techniques at 305 wells where depth-to-water-table measurements are available. Results show that using GRACE-DA-based IHC improves seasonal groundwater forecast performance in terms of both RMSE and correlation. While most regions show improvement, degradation is common in the High Plains, where withdrawals for irrigation practices affect groundwater variability more strongly than the weather variability, which demonstrates the need for simulating such activities. These findings contribute to recent efforts towards an improved U.S. drought monitor and forecast system.
Keyphrases
  • water quality
  • drinking water
  • health risk
  • human health
  • climate change
  • heavy metals
  • health risk assessment
  • healthcare
  • risk assessment
  • primary care
  • heat stress
  • artificial intelligence