| Literature DB >> 32905519 |
Augusto Getirana1,2, Matthew Rodell1, Sujay Kumar1, Hiroko Kato Beaudoing1,2, Kristi Arsenault1,3, Benjamin Zaitchik4, Himanshu Save5, Srinivas Bettadpur5.
Abstract
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.Entities:
Year: 2020 PMID: 32905519 PMCID: PMC7473395 DOI: 10.1175/jhm-d-19-0096.1
Source DB: PubMed Journal: J Hydrometeorol ISSN: 1525-7541 Impact factor: 4.349