Sensitivity of GNSS-Derived Estimates of Terrestrial Water Storage to
Assumed Earth Structure
Abstract
Geodetic methods can monitor changes in terrestrial water storage (TWS)
across large regions in near real-time. Here, we investigate the effect
of assumed Earth structure on TWS estimates derived from Global
Navigation Satellite System (GNSS) displacement time series. Through a
series of synthetic tests, we systematically explore how the spatial
wavelength of water load affects the error of TWS estimates. Large loads
(e.g., >1000 km) are well recovered regardless of the
assumed Earth model. For small loads (e.g., <10 km), however,
errors can exceed 75% when an incorrect model for the Earth is chosen.
As a case study, we consider the sensitivity of seasonal TWS estimates
within mountainous watersheds of the western U.S., finding estimates
that differ by over 13% for a collection of common global and regional
structural models. Errors in the recovered water load generally scale
with the total weight of the load; thus, long-term changes in storage
can produce significant uplift (subsidence) enhancing errors. We
demonstrate that regions experiencing systematic and large-scale
variations in water storage, such as the Greenland ice sheet, exhibit
significant differences in predicted displacement (over 20 mm) depending
on the choice of Earth model. Since the discrepancies exceed GNSS
observational precision, an appropriate Earth model must be adopted when
inverting GNSS observations for mass changes in these regions.
Furthermore, regions with large-scale mass changes that can be
quantified using independent data (e.g., altimetry, gravity) present
opportunities to use geodetic observations to refine structural
deficiencies of seismologically derived models for the Earth’s interior
structure.