Accuracy of Snow Water Equivalent Estimated From GPS Vertical Displacements: A Synthetic Loading Case Study for Western U.S. Mountains

Abstract

GPS monitoring of solid Earth deformation due to surface loading is an independent approach for estimating seasonal changes in terrestrial water storage (TWS). In western United States (WUSA) mountain ranges, snow water equivalent (SWE) is the dominant component of TWS and an essential water resource. While several studies have estimated SWE from GPS‐measured vertical displacements, the error associated with this method remains poorly constrained. We examine the accuracy of SWE estimated from synthetic displacements at 1,395 continuous GPS station locations in the WUSA. Displacement at each station is calculated from the predicted elastic response to variations in SWE from SNODAS and soil moisture from the NLDAS‐2 Noah model. We invert synthetic displacements for TWS, showing that both seasonal accumulation and melt as well as year‐to‐year fluctuations in peak SWE can be estimated from data recorded by the existing GPS network. Because we impose a smoothness constraint in the inversion, recovered TWS exhibits mass leakage from mountain ranges to surrounding areas. This leakage bias is removed via linear rescaling in which the magnitude of the gain factor depends on station distribution and TWS anomaly patterns. The synthetic GPS‐derived estimates reproduce approximately half of the spatial variability (unbiased root mean square error ∼50%) of TWS loading within mountain ranges, a considerable improvement over GRACE. The inclusion of additional simulated GPS stations improves representation of spatial variations. GPS data can be used to estimate mountain‐range‐scale SWE, but effects of soil moisture and other TWS components must first be subtracted from the GPS‐derived load estimates.

Prospects for Imaging Terrestrial Water Storage in South America Using Daily GPS Observations

“…The RMSE for this epoch was 40.07 kg/m 2 , which agrees with previous results for Yunnan Province, China, published by Zhang et al [18], of about 48-52 kg/m 2 at annual time scales based on monthly values, which are smoother than daily solutions used in the present study. Likewise, RMSEs in the range of 25-77 kg/m 2 across the mountains of the western United States were reported by Enzminger et al [16], after using synthetic data to assess the inversion of radial displacements into TWS. Moreover, on the basis of the results of the checkerboard test and the closed-loop simulation, it was found that generally, the results were relatively good near the GPS sites (Figures 6c and 7c).…”

“…Furthermore, GPS-imaged TWS could be used to fill in the temporal gap between the GRACE and GRACE-FO missions, as well as validate their estimations. However, this might be possible only for regions with a dense GPS network [16], although reasonable results have been reported for a relatively small number of stations [18]. Here, 397 GPS stations were considered from which only (at most) 353 were available, with an average of 314 stations having daily solutions.…”

“…Likewise, Fu et al [15] have estimated the TWS series using the GPS-derived radial deformation, and it was revealed that the overall patterns of TWS correlated well with the physiographic properties of the region and also reflected the spatial variabilities of rainfall. Investigations based on a synthetic case study for the western United States were carried out to find the accuracy of snow water storage derived from the knowledge of its induced radial displacements at each GPS station [16]. Fu et al [15] further reported that one of the advantages of GPS-derived TWS is the possibility of increasing the spatial resolution of TWS fields over GRACE observations, and the results can be used as an independent dataset to validate GRACE-derived TWS.…”

Subsurface Water Dominates Sierra Nevada Seasonal Hydrologic Storage

“…We corrected for smoothing-related mass leakage from the SN to its surroundings (Enzminger et al, 2018). Monthly empirical gain factors were derived from a synthetic ΔS time series using data from PRISM 10.1029/2019GL084589…”

Reconstruction of GRACE Data on Changes in Total Water Storage Over the Global Land Surface and 60 Basins

“…Li et al, 2016), soil moisture (Girotto et al, 2019;Tian et al, 2019), evapotranspiration (X. Li, Long, et al, 2019;Long, Longuevergne, & Scanlon et al, 2014), and snow and glaciers (Castellazzi et al, 2019;Chen et al, 2017;Enzminger et al, 2018), by assimilating GRACE observations (Brookfield et al, 2018;Han et al, 2019;Houborg et al, 2012;Kumar et al, 2016;. However, they cannot provide complete information brought by the GRACE satellites; some aquifers and/or human water use are often overlooked, such as deep groundwater storage (GWS) and cropland irrigation (Sun et al, 2019).…”