Downscaling Vertical GPS Observations to Derive Watershed‐Scale Hydrologic Loading in the Northern Rockies

Abstract

GPS time series of vertical displacement include the elastic response of the Earth to a combination of regional and local loading signals arising from hydrologic mass transfer. The regional loading, controlled by seasonal, synoptic precipitation patterns, dominates the displacement of individual stations and is highly correlated among stations with separation distances from 10 to 300 km. The local loading, controlled by small‐scale precipitation and storage variability, has much shorter correlation lengths of <30 km. We develop a new method to separate the regional and local contributions using common mode analysis and show that GPS is capable of measuring the local hydrologic load changes at watershed scales of tens of kilometers. Using this methodology, GPS‐measured displacement provides an integrated measurement of hydrologic load at a spatial scale between the existing long‐wavelength resolution of the Gravity Recovery and Climate Experiment and point measurement resolution of a precipitation station. Thus, GPS time series record critical observations for monitoring integrated hydrologic budgets at scales useful for water management and assessment of the hydro‐ecological response to climate change.

Comparison of Vertical Surface Deformation Estimates Derived From Space‐Based Gravimetry, Ground‐Based GPS, and Model‐Based Hydrologic Loading Over Snow‐Dominated Watersheds in the United States

“…The potential of using ground‐based GPS vertical displacements to represent TWS interannual variations was investigated via the removal of the mean seasonal cycle (i.e., the multiyear average of each month) of vertical displacement embedded within the time series derived from GPS, GRACE, and Catchment. Again, the network‐wide mean of seasonally adjusted vertical displacement time series following Knappe et al (2019) was calculated for GPS, GRACE, and Catchment as shown in Figure 7. A positive, residual vertical displacement (i.e., after removing the mean seasonal cycle) represents a larger than multiyear averaged displacement for that particular month, which indicates less hydrologic loading than during expected climatology.…”

“…(3) SNOTEL SWE measures mass loading resting on a snow pillow, and any mass moving off the sensor (e.g., via snow melt or wind redistribution) generally remains in the surrounding region and, by construct, is measured in the integrated TWS signal but not measured in the local SNOTEL SWE signal (Knappe et al, 2019); and (4) the separation distance between GPS and SNOTEL stations is not the only factor that influences the correlation; e.g., other factors such as elevation difference between the stations should also be considered. Errors in the collection and processing of GPS and SNOTEL measurements can also introduce additional discrepancies.…”

Intraplate Seasonal Seismicity in the Northern Rocky Mountains of Montana and Idaho

“…GPS vertical displacements reflect deflection of the crust excited by changes in hydrologic load; SNOTEL SWE measures effective snow depth at specific locations. In the Northern Rockies snowpack is the dominant hydrologic input (Serreze et al, 1999), and the two measures are correlated (Knappe et al, 2019).…”

“…Alternatively, other studies have linked seasonal variations in seismicity to increases in pore pressure with some delay from peak hydrologic load or precipitation (Christiansen et al, 2005;Johnson et al, 2020;Saar & Manga, 2003;Wolf et al, 1997). Invoking this mechanism, seismic productivity increases will occur after a lag from peak runoff and infiltration, which occurs in late spring to early summer (e.g., Knappe et al, 2019) (Figure 3). As this would result in a minimum cross correlation (or maximum anticorrelation) with SWE rate and a maximum cross correlation with GPS rate at a ∼6-month shift, this interpretation is also supported PERRY AND BENDICK (Figure 4).…”

Akaike’s Bayesian Information Criterion for the Joint Inversion of Terrestrial Water Storage Using GPS Vertical Displacements, GRACE and GLDAS in Southwest China

“…This method also provides a new perspective on achieving a relatively high spatio-temporal resolution of TWS depending on the spatial density and distribution of the continuous GPS network [ 19 ]. In addition, GPS is a ground-based observation technology that should be more sensitive to variations in the overall regional hydrological compartments, including groundwater, nearby reservoirs [ 20 ], snow [ 21 ], and runoffs [ 22 ]. This implies that a ground-based GPS-inferred TWS should reflect the regional characteristics of TWS distribution more realistically than inferred from space-borne GRACE [ 23 ].…”