EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Empirical GNSS-derived terrestrial water storage-streamflow relationship in the Sierra Nevada ranges, California

Nicholas Lau, Ellen Knappe, and Adrian Borsa
Nicholas Lau et al.
  • University of California San Diego, Scripps Institution of Oceanography, San Diego, United States of America (

One of the most dynamic components of Earth surface mass variability is the constant global redistribution of terrestrial water storage (TWS) across temporal scales of hours to decades. Mass loading and unloading from TWS changes induce instantaneous elastic deformation of the solid earth, producing predominantly vertical transient displacements that are observable by geodetic methods. The global expansion of Global Navigation Satellite Systems (GNSS) networks during the last decade have provided new opportunities of directly estimating changes in TWS at high spatial and temporal resolutions. While contemporary GNSS studies have demonstrated the ability to map regional-scale water storage variability, incorporating these geodetic TWS estimates with in-situ hydrologic measurements can provide further insights on the physical mechanisms underlying the terrestrial water cycle.


In this study, we investigate the potential of using GNSS-derived TWS estimates to infer individual watershed condition along California’s Sierra Nevada, a major water source for urban and agricultural use. Utilizing the dense GNSS network in the western United States, we invert vertical displacements for TWS change at subbasin scale spatial resolution (USGS HUC-8). Joint analysis of our TWS estimates and stream gauge data shows contrasting seasonal behaviours in the northern and southern Sierra Nevada. The snow-dominated southern section exhibits a significant time lag between maximum storage and maximum baseflow from March to May, indicating wet-season decoupling between surface storage and the subsurface reservoirs that drive baseflow. In contrast, the northern section exhibits little to no lag, indicative of persistent surface-to-subsurface coupling, consistent with the higher rain-to-snow ratio in the north. Furthermore, we demonstrate that GNSS-derived TWS estimates can be used to infer watershed antecedent storage conditions, in which interannual variability in summer storage (dry season) influences streamflow recession behaviours during early precipitation season. Continued development of GNSS-based water storage estimates and future assimilation with hydrologic models should provide additional understanding of the water budget and hillslope hydrology in the Sierra Nevada.

How to cite: Lau, N., Knappe, E., and Borsa, A.: Empirical GNSS-derived terrestrial water storage-streamflow relationship in the Sierra Nevada ranges, California, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4048,, 2023.