Groundwater flowing through the fractured bedrock composing most mountain ranges has been increasingly recognized as a vital source of freshwater for both low-elevation communities and mountain ecosystems, maintaining streamflow and constituting a large portion of recharge to lowland aquifers used to support human activities. Despite the growing awareness of groundwater’s role in mountain hydrology and the potential impacts of climate change on mountain groundwater, it remains a challenge to study the dynamics of mountain aquifers, largely due to the low density of observational wells and challenges in characterizing the mountain block over large areas and depths. Here, we report on a new approach to characterize the flow and hydraulic properties of mountainous aquifers at a mountain range scale. We utilize high-precision Global Navigation Satellite Systems (GNSS) observations of vertical crustal displacement produced by the redistribution of freshwater on or near the Earth’s surface to estimate changes in groundwater storage within the Sierra Nevada and Cascades Range of the western United States with high spatial (10s of kilometer) and temporal (daily) resolution over the past two decades. We find that on average groundwater annual recharge is less than discharge, driving long-term declines in groundwater storage over the last 19 years. Furthermore, we find groundwater recharge to be up to 3x more variable than groundwater discharge in these mountainous areas, suggesting that mountain aquifers release a relatively constant amount of water to streams and adjacent lowland aquifers despite fluctuating recharge conditions. Utilizing identified periods of groundwater discharge, we characterize the hydraulic conductivity, storativity, and flow path length of these groundwater systems using fluid diffusion models in combination with our GNSS-inferred groundwater estimates. Our initial estimates of these parameters reveal relatively high values of bedrock conductivity (~1x10-3-1x10-4 m/s) relative to expected values based upon each region’s bedrock lithology, suggesting that areas with highly fractured bedrock as well as saprolite may exert a strong control on groundwater discharge at the mountain range scale. Furthermore, our results indicate that groundwater flow paths can span lengths on the order of 100s-1000s of meters, supporting the notion that groundwater can flow over extended areas supporting recharge at both a local and regional scales. Our work seeks to provide a new set of tools for hydrologists to investigate these often poorly understood systems.

We are strengthening the application of GPS's capability to estimate change in total water using measurements of elastic displacements of Earth's surface; breaking down total water into its components such as snow, soil moisture, and groundwater; and integrating GRACE gravity data to infer change in total water in groundwater basins.In California's Sierra Nevada, GPS each day tracks the dumping and dissipation of storm water. In Water Year 2023, total water increased abruptly during each of two sequences of snow-dominated atmospheric rivers. Subsurface water, which we take to be total water inferred from GPS minus snow water equivalent, to rise in early January at the time of the first AR sequence, remain constant from late Jan through March (with no increase during the second AR sequence), and rise from April to June as the snowpack melts. Subsurface water increases in the Sierra Nevada by 0.6 m from Oct 2022 to Jun 2023, 45 per cent of cumulative precipitation of 1.4 m. Such a big rise in subsurface water begins to rejuvenate the Sierra Nevada critical zone (Earth's living outer layer between the top of the trees and the bottom of groundwater) and to replenish subsurface water lost during the prior 3 years of drought from 2020 to 2022.Change in total water in California's Central Valley can be determined neither by GRACE alone nor GPS alone. There GPS records primarily Earth's poroelastic response, from which water change is difficult to infer. GRACE cannot distinguish water change in Central Valley from water change in the Sierra Nevada without assuming a hydrology model. We integrate GPS elastic displacements and GRACE gravity to estimate water change in the Central Valley. In the rigorous inversion, GPS determines water change in the Sierra Nevada and Coast Ranges and the remaining water change from GRACE is placed in the Central Valley. We find Central Valley groundwater increased by 0.75 m in the first nine months of Water Year 2023 (the biggest gain ever recorded), replenishing more groundwater than lost during the prior 3 years of drought.

We estimate the solid Earth's elastic response and change in equivalent water thickness produced by 983 global natural lakes and artificial reservoirs. Using the altimetry and LandSat based lake water storage compilation of Yao et al. (2023b, https://zenodo.org/records/7946043), we assemble the following data products: (a) change in water volume for 287 natural lakes and 696 artificial reservoirs interpolated to be continuous from October 1992 to October 2020, (b) maps of change in lake water storage each month, (c) lake-generated change in equivalent water thickness as seen by Gravity Recovery and Climate Experiment (GRACE) in spherical harmonic coefficients and 3-degree mass concentration elements (mascons), (d) lake-generated east, north, and up components of elastic displacement at 19,827 Global Navigation Satellite System (GNSS) sites that the Nevada Geodetic Laboratory analyzes. Removing estimates of lake water storage reduces the variance of 79% of the 333 affected 3-degree mascons in JPL's mascon solution, with a mean reduction of 2 cm (7%). In northern North America and Asia, lake water storage is predicted to reach its seasonal maximum 4-6 months after observed terrestrial water storage from GRACE, which can increase GRACE's variance when lake water is removed. Removing lake-generated elastic displacements from GNSS station displacements reduces the weighted root mean square of residuals relative to a trended sinusoid with a seasonal period by an average of 4 mm (12%). Applications of GNSS displacements observations, such as glacial isostatic adjustment modeling and tectonic reconstructions can be biased due to lake water loading in the case of stations with short records and large lake water changes.

Persistent declines in groundwater storage observed in mountainous regions of the western US over the past two decades are expected to continue, driven by increasingly variable winter temperatures and snowpack accumulation (Carroll et al., 2024; Hall et al., 2024), threatening human and ecosystem health. However, brief but extreme periods of precipitation associated with frequent and intense atmospheric river events deposit significant amounts of water in the mountains of the western US, acting as potentially significant sources of groundwater recharge in an increasingly arid environment. Here, we provide high-resolution estimates of groundwater storage within the western US by removing estimates of water stored in winter snowpack, the soil column, and artificial reservoirs from Global Navigation Satellite Systems (GNSS) inferred estimates of terrestrial water storage (TWS) between January 2006 and June 2024. We find long-term declines in water storage within mountainous regions of the western US such as the Sierra Nevada and Cascades (approx. 355 mmand 105 mm of equivalent water thickness, respectively) align with estimates derived from GRACE/GRACE-FO and watershed mass balance models, corroborating observed aridification within mountainous regions over the past two decades. Despite these declines, we find periods of extreme precipitation, such as winters 2011, 2017, and 2023, can provide more than twice the average annual recharge of mountain groundwater (Fig.1). Furthermore, we find the state of groundwater in many mountainous regions of the west following winter 2023 were driven from record lows in autumn 2022 to above or near normal conditions and have been maintained over the past year despite moderate winter conditions in 2024, indicating that extreme precipitation events can maintain mountain groundwater storage over prolonged periods. As the strength and frequency of atmospheric river events are predicted to increase due to anthropogenic warming (Gershunov et al., 2019; Nellikkattil et al., 2023), we hypothesize that mountain groundwater storage may be maintained by extreme precipitation events in the coming decades.

Quantification of uncertainty in surface mass change signals derived from Global Positioning System (GPS) measurements poses challenges, especially when dealing with large datasets with continental or global coverage. We present a new GPS station displacement dataset that reflects surface mass load signals and their uncertainties. We assess the structure and quantify the uncertainty of vertical land displacement derived from 3045 GPS stations distributed across the continental US. Monthly means of daily positions are available for 15 years. We list the required corrections to isolate surface mass signals in GPS estimates and screen the data using GRACE(-FO) as external validation. Evaluation of GPS time series is a critical step, which identifies (a) corrections that were missed, (b) sites that contain non-elastic signals (e.g., close to aquifers), and (c) sites affected by background modeling errors (e.g., errors in the glacial isostatic model). Finally, we quantify uncertainty of GPS vertical displacement estimates through stochastic modeling and quantification of spatially correlated errors. Our aim is to assign weights to GPS estimates of vertical displacements, which will be used in a joint solution with GRACE(-FO). We prescribe white, colored, and spatially correlated noise. To quantify spatially correlated noise, we build on the common mode imaging approach by adding a geophysical constraint (i.e., surface hydrology) to derive an error estimate for the surface mass signal. We study the uncertainty of the GPS displacement time series and find an average noise level between 2 and 3 mm when white noise, flicker noise, and the root mean square (rms) of residuals about a seasonality and trend fit are used to describe uncertainty. Prescribing random walk noise increases the error level such that half of the stations have noise > 4 mm, which is systematic with the noise level derived through modeling of spatially correlated noise. The new dataset is available at https://doi.org/10.5281/zenodo.8184285 (Peidou et al., 2023) and is suitable for use in a future joint solution with GRACE(-FO)-like observations.

Storage-discharge relationships and dynamic changes in storage connectivity remain key unknowns in understanding and predicting watershed behavior. In this study, we use Global Positioning System measurements of load-induced Earth surface displacement as a proxy for total water storage change in four climatologically diverse mountain watersheds in the western United States. Comparing total water storage estimates with stream-connected storage derived from hydrograph analysis, we find that each of the investigated watersheds exhibits a characteristic seasonal pattern of connection and disconnection between total and stream-connected storage. We investigate how the degree and timing of watershed-scale connectivity is related to the timing of precipitation and seasonal changes in dominant hydrologic processes. Our results show that elastic deformation of the Earth due to water loading is a powerful new tool for elucidating dynamic storage connectivity and watershed discharge response across scales in space and time.

We are strengthening the application of GPS's capability to estimate change in total water using measurements of elastic displacements of Earth's surface; breaking down total water into its components such as snow, soil moisture, and groundwater; and integrating GRACE gravity data to infer change in total water in groundwater basins. In California's Sierra Nevada, GPS each day tracks the dumping and dissipation of storm water.  In Water Year 2023, total water increased abruptly during each of two sequences of snow-dominated atmospheric rivers.  Subsurface water, which we take to be total water inferred from GPS minus snow water equivalent, to rise in early January at the time of the first AR sequence, remain constant from late Jan through March (with no increase during the second AR sequence), and rise from April to June as the snowpack melts.  Subsurface water increases in the Sierra Nevada by 0.6 m from Oct 2022 to Jun 2023, 45 per cent of cumulative precipitation of 1.4 m.  Such a big rise in subsurface water begins to rejuvenate the Sierra Nevada critical zone (Earth's living outer layer between the top of the trees and the bottom of groundwater) and to replenish subsurface water lost during the prior 3 years of drought from 2020 to 2022. Change in total water in California's Central Valley can be determined neither by GRACE alone nor GPS alone.  There GPS records primarily Earth's poroelastic response, from which water change is difficult to infer.  GRACE cannot distinguish water change in Central Valley from water change in the Sierra Nevada without assuming a hydrology model.  We integrate GPS elastic displacements and GRACE gravity to estimate water change in the Central Valley.  In the rigorous inversion, GPS determines water change in the Sierra Nevada and Coast Ranges and the remaining water change from GRACE is placed in the Central Valley.  We find Central Valley groundwater increased by 0.75 m in the first nine months of Water Year 2023 (the biggest gain ever recorded), replenishing more groundwater than lost during the prior 3 years of drought.

AbstractIncreasing climatic and human pressures are changing the world's water resources and hydrological processes at unprecedented rates. Understanding these changes requires comprehensive monitoring of water resources. Hydrogeodesy, the science that measures the Earth's solid and aquatic surfaces, gravity field, and their changes over time, delivers a range of novel monitoring tools that are complementary to traditional hydrological methods. It encompasses geodetic technologies such as Altimetry, Interferometric Synthetic Aperture Radar (InSAR), Gravimetry, and Global Navigation Satellite Systems (GNSS). Beyond quantifying these changes, there is a need to understand how hydrogeodesy can contribute to more ambitious goals dealing with water‐related and sustainability sciences. Addressing this need, we combine a meta‐analysis of over 3,000 articles to chart the range, trends, and applications of satellite‐based hydrogeodesy with an expert elicitation that systematically assesses the potential of hydrogeodesy. We find a growing body of literature relating to the advancements in hydrogeodetic methods, their accuracy and precision, and their inclusion in hydrological modeling, with a considerably smaller portion related to understanding hydrological processes, water management, and sustainability sciences. The meta‐analysis also shows that while lakes, groundwater and glaciers are commonly monitored by these technologies, wetlands or permafrost could benefit from a wider range of applications. In turn, the expert elicitation envisages the potential of hydrogeodesy to help solve the 23 Unsolved Questions of the International Association of Hydrological Sciences and advance knowledge as guidance toward a safe operating space for humanity. It also highlights how this potential can be maximized by combining hydrogeodetic technologies simultaneously, exploiting artificial intelligence, and accurately integrating other Earth science disciplines. Finally, we call for a coordinated way forward to include hydrogeodesy in tertiary education and broaden its application to water‐related and sustainability sciences in order to exploit its full potential.

GPS measurements of solid Earth's displacements are bringing a better understanding of the water cycle in the Pacific Mountain system of the western U.S.in particular on how water processes transfer water between storage reservoirs through the season. In this study, we estimate change in water in the mountains of California, Oregon and Washington every 10 days with an accuracy of 0.1 mm and a spatial resolution of about 75 km.In the 2023 rainy season, big storms dumped 1.5 m of snow and water on the Sierra Nevada. During the 1st sequence of atmospheric rivers in Jan 2023, subsurface water increased by 0.2 m and 0.25 m of snowpack formed, accounting for most of 0.5 of water dumped. During the 2nd sequence of atmospheric rivers in Mar 2023, snowpack increased by 0.25 m but subsurface water held constant, because Earth's surface was either frozen or saturated. As the snow melted from Apr to Jun, subsurface water increased by 0.3 m. During the 12 months of the water year from Oct 2022 to Sep 2023, subsurface water increased by 0.5 m, 1/3 of total precipitation for the year.To estimate water change in the southern Central Valley, where there are few GPS sites recording elastic deformation, we added GRACE gravity data to execute a joint inversion. GRACE gravity resolves water change with coarse spatial resolution, but GRACE resolves change in water in southern Central Valley given that GPS determines water change in the mountains surrounding the Valley. We estimate that Central Valley groundwater increases slowly by 0.5 m from Jan 2022, the time of the 1st atmospheric river to Jul 2023, the time Sierra Nevada snow has melted. We find that in the southern Central Valley, groundwater increase slightly exceeds cumulative precipitation. We postulate that this is because significant water is moving from the Sierra Nevada to the Central Valley deep underground (mountain block recharge). It is believed to take decades to centuries for groundwater to flow from the Sierra Nevada to the Central Valley, but an increase in fluid pressure in the Sierra Nevada could move groundwater underground perhaps over tens of days.In conclusion, GPS and GRACE data are characterizing spatial and temporal fluctuations in water storage and how the water cycle transfers water between different reservoirs.

AbstractAtmospheric rivers (ARs) deliver significant and essential precipitation to the western United States (US) with consequential interannual variability. The intensity and frequency of ARs strongly influence reservoir levels, mountain snowpack, and groundwater recharge, which are key drivers of water‐resource availability and natural hazards. Between October 2022 and April 2023, western states experienced exceptionally heavy precipitation from several families of powerful ARs. Using observations of surface‐loading deformation from Global Navigation Satellite Systems, we find that terrestrial water‐storage gains exceeded 100% of normal within vital California watersheds. Independent water‐storage solutions derived from different data‐analysis and inversion methods provide an important measure of precision. The sustained storage increases, which we show are closely associated with ARs at daily‐to‐weekly timescales, alleviated both meteorological and hydrological drought conditions in the region, with a lag in hydrological‐drought improvements. Quantifying water‐storage recovery associated with extreme precipitation after drought advances understanding of an increasingly variable hydrologic cycle.

For 25 years, geodesists have inferred that the displacement of the "geocenter" estimated from (SLR) satellite laser ranging represents fluctuation of Earth's fluid envelope relative to solid Earth. However, SLR determines the displacement of the (CN) center of network of geodetic sites relative to the (CM) center of mass of Earth, consisting of solid Earth, the oceans, the atmosphere, and continental water, snow, and ice. Because solid Earth's surface is deforming in elastic response to the changing load of continental water, atmosphere and oceans, CN only roughly approximates the (CE) center of mass of solid Earth. In this study, estimate the velocity of CM relative to the (CE) center of mass of Earth by first correcting SLR site displacements (estimated by the International Laser Ranging Service 2020) for their elastic response relative to CE produced by fluctuations of continental water, atmosphere and oceans. We maintain that by correcting for loading displacements relative to CE, we arrive at an estimate of the displacement of CE. We find that transforming the SLR series from CN to CE reduces the discrepancy between the seasonal oscillation of Earth's fluid envelope estimated by SLR and that assumed by GRACE (using the technique of Sun et al. 2017) by 40 per cent. In both SLR and GRACE, a total of 0.5 x 1016 kg of mass moves between hemispheres from southern oceans in August to snow-covered areas in North America and Europe (in particular in Canada and Siberia). The primary remaining difference between the two techniques is that mass in the northern hemisphere is maximum on February 5 in SLR, 20 days before it is maximum on Feb 25 in GRACE. Knowing the total transfer of the mass of between hemispheres places a boundary constraint on global models of circulation of water on land and in the oceans and atmospheres (that may be applied to forecasting extreme events such as flooding and drought).

We developed a high-quality global integrated water vapour (IWV) dataset from 12 552 ground-based global positioning system (GPS) stations in 2020. It consists of 5 min GPS IWV estimates with a total number of 1 093 591 492 data points. The completeness rates of the IWV estimates are higher than 95 % at 7253 (58 %) stations. The dataset is an enhanced version of the existing operational GPS IWV dataset provided by the Nevada Geodetic Laboratory (NGL). The enhancement is reached by employing accurate meteorological information from the fifth generation of European ReAnalysis (ERA5) for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. A dedicated data screening algorithm is also implemented. The GPS IWV dataset has a good agreement with in situ radiosonde observations at 182 collocated stations worldwide. The IWV biases are within ±3.0 kg m−2 with a mean absolute bias (MAB) value of 0.69 kg m−2. The standard deviations (SD) of IWV differences are no larger than 3.4 kg m−2. In addition, the enhanced IWV product shows substantial improvements compared to NGL's operational version, and it is thus recommended for high-accuracy applications, such as research of extreme weather events and diurnal variations of IWV and intercomparisons with other IWV retrieval techniques. Taking the radiosonde-derived IWV as reference, the MAB and SD of IWV differences are reduced by 19.5 % and 6.2 % on average, respectively. The number of unrealistic negative GPS IWV estimates is also substantially reduced by 92.4 % owing to the accurate zenith hydrostatic delay (ZHD) derived by ERA5. The dataset is available at https://doi.org/10.5281/zenodo.6973528 (Yuan et al., 2022).

We installed a purpose-built network of co-located Global Navigation Satellite System (GNSS) stations and meteorological instrumentation to investigate water storage in a high-mountain watershed along the Idaho-Montana border. Twelve GNSS stations are distributed across the Selway-Lochsa watersheds at approximately 30-40 km spacing, filling a critical observational gap between localized point measurements and regional geodetic and satellite data sets. The unique coupling of geodetic and hydrologic observations in this network enables direct comparison between co-located GNSS measurements of the elastic response of the solid Earth and local changes in measured water storage. This network is specifically designed to address questions of hydrologic storage and movement at the mountain watershed scale. Here, we describe technical details of the network and its deployment; introduce new hydrologic, meteorologic, and geodetic data sets recorded by the network; process and analyze the source data (e.g., time series of daily three-dimensional GNSS site positions, removal of non-hydrologic signals); and characterize basic empirical relationships between water storage, water movement, and GNSS-inferred surface displacement. The network shows preliminary evidence for spatial differences in displacement resulting from a range of snow loads across elevations, but longer and more complete data records are needed to support these initial findings. We also provide examples of additional scientific applications of this network, including estimations of snow depth and snow water equivalent from GNSS multipath reflectometry. Finally, we consider the challenges, limitations, and opportunities of deploying GNSS and weather stations at high elevations with heavy snowpack and offer ideas for technical improvements.

Quantification of uncertainty in surface mass change signals derived from GNSS measurements poses challenges, especially when dealing with large datasets with continental or global coverage. Our aim is to assign weights to GNSS estimates of vertical land displacement (VLD), which will be used in a future joint solution with GRACE observations. Thus, we study the structure and quantify the uncertainty present in VLD estimates derived from 3045 GNSS stations distributed across the continental US. Monthly means of daily positions are available for 15 years. First, we remove outliers by performing a 3σ test, and data screening via a number of correlation metrics between the input GNSS VLD estimates and external validation datasets (i.e., VLD predicted from GRACE/GRACE-FO and hydrology models). Afterwards, we employ various processing schemes to characterize the uncertainty of VLD through stochastic modeling and quantification of the spatially correlated errors. In particular, we test for white, colored and spatially correlated noise. When only white noise is considered nearly 30% of the stations exhibit noise level < 2 mm, 65% noise between 2-4 mm and 5% noise > 4 mm. In case of colored noise, error smaller than 2 mm, between 2-4 mm and >4mm, is mapped in 20%, 60% and 20% of the stations, respectively. Spatially correlated noise is in family but slightly smaller in magnitude compared to colored noise.

Globally, groundwater represents a critical natural resource that is affected by changes in natural supply and renewal, as well as by increasing human demand and consumption. However, despite its critical role, groundwater is difficult to accurately quantify as it is beneath the Earth surface. Here, we review several state-of-the-art remote sensing techniques useful for local- to global-scale groundwater monitoring and assessment, including proxies for groundwater extraction. These include inferring changes in subsurface water from mass changes using gravitational measurements, and analyzing changes in the Earth surface height using Interferometric Synthetic Aperture Radar, Light Detection and Ranging, Airborne Electromagnetic Systems, and satellite altimetry. Remote sensing information is often used in tandem with ground-based observations such as hydraulic head in wells, Global Navigational Satellite System monitoring, and numerical modeling to complement the space-based approaches. In the future, fusing different remote sensing techniques capable of operating in various environments will yield additional insight on the state and rate of use for groundwater across the globe.

By far the most prescient insights into the interior structure of the planet have been provided on the basis of elastic wave seismology. Analysis of the travel times of shear or compression wave phases excited by individual earthquakes, or through analysis of the elastic gravitational free oscillations that individual earthquakes of sufficiently large magnitude may excite, has been the central focus of Earth physics research for more than a century. Unfortunately, data provide no information that is directly relevant to understanding the solid state ‘flow’ of the polycrystalline outer ‘mantle’ shell of the planet that is involved in the thermally driven convective circulation that is responsible for powering the ‘drift’ of the continents and which controls the rate of planetary cooling on long timescales. For this reason, there has been an increasing focus on the understanding of physical phenomenology that is unambiguously associated with mantle flow processes that are distinct from those directly associated with the convective circulation itself. This paper reviews the past many decades of work that has been invested in understanding the most important of such processes, namely that which has come to be referred to as ‘glacial isostatic adjustment’ (GIA). This process concerns the response of the planet to the loading and unloading of the high latitude continents by the massive accumulations of glacial ice that have occurred with almost metronomic regularity over the most recent million years of Earth history. Forced by the impact of gravitational n -body effects on the geometry of Earth’s orbit around the Sun through the impact upon the terrestrial regime of received solar insolation, these surface mass loads on the continents have left indelible records of their occurrence in the ‘Earth system’ consisting of the oceans, continents, and the great polar ice sheets on Greenland and Antarctica themselves. Although this ice-age phenomenology has been clearly recognized since early in the last century, it was for over 50 years considered to be no more than an interesting curiosity, the understanding of which remained on the periphery of the theoretical physics of the Earth. This was the case in part because no globally applicable theory was available that could be applied to rigorously interpret the observations. Equally important to understanding the scientific lethargy that held back the understanding of this phenomenon involving mantle flow processes was the lack of appreciation of the wide range of observations that were in fact related to GIA physics. This paper is devoted to a review of the global theories of the GIA process that have since been developed as a means of interpreting the extensive variety of observations that are now recognized as being involved in the response of the planet to the loading and unloading of its surface by glacial ice. The paper will also provide examples of the further analyses of Earth physics and climate related processes that applications of the modern theoretical structures have enabled.

Hydrogeodesy, a relatively new field within the earth sciences, is the analysis of the distribution and movement of terrestrial water at Earth's surface using measurements of Earth's shape, orientation, and gravitational field. In this paper, we review the current state of hydrogeodesy with a specific focus on Global Navigation Satellite System (GNSS)/Global Positioning System measurements of hydrologic loading. As water cycles through the hydrosphere, GNSS stations anchored to Earth's crust measure the associated movement of the land surface under the weight of changing hydrologic loads. Recent advances in GNSS-based hydrogeodesy have led to exciting applications of hydrologic loading and subsequent terrestrial water storage (TWS) estimates. We describe how GNSS position time series respond to climatic drivers, can be used to estimate TWS across temporal scales, and can improve drought characterization. We aim to facilitate hydrologists' use of GNSS-observed surface deformation as an emerging tool for investigating and quantifying water resources, propose methods to further strengthen collaborative research and exchange between geodesists and hydrologists, and offer ideas about pressing questions in hydrology that GNSS may help to answer.

Knowledge of Earth system mass change is limited to spatial scales of approximately 300 km x 300 km, as this is near the native resolution of the data collected from the GRACE and GRACE-FO (G/GFO) satellite gravimetry missions. Measurements of surface height change at much finer spatial scales can additionally be exploited to derive mass change, albeit with the proper treatment of the data. Here, we jointly invert inter-satellite range-rate measurements from GRACE and GRACE-FO, surface height changes measured by in-situ GNSS receivers, and surface elevation changes from a multi-mission synthesis of radar and laser satellite altimeters to estimate mass change at spatial scales of 100 km x 100 km within a Bayesian framework over the time period 2002 - 2021. In this talk, we will focus on results over North America, where nearly 3,000 in-situ GNSS measurements are processed in combination with G/GFO, and over Antarctica, where Envisat, ICESat, CryoSat-2, and ICESat-2 measurements have been processed in combination with G/GFO. We find agreement between the geodetic data combination solution and the G/GFO-only solution at large basin scales, but unique knowledge of mass change is gained with the geodetic data combination solution at smaller spatial scales not observed by satellite gravimetry alone.

We integrate Global Positioning System displacements, Gravity Recovery and Climate Experiment gravity data, reservoir water volumes, and snowpack to estimate change in subsurface water in California. We find 29% of precipitation infiltrates mountain soil and fractured bedrock each autumn and winter and is lost in the spring and summer by evapotranspiration and lateral subsurface flow either within mountain watersheds or into California's Central Valley. The Central Valley lost groundwater at 2.2 ± 0.7 km3/yr from 2006 to 2021, with 68% of the loss occurring in the southern third of the Valley. Water in Central Valley fluctuates each year by a mean of 10.7 ± 1.1 km3 with maximum water in April (not August). A third of Central Valley groundwater lost during recent severe drought is recharged during subsequent years of heavy precipitation. Of the 50 km3 of water entering Central Valley each year, 28 km3 comes from rivers, 17 km3 from precipitation, and 5 km3 from mountain groundwater.