SUMMARY
Crustal deformation caused by hydrological processes has long been detected using space geodetic techniques, yet questions remain about the relative contributions of surface water and ...groundwater to the geodetic signals in different regions. Here, we investigate forward models of elastic loading deformation caused by a variety of water-storage changes within the Great Lakes region, including fluctuations in lake-water volume, soil moisture and snow load. We use lake-level data from the Great Lakes Environmental Research Laboratory, soil-moisture content from the North American Land Data Assimilation System (NLDAS), snow load from the Snow Data Assimilation System (SNODAS) and background hydrological load at the global scale from Gravity Recovery and Climate Experiment (GRACE). We compare the modelled surface deformation with estimates of hydrological loading deformation inferred from Global Navigation Satellite System (GNSS) measurements. We find that seasonal deformation measured by GNSS is dominated by regional-scale hydrological loading based on strong correlations with the modelled loading displacements. The mean correlation coefficient for the study network is 0.56. The correlation coefficients vary spatially within the study region and exceed 0.9 at some stations near to the Great Lakes. We assess the relative contribution of each individual hydrological component to the total integrated hydrological load. We find that soil moisture consistently explains the largest percentage (27–69 per cent) of the total vertical loading deformation for 87 per cent of GNSS stations in the Great Lakes region. Snow loading and soil moisture contribute relatively equally in the northern reaches of the study area (e.g. Canadian shield, northern Superior basin). Lake loading accounts for about 10–25 per cent of the total loading signal in the immediate vicinity of the lakes. We also investigate the sensitivities of the surface loading displacements to three different Earth models, including two with lateral variations in structure. The structural variations considered here have limited impact (<0.2 mm) on the predicted hydrological loading displacements and could be neglected at the current level of observational precision.
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.
Plain Language Summary
Hydrogeodesy is a relatively new discipline within the earth sciences that analyzes the storage and movement of water at or near Earth's surface using measurements of Earth's shape, orientation, and gravitational field. In this paper, we review the current state of hydrogeodesy, focusing on the use of Global Positioning System and Global Navigation Satellite System (GNSS) to measure water masses as they change over time and in location. GNSS stations are anchored directly to Earth's crust and measure the movement of the land surface under the weight of changing (i.e., addition, loss, or movement) water masses. Herein, we describe how GNSS position time series respond to changing inputs of rain and snow and variable water loss, how they can be used to estimate the distribution of terrestrial water storage over time, and how they can improve drought characterization. We assert that GNSS‐based hydrogeodesy is an emerging tool that hydrologists can use to investigate and quantify water resources and we seek to explain and facilitate its use, 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.
Key Points
Hydrogeodesy analyzes the distribution and movement of terrestrial water using measurements of Earth's shape, orientation, and gravity
We review the current state of hydrogeodesy, focusing on Global Navigation Satellite System (GNSS) measurements of hydrologic loading and terrestrial water storage
We aim to facilitate the use of GNSS‐observed surface deformation as an emerging tool for investigating and quantifying water resources
We explore Earth's elastic deformation response to ocean tidal loading (OTL) using kinematic Global Positioning System (GPS) observations and forward-modelled predictions across South America. ...Harmonic coefficients are extracted from up to 14 yr of GPS-inferred receiver locations, which we estimate at 5 min intervals using precise point positioning. We compare the observed OTL-induced surface displacements against predictions derived from spherically symmetric, non-rotating, elastic and isotropic (SNREI) Earth models. We also compare sets of modelled predictions directly for various ocean-tide and Earth-model combinations. The vector differences between predicted displacements computed using separate ocean-tide models reveal uniform-displacement components common to all stations in the South America network. Removal of the network-mean OTL-induced displacements from each site substantially reduces the vector differences between observed and predicted displacements. We focus on the dominant astronomical tidal harmonics from three distinct frequency bands: semidiurnal (M2), diurnal (O1) and fortnightly (Mf). In each band, the observed OTL-induced surface displacements strongly resemble the modelled displacement-response patterns, and the residuals agree to about 0.3 mm or better. Even with the submillimetre correspondence between observations and predictions, we detect regional-scale spatial coherency in the final set of residuals, most notably for the M2 harmonic. The spatial coherency appears relatively insensitive to the specific choice of ocean-tide or SNREI-Earth model. Varying the load model or 1-D elastic structure yields predicted OTL-induced displacement differences of order 0.1 mm or less for the network. Furthermore, estimates of the observational uncertainty place the noise level below the magnitude of the residual displacements for most stations, supporting our interpretation that random errors cannot account for the entire misfit. Therefore, the spatially coherent residuals may reveal deficiencies in the a priori SNREI Earth models. In particular, the residuals may indicate sensitivity to regional deviations from standard globally averaged Earth structure due to the presence of the South American craton.
Atmospheric 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.
Plain Language Summary
Human communities in the western United States rely on seasonal mountain snowpack and precipitation for agriculture, industry, and the civilian water supply. Over the past two decades, increasingly severe drought conditions have plagued western states. In this study, we investigate gains in water storage related to recent atmospheric rivers, which are long and narrow corridors of atmospheric moisture associated with extreme precipitation, using an interdisciplinary approach called hydrogeodesy. Hydrogeodesy uses satellite‐ and ground‐based sensors to track subtle changes in the shape of the Earth and its gravity field caused by the redistribution of water through the Earth system. By treating the Earth as a natural scale, we can infer how much water is gained or lost from a particular area over time. Advancing our understanding of water‐resource availability, the Earth's water cycle, and the Earth's changing climate is critical for improving water‐resource management, sustaining natural ecosystems, and mitigating natural hazards.
Key Points
We use surface deformation to assess changes in terrestrial water storage (TWS) associated with families of strong atmospheric rivers (ARs) in 2022–2023
Large jumps in mountain water storage from ARs spurred recoveries from major California droughts in 2012–2015 and 2019–2022
Early‐season water‐storage gains, driven by ARs, nearly equal precipitation inputs, indicating extensive reservoir recharge
Temporal variations of surface masses, such as the hydrosphere and atmosphere of the Earth, load the surfaces of planetary bodies causing temporal variations in deformation. Surface shear forces and ...gravitational fields also drive ongoing planetary deformation. Characterizing the spatiotemporal patterns of planetary deformation can constrain allowable models for the interior structure of a planetary body as well as for the distribution of surface and body forces. Pertinent applications include hydrology, glaciology, geodynamics, atmospheric science, and climatology. To address the diversity of emerging applications, we introduce a software suite called LoadDef that provides a collection of modular functions for modeling planetary deformation within a self‐consistent, Python‐based computational framework. Key features of LoadDef include computation of real‐valued potential, load, and shear Love numbers for self‐gravitating and spherically symmetric planetary models; computation of Love‐number partial derivatives with respect to planetary density and elastic structure; computation of displacement, gravity, tilt, and strain load Green's functions; and computation of three‐component surface displacements induced by surface mass loading. At a most basic level, only a planetary‐structure model and a mass‐load model must be supplied as input to LoadDef to utilize all the main features of the software. The end‐to‐end forward‐modeling capabilities for mass‐loading applications lay the foundation for sensitivity studies and geodetic tomography. LoadDef results have been validated with Global Navigation Satellite System observations and verified against independent software and published results. As a case study, we use LoadDef to predict the solid Earth's elastic response to ocean tidal loading across the western United States.
Plain Language Summary
The Earth and other planets are continually stretched and compressed due to changes in gravity and surface pressure. The amount of distortion that a planet experiences depends on the nature of the force as well as on the interior structure of the planet. We have developed a software package, called LoadDef, that models how the shapes of planets become altered when acted upon by various forces, including gravity and the weights of surface fluids. Examples of surface fluids include the atmosphere, fresh‐water reservoirs, and the oceans. As the ocean tides ebb and flow, for instance, the pressure on the ocean floor changes. Due to the changes in pressure, the surface of the Earth compresses downward and decompresses upward with time, much like the push of a finger could indent a foam ball. The amount of surface compression depends not only on the changing weight of the water, but also on the density and elasticity of rocks inside the Earth. In essence, LoadDef can predict how the different forces interact with a planetary body to cause distortion. Applications of the software span a variety of fields, including climate science, natural hazards, hydrology, geodynamics, and planetary science.
Key Points
We introduce a software to model elastic planetary deformation driven by gravitational fields, surface mass loading, and shear forcing
LoadDef computes real‐valued potential, load, and shear Love numbers, as well as Love‐number partial derivatives for sensitivity studies
LoadDef performs end‐to‐end forward modeling of planetary surface displacements generated by surface mass loading
We have captured a remarkable sequence of microearthquakes showing progressive melt intrusion of a dyke moving upward from a sill at 18
km depth in the mid-crust of the northern volcanic rift zone in ...Iceland. Two-thirds of the earth's crust is created at mid-ocean rifts. Two-thirds of that crust is formed by intrusion and freezing before it erupts of molten rock generated within the underlying mantle. Here we show seismicity accompanying melt intrusion from 17.5 to 13.5
km depth along a dyke dipping at 50° in the mid-crust of the Icelandic rift zone. Although the crust at these depths is normally aseismic, high strain rates as melt intrudes generate microearthquakes up to magnitude 2.2. Moment tensor solutions show dominantly double-couple failure, with fault mechanisms sometimes flipping between normal and reverse faulting within minutes in the same location, but breaking along fault planes with the same orientations. We suggest several possible reasons for the flipping fault mechanisms: the breakage of solidified plugs of basalt within the dyke itself as more melt intrudes; intrusion along sub-parallel fractures or dykelet fingers into the local stress field created near the tip of a propagating dyke; or movement on small jogs or offsets between adjacent
en echelon dykes. Although the faulting is caused ultimately by melt movement, there is no resolvable volumetric component in the moment tensor solutions. The inferred fault planes from microearthquakes align precisely with the overall plane of the dyke delineated by hypocentres. Melt injection occurs in bursts propagating at 2–3
m/min along channels c. 0.2
m thick, producing swarms of microearthquakes lasting several hours. Intervening quiescent periods last tens to hundreds of hours.
► Microearthquakes track melt injecting a dyke 18–13
km deep under Icelandic rift zone. ► Precise hypocentre locations fall on a single plane striking east–west with 50° dip. ► Moment tensor inversions show dominantly double couple faulting. ► Individual fault planes align perfectly with overall orientation and dip of dyke. ► Faults sometimes flip from normal to reverse within minutes at the same location.
The Global Positioning System (GPS) has revolutionized the ability to monitor Earth-system processes, including Earth’s water cycle. Several analysis centers process GPS data to estimate ...ground-antenna positions at daily temporal resolution. Differences in processing strategies can lead to inconsistencies in coordinate-position estimates and therefore influence the analysis of crustal displacement associated with variations in atmospheric and hydrologic mass loading. Here, we compare five GPS data products produced by three processing centers: the Nevada Geodetic Laboratory, Jet Propulsion Laboratory, and UNAVCO Consortium. We find that 5 to 30% of the scatter in residual GPS time series (commonly considered noise) can be explained by atmospheric loading in the contiguous USA and Alaska, but that the percentages vary widely by data product. Positions derived using high-resolution troposphere models (e.g., ECMWF) exhibit significantly lower scatter after correcting for atmospheric loading than positions estimated using constant or slowly varying troposphere models (e.g., GPT2w). The data products also exhibit differences in seasonal deformation (commonly attributed, in large part, to fluctuations in hydrologic mass loading): median vector differences in estimated seasonal amplitude range from 0.4–1.0 mm in the vertical component and 0.1–0.3 mm in the horizontal components, or about 10–40% of the mean amplitudes of seasonal oscillation. Newer products exhibit lower total scatter and stronger correlations than older products. Network-coherent differences in estimates of seasonal deformation reveal reference-frame inconsistencies between data products. We also cross-check two independent models of atmospheric pressure loading: ESMGFZ and LoadDef.
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., >1,000 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 properties of seismologically derived models for the Earth's interior structure.
Plain Language Summary
In many regions of the Earth, water resources used for agriculture, domestic, and industrial purposes rely on stream flow and groundwater sourced from the melting of winter snowpack in adjacent mountains. Modern shifts in climate have resulted in increasingly variable precipitation patterns and temperatures during winter months. Coupled with a rising global population, there has been a growing need for accurate estimates of freshwater stored above and beneath the land surface. A relatively new interdisciplinary approach called hydrogeodesy allows for freshwater resources to be monitored by using satellite‐ and ground‐based sensors to accurately measure changes in the shape and gravitational field of the Earth produced by the redistribution of water between hydrologic reservoirs. As this approach becomes increasingly utilized to inform decision‐makers, however, we require a deeper understanding of the assumptions and uncertainties of the models used to translate between geodetic measurements and estimates of water storage. Here, we consider the impact of assumptions about the Earth's interior structure on the error of geodetic water storage estimates. We present a set of case studies that display the varied influence of assumed Earth structure on water storage estimates depending on the spatial scale and amplitude of water storage variations.
Key Points
Estimates of water storage made at fine spatial scales are highly sensitive to the Earth model used to invert geodetic measurements
Sensitivities to Earth structure produce uncertainties in estimates of water storage that scale with the total weight of the water load
Predictions of uplift produced by melting of the Earth's ice sheets over the past two decades can differ by over 20 mm between Earth models
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