See our new study on groundwater decline in the Colorado River basin in WRR. The work has been covered by several media reports, including VT News, further to follow.
Welcome our new lab member: Postdoctoral Researcher Dr. Shivprasad More!
Read the exciting research story from Nitheshnirmal Sadhasviam on Groundwater preservation, geohazards, and the human impact beyond the surface with the VT Center for Communicating Sciences
Follow Disappearing water: Groundwater crisis in the U.S. Southwest, a VT story map from Esther Oyedele
Read Esther Oyedele's wonderful perspective on Disappearing Groundwater: Unequal Consequences in the Colorado River Basin published by the University of Colorado Boulder's Natural Hazards Center
HIRS lab's Ph.D. candidate Esther Oyedele was recognized by the Graduate School with the university's Graduate Teaching Excellence - Assistant Award. Congratulations & well done, Esther!
Susanna Werth is invited as guest speaker at the Virginia Tech Office for GIS and Remote Sensing Research 2026 Symposium on April 10, 2026 at the Newman Library. Please join the event if you can!
A recent publication in Nature led by L. Ohenhen in collaboration with multiple HIRS lab members focuses on drivers of land subsidence in river deltas worldwide, including groundwater: https://doi.org/10.1038/s41586-025-09928-6
See two recent publications from our lab in Nature Sustainability led by N. Sadhasivam https://www.nature.com/articles/s41893-025-01663-0 and in Journal of Hydrology: Regional Studies led by M. Khorrami https://doi.org/10.1016/j.ejrh.2025.102996.
We contributed to the Nature Cities publication authored by Leonard Ohenhen on Land Subsidence Risk in US Metropolises, which was highlighted by the New York Times, Washington Post, VT news, and many more ...
Groundwater plays a critical role in sustaining the water supply in the Colorado River Basin (CRB), a region experiencing persistent drought, population growth, and increasing water demand. Using GRACE/GRACE-FO satellite observations combined with hydrological data sets, we analyze basin-scale variations and long-term trends in terrestrial and groundwater storage across the CRB from water year 2004–2023. We further apply a joint framework integrating copula-based statistical modeling with statistical inference to quantify probabilistic relationships among storage-based drought indicators and to characterize groundwater–surface water interactions. Results reveal sustained basin-wide groundwater depletion over the past two decades, with accelerated losses since 2019 and during the water year 2020–2022 drought. Notably, during this recent drought period, groundwater losses were larger in the typically more resilient Upper CRB (17.5 ± 3.5 km3) than in the Lower CRB (9.4 ± 6.5 km3), indicating increasing vulnerability across both subbasins. Copula-based analysis shows strong coupling between surface-water deficits and groundwater drought probability in the Upper CRB, whereas parts of the Lower CRB exhibit weaker statistical dependence, consistent with groundwater extraction operating partly independently of surface water availability under chronically limited supply conditions. These findings provide a basin-wide observational synthesis of groundwater–surface water dynamics and demonstrate the value of satellite-based monitoring for diagnosing hydroclimatic stress in large managed river basins. The results highlight emerging shifts in groundwater vulnerability across the CRB and underscore the need for integrated water-management strategies that jointly consider climatic pressures and sustained anthropogenic demand.
We develop a novel hybrid GNSS, GRACE, and InSAR joint inversion approach to constrain water loss during a record-setting drought in California. Here, we present a unified hybrid physics-based stochastic model incorporating measurements from three geodetic sensors to produce a high-resolution map of terrestrial water storage change (∆TWS) across California during the 2020–2021 dry years. The novel joint inversion framework combines Global Navigation Satellite System (GNSS) elastic vertical displacements, ∆TWS from the Gravity Recovery and Climate Experiment Satellites (GRACE and the follow-on mission, GRACE-FO) and Interferometric Synthetic Aperture Radar (InSAR) measurements of poroelastic deformation through a model comprising elastic loading and poroelastic Green's functions. This framework yields a high-resolution and more realistic estimate of ∆TWS (top image to the left) within the Central Valley and the surrounding mountain ranges by accounting for poroelastic aquifer deformation. Besides the total ∆TWS, our novel inversion framework simultaneously solves the change in groundwater storage and is used to produce a high-resolution map of groundwater storage loss across the Central Valley (bottom image to the left). We calculate a groundwater volume loss of 20.4+/− 2.6 km3 in the semi-confined to confined portion of the aquifer-system, with the largest groundwater volume loss in the southern Central Valley over the two dry years. We show that groundwater loss estimates found using our joint inversion framework agree with results from a conventional approach for GRACE-FO-derived groundwater loss estimates when considering underlying processes and uncertainties. Finally, we compare shallow groundwater storage change estimates with those derived from in-situ groundwater level measurements in the Sacramento Valley.
We develop a shrinkage-free approach for fusing GRACE-based total water storage changes with models using wavelet multiresolution analysis. Here, we present a fusion approach based on wavelet multiresolution analysis to combine long-wavelength GRACE TWSC observations with short-wavelength measurements of TWSC from the GLDAS Noah model in the contiguous United States (CONUS). We decompose TWSC maps into building blocks at different spatial wavelengths, examine their statistical characteristics, and combine complementary components at wavelet coefficient levels. The fused TWSC is then obtained by inverse wavelet transform. A spectral analysis indicates that the fused TWSC comprises frequency content that balances spectral characteristics of both input datasets. The fused TWSC dataset possesses enhanced details in the spatial domain, while it accurately quantifies the water budget and its long-term spatial trend at basin scale during 2003–2015, showing a good agreement with GRACE estimates. Independent validation against elastic hydrologic loading deformation measured at ~2000 GNSS stations across CONUS shows similar overall performance for GRACE and fused datasets, while it outperforms GRACE in modeling ground- water storage changes in CONUS when compared to CLSM-DA.
Groundwater withdrawal can cause localized and rapid poroelastic subsidence, spatially broad elastic uplift of low amplitude, and changes in the gravity field. Constraining groundwater loss in Mexico City, we analyze data from the Gravity Recovery and Climate Experiment and its follow-on mission (GRACE/FO) and Synthetic Aperture Radar (SAR) Sentinel-1A/B images between 2014 and 2021. GRACE/FO observations yield a groundwater loss of 0.85–3.87 km3/yr for a region of ∼300 × 600 km surrounding Mexico City. Using the high-resolution interferometric SAR data set, we measure >35 cm/yr subsidence within the city and up to 2 cm/yr of uplift in nearby areas. Attributing the long-term subsidence to poroelastic aquifer compaction and the long-term uplift to elastic unloading, we apply respective models informed by local geology, yielding groundwater loss of 0.86–12.57 km3/yr. Our results suggest Mexico City aquifers have been depleting at faster rates since 2015, exacerbating the socioeconomic and health impacts of long-term groundwater overdrafts.
We put forward the mathematical framework for a joint inversion of GNSS vertical displacement time series with GRACE ∆TWS to produce more accurate spatiotemporal maps of ∆TWS, accounting for the observation errors, data gaps, and nonhydrologic signals. We aim to utilize the regional sensitivity to ∆TWS provided by GRACE mascon solutions with higher spatial resolution provided by GNSS observations. We focus our study in California, USA, which has a dense GNSS network and where recurrent, intense droughts put pressure on freshwater supplies. We find that our joint inversion framework results in a solution that is regionally consistent with the GRACE ∆TWS solutions at different temporal scales but has an increased spatial resolution that allows us to differentiate between regions of high and low mass change better than using GRACE alone.
We show that GPS‐derived elastic load models may not fully capture the contribution of groundwater to terrestrial water loading. Measured GPS vertical displacement rate compared to the predicted vertical displacement rate from the elastic response to groundwater loss in the Central Valley as given by a 1D-poroelastic model applying InSAR deformation rates. Blue dots show forward‐modeled vertical velocity of elastic groundwater unloading. Red stars show measured GPS vertical velocity from Nevada Geodetic Laboratory for each station. Purple dots show predicted vertical velocity using the 300 km (orange), meant to show similar resolution to what is achievable using GRACE, and Orange dots show predicted vertical velocity using the 50‐km Gaussian filtered data set. Dashed black line shows mean GPS vertical velocity error of the stations included. All rates are given in mm/year.
Frequent droughts and growing population in the Southwest US stress water resources and cause groundwater overdraft. Following droughts, the land subsidence might continue for years, even though different components of the hydrological cycle show a recovery, which is evident from groundwater levels, precipitation anomalies, and TWS variations. Residual compaction is variable depending on local hydrogeology and pumping history. This phenomenon has to be considered for integration of deformation and gravity data.
Here we show a compilation of data sets collected for the San Joaquin Valley in California. a) Total water storage change for the GRACE data frame, interpolated from scaled and unscaled GRACE JPL mascons, and smoothed monthly precipitation anomalies (black) derived from TRMM for the period 2002 and 2017. For San Joaquin Valley, b) InSAR vertical velocity map from January 2015 to October 2017 across the San Joaquin valley. c) Time-series of groundwater level changes obtained from the USGS groundwater level network for the period 2002–2017. f) Time-series of surface deformation at selected locations (panel b).
Contact: swerth@vt.edu
Department of Geosciences, 926 West Campus Drive, Blacksburg, VA 24061.
Copyright © 2020 Susanna Werth. All rights reserved.