Welcome to Virginia Tech's Hydrologic Innovation & Remote Sensing (HIRS) Lab!

At the HIRS lab, our research centers on advancing water resources monitoring through cutting-edge remote sensing techniques. We specialize in geodetic methods that capture variations in Earth's gravity, surface deformation, and surface water extent. By leveraging data science and signal processing techniques to analyze these datasets and integrating them into geophysical models, we extract valuable insights into water cycle dynamics and groundwater systems. Our ultimate goal is to enhance the prediction of environmental hazards and empower water managers to develop equitable and sustainable resource management strategies.

News, Press Releases & Social Media

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 ...
The HIRS lab got funding to study vertical land motions in Alaska and we will investigate their interactions with the water cycle in permafrost regions from local to regional scales . Read the story at VT News: https://news.vt.edu/articles/2025/03/science-radar-satellite-based-observatory.html
Read Esther's Research Story at VT News: https://communicatingscience.isce.vt.edu/research-stories/Esther_Oyedele.html
Dr. Werth was interviewed by NASA's press office to comment on a revealing and interesting study revealing abrupt drop in terrestrial water storage during the last decade
Welcome our new lab member: Postdoctoral Researcher Dr. Shubham Awasthi!
See our new publication on integration of InSAR, GNSS and GRACE observations to quantify total and groundwater storage in California at unprecedented accuracy: https://doi.org/10.1016/j.rse.2024.114303. Congratulation Grace Carlson on the important and novel work.
Congratulations to Nitheshnirmal Sadhasivam for receiving the first place in the "Student GIS/Remote Sensing Poster Competition and Showcase" at the "The Virginia Tech Office for GIS and Remote Sensing Research 2024 Symposium" on April 5, 2024 https://sites.google.com/vt.edu/ogis/2024-ogis-symposium
Read this excellent EGU blog entry by Khosro Ghobadi-Far about our recent publication on "High resolution terrestrial water storage changes from combination of GRACE and models" https://blogs.egu.eu/divisions/g/2024/02/07/high-resolution-terrestrial-water-storage-changes-from-combination-of-grace-and-models
The lab was highlighted in VT news: “Geosciences faculty receive $1.3 million to quantify the impact of freshwater demand and flooding in the Chesapeake Bay”, Lindsey Byars, Jan 29, 2024, https://news.vt.edu/articles/2024/01/cm-geosciencegrant.html

Research Highlights

Carlson, Werth & Shirzaei (2024)

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.

Carlson, G., Werth, S., & Shirzaei, M. (2024). A novel hybrid GNSS, GRACE, and InSAR joint inversion approach to constrain water loss during a record-setting drought in California. Remote Sensing of Environment, 311, 114303. https://doi.org/10.1016/j.rse.2024.114303

Ghobadi-Far, Werth & Shirzaei (2023)

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.

Ghobadi-Far, K., Werth, S., & Shirzaei, M. (2023). A shrinkage-free approach for fusing GRACE-based total water storage changes with models using wavelet multiresolution analysis. Journal of Hydrology, 626, 130217. https://doi.org/10.1016/j.jhydrol.2023.130217

Khorrami et al. (2023)

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.

Khorrami, M.; Shirzaei, M.; Ghobadi‐Far, K.; Werth, S.; Carlson, G.; & Zhai, G. (2023). Groundwater Volume Loss in Mexico City Constrained by InSAR and GRACE Observations and Mechanical Models. Geophysical Research Letters, 50(5). https://doi.org/10.1029/2022gl101962

Carlson, Werth & Shirzaei (2022)

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.

Carlson, G.; Werth, S. & Shirzaei, M. (2022). Joint Inversion of GNSS and GRACE for Terrestrial Water Storage Change in California. Journal of Geophysical Research - Solid Earth, 127(3), e2021JB023135. https://doi.org/10.1029/2021JB023135

Carlson et al. (2020)

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.

Carlson, G., Shirzaei, M., Werth, S., Zhai, G., & Ojha, C. (2020). Seasonal and Long‐Term Groundwater Unloading in the Central Valley Modifies Crustal Stress. Journal of Geophysical Research: Solid Earth, 125(1), 1–17. https://doi.org/10.1029/2019JB018490.

Ojha, Werth & Shirzaei (2020)

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).

Ojha, C., Werth, S., & Shirzaei, M. (2020). Recovery of aquifer-systems in Southwest US following 2012 – 2015 drought : Evidence from InSAR , GRACE and groundwater level data. Journal of Hydrology, 587(March), 124943. https://doi.org/10.1016/j.jhydrol.2020.124943.

Contact: swerth@vt.edu
Department of Geosciences, 926 West Campus Drive, Blacksburg, VA 24061.

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