Towards Sustained Monitoring of Subsidence at the Coast Using InSAR and GPS: An Application in Hampton Roads, Virginia

Hampton Roads is among the regions along the U.S. Atlantic Coast experiencing high rates of relative sea level rise. Partly to mitigate subsidence from aquifer compaction, Hampton Roads is injecting treated wastewater into the underlying aquifer. However, the GPS (Global Positioning System) station spacing (∼30 km) is too coarse to capture the spatial variability of subsidence and potential uplift from the injection. We present a cost‐effective workflow for generating an InSAR (interferometric synthetic aperture radar) and GPS combined displacement product. We leverage a live, open‐access archive of InSAR products generated from Sentinel‐1 data. We find an overall subsidence rate of −3.6 ± 2.3 mm/year with considerable spatial variability. The effects of groundwater injection are currently below detection. The workflow presented here is an asset for sustained monitoring of the injection effort and regional subsidence that is applicable along the U.S. coasts for assisting in mitigation and adaptation of relative sea level rise

Vertical Land Displacement Rates and Uncertainty in Hampton Roads, VA [Dataset]

These data contain vertical rates (mm/yr) of surface land displacements and their associated uncertainties from 2015-03-15 to 2019-06-01. They are associated with Buzzanga, B. A., Bekaert, D. P. S., Hamlington, B. D., and Sanga, S. (2020), Towards Sustained Monitoring of Subsidence at the Coast Using InSAR and GNSS: An Application in Hampton Roads, Virginia submitted to Geophysical Research Letters

Landslide Sensitivity and Response to Precipitation Changes in Wet and Dry Climates

Slow-moving landslides are hydrologically driven. Yet, landslide sensitivity to precipitation, and in particular, precipitation extremes, is difficult to constrain because landslides occur under diverse hydroclimatological conditions. Here we use standardized open-access satellite radar interferometry data to quantify the sensitivity of 38 landslides to both a record drought and extreme rainfall that occurred in California between 2015 and 2020. These landslides are hosted in similar rock types, but span more than ∼2 m/yr in mean annual rainfall. Despite the large differences in hydroclimate, we found these landslides exhibited surprisingly similar behaviors and hydrologic sensitivity, which was characterized by faster (slower) than average velocities during wetter (drier) than average years, once the impact of the drought diminished. Our findings may be representative of future landslide behaviors in California where precipitation extremes are predicted to become more frequent with climate change

Toward Sustained Monitoring of Subsidence at the Coast Using InSAR and GPS: An Application in Hampton Roads, Virginia

Hampton Roads is among the regions along the U.S. Atlantic Coast experiencing high rates of relative sea level rise. Partly to mitigate subsidence from aquifer compaction, Hampton Roads is injecting treated wastewater into the underlying aquifer. However, the GPS (Global Positioning System) station spacing (∼30 km) is too coarse to capture the spatial variability of subsidence and potential uplift from the injection. We present a cost‐effective workflow for generating an InSAR (interferometric synthetic aperture radar) and GPS combined displacement product. We leverage a live, open‐access archive of InSAR products generated from Sentinel‐1 data. We find an overall subsidence rate of −3.6 ± 2.3 mm/year with considerable spatial variability. The effects of groundwater injection are currently below detection. The workflow presented here is an asset for sustained monitoring of the injection effort and regional subsidence that is applicable along the U.S. coasts for assisting in mitigation and adaptation of relative sea level rise

ASFHyP3/hyp3: HyP3 v3.3.0

Added <ul> <li>Added <code>hyp3-carter</code> deployment.</li> <li>An <a href="job_spec/INSAR_GAMMA_TEST.yml"><code>INSAR_GAMMA_TEST.yml</code></a> job spec has been added, exposing the adaptive phase filter parameter used when processing InSAR products.</li> <li><code>INSAR_GAMMA_TEST.yml</code> job spec has been added to the HyP3 Enterprise Test and HyP3 AVO deployments.</li> </ul&gt

ASFHyP3/hyp3: HyP3 v3.7.0

Added <ul> <li>Added the <code>WATER_MAP_TEST</code> job spec to the <code>hyp3-watermap</code> deployment. ### Changed</li> <li>the <code>flood_depth_estimator</code> parameter in both the <code>WATER_MAP</code> and <code>WATER_MAP_TEST</code> job spec is now nullable.</li> </ul&gt

ASFHyP3/hyp3: HyP3 v3.2.0

Added <ul> <li><a href="job_spec/"><code>job_spec</code>s</a> can now specify a required set of secrets and an AWS Secrets Manage Secret ARN to pull the secret values from. Notably, secrets are now externally managed and not part of the HyP3 stack. </li> </ul&gt

ASFHyP3/hyp3: HyP3 v3.5.0

Added <ul> <li>Added <code>resolution=20.0</code> option for <code>RTC_GAMMA</code> jobs.</li> <li>Added a <a href="job_spec/WATER_MAP_EQ.yml"><code>WATER_MAP_EQ</code></a> job spec to the <code>hyp3-streamflow</code> and <code>hyp3-enterprise-test</code> deployments.</li> </ul&gt

ASFHyP3/hyp3: HyP3 v3.5.1

Changed <ul> <li>Increased memory available to INSAR_GAMMA jobs in azdwr-hyp3 deployment. ### Fixed</li> <li>Job <code>status_code</code> field should only switch to <code>RUNNING</code> if current value is <code>PENDING</code> (fixes <a href="https://github.com/ASFHyP3/hyp3/issues/1539">#1539</a>).</li> </ul&gt

Using Sentinel-1 and GRACE satellite data to monitor the hydrological variations within the Tulare Basin, California.

Subsidence induced by groundwater depletion is a grave problem in many regions around the world, leading to a permanent loss of groundwater storage within an aquifer and even producing structural damage at the Earth's surface. California's Tulare Basin is no exception, experiencing about a meter of subsidence between 2015 and 2020. However, understanding the relationship between changes in groundwater volumes and ground deformation has proven difficult. We employ surface displacement measurements from Interferometric Synthetic Aperture Radar (InSAR) and gravimetric estimates of terrestrial water storage from the Gravity Recovery and Climate Experiment (GRACE) satellite pair to characterize the hydrological dynamics within the Tulare basin. The removal of the long-term aquifer compaction from the InSAR time series reveals coherent short-term variations that correlate with hydrological features. For example, in the winter of 2018-2019 uplift is observed at the confluence of several rivers and streams that drain into the southeastern edge of the basin. These observations, combined with estimates of mass changes obtained from the orbiting GRACE satellites, form the basis for imaging the monthly spatial variations in water volumes. This approach facilitates the quick and effective synthesis of InSAR and gravimetric datasets and will aid efforts to improve our understanding and management of groundwater resources around the world