California's arid Central Valley relies on groundwater pumped from deep aquifers and surface water transported from the Sierra Nevada to produce a quarter of the United States' food demand. The natural recharge to deep aquifers is thought to be regulated by the adjacent high Sierra Nevada mountains, but the underlying mechanisms remain elusive. We investigate large sets of geodetic remote sensing, hydrologic, and climate data and employ process-based models at annual time scales to investigate possible recharge mechanism. Peak annual groundwater storage in the Central Valley lags several months behind that of groundwater levels, which suggests a longer transmission time for water flow than pressure propagation. We further find that peak groundwater levels lag the Sierra Nevada snowmelt by about one month, consistent with an ideal fluid pressure diffusion time in the Sierra's fractured crystalline body. This suggests that Sierra Nevada snowpack changes likely impact freshwater availability in the Central Valley aquifers. Our datasets, analysis and process-based models link the current precipitation and meltwater in the high mountain Sierra to deep Central Valley aquifers through the mountain block recharge process. We call for new hydroclimate models to account for the role of the Sierra in California's water cycle and for revision of the current management and drought resiliency plans.

On September 5-7, 2018, a series of tremors were reported in Nigeria's capital city, Abuja. These events followed a growing list of tremors felt in the stable intra-plate region, where earthquakes are not expected. Here, we review available seismological, geological, and geodetic data that may shed light on the origin of these tremors. First, we investigate the seismic records for parent location of the orphan tremors using a technique suitable when a single-seismic station is available such as the Western Africa region, which has a sparse seismic network. We find no evidence of the reported tremors within the seismic record of Western Africa. Next, we consider the possibility of a local amplification of earthquakes from regional tectonics, reactivation of local basement fractures by far-field tectonic stresses, landward continuation of oceanic fracture zones, or induced earthquakes triggered by groundwater extraction. Our assessments pose important implications for understanding Western Africa's intraplate seismicity and its potential connection to tectonic inheritance, active regional tectonics, and anthropogenic stress perturbation.

The complexity of induced seismicity mechanisms significantly hampers seismic hazard assessment around injection wells. The largest magnitude events are commonly thought to be controlled by the size of the injection-affected area, but what controls the size of this area and what is the role of the regional geologic setting? Here we explore observations of deep and distant induced earthquakes in Oklahoma and California. Despite wide-spread injection close to seismically active faults, fluid injection-induced seismicity is comparably rare in California hydrocarbon basins. We identified a potential case of injection-induced earthquakes associated with San Ardo oilfield operations, with the largest events occurring in 1955 (ML5.2) and 1985 (Mw4.5) within ∼6 km from the oilfield. We performed an interferometric analysis of SAR images acquired by Sentinel-1A/B satellites between 2016 and 2020, and find surface deformation of up to 1.5 cm/yr, indicating pressure-imbalance in parts of the oilfield. Temporal correlations are observed over more than 40 years, with correlation coefficients of up to 0.71 for seismicity within 24 km of the oilfield. Such large distances have not previously been observed in California but are similar to the large spatial footprint of injection in Oklahoma. The San Ardo seismicity shows anomalous clustering with earthquakes consistently occurring at close spatial proximity but long inter-event times, analogous to induced earthquakes in geothermal reservoirs. The complexity of seismic behavior at San Ardo indicates that multiple processes, such as elastic stress transfer and aseismic slip transients, contribute to the potentially induced earthquakes. The observed power-law distance decay of induced events from the reservoir is in line with observations of stress decay from poroelastic models in which basement faults may be hydraulically isolated from the injection zone. Our model’s resolved fluid/solid stress interactions suggest that shallow injection can 1) activate deep basement faults and 2) lead to spatially extensive induced earthquake sequences. Both of these observations may significantly elevate the seismic hazard associated with fluid injection operations.

Relative sea-level rise is a major coastal hazard affecting about half the population of the United States. The Chesapeake Bay is characterized by the fastest rate of sea-level rise along the Atlantic coast of North America, in part because of land subsidence. Previous studies have quantified a range of land subsidence rates in the Chesapeake Bay (~1-4 mm/yr) from various measurement techniques that contribute to high rates of relative sea-level rise. In this study, we present progress towards developing a new vertical land motion map for the Chesapeake Bay region to provide more robust constraints on estimates of relative sea-level rise. We are using a combination of GNSS observations and InSAR interferograms. Available continuous GNSS data in the region that span November 2014 - September 2020 are processed with GAMIT-GLOBK to align temporally with available Sentinel-1 InSAR satellite data. We are using an approach that combines the two geodetic observations to provide a new solution of vertical land motions for the Chesapeake Bay. Additionally, this project is collecting new campaign GNSS observations across the Chesapeake Bay each fall for 5 years, beginning in 2019. We will also present about the 2020 and planned 2021 campaign GNSS observations, which will ultimately be incorporated into our new map of vertical land motions for the region. The impacts of this work will be improved flooding and inundation hazard maps, as well as updated projections for municipal flood mitigation planning that will be created using the new dataset.

Future projections of sea-level rise used to assess coastal flooding hazards and exposure throughout the 21st century and devise risk mitigation efforts often lack an accurate estimate of coastal Vertical Land Motion (VLM) rate, driven by anthropogenic and non-climate factors in addition to climatic factors. The Chesapeake Bay (CB) region of the United States is experiencing one of the fastest rates of relative sea-level rise on the Atlantic coast of the United States. This study uses a combination of space-borne Interferometric SAR (InSAR), Global Navigation Satellite System (GNSS), Light Detecting and Ranging (LIDAR) datasets, available National Oceanic and Atmospheric Administration (NOAA) long term tide gauge data, and sea-level rise projections from the Intergovernmental Panel on Climate Change (IPCC), AR6 WG1 to quantify the regional rate of RSLR and future flooding hazards for the years 2030, 2050, and 2100. By the year 2100, the total inundated areas from SLR and subsidence are projected to be 454-600 for Shared Socioeconomic Pathways (SSPs) 1-1.9 to 5-8.5 respectively, and 343-627 only from SLR. The effect of storm surges based on Hurricane Isabel can increase the inundated area to 849-1117 km2 under different VLM and SLR scenarios. We present that accurate estimates of the VLM rate, such as those obtained here, are essential to revise IPCC projections and obtain accurate maps of coastal flooding and inundation hazards. The results provided here inform policymakers when assessing hazards associated with global climate changes and local factors in CB, required for developing risk management and disaster resilience plans.